Genetics - Cmi 5l4up

KEY ARTICLES

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Refuting Evolution 2 - Argument: Common design points to common ancestry …………………………………….…4 Genetics and creation demographic events …..…………………………………………………………………………...5 Evolutionists abandon the idea of 99% DNA similarity between humans and chimps ………………………………..6 DNA: marvellous messages or mostly mess? ……………………………………………………………………………..6

DO GENE DUPLICATION AND POLYPLOIDY PROVIDE A MECHANISM FOR EVOLUTION

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Do new functions arise by gene duplication? ……………………………………………………………………………...9 Does gene duplication provide the engine for evolution? ……………………………………………………………….14 Dawkins and the origin of genetic information

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WHAT ABOUT “JUNK” DNA

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‘Junk’ DNA: evolutionary discards or God’s tools? ……………………………………………………………………….18 The slow, painful death of junk DNA ………………………………………………………………………………………26 No joy for junkies ……………………………………………………………………………………………….……………27 Large scale function for ‘endogenous retroviruses’ ……………………………………………………………………...28 Hox (homeobox) Genes—Evolution’s Saviour? …………………………………………………………………………..29 Hox Hype …………………………………………………………………………………………………..…………………29

HOW DOES GENETICS POINT TO DESIGN

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Cell systems—what’s really under the hood continues to drop jaws …………………………………………………...30 Meta-information …………………………………………………………………………………………………….………32 Splicing and dicing the human genome …………………………………………………………………………………...33 Genetics: no friend of evolution …………………………………………………………………………………………… 34 Astonishing DNA complexity uncovered …………………………………………………………………………………..36 Astonishing DNA complexity update ……………………………………………………………………………………….37 Evidence for the design of life: part 1—Genetic redundancy …………………………………………………………..37 The design of life: part 3—an introduction to variation-inducing genetic elements ………….………………………..40 The design of life: part 4—variation-inducing genetic elements and their function …………………………………...45

INFORMATION THEORY

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Refuting Evolution—Chapter 9 Is the design explanation legitimate? ………………………………………………….50 Scientific laws of information and their implications—part 1 …………………………………………………………….52 Implications of the scientific laws of information—part 2 ……………………………………………………………….. 57 Variation, information and the created kind ……………………………………………………………………………….60

ARE THERE EVOLUTIONARY PROCESSES THAT LEAD TO INFORMTION INCREAS?  Bears across the world … …………………………………………………………………………………………………..63  Was Dawkins Stumped? ………………………………………………………………………………………….…………65  The adaptation of bacteria to feeding on nylon waste ……………………………………………………………………67  New plant colours—is this new information? ……………………………………………………………………………..68  Is antibiotic resistance really due to increase in information? …………………………………………………………...69 WHAT IS THE DIFFERENCES BETWEEN ORDER AND COMPLEXITY  The treasures of the snow …………………………………………………………………………………………………..71 HOW DOES INFORMATION THEORY CREATION?  Information, science and biology …………………………………………………………………………………………... 73  The marvellous ‘message molecule’ ……………………………………………………………………….………………78  More or less information? / Has a recent experiment proved creation? ……………………………………………….79  Life’s irreducible structure—Part 1: autopoiesis …………………………………………………………………………..81 DNA INFORMATION

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Information Theory—part 1: overview of key ideas ……………………………………………………………………... 85 Information Theory—part 2: weaknesses in current conceptual frameworks …………………………………………89 Information Theory—part 3: introduction to Coded Information Systems ……………………………………………...93 Information Theory—part 4: fundamental theorems of Coded Information Systems Theory ………………………..96 Genetic code optimisation: Part 1 ………………………………………………………………………………..………101 Evidence for the design of life: part 1—Genetic redundancy ………………………………………………………….108

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Evidence for the design of life: part 2—Baranomes ……………………………………………………………………111 The design of life: part 3—an introduction to variation-inducing genetic elements ………………………………….116 The design of life: part 4—variation-inducing genetic elements and their function ………………………………….121 And then there was life ……………………………………………………………………………………………..………126 Cell systems—what’s really under the hood continues to drop jaws …………………………………………………..126 Transposon amplification in rapid intrabaraminic diversification ………………………………………………………128 Myriad mechanisms of Gene regulation ………………………………………………………………………………… 133 More marvellous machinery: ‘DNA scrunching’ ………………………………………………………………………….134 The genetic puppeteer …………………………………………………………………………………………………..…135

MUTATIONS

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Can mutations create new information? …………………………………………………………………………………. 137 Refuting Evolution 2 - Argument: Some mutations are beneficial …………………………………………………….141 Beetle bloopers …………………………………………………………………………………………………..…………142 The evolution train’s a-comin’ ……………………………………………………………………………………….…….143 Ancon sheep: just another loss mutateon ………………………………………………………………………………144 Bacteria ‘evolving in the lab’? …………………………………………………………………………………………….145 A cat with four ears (not nine lives) ………………………………………………………………..…………………… 146 Sickle-cell anemia does not prove evolution! ……………………………………………………..…………………….147 Evolution of a new master race? …………………………………………………………………………………………148 The 'werewolf' gene ………………………………………………………………………………………….…………… 148 ‘Evolution in a Petri dish’? ……………………………………………………………………………………….…………149 Breathtaking new frog surprise …………………………………………………………………………...………………149

CAN MUTATION BE THE MECHANISM FOR EVOLUTION?

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Hox (homeobox) Genes—Evolution’s Saviour? …………………………………………………………………………150 Gain-of-function mutations: at a loss to explain molecules-to-man evolution ………………………………………..150 Are ‘gain of function’ mutations really downhill and so not ing of evolution? ………………………………..152

ARE MUTATIONS EVER BENEFICIAL?

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CCR5-delta32: a very beneficial mutation

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The mutant ‘feather-duster’ budgie ………………………………………………………………………….……………154 ‘Lost World of Mutants’ discovered ……………………………………………………………………………………….154 New eyes for blind cave fish? ……………………………………………………………………………………….……155 Christopher Hitchens—blind to salamander reality ……………………………………………………..………………156 Can’t drink milk? You’re “normal”! ……………………………………………………………………………..…………158 At last, a good mutation? …………………………………………………………………………………………………..159 A-I Milano mutation—evidence for evolution? …………………………………………………………………………...159 Special tools of life ………………………………………………………………………………………………….………160

Mutations: evolution’s engine becomes evolution’s end! ………………………………………………………………. 162 Meiotic recombination—designed for inducing genomic change ……………………………………………………...166 Teenage mutant ninja people ………………………………………………………………………………………..……168 Critic ignores reality of Genetic Entropy ……………………………………………………………………….………… 169 Genetic entropy and simple organisms ……………………………………………………………………..……………172 The diminishing returns of beneficial mutations …………………………………………………………………………174 Pesticide resistance is not evidence of evolution ………………………………………………………………….……175

KEY ARTICLES Refuting Evolution 2 A sequel to Refuting Evolution that refutes the latest arguments to evolution (as presented by PBS and Scientific American). by Jonathan Sarfati, Ph.D. with Michael Matthews Argument: Common design points to common ancestry Evolutionists say, ‘Studies have found amazing similarities in DNA and biological systems—solid evidence that life on earth has a common ancestor.’ Common structures = common ancestry? In most arguments for evolution, the debater assumes that common physical features, such as five fingers on apes and humans, point to a common ancestor in the distant past. Darwin mocked the idea (proposed by Richard Owen on the PBS dramatization of his encounter with Darwin) that common structures (homologies) were due to a common designer rather than a common ancestor.But the common Designer explanation makes much more sense of the findings of modern geneticists, who have discovered just how different the genetic blueprint can be behind many apparent similarities in the anatomical structures that Darwin saw. Genes are inherited, not structures per se. So one would expect the similarities, if they were the result of evolutionary common ancestry, to be produced by a common genetic program (this may or may not be the case for common design). But in many cases, this is clearly not so. Consider the example of the five digits of both frogs and humans—the human embryo develops a ridge at the limb tip, then material between the digits dissolves; in frogs, the digits grow outward from buds (see diagram below). This argues strongly against the ‘common ancestry’ evolutionary explanation for the similarity. Development of human and frog digits Stylized diagram showing the difference in developmental patterns of frog and human digits.

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Left: In humans, programmed cell death (apoptosis) divides the ridge into five regions that then develop into digits (fingers and toes). [From T.W. Sadler, editor, Langman’s Medical Embryology, 7th ed. (Baltimore, MD: Williams and Wilkins, 1995), p. 154–157.] Right: In frogs, the digits grow outward from buds as cells divide. [From M.J. Tyler, Australian Frogs: A Natural History (Sydney, Australia: Reed New Holland, 1999), 80.]

The PBS program and other evolutionary propagandists claim that the DNA code is universal, and proof of a common ancestor. But this is false—there are exceptions, some known since the 1970s, not only in mitochondrial but also nuclear DNA sequencing. An example is Paramecium, where a few of the 64 codons code for different amino acids. More examples are being found constantly.1 The Discovery Institute has pointed out this clear factual error in the PBS program. 2 Also, some organisms code for one or two extra amino acids beyond the main 20 types. 3The reaction by the PBS spokeswoman,

Eugenie Scott, showed how the evolutionary establishment is more concerned with promoting evolution than scientific accuracy. Instead of conceding that the PBS show was wrong, she attacked the messengers, citing statements calling their (correct!) claim ‘so bizarre as to be almost beyond belief.’ Then she even implicitly conceded the truth of the claim by citing this explanation: ‘Those exceptions, however, are known to have derived from organisms that had the standard code.’To paraphrase: ‘It was wrong to point out that there really are exceptions, even though it’s true; and it was right for PBS to imply something that wasn’t true because we can explain why it’s not always true.’But assuming the truth of Darwinism as ‘evidence’ for their explanation is begging the question. There is no experimental evidence, since we lack the DNA code of these alleged ancestors. There is also the theoretical problem that if we change the code, then the wrong proteins would be made, and the organism would die—so once a code is settled on, we’re stuck with it. The Discovery Institute also demonstrated the illogic of Scott’s claim.4 Certainly most of the code is universal, but this is best explained by common design. Of all the millions of genetic codes possible, ours, or something almost like it, is optimal for protecting against errors.5 But the exceptions thwart evolutionary explanations. DNA comparisons—subject to interpretation Scientific American repeats the common argument that DNA comparisons help scientists to reconstruct the evolutionary development of organisms:Macroevolution studies how taxonomic groups above the level of species change. Its evidence draws frequently from the fossil record and DNA comparisons to reconstruct how various organisms may be related. [SA 80] DNA comparisons are just a subset of the homology argument, which makes just as much sense in a young age framework. A common Designer is another interpretation that makes sense of the same data. An architect commonly uses the same building material for different buildings, and a car maker commonly uses the same parts in different cars. So we shouldn’t be surprised if a Designer for life used the same biochemistry and structures in many different creatures. Conversely, if all living organisms were totally different, this might look like there were manydesigners instead of one.Since DNA codes for structures and biochemical molecules, we should expect the most similar creatures to have the most similar DNA. Apes and humans are both mammals, with similar shapes, so both have similar DNA. We should expect humans to have more DNA similarities with another mammal like a pig than with a reptile like a rattlesnake. And this is so. Humans are very different from yeast but they have some biochemistry in common, so we should expect human DNA to differ more from yeast DNA than from ape DNA.So the general pattern of similarities need not be explained by common-ancestry (evolution). Furthermore, there are some puzzling anomalies for an evolutionary explanation—similarities between organisms that evolutionists don’t believe are closely related. For example, hemoglobin, the complex molecule that carries oxygen in blood and results in its red color, is found in vertebrates. But it is also found in some earthworms, starfish, crustaceans, mollusks, and even in some bacteria. An antigen receptor protein has the same unusual single chain structure in camels and nurse sharks, but this cannot be explained by a common ancestor of sharks and camels. 6 And there are many other examples of similarities that cannot be due to evolution. Debunking the ‘molecular clock’ Scientific American repeats the common canard that DNA gives us a ‘molecular clock’ that tells us the history of DNA’s evolution from the simplest life form to mankind:Nevertheless, evolutionists can cite further ive evidence from molecular biology. All organisms share most of the same genes, but as evolution predicts, the structures of these genes and their products diverge among species, in keeping with their evolutionary relationships. Geneticists speak of the ‘molecular clock’ that records the age of time. These molecular data also show how various organisms are transitional within evolution. [SA 83]Actually, the molecular clock has many problems for the evolutionist. Not only are there the anomalies and common Designer arguments I mentioned above, but they actually a creation of distinct types within ordered groups, not continuous evolution, as non-creationist microbiologist Dr Michael Denton pointed out in Evolution: A Theory in Crisis. For example, when comparing the amino acid sequence of cytochrome C of a bacterium (a prokaryote) with such widely diverse eukaryotes as yeast, wheat, silkmoth, pigeon, and horse, all of these have practically the same percentage difference with the bacterium (64 –69%). There is no intermediate cytochrome between prokaryotes and eukaryotes, and no hint that the ‘higher’ organism such as a horse has diverged more than the ‘lower’ organism such as the yeast.The same sort of pattern is observed when comparing cytochrome C of the invertebrate silkmoth with the vertebrates lamprey, carp, turtle, pigeon, and horse. All the vertebrates are equally divergent from the silkmoth (27–30%). Yet again, comparing globins of a lamprey (a ‘primitive’ cyclostome or jawless fish) with a carp, frog, chicken, kangaroo, and human, they are all about equidistant (73–81%). Cytochrome C’s compared between a carp and a bullfrog, turtle, chicken, rabbit, and horse yield a constant difference of 13–14%. There is no trace of any transitional series of cyclostome → fish → amphibian → reptile → mammal or bird.Another problem for evolutionists is how the molecular clock could have ticked so evenly in any given protein in so many different organisms (despite some anomalies discussed earlier which present even more problems). For this to work, there must be a constant mutation rate per unit time over most types of organism. But observations show that there is a constant mutation rate per generation, so it should be much faster for organisms with a fast generation time, such as bacteria, and much slower for elephants. In insects, generation times range from weeks in flies to many years in cicadas, and yet there is no evidence that flies are more diverged than cicadas. So evidence is against the theory that the observed patterns are due to mutations accumulating over time as life evolved. Genetics and creation demographic events by C.W. Nelson With the relatively recent mapping of the human genome, 1 new questions can be raised concerning potential genetic evidence for creation events (specifically demographic events; that is, events affecting population) such as Creation and the global Flood. Evidence for a Mitochondrial Eve2,3 suggests that the historical record of one man and one woman at the beginning might be accurate, and this idea has already been discussed in the context of creation. 4 When actual measured mutation rates are used with the mitochondrial DNA data, the time frame for Mitochondrial Eve reduces to fit with the biblical Eve.5,6 Single nucleotide polymorphisms and linkage disequilibrium also provide relevant data concerning past populations, and could serve as quite objective evidence for such demographic events as a global flood, for instance. I outline a number of research findings and ideas here. Genetic variation and the population bottleneck By comparing DNA from different humans around the world, it has been found that all humans share roughly 99.9% of their genetic material—they are almost completely identical, genetically.7 This means that there is very little polymorphism, or variation. Much evidence of this genetic continuity has been found. For example, Dorit et al.8examined a 729-base pair intron (the DNA in the genome that is not read to make proteins) from a worldwide sample of 38 human males and reported no sequence variation. This sort of invariance‘ … likely results from either a recent selective sweep, a recent origin for modern Homo sapiens, recurrent male population bottlenecks, or historically small effective male population sizes … any value of Q [lowest actual human sequence diversity] > 0.0011 predicts polymorphism in our sample [and yet none

was found] … . The critical value for this study thus falls below most, but not all, available estimates, thus suggesting that the lack of polymorphism at ZFY [a locus, or location] is not due to chance.’After citing additional evidence of low variation on the Y chromosome, they note in their last paragraph that their results ‘are not compatible with most multiregional models for the origin of modern humans.’ Knight et al.9 have had similar research results:‘We obtained over 55 kilobases of sequence from three autosomal loci encoming Alu repeats for representatives of diverse human populations as well as orthologous sequences for other hominoid species at one of these loci. Nucleotide diversity was exceedingly low. Most individuals and populations were identical. Only a single nucleotide difference distinguished presumed ancestral alleles from descendants. These results differ from those expected if alleles from divergent archaic populations were maintained through multiregional continuity. The observed virtual lack of sequence polymorphism is the signature of a recent single origin for modern humans, with general replacement of archaic populations.’These results are quite consistent with a recent human origin and a global flood. Evolutionary models of origins did not predict such low human genetic diversity. Mutations should have produced much more diversity than 0.1% over millions of years. And yet this is exactly what we would expect to find if all humans were closely related and experienced a relatively recent event in which only a few survived. Research is needed to determine what variation should actually be present in the human genome—what would we expect within an evolutionary framework, and how does that compare with what we find? These results could have a great impact on biological evolution, population genetics, and could provide telling results about the age of the humankind. It could also affect the so-called molecular clock.Another piece of evidence involves single nucleotide polymorphisms (hereafter SNPs), which are mutations common to the human genome (meaning that many humans share them), being present in the human population at a frequency of roughly 1%.7 These provide great insight into both medical research and population genetics. Many humans share large blocks of SNPs (called haplotypes), suggesting that all humans could have descended from a relatively recent demographic event. Linkage disequilibrium (or LD) s the same conclusion. Genes are located on chromosomes in cells, and these genes may either be far away or close to each other. All of the genes that are located on one chromosome are said to be linked. When cells divide through meiosis, crossing over (or genetic recombination) often occurs. This involves two chromosomes aligning and swapping segments of DNA, resulting in genes getting shuffled around. The closer two genes are together, the more likely that they will be inherited together —because they are close, it is unlikely that they will be separated during crossing over. When this holds true, genes are said to be in linkage disequilibrium—a state where they are not thoroughly mixed, but tend to be inherited together.10 Likewise, if genes are thoroughly mixed, they are in equilibrium. LD has provided much evidence for a population bottleneck, because humans contain long-range LD, or LD that extends quite far in the genome, meaning that many genes tend to be inherited together. This type of evidence has been found in Northern Europe, for example. In fact, data gathered by Reich et al.,11 suggests that in general, blocks of LD are large in humans, because many genes are closely associated. The explanation of this can have significant implications: Crossing over (or ‘Why does LD extend so far? LD around an allele [or variant form of a gene] arises because genetic recombination) of selection or population history—a small population size, genetic drift or population mixture during meiosis, results —and decays owing to recombination [crossing over], which breaks down ancestral in shuffled genes. haplotypes [blocks of SNPs]. The extent of LD decreases in proportion to the number of generations since the LD-generating event. The simplest explanation for the observed longrange LD [such as what we find in humans] is that the population under study experienced an extreme founder effect or bottleneck: a period when the population was so small that a few ancestral haplotypes gave rise to most of the haplotypes that exist today.’11This study concluded with the possibility that 50 individuals may have founded the entire population of Europe. This evidence is also quite consistent with a historical global flood. Research is needed on the implications of this data for the flood. Certainly, humankind has undergone a relatively recent (tens of thousands of years at most, within an evolutionary time frame) population bottleneck. However, it must be further investigated as to the proportionality of evolutionary dates to the creation model, and as to how the molecular clock can be adequately explained in such a context. Data aiding this understanding has already been published.5We should also seek to understand genetic evidence in the context of the tower of Babel event. Evidence exists that, after the bottleneck, ‘the [human] population rebounded in a series of separate, rapid expansions on different continents.’12

Evolutionists abandon the idea of 99% DNA similarity between humans and chimps by Daniel Anderson In a recent Science article, several evolutionary scientists openly itted that the claim of 99% DNA similarity between humans and chimpanzees is a myth. 1 Since 1975, this misleading statistic has been touted (e.g., see box) as clear cut evidence that humans and chimps are closely related on the evolutionary tree of life. 2 However, more and more genetic research has revealed that the percentage of DNA similarity has been vastly overstated. Revealing quotes Author Jon Cohen wrote ‘But truth be told … the 1% difference wasn’t the whole story …’ Cohen also wrote about recent studies ‘… raising the question of whether the 1% truism should be retired.’UCSD zoologist, Pascal Gagneux, said ‘For many, many years, the 1% difference served us well because it was underappreciated how similar we were. Now it’s

totally clear that it’s more a hindrance for understanding than a help.’Svante Pääbo, after itting he didn’t think there was any way to actually calculate a precise percentage difference, said ‘In the end, it’s a political and social and cultural thing about how we see our differences.’ In other words, as creationists have long stated, scientific interpretations are often driven by philosophical presuppositions. More recent studies highlight greater genetic differences Last year, a study of gene copy numbers revealed a 6.4% difference. 3In 2005, scientists discovered that the chimpanzee genome was 12% larger than the human genome.In 2003, scientists calculated a 13.3% difference in sections of our immune systems.4One study has even revealed a 17.4% difference in gene expression in the cerebral cortex. 5Creation geneticist, Dr Rob Carter, recently stated on the USA-nationally syndicated Janet Parshall Show, that our genomes are at least 8–12% different. Another icon falls by the wayside Just this year, we have witnessed the downfall of two ‘icons of evolution’. Not only has the idea of 99% genetic similarity between humans and chimps been abandoned, but also the myth of so-called ‘Junk DNA’ has been debunked— see Astonishing DNA complexity uncovered and Astonishing DNA complexity Update. As has so often been observed since Darwin published his Origin of Species, evolutionary icons eventually collapse under the weight of the empirical data. DNA: marvellous messages or mostly mess? by Jonathan Sarfati 2003 is the 50th anniversary of the discovery of the double helix structure of DNA. Its discoverers, James Watson, Francis Crick and Maurice Wilkins, won the Nobel Prize for Physiology and Medicine in 1962 for their discovery. [2011 update: this online version has been updated with animations and links to further amazing discoveries about the multiple codes in DNA.]The amazing design and complexity of living things provides strong evidence for a Designer. Information technology One aspect of this sustenance is that the ‘recipe’ for all these structures on the famous double-helix molecule DNA were programed.1 This recipe has an enormous information content, which is transmitted one generation to the next, so that living things reproduce ‘after their kinds’ .Leading atheistic evolutionist Richard Dawkins its:‘[T]here is enough information capacity in a single human cell to store the Encyclopaedia Britannica, all 30 volumes of it, three or four times over.’ 2Just as the Britannica had intelligent writers to produce its information, so it is reasonable and even scientific to believe that the information in the living world likewise had an original compositor/sender. 3 There is no known non-intelligent cause that has ever been observed to generate even a small portion of the literally encyclopedic information required for life. 4The genetic code (see ‘The programs of life’ below) is not an outcome of raw chemistry, but of elaborate decoding machinery in the ribosome. Remarkably, this decoding machinery is itself encoded in the DNA, and the noted philosopher of science Sir Karl Popper pointed out:‘Thus the code can not be translated The unity of life except by using certain products of its translation. This Many evolutionists claim that the DNA code is constitutes a baffling circle; a really vicious circle, it seems, for universal, and that this is proof of a common any attempt to form a model or theory of the genesis of the ancestor. But this is false—there are exceptions, 5,6 genetic code.’ some known since the 1970s. An example is So, such a system must be fully in place before it could work at Paramecium, where a few of the 64 (4³ or 4x4x4) all, a property called irreducible complexity. This means that it is possible codons code for different amino acids. impossible to be built by natural selection working on small More examples are being found constantly.1 Also, changes.DNA is by far the most compact information storage some organisms code for one or two extra amino system in the universe. Even the simplest known living organism acids beyond the main 20 types. 2 But if one has 482 protein-coding genes. This is a total of 580,000 ‘letters,’ 7 organism evolved into another with a different —humans have three billion in every nucleus. (See ‘The code, all the messages already encoded would be programs of life’, for an explanation of the DNA ‘letters.’)The scrambled, just as written messages would be amount of information that could be stored in a pinhead’s volume jumbled if typewriter keys were switched. This is a of DNA is equivalent to a pile of paperback books 500 times as huge problem for the evolution of one code into high as the distance from Earth to the moon, each with a another.Also, in our cells we have ‘power plants’ 8 different, yet specific content. Putting it another way, while we called mitochondria, with their own genes. It turns think that our new 40 gigabyte hard drives are advanced out that they have a slightly different genetic code, technology, a pinhead of DNA could hold 100 million times more too.Certainly most of the code is universal, but this information.The ‘letters’ of DNA have another vital property due to is best explained by common design—one their structure, which allows information to be transmitted: A pairs designer. Of all the millions of genetic codes only with T, and C only with G, due to the chemical structures of possible, ours, or something almost like it, is the bases—the pair is like a rung or step on a spiral staircase. optimal for protecting against errors. 3 But the This means that the two strands of the double helix can be created exceptions thwart attempts to explain the separated, and new strands can be formed that copy the organisms by common-ancestry evolution. information exactly. The new strand carries the same information as the old one, but instead of being like a photocopy, it is in a sense like a photographic negative. The copying is far more precise than pure chemistry could manage—only about 1 mistake in 10 billion copyings, because there is editing (proofreading and error-checking) machinery, again encoded in the DNA. But how would the information for editing machinery be transmitted accurately before the machinery was in place? Lest it be argued that the accuracy could be achieved stepwise through selection, note that a high degree of accuracy is needed to prevent ‘error catastrophe’—the accumulation of ‘noise’ in the form of junk proteins. Again there is a vicious circle (more irreducible complexity).Also, even the choice of the letters A, T, G and C now seems to be based on minimizing error. Evolutionists usually suppose that these letters happened to be the ones in the alleged primordial soup, but research shows that C (cytosine) is extremely unlikely to have been present in any such ‘soup.’9 Rather, Dónall Mac Dónaill of Trinity College Dublin suggests that the letter choice is like the advanced error-checking systems that are incorporated into ISBNs on books, credit card numbers, bank s and airline tickets. Any alternatives would suffer error catastrophe.10 Introns

DNA is not read directly, but first the cell makes a negative copy in a very similar molecule called RNA, 11 a process called transcription. But in all organisms other than most bacteria, there is more to transcription. This RNA, reflecting the DNA, contains regions called exons that code for proteins, and non-coding regions called introns. So the introns are removed and the exons are ‘spliced’ together to form the mRNA (messenger RNA) that is finally decoded to form the protein. This also requires elaborate machinery called a spliceosome. This is assembled on the intron, chops it out at the right place and s the exons together (see also this animation of the spliceosome machinery). This must be in the right direction and place, because, as shown above, it makes a huge difference if the exon is ed even one letter off. Thus, partly formed splicing machinery would be harmful, so natural selection would work against it. Richard Roberts and Phillip Sharp won the 1993 Nobel Prize in Physiology and Medicine for discovering introns in 1977. It turns out that 97–98% of the genome may be introns and other non-coding sequences, but this raises the question of why introns exist at all. [Update, 2011: now we know there is a splicing code; see related articles below.] Junk DNA? Dawkins and others have claimed that this non-coding DNA is ‘junk,’ or ‘selfish’ DNA. Supposedly, no intelligent designer would use such an inefficient system, therefore it must have evolved, they argue. This parallels the 19th century claim that about a hundred ‘vestigial organs’ exist in the human body,12 i.e. allegedly useless remnants of our evolutionary history.13 But more enlightened evolutionists such as Scadding pointed out that the argument is logically invalid, because it is impossible in principle to prove that an organ has no function; rather, it could have a function we don’t know about. Scadding also reminds us that ‘as our knowledge has increased the list of vestigial structures has decreased.’14,15,16While Dawkins has often claimed that belief in a designer is a ‘cop-out,’ it’s claims of vestigial or junk status that are actually ‘copouts.’ Such claims hindered research into the vital function of allegedly vestigial organs, and they do the same with non-coding DNA. Actually, even if evolution were true, the notion that the introns are useless is absurd. Why would more complex organisms evolve such elaborate machinery to splice them? Rather, natural selection would favour organisms that did not have to waste resources processing a genome filled with 98% junk. And there have been many uses discovered for so-called junk DNA, such as the overall genome structure and regulation of genes. Some creationists believe that this DNA has a role in rapid post-Flood diversification of the ‘kinds’.17Some non-coding RNAs called microRNAs (miRNAs) seem to regulate the production of proteins coded in other genes, and seem to be almost identical in humans, mice and zebrafish. The recent sequencing of the mouse genome18surprised researchers and led to headlines such as ‘“Junk DNA” Contains Essential Information.’ 19 They found that 5% of the genome was basically identical but only 2% of that was actual genes. So they reasoned that the other 3% must also be identical for a reason. The researchers believe the 3% probably has a crucial role in determining the behaviour of the actual genes, e.g. the order in which they are switched on. 20Also, damage to introns can be disastrous—in one example, deleting four ‘letters’ in the centre of an intron prevented the spliceosome from binding to it, resulting in the intron being included.21 Mutations in introns also interfere with imprinting, the process by which only certain genes from the mother or father are expressed, not both. Expression of both genes results in a variety of diseases and cancers. 22Another intriguing discovery is that DNA can conduct electrical signals as far as 60 ‘letters,’ enough to code for 20 amino acids. This is a typical length for molecular switches that turn on ading genes. Theoretically, the electrical signals could travel indefinitely. However, single or multiple pairings between A and T stop the signals; that is, they are insulators or ‘electronic hinges in a circuit.’ So, although these particular regions don’t code for proteins, they may protect essential genes from electrical damage from free radicals attacking a distant part of the DNA. 23 So times have changed—Alexander Hüttenhofer of the University of Münster, , says: ‘Five or six years ago, people said we were wasting our time. Today, no one regards people studying non-coding RNA as time-wasters.’24 Advanced operating system? Dr John Mattick of the University of Queensland in Brisbane, More than just a super hard drive Australia, has published a number of papers arguing that the Actually, DNA is far more complicated than simply non-coding DNA regions, or rather their non-coding RNA coding for proteins, as we are discovering all the ‘negatives,’ are important components of a complicated genetic time.1 For example, because the DNA letters are network.25,26 These interact with each other, the DNA, mRNA and read in groups of three, it makes a huge difference the proteins. Mattick proposes that the introns function as nodes, which letter we start from. E.g. the sequence linking points in the network. The introns provide many extra GTTCAACGCTGAA … can be read from the first connections, enabling what in computer terminology would be letter, GTT CAA CGC TGA A … but a totally called multi-tasking and parallel processing.In organisms, this different protein will result from starting from the network could control the order in which genes are switched on second letter, TTC AAC GCT GAA … and off. This means that a tremendous variety of multicellular life This means that DNA can be an even more could be produced by ‘rewiring’ the network. In contrast, ‘early compact information storage system. This partly computers were like simple organisms, very cleverly designed explains the surprising finding of The Human 27 [sic], but programmed for one task at a time.’ The older Genome Project that there are ‘only’ about 35,000 computers were very inflexible, requiring a complete redesign of genes, when humans can manufacture over the network to change anything. Likewise, single-celled 100,000 proteins. organisms such as bacteria can also afford to be inflexible, because they don’t have to develop as many-celled creatures do. Evolutionary interpretation Mattick suggests that this new system somehow evolved (despite the irreducible complexity) and in turn enabled the evolution of many complex living things from simple organisms. However, the same evidence is better interpreted from a young age framework. This system can indeed enable multicellular organisms to develop from a ‘simple’ cell—but this is the fertilized egg. This makes more sense; the fertilized egg has all the programming in place for all the information for a complex life-form to develop from an embryo.It is also an example of good design economy pointing to a single designer as opposed to many. In contrast, the first simple cell to allegedly evolve the complex splicing machinery would have no introns

needing splicing.But Mattick may be partly right about diversification of life. Creationists also believe that life diversified— after the Flood. However, this diversification involved no new information. Some creationists have proposed that certain parts of currently non-coding DNA could have enabled faster diversification, 28 and Mattick’s theory could provide still another mechanism. Hindering science A severe critic of Mattick’s theory, Jean-Michel Claverie of CNRS, the national research institute in Marseilles, , said something very revealing: The circle of life All living things have encyclopedic information content, a recipe for all their complex machinery and structures.This is stored and transmitted to the next generation as a message on DNA ‘I don’t think much of this work. In general, all these global ideas ‘letters,’ but the message is in the arrangement, don’t travel very far because they fail to take into the not the letters themselves.The message requires most basic principle of biology: things arose by the additive decoding and transmission machinery, which itself addition of evolution of tiny subsystems, not by global design. It is is part of the stored ‘message.’The choices of the perfectly possible that one intron in one given gene might have code and even the letters are optimal.Therefore, evolved—by chance—some regulatory property. It is utterly the genetic coding system is an example of improbable that all genes might have acquired introns for the irreducible complexity. future property of regulating expression.’ Two points to note: This agrees that if the intron system really is an advanced operating system, it really would be irreducibly complex, because evolution could not build it stepwise.It illustrates the role of materialistic assumptions behind evolution. Usually, atheists such as Dawkins use evolution as ‘proof’ for their faith; in reality, evolution is deduced from their assumption of materialism! E.g. Richard Lewontin wrote, ‘ … we have a prior commitment, a commitment to materialism. … Moreover, that materialism is absolute, for we cannot allow a Divine Foot in the door.’ 29 Scott Todd said, ‘Even if all the data point to an intelligent designer, such an hypothesis is excluded from science because it is not naturalistic.’30 Similarly, while many use ‘junk’ DNA as ‘proof’ of evolution, Claverie is using the assumption of evolution as ‘proof’ of its junkiness! This is again a parallel with vestigial organs. In reality, evolution was used as a proof of their vestigiality, and hindered research into their function. Claverie’s attitude could likewise hinder research into the networking capacity of noncoding DNA. Summary ‘Junk DNA’ (or, rather, DNA that doesn’t directly code for proteins) is not evidence for evolution. Rather, its alleged junkiness is a deduction from the false assumption of evolution. Just because no function is known, it doesn’t mean there is no function. Many uses have been found for this non-coding DNA. There is good evidence that it has an essential role as part of an elaborate genetic network. This could have a crucial role in the development of many-celled creatures from a single fertilized egg, and also in the post-Flood diversification (e.g. a canine kind giving rise to dingoes, wolves, coyotes etc.).

The programs of life Information is a measure of the complexity of the arrangement of parts of a storage medium, and doesn’t depend on what parts are arranged. For instance, the printed page stores information via the 26 letters of the alphabet, which are arrangements of ink molecules on paper. But the information is not contained in the letters themselves. Even a translation into another language, even those with a different alphabet, need not change the information, but simply the way it is presented. However, a computer hard drive stores information in a totally different way—an array of magnetic ‘on or off’ patterns in a ferrimagnetic disk, and again the information is in the patterns, the arrangement, not the magnetic substance. Totally different media can carry exactly the same information. An example is this article you’re reading—the information is exactly the same as that on my computer’s hard drive, but my hard drive looks vastly different from this page. In DNA, the information is stored as sequences of four types of DNA bases, A,C,G and T. In one sense, these could be called chemical ‘letters’ because they store information an analogous way to printed letters. 1 There are huge problems for evolutionists explaining how the ‘letters’ alone could come from a primordial soup.2 But even if this was solved, it would be as meaningless as getting a bowl of alphabet soup.The ‘letters’ must then link together, in the face of chemistry trying to break them apart. 3 Most importantly, the letters must be arranged correctly to have any meaning for life.A group (codon) of 3 DNA ‘letters’ codes for one protein ‘letter’ called an amino acid, and the conversion is called translation. Since even one mistake in a protein can be catastrophic, it’s important to decode correctly. Think again about a written language—it is only useful if the reader is familiar with the language. For example, a reader must know that the letter sequence c-a-t codes for a furry pet with retractable claws. But consider the sequence g-i-f-t—in English, it means a present; but in German, it means poison. Understandably, during the post–September-11 anthrax scare, some German postal workers were very reluctant to handle packages marked ‘Gift.’

DO GENE DUPLICATION AND POLYPLOIDY PROVIDE A MECHANISM FOR EVOLUTION Do new functions arise by gene duplication? by Yingguang Liu and Dan Moran Evolution requires a simple form of life to have morphed into increasingly complex organisms. Since the basis for biological complexity is genetic complexity, some biologists propose that the complicated genomes in modern organisms arose from

one or a few genes in a common ancestor through duplication, with subsequent neofunctionalization through mutation and natural selection. Here we examine the known mechanisms of gene duplication in the light of genomic complexity and postduplication events, and argue that: (1) gene duplications are aberrations of cell division processes and are more likely to cause malformation or diseases rather than selective advantage; (2) duplicated genes are usually silenced and subjected to degenerative mutations; (3) regulation of supposedly duplicated gene clusters and gene families is irreducibly complex, and demands simultaneous development of fully functional multiple genes and switching networks, contrary to Darwinian gradualism. Figure 1. Equal (a) and unequal (b) crossing-over. Black and white colours represent homologous chromosomes. Only one sister chromatid of each chromosome is shown. After unequal crossing-over, one chromosome gains an extra repetition of ABC genes while the other chromosome loses DNA and becomes shorter. ‘Natural selection merely modified, while redundancy created.’1‘It might be said that all of the new genes arose from redundant copies of the pre-existed [sic] genes.’2Regardless of how the first gene came into being, it is taught in textbooks that gene duplication is the major force driving evolution.3,4 Gene duplications do indeed add extra material to the genome, for example, by aberrations in the division of chromosomes during mitosis or meiosis, or by erroneous DNA replication. Evolutionists argue that with subsequent mutation and natural selection, one or all copies of a duplicated gene eventually encode new proteins (a process called ‘neofunctionalization’). Over millions of years, small simple genomes thus are believed to have evolved into large, complex ones, giving rise to the multiplicity of life forms both living and extinct.One frequently cited evidence for gene duplication comes from gene sequence analyses. Sequence comparisons have revealed that some genes in modern organisms are more similar to each other than to other genes, and so they are classified into families. Gene families are especially abundant in large genomes. Family within a genome, the paralogs, are believed to be products of gene duplications that have occurred in the past. Furthermore, functional domains of many proteins encoded by apparently unrelated genes also bear structural and functional similarities. All of these are used as evidence that the thousands of genes discovered so far (and those yet to be discovered) have evolved from a few—maybe one—ancestral gene(s).5In this article we examine the major mechanisms proposed for gene duplication and evaluate their likely contribution to the history of life in the light of recent evidences on post-duplication events and gene regulation mechanisms. Mechanisms of gene duplication Polyploidy Polyploidy refers to an increase in the number of sets of chromosomes per cell. Normally, most eukaryotic cells are diploid (with two sets of chromosomes, 2n, one from the male parent and one from the female parent) while the sex cells are haploid (with one set of chromosomes, 1n). A cell with 3n or more is polyploid. Polyploidy may arise naturally when a cell fails to divide after DNA replication. If the cell with doubled genome is involved in the generation of sex cells (meiosis), polyploid organisms may be subsequently produced upon fertilization. Alternatively, polyploidy can be artificially induced by treating cells with chemicals such as colchicine.Since all genes are duplicated simultaneously in a polyploid cell, the stoichiometric relationships between genetic products are preserved. For this reason, polyploidy is the least detrimental and therefore the best surviving duplication mutation. 6 Polyploidy is seen in ferns, flowering plants and some lower animals. 7,8 It is usually associated with hermaphroditism, parthenogenesis (mother producing young asexually), or species without disparate sex chromosomes.8 In most dioecious (possessing either male or female organs) animals and humans, however, polyploid embryos typically suffer generalized malformation and die during development.8 It is not only sex determination per se (as was proposed by Muller9 ), but more importantly, the delicate balancing between homologous genes, that is disrupted in polyploid individuals of higher animals. For instance, parental imprinting (differences in the expression of maternal and paternal genes) by DNA methylation may be disrupted as the cell endeavours to silence extra chromosomes by extensive methylation (see below under ‘After duplication’).Autopolyploidy (all chromosome sets are from the same species) can result in useful variation of quantitative traits such as biomass, organ size, flowering time, drought tolerance, etc. But crucially, polyploid organisms have an intrinsic mechanism to maintain genetic stability by silencing extra copies of genes (inhibiting their expression).10 Silencing of homeologs (genes duplicated by polyploidy) is nonrandom, genetically programmed, and organspecific. It is a universal phenomenon seen in both plants and animals.7,11 Silencing of inferior alleles may be able for the advantageous phenotypes of some polyploid species. Alternatively, superior alleles may take dominance even though inferior ones are expressed simultaneously. In other words, there are no new genetic products, but old genes with altered expression levels under the control of pre-existing programs. Figure 2. (a) Xenopus globin gene clusters.50,51Grey: tadpole; Dark: adult. 53 (b) Human globin gene clusters. Light grey: embryonic; Dark grey: fetal; Dark: fetal/adult (α) or adult only (δ and β); White: pseudogenes. Intergenic spacer sequences are omitted.Allopolyploidy results when the sets of chromosomes are derived from two or more distinct, though related species. Unlike allodiploid hybrids such as the mule, allopolyploid organisms may be fertile and give rise to new species. However, the hybrid species display merely a new combination of pre-existing parental traits encoded by pre-existing genes. For example, some strains of the Triticale, synthetic allopolyploids from wheat and rye, combine the high yield of wheat and the adaptability of rye. Another artificial hybrid species between the tall fescue grass (Festuca arundinacea) and the short Italian ryegrass (Lolium multiflorum) shows quantitative traits (e.g. height) that are intermediate between the parental species.12 The historical Raphanobrassica, hybrid between cabbage and radish, has

the roots of cabbages and leaves resembling that of a radish.In allopolyploids there may be interactions between genes from different parents.13Disharmonious interactions between homeologous genes are thought to be the reason for most cases of hybrid sterility in allodiploid animals. 14 In plants, neoallopolyploid genomes are often unstable, displaying ‘sterility, lethality, and phenotypic instability’.15 Trisomy In contrast to polyploidy, aneuploid cells (having a chromosome number that is not a multiple of the haploid) with one extra chromosome (trisomy) have a severely imbalanced genome. Consequently, the organism will manifest defective phenotypes. Aneuploidy is the result of failure to segregate a pair of homologous chromosomes during meiosis I or failure to segregate sister chromatids during meiosis II (meiotic nondisjunction). When a sex cell with one extra chromosome unites with a normal haploid sex cell, the zygote will be trisomic for that particular chromosome. Much knowledge about trisomy has been accumulated clinically in humans. Autosomal trisomies have more dramatic effects than sex chromosome trisomies. From the familiar Down syndrome (21 trisomy) to the less common Edward syndrome (18 trisomy) and Patau syndrome (13 trisomy), autosomal trisomies always hinder the development of the central nervous system and manifest mental retardation in live births. Developmental defects of other organs are also common. Trisomies involving other autosomes are rare, and are seen only in spontaneous abortions and in vitro fertilizations.16Triplo-X females (karyotype XXX) have only mild symptoms (tallness and menstrual irregularities). While men with Klinefelter syndrome (karyotype XXY) show symptoms varying from infertility to severe structural deformation, XYY males are generally normal except for tallness and acne.17 The reason that sex chromosome trisomies show less severe symptoms than autosomal trisomies may lie in the fact that the X chromosome has a well established intrinsic inactivation mechanism to silence one homo the normal woman; while the Y chromosome is small with few genes. Unequal crossing-over Crossing-over refers to the exchange of fragments between homologous chromosomes during the initial stages of meiosis. Normally the exchange is equal as the genes line up based on sequence homology (synapsis). However, because of the numerous sequence repetitions in eukaryotic chromosomes, the lining up may be inaccurate, causing deletion in one chromosome and duplication in the other (figure 1). The mechanism is believed to be the major cause of deletions of red or green pigment genes in the X chromosome resulting in colour blindness and deletions of globin genes causing various forms of thalassemias.18,19 Repeated duplications have been associated with cancer.20 Duplication of a large segment of chromosome 15 in human beings can cause mental retardation and other symptoms while smaller duplications are asymptomatic or cause minor disorders such as panic attacks. Presumably, small segmental duplications are successfully managed by the cell’s silencing programs. However, segmental duplications within protein-coding sequences may interrupt gene structure, causing frame-shift mutations.21 Figure 3. Viral genes are expressed sequentially in a highly regulated hierarchy. Each set of viral genes encode transcription factors that turn on the next set of genes by interacting with their corresponding promoter/enhancer sequences. Unequal crossing-over may have been the major mechanism in altering the number of genes in repetitive clusters. Gene clusters such as the human green pigment genes and the human immunoglobulin heavy chain genes that vary in numbers within the population certainly manifest recent duplications.22,23 Clusters of identical rRNA and histone genes also vary in number within the species, presumably via unequal crossing-over.24–28 Recently, it has been found that copy-number polymorphisms of this kind are more abundant than previously realized. 29,30However, it is unlikely that gene clusters originated through unequal crossing-over, because: (1) unequal crossing-over depends on pre-existing clustering. Although it may change the number of repetitions within clusters, unequal crossing-over is not the ultimate cause of their being; (2) multiplicity of identical genes in the clusters is often required for the cell to function properly. For instance, to meet the need of the cell to produce large numbers of ribosomes in a short time, all cells contain multiple copies of rRNA genes in tandem arrays. In the large oocyte (egg) of amphibians, the rRNA genes have to be further amplified approximately 2000-fold, resulting in about a million copies per cell, to maintain the number of ribosomes at about 1012.31 Likewise, multiple histone genes are required for the cell to synthesize histones rapidly during S phase of the cell cycle. But diversification and neofunctionalisation of these identical copies is actually prevented, not promoted, by as yet unknown mechanisms.32 Transposition Transposons are mobile genetic elements that can change their positions within the genome (the process is known as transposition). While some transpositions occur by a ‘cut and paste’ mechanism, others go by a ‘copy and paste’ mechanism, resulting in duplications. Unlike unequal crossing-over that produces tandem gene arrays, transpositions cause duplications dispersed randomly throughout the genome. Transposons that duplicate via an RNA intermediate, known as retrotransposons, are abundant in eukaryotic cells.Despite the abundance of transposons and retrotransposons in complex genomes (e.g. 45% of the human genome), their function remains elusive. Traditionally, they have been considered as ‘selfish DNA’ because random insertion of transposons disrupts other genes, causing deleterious mutations. A classical example is the Drosophila retrotransposon, the P element, which induces chromosomal breaks and causes sterility.33 Consequently, it seems to be beneficial to the organism for transposition events to be suppressed. Indeed, transposition is rare in the human cell. (Therefore, the vast majority of the human transposable elements must have been present in the genome since ancient times.) However, in mice, Drosophila (fruit-fly), and Arabidopsis (plant), transposition is still responsible for many mutations.34Recently, Peaston and associates discovered that retrotransposons are actively transcribed in mouse oocytes and early embryos, providing alternative promoters and first exons to a subset of host genes.35 This report suggests that transposons function as regulatory elements during early development. From this point of view, transposition-induced mutation may be a side effect, instead of the intended function, of these repetitive genetic elements. After duplication

Figure 4. The major immediate early gene (mIE) of the human cytomegalovirus is regulated by a network of viral and cellular factors. IE1 and IE2 are products of the gene through alternative splicing. IE1 acts as a positive signal to accelerate initial transcription, while IE2 provides a negative mechanism by binding to a cis-repression signal (crs) later in infection. Viral proteins pp71 and ppUL35 interact with each other. pp71 also binds to a host cell protein, hDaxx. IE1, IE2, the enhancer, pp71 and ppUL35 are all critical for effective viral replication.In order for evolution to harness gene duplications to produce complex genomes, it was originally proposed that one or more copies of the duplicated gene will acquire advantageous mutations (neofunctionalization).5,36,37 This was thought to be the only mechanism to generate new genes from existing ones.38 However, biologists are now becoming more and more convinced theoretically and empirically that most duplicated gene copies undergo degenerative, rather than constructive, mutations, ending up in nonfunctionalization.As stated above, the first event awaiting a duplicated gene is silencing. The best studied mechanism of silencing is through methylation of cytosine bases in CG islands around promoters. 39 Subsequently, methylated cytosines tend to be spontaneously deaminated and are substituted with thymine bases. 39,40 The phenomenon is known as CG depletion. Duplicated genes are especially prone to CG depletion. 39–41 Without selective constraint, silenced duplicates may also undergo other mutations. Indeed, ‘extensive genomic change’ can be detected within a few generations after synthetic polyploidy.42 Using silent mutations (mutations that do not affect translated protein structures) to reflect time, Lynch and Conery calculated that duplicated genes are lost exponentially with time and are ‘nonfunctionalized by the time silent sites have diverged by only a few percent’.6 On the other hand, mutations in functioning gene family are limited by purifying selection. In paralogous genes that evolutionists believe were created by ancient duplication events, ‘only about 5% of amino acid-changing mutations are able to rise to fixation’.6 There is a recent report that mutation rates in gene family are actually lower than in singletons (genes without paralogs).43 In contrast, differences in amino acid sequences between modern paralogous genes are generally large, e.g. 58% between human α and β globins, 28% between human β and γ globins, 75% between human β globin and myoglobin.Faced with this dilemma, some evolutionists theorized that mutations leading to neofunctionalization must have happened within a brief period of time immediately after duplication (in spite of the fact that the frequent mutations observed in recent duplicates are mostly degenerative).43 Realizing the impossibility of neofunctionalization, Lynch and Conery argued that gene duplication only ively contributes to the generation of biodiversity by building up reproductive barriers as duplicates are silenced stochastically.6 In other words, gene duplication does not produce new genes because silencing and subsequent degradation of duplicated genes cannot provide new information.Meanwhile, several other models have been proposed concerning the fate of duplicated genes. One theory states that both the original and duplicated gene copies each lose only part of their function through degenerative mutations (subfunctionalization). If each gene copy retains a different fraction of its original function, the duplicates may complement each other and function together as one gene. If the regulatory elements of duplicated genes subfunctionalize (while the protein-coding regions are somehow spared from degeneration), they may be expressed at different stages/tissues. The theory is known as duplicationdegeneration-complementation (DDC) model.44–46 The DDC model may allow partial preservation of duplicated genes, but it fails to explain the evolution of new genes or new regulatory elements. (Let alone the complicated mechanisms of tissue/organ-specific regulation. See below under ‘Gene Regulation’). Figure 5. Proposed initial coagulation network (a)and proposed intermediate coagulation network after gene duplication (b).75 Line arrows: activation; block arrows: conversion. Recently, another model, called epigenetic complementation (EC), has been proposed by Rodin and colleagues. 47,48 The theory states that if a gene is copied into a different position within the genome, it may be put under the control of a different regulatory environment and therefore expressed in a different tissue or stage of life. Epigenetic silencing mechanisms (such as cytosine methylation) work in such a way that one copy is silenced whenever or wherever the other copy is expressed. According to this model, there is no need for mutation to alter the regulatory elements of the duplicates in order to achieve complementation.The EC model does not explain the existence of clustered gene families with divergedfunctions for each member. For example, the linked α and β globin genes in Xenopus laevis are expressed at different (tadpole and adult) stages of life (figure 2).49–51 But their temporal regulation is difficult to explain with differing epigenetic environments, since the adult genes are sandwiched between tadpole genes. Rather, it can be better ed for by differences in their regulatory sequences that respond to stage-specific transcription factors.52,53Similarly, of the clustered human α globin gene family are expressed in two stages (embryonic and adult) and the clustered β globin gene family are expressed in three stages (embryonic, fetal, and adult) (figure 2). Again, temporal regulation (especially silencing) is accomplished genetically, rather than epigenetically, via distinct regulatory elements associated with the genes. 54–56 Furthermore, there is no change in regulation of the globin genes after the supposed separation of α and β genes onto different chromosomes in mammals and birds. Both the ζ gene of the α family and the ε gene of the β family are expressed during the embryonic stage in human development, to form the ζ 2 ε2 tetramer, even though they are on different chromosomes; while the α and β genes are expressed simultaneously in adults. Like the DDC model, the EC model still depends on mutation and natural selection for neofunctionalization.

Genome complexity If the evolution-by-gene-duplication theory is correct then DNA content and gene number should increase proportionately with organism complexity. However, this is not the case (Table 1). For example, the unicellular algae, Euglena, has a bigger genome than some vertebrate animals such as zebrafish and chicken. Amphibians may have genomes larger than some birds and mammals. The plant, Zea mays (corn), has more genomic DNA than does the human species. This phenomenon, known as the C-value paradox, demonstrates that the amount of genomic DNA is certainly not a good index for biological complexity. Table 1. Genome characteristics of selected species.57–59 Table 1 also shows that the number of genes within a genome does not increase in proportion to the amount of genomic DNA. As a general rule, larger genomes have sparser genes. Prokaryotic genomes are much more compact than eukaryotic genomes, e.g. 89% of Haemophilusgenome consists of protein-coding genes as compared to 1–1.5% in the human genome. Consequently, the number of genes is an even poorer indicator of genome complexity than haploid DNA content. For example, human beings with 1014 cells have a total gene number comparable to that of Caenorhabditis elegans, which has only 959 somatic cells. Likewise, Drosophila, with its 50,000 cells, has only twice as many genes as the single-celled baker’s yeast.In other words, simpler organisms already have DNA content and gene numbers comparable to that of advanced species. Further gene duplication (and mutation) will not help them climb up Darwin’s tree of life. Gene regulation Of course, it is not only the number of cells, but also the types of cells in an organism, that indicates complexity. On the genetic level, differentiation into various cell types is a result of the spatial and temporal regulation of genes. Therefore, the genes for transcription factors, which act as molecular switches in the genome, have much to do with genetic complexity. Prokaryotic genes are generally regulated as a group (polycistronic, i.e. several genes are controlled by one transcription factor) while eukaryotic genes are regulated individually (monocistronic).Szathmary and associates proposed a mathematical formula to calculate genome complexity in of the interactions between genes (usually through their encoded protein products including transcription factors).60 He borrowed a parameter, connectivity (C), from ecology which uses the term to describe trophic interactions in food webs: C = 2 L/[N(N-1)] L refers to the number of interactions among genes (it originally meant ‘trophic links’ in ecology), while N refers to the number of genes in a genome (originally the number of species in an ecosystem). C is equal to the number of actual interactions out of all possible interactions.The most important aspect of genetic interaction that determines the value of C in Szathmary’s equation is the number of levels constituting a regulation hierarchy. In ecosystems, adding trophic levels generates more connectivity than increasing the number of species. Like a food chain, a gene regulation pathway can have multiple levels of interactions, whereby upstream transcription factors regulate downstream transcription factors.The concept of irreducible complexity61 applies to gene regulation systems. An irreducibly complex system is one in which all the essential parts must be present at the same time, and thus could not have been built up slowly over millions of years in a step-wise Darwinian fashion. In order for a gene regulation unit to function, many genetic elements, including trans-acting elements that encode the transcription factors, cis-acting elements that respond to the transcription factors, and the structural genes, have to be present simultaneously. Although there are examples of functional overlaps between pathways, multiple unique elements are usually required for each pathway. Knocking out any of the elements will frequently result in dysfunction, even loss of life.In the simplest case, many viruses have three sets of genes regulated as a cascade (figure 3). The immediate-early (α) genes have promoter elements (binding sites for RNA polymerase or some transcription factors) similar to those of the host cell and are transcribed by a host cell RNA polymerase. The products of immediate-early genes are mostly transcription factors that interact with the cis-acting regulatory elements (promoter/enhancer) of early (β) genes. The early gene products, in their turn, activate the late (γ) genes, by interacting with their cis-acting elements. The early genes also encode enzymes to replicate the viral DNA, so that the late genes are multiplied before their expression, allowing for rapid accumulation of late gene products toward the end of infection. This scenario enables the virus to divert the resources of the host cell to the production of new viruses effectively.A specific example of a regulation network is the major immediate-early gene (mIE) of the human cytomegalovirus (HCMV) which encodes two major products, IE1 and IE2, by alternative splicing (figure 4). The two proteins act synergistically to activate the β genes. Adjacent to the gene is a 1.1-Kb cis-regulatory sequence called the major immediate-early enhancer-promoter (MIEP), which contains concentrated binding sites for multiple cellular transcription factors. One of the products of the mIE gene, IE1, functions as an autoregulatory trans-activator that recruits a cellular protein, NF-kB, which binds to the enhancer and activates transcription. The IE2 product of the gene, on the other hand, represses the gene by binding to a cis-repression sequence (crs, see figure 4).62 The virus also carries several other viral proteins into the host cell for effective transcription of mIE. Among these are ppUL35 and pp71, which interact with each other in the infected cell. 63,64Meanwhile, pp71 interacts with a cellular protein, hDaxx, which is required for mIE transcription. 65Because the viral genome is relatively small and easy to manipulate, HCMV provides a good model in which to study the effects of knocking out a gene from the genome. Deletion of the sequences that encode IE2, or the proximal portion of the enhancer, from the HCMV genome completely inactivates the virus. 66,67 Deletion of any of the genes that encode IE1, pp71, or ppUL35 renders the virus incapable of replicationin vitro at low multiplicity of

infection (MOI), which resembles natural human infection.68–70 All these regulatory factors have to be present and functional at the same time for HCMV to survive (if it cannot replicate it becomes extinct)..Virus genomes are far simpler in the complexity of their regulation than prokaryotes and eukaryotes, so it follows that their regulatory systems are also irreducibly complex. For evolution to have occurred via gene duplication, both the gene and its cis-regulatory elements have to be duplicated simultaneously. Furthermore, since gene family often have distinctly different expression patterns, both the gene and the cis-regulatory elements have to mutate concertedly in order to confer a selective advantage to the organism. For example, the ζ and ε globins have to acquire higher oxygen affinity than the α and β globins in order for the embryonic hemoglobin tetramer ζ2 ε2 to extract oxygen from the maternal α2 β2tetramers. Meanwhile, the regulatory elements of the embryonic and adult globins have to develop binding affinity for the transcription factors expressed during their respective developmental stages. Most importantly, a delicate globin switching mechanism, known to involve numerous trans-acting factors and multiple levels of regulation, has to be developed. In the case of the human β-like globin switching, which is the best understood, some of these factors are universal, while others are erythroid-specific. 54–56,71Deletion of the regulatory elements or a member of the gene family will result in thalassemia.Another example of clustered gene families whose expression follows a temporal pattern is the immunoglobulin heavy chain family produced by B lymphocytes. There are five classes and each has properties that cannot be replaced by others. All B lymphocytes start by secreting IgM and switch to IgG, IgE, or IgA within a few days via a complex switching mechanism. 72–74 The most important aspect of class switch is targeting of DNA recombination enzymes to specific sites. Gene duplication theory would require coordinated mutations in the structural genes and the cis-regulatory elements, and a unique recombination mechanism different from the known mechanisms.Michael Behe used the blood clotting factors to illustrate irreducible complexity. 61 Dozens of proteins activate or inhibit each other in the blood coagulation and subsequent clot-dissolving pathways. Accidental deletion of factors leads to diseases such as hemophilia. Since many factors share similar functional domains, they are thought to have evolved by ancient gene duplication events, including polyploidy during the Cambrian explosion. 75–77 However, these duplications have to be followed by coordinated mutations that ‘work just right’. A proposed functional intermediate blood clotting pathway75 in figure 5 shows how much coordinated change is required. Conclusion The majority of gene duplications are meiotic or mitotic aberrations, resulting in malformations or diseases. Plants can tolerate duplications, especially polyploidy, better than animals due to differences in their styles of reproduction. To maintain genomic stability, all cells have built-in mechanisms to silence duplicated genes, after which they become subject to degenerative mutations.Clusters of identical genes need complicated mechanisms to prevent diversification in order for them to work in unison. Likewise, gene families whose perform distinct functions are maintained by purifying selection. While duplication may alter the number of in gene families, it is not their ultimate origin. Current models explaining the preservation and neofunctionalization of duplicated genes encounter obstacles one way or the other.Evolution by gene duplication predicts a proportional increase in genome size with organism complexity but this is contradicted by the evidence. It is not genome size but intergenic regulatory sequences and gene regulation hierarchies that determine complexity. Gene regulation networks are irreducibly complex and constitute an insurmountable barrier for the theory. Does gene duplication provide the engine for evolution? by Jerry Bergman Proponents of the gene-duplication hypothesis of evolution argue that a mutation can cause the duplication of a gene that allows one copy of the gene to mutate and evolve to perform a novel function, while allowing the other copy of the gene to continue to perform the original gene’s function. Gene duplication is now widely believed by Darwinists to be the main source of all new genes. A review of the evidence shows that there are numerous problems and contradictions in this theory and the empirical evidence indicates that gene duplication has a role in variation within kinds but not in evolution. Darwinists therefore have nothing more to go on than to depend heavily upon extrapolations from gene similarities—a circular argument founded upon the assumption of evolution, and yet another example of evolutionary story telling. The adverse effects of gene duplication, such as Down’s syndrome, are well known. Although the methodology is available, evidence of functionally useful genes as a result of duplication is yet to be documented. ‘One of biology’s greatest mysteries is how an organism as simple as a one-celled bacterium could give rise to something as complicated as a human.’ 1 How life evolved from a few primordial genes to the tens of thousands of genes in higher organisms is still a major issue in Darwinism. The current primary hypothesis is that it occurred via gene duplication. 2–6 Shanks concluded that ‘duplication is the way in which organisms acquire new genes. They do not appear by magic; they appear as the result of duplication.’7 Ernst Mayr, one of the most respected Darwinists of the 20 th century, agrees saying,‘Such a new gene is called a paralogous gene. At first, it will have the same function as its sister gene. However, it will usually evolve by having its own mutations and in due time it may acquire functions that differ from those of its sister gene. The original gene, however, will also evolve, and such direct descendants of the original gene are called orthologous genes.’8Ohno goes further, concluding that ‘gene duplication is the only means by which a new gene can arise’ (emphasis mine), a view that Li concludes is ‘largely valid’.9Furthermore, Ohno argues that not just genes but whole genomes have been duplicated in the past, causing ‘great leaps in evolution—such as the transition from invertebrates to vertebrates—[which] could occur only if whole genomes were duplicated’. Kellis et al., agree that ‘whole-genome duplication followed by massive gene loss and specialization has long been postulated as a powerful mechanism of evolutionary innovation’.10,11Evolution by gene duplication is a form of exaptation.12-14 Exaptation is the putative evolutionary process by which a structure that evolved for some other purpose is reassigned to its current role. Evidence for gene duplication Gene duplication does occur. For example, chromosomal recombination can result in the loss of a gene on one chromosome and the gain of an extra copy on the sister chromosome. Gene duplication can involve not only whole genes, but also parts of genes, several genes, parts of a chromosome, or even entire chromosomes.All of these conditions are well known because they are important causes of disease (including cancer) and can even cause death. Eakin and Behringer conclude:‘Spontaneous duplication of the mammalian genome occurs in approximately 1% of fertilizations. Although one or more whole genome duplications are believed to have influenced vertebrate evolution, polyploidy of contemporary mammals is generally incompatible with normal development and function of all but a few tissues. Most often, divergence of ploidy from the diploid (2n) norm results in a disease state.’ 15Li has noted that polyploidy (having more chromosomes than the

usual diploid number) is ‘likely to cause a severe imbalance in gene product, and their chance of being incorporated into the population is small’.16 He concludes that for both vertebrates and invertebrates only when single genes, or a few genes, are duplicated is the possibility to evolve new genes created.The gene-duplication idea has been researched for more than 30 years. Although first discussed by Haldane in 1932 and Miller in 1935, it was not discussed in detail until 1970 in Susumu Ohno’s book, Evolution by Gene Duplication.17 When Ohno proposed the idea many of his colleagues then considered his proposal ‘outrageous’.10 Gene duplication could not be evaluated experimentally, though, until the development of molecular biology techniques. Even now the primary evidence for gene duplication having a role in evolution must be inferred from gene similarity (i.e. an argument from homology). In the words of Hurles:‘The primary evidence that duplication has played a vital role in the evolution of new gene functions is the widespread existence of gene families. of a gene family that share a common ancestor as a result of a duplication event are denoted as being paralogous, distinguishing them from orthologous genes in different genomes, which share a common ancestor as a result of a speciation event. Paralogous genes can often be found clustered within a genome, although dispersed paralogues, often with more diverse functions, are also common.’18Because two genes are similar, though, does not prove that one was produced as a result of duplication.The ideal method to prove the origin of functionally useful genes as a result of gene duplication would be to use the same techniques that have been used to prove the adverse effects of gene duplication. A child with an abnormality such as Down’s syndrome (trisomy 21) is studied for genetic differences compared to the population as a whole and, especially, compared to his or her parents. If neither parent has a trisomy 21, and the cause, an extra chromosome 21, is determined to be a result of non-disjunction, it can be concluded that gene duplication has caused the abnormality. In the opposite case, if a child that has an exceptional ability is determined to have a gene not found in his parents and genetic studies of the family genetic history lend evidence of gene duplication and mutations in the child’s genetic inheritance, this is powerful evidence for gene duplication having produced the advantageous trait. This method can be used to trace the process for several generations so as to determine cases that involve more than one mutation. So far, however, no one seems to have done this research, or if they have, the results have not ed the gene duplication theory and were not published Chromosome doubling in plants Chromosome abnormalities, such as triploidy, are usually harmful in most animals, especially higher animals. Conversely, polyploidy in plants is very common and can, in many circumstances, benefit the plant, although few researchers argue that it plays a significant role in large scale evolution.19 Some evidence exists that polyploidy is a mechanism that produces variety within created kinds, similar to the effects of crossing over that occurs during meiosis. The specific effects of polyploidy depend on the environment and the plant. Polyploidy increases cell size, causing a reduction of the surface-tovolume ratio that can reduce the rate of some cell functions, including metabolism and growth. Conversely, some polyploids are more tolerant to drought and nutrient-deficient soils. In addition, some polyploids have greater resistance to pests and pathogens.20 However, in all of these cases, a fitness cost exists, meaning that in many environments polyploidy is a disadvantage.Much more research is needed for a proper understanding of plant polyploidy in order to determine under what specific conditions it is harmful and, conversely, under what specific conditions it is beneficial. As its biological function seems to be primarily to produce variety, it is not normally lethal (or even regularly lethal), as are most examples of animal polyploidy.Some invertebrates can tolerate polyploidy. Male bees, for example, have a haploid number of chromosomes and females a diploid number. This does not cause the females to evolve faster, however, as the gene duplication theory might predict. In the rare cases of polyploidy in vertebrates, most examples involve unusual species that ‘demonstrate a parthenogenetic mode of reproduction, lack heteromorphic sex chromosomes or have an environmentally induced sexdetermining system’.21Artificial gene duplication for experimental purposes has been developed in mice, but it has not provided any evidence for evolution because it is lethal:‘The production of tetraploid (4n) embryos has become a common experimental manipulation in the mouse. Although development of tetraploid mice has generally not been observed beyond mid-gestation [i.e. it is fatal], tetraploid:diploid (4n:2n) chimeras are widely used as a method for rescuing extra-embryonic defects [i.e. a genetic defect that is normally fatal can be artificially made to survive in the chimera].’22 Problems with the gene-duplication theory The statistical challenge Statistical evaluation of the predictions of the gene duplication theory does not appear to be favourable to it. For example, the theory predicts a positive correlation between organismal complexity and gene number, genome size and/or chromosome number. All of these predictions are contradicted by the evidence.In regard to gene number, humans have about 25,000 genes,23 while rice has 50,000.24 In of genome size, the largest known genome does not occur in man, but rather in a bacterium! Epulopiscium fishelsoni carries 25 times as much DNA as a human cell, and one of its genes has been duplicated 85,000 times yet it is still a bacterium. 25In of chromosome number, the descending rank order of diploid numbers for a selection of animals is as follows: Cambarus clarkii (a crayfish) 200, dog 78, chicken 78, human 46, Xenopus laevis (South African clawed frog) 36, Drosophila melanogaster (fruit fly) 8, Myrmecia pilosula (an ant) 2. These results do not fit the predictions of the gene duplication theory—perhaps they imply that flying on your own wings or in airplanes (fruit fly and human, respectively) needs less chromosomal input than lying around in swamps (frog and crayfish, respectively).Another statistical challenge has been noted by evolutionist genetics professor Steve Jones who concluded that an inverse relationship exists between the amount of DNA on one hand, and, on the other, both lethargic lifestyles and the speed at which organisms can evolve: the more DNA, the slower it is able to evolve. It takes a great deal of energy and resources to duplicate DNA, and the less of it an organism has, the faster it can reproduce (and the more efficient it is). Jones notes that ‘all weeds have small genomes, while more established plants are packed with DNA and can take a month to make a single egg cell’.26 Another example Jones cites is lungfish, which ‘are stuffed with DNA (most of it with no apparent function) and their evolution has stalled altogether … bacteria are speedy and have no excess genetic material, while salamanders, torpid as they are, are filled with DNA’.26 In his view, natural selection selects against gene duplication. The evo-devo challenge Male bees have a haploid number of chromosomes whereas female bees are diploid. This however, does not cause females to evolve faster, as predicted by gene duplication theory.An important alternative to the Darwinists exclusive focus on genes is emerging in ‘evo-devo’ (evolutionary development theory). They claim (with a great deal of experimental evidence behind them) that the content of the genome is not the primary determinant of identity; it is the epigenetic control system that decides how the genes are used. ‘A surprisingly small number of genes —“tool kit genes”—are the primary components for building all animals, and these genes emerged before … the Cambrian explosion [emphasis added].’27 That means the essential genes have not changed significantly over time, contradicting the central claim of neo-Darwinism. The function

of these genes can be compared to keys on a piano keyboard. The kind of music that is played (i.e. whether an embryo turns into a man or a mouse) is determined, not so much by the keys themselves, but by the player who strikes the keys and by the musical score that the player follows. If this is true, then arguments about gene duplication are irrelevant because ‘evolution’ occurs somewhere else (i.e. in the ‘playing’ and in ‘musical score’). The functional challenge Because whole genome duplication in animals is usually lethal, Ohno originally concluded that only two whole genome duplications had occurred throughout history; later he argued that a total of three had occurred. 28But Darwinists have itted that even the process of single gene duplication is poorly understood. Lynch and Conery note that, although ‘gene duplication has generally been viewed as a necessary source of material for the origin of evolutionary novelties, the rates of origin, loss, and preservation of gene duplicates are not well understood’. 29Behe and Snoke have pointed out that evolutionists must assume that multiple mutation events are required to produce a new functional gene, and each of the mutations must not be deleted until the gene has evolved to the degree that positive selection occurs.30 Meanwhile however, a duplicated gene may produce either defective proteins that can be toxic or fatal, or, at the least, will tax the cell’s resources and waste amino acids and energy. Because of this, natural selection acts on‘gene duplications, most often by deleting them from the gene pool or by degrading them into non-functional pseudogenes. This is because fully functional duplicated genes, in combination with the corresponding parent gene, produce abnormally abundant quantities of transcripts. This over-expression often alters the fragile molecular balance of gene products on a cellular level, ultimately resulting in deleterious phenotypic consequences.’31Zhang, in a study of gene duplication, concluded that many duplicated genes become degenerate, nonfunctional pseudogenes and, in only ‘rare cases’, a ‘new function may evolve’, as is believed to have occurred in the douc langur monkey.32 These langurs have two copies of an RNA-degrading enzyme gene, while other monkeys have only one copy. The extra copy aids the langur in digesting its specialized diet of leaves. Pseudogenes are considered by some to be damaged genes, and by others a source of new genes,33 and recent work suggests that they may be functional.10Yet another functional problem, noted by geneticist Manfred Schartl, is that‘it would be very difficult for the first tetraploid fish—those with four rather than the usual two copies of each chromosome—to engage in sexual reproduction.’28 Although the globin gene family is the most commonly sited example of ‘evolution by gene duplication’, there is no evidence to this. Moreover, it is known that the various globin variants of hemoglobin are designed to meet the differing demands for oxygen metabolism during the various stages of embryological, fetal and neonatal (and later) development.Another putative mechanism is partial duplication, which results in a gene mosaic. This condition, called a patchwork gene, often consists of several different regions that are similar to other genes. Likewise, because of this similarity it is assumed that the gene segments haphazardly combined until a rare combination occurred that was beneficial, so that this gene was selected. The most common hypothetical example is the LDL (LowDensity Lipoprotein) receptor. This relationship is hypothesized because part of the LDL receptor is similar to the epidermal growth factor hormone.Some theorize that this part of the gene evolved from a partial duplication of the epidermal growth factor gene. But how was the function of the LDL receptor maintained until this gene evolved? Without functional LDL receptors, a cell cannot effectively take in lipids, causing not only a supply deficiency in the cell, but also excess LDL in the blood, resulting in vascular problems from stroke, to embolisms, to heart disease. An example is hypercholesterolemia, a disease caused by defective lipid receptors. The victims often have strokes and heart attacks before their teens, even if on a low-fat diet. Gene Families? A group of genes that is closely related and theorized to have evolved by successive duplication is called a gene family, and an even larger group of genes that has structural similarities is titled a gene superfamily. No evidence of ancient genes exists to empirically document the theorized evolution of any gene family or superfamily. Instead, a gene ‘family’ is determined merely by making comparisons among existing genes, noting those that are similar.But any arbitrary collection of items—words, ideas, or physical objects—can be grouped together to form ‘families’ and ‘super families’, and no exception exists for genes. An automobile and a lawnmower, for example, both belong to the ‘four-wheeled machine family’ but this does not necessarily imply common ancestry. We are therefore not compelled to believe that because some genes have similar components that they evolved from a common ancestor.The first genes speculated to have evolved as a result of gene duplication were therefore the alpha and beta hemoglobin chains used to carry oxygen in erythrocytes. 9 The globin gene family is now the most commonly cited example of evolution by gene duplication. Myoglobin, a monomeric protein found mainly in muscle tissue where it serves as an intracellular storage site for oxygen, is hypothesized to have evolved into the tetrameric hemoglobin. Hemoglobin consists of two dimers, each one containing an alpha globin and a non-alpha globin. The ancestral non-alpha globin, called beta globin, supposedly gave rise to modern gamma, delta, and epsilon globin genes, and duplication of the alpha globin produced the epsilon and zeta globin genes. These globin variants are all used during different stages of embryological, fetal and neonatal (and later) development. The alpha, zeta and epsilon globin chains are produced in the early embryo and, during about the third month, the latter chains are replaced by the gamma chain and then later by the adult beta or delta chains at birth.But all of this supposed evolution is based on nothing more than speculation. In real life, the multiple uses of globin molecules in oxygen metabolism is no more an indicator of blind replication than is the multiple use of cogwheels in a clockwork mechanism. Just as each cogwheel is specifically structured and located to do a particular job, is functionally integrated with its fellows to optimally do that job, and is precisely regulated to do it at the right time, so are the globin molecules designed to meet the differing demands for oxygen metabolism during the development of the organism. The site of hemoglobin synthesis also changes from yolk sac to liver to bone marrow during development, so differing environments and transport systems are also involved. Disruption to hemoglobin synthesis leads to a wide range of diseases, and neo-Darwinists have been unable to explain how development could have proceeded successfully before the complex system was all in place.Another example of duplication is believed to be the evolution of the Human Major Histocompatibility Complex (MHC). But further study has likewise disputed some of these claims:‘Regions that are paralogous to the MHC on chromosomes 1, 9, and 19 have been proposed to result from ancient chromosomal duplications, although this has been disputed based on phylogenetic analysis.’34 The gene duplication rate problem

Is gene duplication common enough to provide an adequate source for evolution? The rate can be as high as 17% in some bacteria to 65% in the plant Arabidopsis but these are extreme examples.32 One empirical study by Lynch and Conery used steady-state demographic techniques to accurately determine the number of duplicate genes. This study evaluated seven completely sequenced genomes. From their research, they estimated that ‘the average rate of duplication of a eukaryotic gene to be on the order of 0.01/gene/million years, which is of the same order of magnitude as the mutation rate per nucleotide site’. The researchers concluded from their study that ‘the origin of a new function appears to be a very rare fate for a duplicate gene’ (emphasis mine).35Another study by Behe and Snoke 30 evaluated gene duplication by using mathematical modeling and published gene-duplication data. Their model assumes the simplest route to produce a new gene function: a duplicated gene that is free from purifying selection and subject to point mutation, and the minimum number of biologically relevant modifications required to create a novel function. Because the minimum number of changes necessary for most new gene functions is greater than one altered amino acid, and the number of changes needed in DNA for each altered amino acid varies between one and three, definitive estimates are difficult to obtain. Nonetheless, a reasonable estimate can be obtained in attempting to evaluate the validity of the duplication-mutation model. Behe and Snoke concluded that, even given liberalestimates, fixation of features requiring changes in multiple residues requires both population sizes and numbers of generations so large that they ‘seem prohibitive’. They concluded that gene duplication, coupled with point mutations, does not appear to be a promising mechanism for producing new proteins that require more than a single point mutation.Standish concludes that the Behe-Snoke paper does not exclude the possibility that‘more complex mechanisms involving larger mutations and/or selection of intermediate states acting on duplicated genes may serve as engines of new gene production. The problem is that these other mechanisms appear to be even more complex and thus less probable than the conceptually simple duplication-point mutation model Behe and Snoke examined. While their paper suggests that other potential mechanisms should be rigorously examined before discarding gene duplication and modification as a potential mechanism of evolution, it clearly demonstrates that even the most superficially reasonable sounding Darwinian mechanisms should be carefully evaluated before they are accepted as truly reasonable’ [emphases added].36This study (and others) indicate(s) that gene duplication does not appear to provide Darwinists with a significant source of new genes. Although many, if not most, genes are assumed to have arisen by gene duplication, a clear lack of evidence exists for gene duplication as the source of specific genes.12 Another major problem is ‘distinguishing adaptations from exaptations’. In others words, how do we know a gene resulted from duplication, and not by some other means such as independent evolution?37 The indefinite regress problem Gene duplication is a supposed method of exaptation—the takeover of an existing function to serve another purpose. Gould believed exaptation was so important that ‘the defining notion of quirky functional shift [i.e. exaptation] might almost be equated with evolutionary change itself … in textbook parlance, “the origin of evolutionary novelites”’. 38 But this kind of argument is fundamentally flawed. If all evolutionary novelties arise from something else that was itself exapted from something else, then an indefinite regress results. The problem with an indefinite regress is that explanation ‘A’ depends on an earlier explanation ‘B’ that you have not given, and explanation ‘B’ itself depends upon an earlier explanation ‘C’ that you likewise have not given. While you may appear to be explaining something, there is no actual explanatory content—it is no explanation at all. The conservation problem Multiple information conservation mechanisms are at work in all living organisms, ranging from natural selection eliminating the unfit, through various reproductive and chromosomal controls, to error correction routines and DNA repair mechanisms, including (it appears) restoration from non-DNA sources. As a result, many, if not most, genes are ‘evolutionarily conserved’, meaning that they are very similar in many unrelated organisms, both ‘simple’ and complex, modern and ancient. Many genes in the assumed earliest forms of life are very similar to those in the most advanced forms. These facts argue strongly against gene duplication as a mechanism of evolution, because they indicate that most genes were optimally functional from the beginning. Conclusions The proposition that large scale evolution has occurred via gene duplication is contradicted by numerous lines of evidence. Little evidence currently exists to the belief that gene duplication is a significant source of new genes, ing one University of South Carolina molecular evolutionist’s conclusion that scientists can not ‘prove that [genome duplication] didn’t happen, but [if it did], it didn’t have a major impact. … For me, it’s a dead issue’. 10It also is clear that the evidence for gene duplication at present is totally inferential, and not empirical or experimental. Chromosome duplication can produce useable variety—but only within what are most likely created kinds—in plants and invertebrates, and single gene duplication appears to do likewise in rare cases in vertebrates, but otherwise gene duplication generally causes disease and deformity. The existing experimental evidence does not gene duplication as a source of new genes for at least populations of fewer than one billion.30 According to Hughes, ‘Everything we’ve looked at [fails to] the hypothesis.’ 39 Darwinists promote gene duplication as an important means of evolution, not because of the evidence, but because they see no other viable mechanism to produce the required large number of new functional genes to turn a microbe into a microbiologist. In other words, evolution by gene-duplication is yet another example of just-so story-telling. Dawkins and the origin of genetic information Is it legitimate to demand of evolutionists an explanation for the origin of genetic information? Some amoebae have a huge amount of DNA in each cell, much more than humans. Does that mean they are more biologically complex? Hardly. It just shows we have a lot to learn yet.The leading antichristian and eugenicist Clinton R. Dawkins is not without his defenders. One questions us on the issue of genetic information, a question Dawkins had immense difficulties with. Don Batten responds with instructive points about the latest discoveries about information and meta-information (information about information), as well as pointing out the confusion between amount of DNA and amount of information it holds. I would like to respond to the ‘Skeptics choke on frog’ article regarding, among others, Richard Dawkins. The idea that biological complexity equates to genetic complexity is completely wrong. Charging evolutionists to describe a mutation which would ‘add information’ to an organism’s genome is an irrelevant question. In fact, there ARE actually such

mutations, which will increase the volume of a genome and even add genes (they are due to the activity of some viruses and of translocons, and to chromosomal recombination). However, the evolution of organisms from ‘simple’ to ‘complex’ has nothing to do with how many genes an organism has or how large its genome is. In science, we even have a name for the fact that the number of a species’ genes has no relation to the relative complexity of that organism: it is called the C value paradox. As an example, humans have approximately 20,000 to 25,000 genes. Rice has somewhere around 37,000 genes. If an organism’s evolutionary complexity actually had anything to do with how large its genome is, or even with how many protein-coding genes it contains, then rice would be the considered the paragon of evolutionary AND creationary mechanisms. Nicole USA Dear Nicole, Thanks for your query, which does afford us the opportunity to correct a misconception. You are correct: the complexity of an organism is not to be measured simply by counting the number of protein coding genes. Life is far more complex than that. I don’t think we have ever suggested that the status of an organism is to be measured by the number of such genes and that therefore humans would necessarily have the most.However, the evolution of a microbe into a complex organism such as rice or a human does require the addition of new genes. For example, the simplest single-celled organism has about 500 protein-coding genes and humans have over 20,000. So, if we began as microbes in some primordial soup, as evolutionary theory posits, then a lot of new genes had to be added by mutations—the only game in town for the evolutionist. There have to be a lot of mutations that add such new genes, not just twiddle with the existing ones. For example, the genes that make nerves and all the enzymes that enable nerves to operate are absent from microbes. They have to be created de novo if we evolved from them. There are many gene families in humans that are completely missing from microbes, so there has to be a viable mechanism for adding this genetic information if evolution is to be feasible. And mutations (accidental changes) of one form or other are the only mechanism for Darwinism.So the question to Richard Dawkins was a legitimate one. Indeed, Dawkins himself says that it is the information in living things that evolution has to explain. He candidly its this in the rest of the interview that is included on the documentary. In The Blind Watchmaker Dawkins clearly outlines the ‘problem’ of information in living things. Of course, being a ‘true believer’ in evolution by necessity of his atheism, he has to believe that mutations and natural selection can do the job and he spends the rest of the book with various story-telling ploys to make a case for the adequacy of evolution to create the required information.Is rice more complex than a human because it has more protein-coding genes? It might be, because it is an autotroph, meaning that it is capable of creating all its own energyrich biochemical building blocks using the energy from sunlight (in photosynthesis). In contrast, humans are heterotrophs, ultimately depending on plants to live. We are incapable of making many of the complex biochemicals needed for life; we get them from plants. There are many genes involved in photosynthesis and the biosynthesis of the essential amino acids, for example, that we do not have (the origin of photosynthesis is another conundrum for evolutionists—see Shining light on the evolution of photosynthesis and Green power: God’s solar power plants amaze chemists). But we also have many genes that rice does not have: ones for making muscle fibres, nerves, hemoglobin, etc. So rice and humans are not really comparable; it’s like comparing apples with jellyfish.Comparison of rice with humans is a red herring. No one has proposed that humans evolved from rice, or vice versa. Evolutionists (such as Dawkins) readily it that the evolution of humans (and rice) involved the addition of a lot of new genetic information to simpler organisms that supposedly made themselves in the beginning (another unanswerable problem for evolutionists—see Origin of Life Q&A). If someone wants to argue that all the information needed to make a human was there in the beginning, it just makes the origin of life even more immensely difficult to explain! Life is more than genes But life is more than genes. The very concept of a gene as the basic unit of heredity that controls everything is being seriously questioned. The ENCODE project in particular has blown away the idea that life is just about protein-coding genes, although there were prior indications that this was incorrect (see No joy for junkies). In short, the rest of the DNA of humans and other complex organisms is not junk, but incredibly important. Basically, it controls how the genes work—for example, why it is that hemoglobin is only produced in red blood cells when all cells have the genes for hemoglobin protein. And it controls the incredible sequencing of genes so that orderly embryo development occurs. See also Meta-information: An impossible conundrum for evolution.So life is much more than genes. When we take into the total DNA, rice has 466 million base pairs and humans have 3 billion (six times as much), which might be better for our egos than the comparison of the number of genes. However, even the number of base pairs, or the picograms of DNA per nucleus, is no adequate measure of genetic complexity. The smallest flowering plant genome is only about 0.1 picograms (flowering plant range 0.10–127.0 pg), whereas the largest alga is 19.6 picograms (algal range 0.01–19.6 pg). 1 Clearly, flowering plants are much more complex than algae, so there is more to complexity than a simple comparison of genome sizes.Protozoa (for example amoebae) range from tiny to huge in their nuclear DNA amounts, some of them greatly exceeding the human number of base pairs.2 It is not really understood why this is so. It could have something to do with cell size, where organisms with large cells have a form of endoreduplication, where the DNA multiplies up to be able to provide enough mRNA transcripts to supply the large cell’s protein requirements. Specialized, enlarged plant cells do this (I have measured the relative amounts of DNA in the nuclei of such cells using microfluorimetry). Actual genome decoding does not suggest that protozoan genomes are large in of numbers of different genes, although at present the largest amoeba genomes have not been sequenced. Typical sequenced genomes of protozoans seem to be of the order of about 25 million base pairs.3 I expect that the large protozoan genomes, when they are sequenced, will reveal large-scale duplication of genes, such that that total number of different genes will be of the same order as other protozoans. In of this, Amoeba dubia, the one with the largest reported amount of DNA, is the largest sized amoeba cell known, being visible to the naked eye—up to a millimetre in length. This compares with 0.009 mm diameter for a human red blood cell. Considering that the volume of a cell scales with greater than the square of the radius, the volume of Amoeba dubia cells is huge (~10,000x) compared to human cells. This almost certainly has something to do with the huge amount of DNA it contains. Your statement, ‘The idea that biological complexity equates to genetic complexity is completely wrong,’ begs the question, which is, ‘What do you mean by biological complexity and what do you mean by genetic complexity?’ As we have seen, genetic complexity is far more than just counting the number of protein-coding genes. Much of it is only just beginning to be discovered. Adding information? ‘In fact, there ARE actually such mutations, which will increase the volume of a genome and even add genes (they are due to the activity of some viruses and of translocons, and to chromosomal recombination).’ I think you meant to say ‘transposons’, not ‘translocons’, which are quite different (and a huge problem in themselves for evolution to explain, but that’s another story). Actually, movement of DNA with transposons or viruses does not create

any new information; it only transfers it around, as we have explained before—this does not explain the origin of the genetic information. But there is now strong evidence that transposons are not ‘parasitic DNA’ or ‘endogenous retroviruses’ at all, willy-nilly shifting chunks of DNA around at random, but are involved in the regulation of gene activity during embryo development, for example (see the No joy for junkies article).Recombination during meiosis also does not create new information; it just selects from the existing alleles, giving different combinations in the offspring. Darwin made the mistake of thinking that variety in offspring meant new features arising spontaneously, whereas we now know, following the pioneering work of the famous creationist scientist, Gregor Mendel, that the variety is due to the recombination of existing genes, not the creation of new ones. See Genetics: no friend of evolution. If Darwin had known what we know about genes and mutations, he might not have become a Darwinist.Evolutionists also claim that genes can be duplicated and this is an increase in information. But if you write an essay of 5,000 words and it needs to be 10,000 words, you won’t get any credit for photocopying (duplicating) the 5,000 to get the 10,000. That’s what evolutionists are claiming when they say that virus transfer or duplication ‘increases information’. See also Does gene duplication provide the engine for evolution? The question to Professor Dawkins was quite legitimate, as he himself readily its in his voluminous works. Evolution has to explain the origin of enormous quantities of information in living things (but it can’t). I hope this helps answer your questions. Sincerely, WHAT ABOUT “JUNK” DNA ‘Junk’ DNA: evolutionary discards or God’s tools? by Linda K. Walkup Summary ‘Junk’ DNA is thought by evolutionists to be useless DNA leftover from past evolutionary permutations. According to the selfish or parasitic DNA theory, this DNA persists only because of its ability to replicate itself, or perhaps because it has randomly mutated into a form advantageous to the cell. The types of junk DNA include introns, pseudogenes, and mobile and repetitive DNAs. But now many of the DNA sequences formerly relegated to the junk pile have begun to obtain new respect for their role in genome structure and function, gene regulation and rapid speciation. On the other hand, there are examples of what seem to be true junk DNAs, sequences that had lost their functions, either to mutational inactivation that could have occurred post-Fall, or by time limits set on their functions.Criteria are presented by which to identify legitimate junk DNA, and to try to decipher the genetic clues of how genomes function now and in the past, when rates of change of genomes may have been very different. The rapid, catastrophic changes in the earth caused by the Flood may also have been mirrored in genomes, as each species had to adapt to post-Flood conditions. A new creationist theory may explain how this rapid diversification came about by the changes caused by repetitive and mobile DNA sequences. The so-called ‘junk’ DNAs that have perplexed creationists and evolutionary scientists alike may be the very elements that can explain the mechanisms.The last decade of the 20th century has seen an explosion in research into the structure and function of the DNA in genomes of a wide range of organisms. As of April 2000, the whole genomes, or full DNA complements of over 600 organisms have been sequenced or mapped.1The sequence of the fruit fly genome, just completed, has over 130 million base pairs (bp) and is the largest genome sequenced so far.2 The first complete human chromosome has been sequenced,3 and the Human Genome Project expects to complete its work sometime in 2003, as does the Mouse Genome Project. Researchers in the new field of genomics—the comparison of the structures, functions and hypothetical evolutionary relationships of the world’s life-forms—are working furiously to deal with the huge inflow of data. Now more than ever, scientists can see at the most basic level the similarities and differences of organisms, and are seeking to understand how the blueprints of cells are decoded and regulated.A major goal of genomic studies is to understand the role, if any, of the various classes of so-called ‘junk’ DNA. Junk or ‘selfish’ DNA is believed to be largely parasitic in nature, persisting in the genomes of higher organisms as ‘evolutionary remnants’ by their ability to reproduce and spread themselves, or perhaps because they have supposedly mutated into a function the cell can use. Origin of the junk DNA hypothesis The idea that a large portion of the genomes of eukaryotes*4 is made up of useless evolutionary remnants comes from the problem known as the ‘c-value paradox’, ‘c’ meaning the haploid* chromosomal DNA content. There is an extraordinary degree of variation in genome size between different eukaryotes, which does not correlate with organismal complexity or the numbers of genes that code for proteins. For instance, the newt Triturus cristatus has around six times as much DNA as humans, who have about 7.5 times as much as the pufferfish Fugu rubripes.5 The c-value between different frog species can differ by as much as 100-fold.6 Early DNA-RNA hybridisation* studies and recent genome sequencing results have confirmed that >90% of the DNA of vertebrates does not code for a product. Much of this variation is due to non-coding (i.e. not producing an RNA or protein product), often very simple, repeated sequences. With the discovery that many of these sequences seemed to have arisen from mobile DNAs which are able to reproduce themselves, the selfish or parasitic DNA hypothesis was born.7,8 This said that these sequences served no function in the host organism, but were simply carried on the genome by their ability to replicate or spread copies of themselves within and even between genomes.Plasterk stated it this way when he wrote about transposons*, one of the ‘junk’ DNA types:‘This ability to replicate is a sufficient raison d’etre for transposons; they have the same reason for living as, say, the readership of Cell: none. They exist not because they are good, pretty, or intelligent, but because they survive.’ 9 Just as Plasterk was wrong about our reason for living, he is wrong about the purposes of these DNA sequences. Recent research has begun to show that many of these useless-looking sequences do have a function, and that they may have played a role in intrabaraminic10 (‘within-kind’) diversification. Types of junk DNA There are four major kinds of junk DNA: introns, internal segments in genes that are removed at the RNA level; pseudogenes, genes inactivated by an insertion or deletion; Figure 1. Only portions of a eukaryotic gene code for a protein product.

satellite sequences, tandem arrays of short repeats; and interspersed repeats, which are longer repetitive sequences mostly derived from mobile DNA elements. Introns After most eukaryotic genes and a very few prokaryotic* (bacterial) genes are transcribed, or copied into RNA, there are segments that are cut out of the messenger RNA (mRNA) before it is used as a template to make a protein (Figure 1). Introns in fact form the majority of the sequence of most genes, as was seen when human chromosome 22 was sequenced (Table 1). Why are these RNA pieces present if they are only to be discarded? Evolutionary theory tries to explain these as vestigial sequences, or that they are useful only as sites at which recombination can safely take place to reshuffle exons (coding or protein making segments) into new proteins or new forms of these proteins. Their ubiquity in eukaryotes argues that they are not post-Fall aberrations, but designed features.What then, could these throwaway segments be doing? There are several possibilities emerging from recent research. One general regulatory role may be to slow down the rate of translation*, as the splicing* process does take time. Alternative splicing allows greater diversity, as certain exons can be skipped and spliced out to allow a different protein to be made from the same mRNA, as is seen in some viruses and in the generation of diversity in antibodies. Another example is the CD6 gene, which is involved in T cell stimulation. Variable splicing of exons gives rise to at least five different forms of the protein, which allows regulation of its activity. 11Another observed mechanism by which introns can regulate gene activity is through the binding of the snipped-out intron RNA to DNA or RNA. There are now a few examples of the role of introns in regulating the genes they are in, as well as other genes. One interesting example is the lin-4 gene intron from the nematodeCaenorhabditis elegans. A developmental control gene was found to reside in the intron of another gene (Figure 2). 12,13 The small RNA encoded by lin-4 binds to the mRNA of another developmental gene, lin-14, blocking its ability to make protein. The binding site in lin-14 was in another supposedly useless stretch of RNA, the 3' untranslated region (3’UTR*) found after the last coding region. It was later found that lin4 RNA also binds to the 3’UTR in another gene in the developmental pathway, lin-28.14 In fact, more and more cases of 3’UTRs performing gene regulatory activities have been observed. 15,16There are examples of protein-encoding genes within introns of other genes that have been recently discovered. For example, on human chromosome 22, the 61-kilobase (kb) TIMP3 gene, which is involved in macular degeneration, lies within a 268-kb intron of the large SYN3 gene, and the 8.5-kb HCF2 gene lies within a 27.5-kb intron of the PIK4CA gene.3 Some introns also play a role in mRNA editing, a process where the A (adenine) residues in the mRNA are changed to G (guanine).17 Self-complementary* or exon-complementary intron sequences, can bind to each other to form a hairpin loop structure, allowing the sequence of the RNA to be changed after transcription* from the DNA. Thus introns can cause new messages to arise from a gene without altering its DNA coding sequences.The most general function of introns may be to stabilize closed chromatin* structures in, and around, genes and their associated regulatory DNA elements. 18,19 An isochore* is an approximately 300-kb segment of DNA whose base pair composition is uniform above a 3-kb level, for example 67% A-T bp.20 The general ability of an isochore to be transcribed is dependent on the accessibility of its DNA, i.e. how tightly histones* and other DNA-binding proteins wrap up the DNA. This is seen as being at least partially dependent on the A-T or G-C bp content of a segment of DNA. Though this content can be skewed somewhat by the choice of triplet codons*used in the coding DNA (since the code is redundant21), exons are still constrained in their ability to vary the bp content. The presence of introns throughout genes allows the proper levels to be maintained, and indeed introns reflect the general isochore type much more closely than the coding regions. The presence of introns may well be a condition for at least some forms of sectorial repression like superrepression, where large sections of chromatin are altered Table 1. Types and amounts of DNA sequence classes of to turn off groups of cell-type-specific genes or developmental the sequenced euchromatin* of human chromosome 22 genes. It was shown, for example, that the gene for rat growth 3 (after Dunham et al.). hormone, when deprived of its introns, was no longer able to 1. All other types of interspersed repeats seen, not form its normal more condensed structure when reinserted detailed here. back into cells.22It is important to know whether the specific 2. Tandem repeats from 2 to 5 bp in length (microsatellite sequence of an intron is required for its function when DNA). It is estimated that most of the remaining DNA not constructing phylogenetic or family trees, or when determining sequenced is satellite DNA, as tandem repeats are mostly baraminic* placement of an organism. In evolutionary studies, located in the heterochromatin, which was not sequenced. DNA sequence comparisons are used to try to build 3. Includes all tandem and interspersed repeat types. phylogenetic trees to trace ancestors to descendants. Since introns are generally believed to be free from the constraints of functionality when mutations cause changes in their sequence, introns in a particular gene are often compared between organisms, with the bp differences seen between their sequences supposedly indicating the degree and time of divergence since they last shared a common ancestor. In some instances, the assumption that an intron is likely to have mutated freely and extensively during the presumed millions of years of evolutionary history has proved wrong. Koop and Hood found that the DNA of the T cell receptor complex, a crucial immune system protein, is 71% identical between humans and mice over a stretch of 98-kb of DNA. This was an unexpected finding, as only 6% of the region encodes protein, while the rest consists of introns and non-coding regions around the gene. 23 Does it follow then that we have a recent common ancestor with mice? Since this does not fit in with evolutionary theory, the authors conclude instead that the region must have specific functions that place constraints on the fixation of mutations. This illustrates that DNA sequence comparisons to establish evolutionary relationships are not the independent tests that they are claimed to be. If the data do not the desired evolutionary theory, ad hoc explanations of altered rates of mutation, functional constraints, etc., can be brought in to explain away discrepancies.24

Another example of selective interpretation of DNA sequence comparison data using introns is the study of an intron in an important sperm maturation gene on the Y chromosome of humans.25,26 It was hoped that the ancestry of modern humans could be traced by sequencing this 729bp intron from 38 different men from different ethnic groups. Surprisingly, all 38 men had exactly the same sequence, which was then interpreted as a ‘recent’ common ancestor (27,000–270,000 years ago) for the whole human race, or possibly that the intron had functional constraints on its mutability. This latter premise was rejected by the authors because the sequence of the same intron in chimp, gorilla and orangutan was progressively more different. These data would strongly the young age view that there was a severe bottleneck in the human population when the Flood reduced the varieties of Y chromosomes to the one shared by the survivors. Apes would not be expected to have exactly the same sequence as humans, as they are from separate created kind(s). The fact that they do have a similar intron argues for a function for this sequence, and the intron may have been originally created slightly different for proper function in an ape versus a human.Thus evidence is mounting to the important role of introns Figure 2. Interaction of two ‘junk’ RNAs in gene regulation and chromosome structure, which would remove regulates a developmental gene. 8.15%27 of the junk DNA of the human genome from the trash heap. Pseudogenes* Occasionally located near functional genes or gene families, there are sequences that very closely resemble other functional genes, but have been inactivated in someway. Some have a mobile element inserted in their open reading frames (ORFs*), others seem to be ‘processed’ genes, i.e. they look as though the RNA from another gene has been reverse transcribed (RNA used as a template to make DNA) and reinserted back into the DNA (Figure 3). A processed pseudogene* thus precisely lacks the introns, possesses 3'-terminal poly-(A) tracts*, and lacks the upstream promoter* sequence required for transcription of the corresponding parent gene. Pseudogenes are common in mammals, but virtually absent in Drosphila.28 Nineteen percent of the coding sequences identified in human chromosome 22 were designated as pseudogenes, because they had significant similarity to known genes or proteins but had disrupted protein coding reading frames. 82% appeared to be processed pseudogenes.3 Many pseudogenes have additional mutations in them, presumably because there is no functional constraint on their mutation. For example, the human beta-tubulin gene family consists of 15– 20 , of which five have these pseudogene hallmarks. 29 Some pseudogenes affect gene activity by binding transcriptional factors that activate the normal gene. Whether this is intentional design or something the organism has simply adjusted to is difficult to say. Many pseudogenes do seem to fit the profile of true junk DNAs. Repetitive DNA sequences, including mobile DNA sequences Repetitive DNA sequences form a substantial fraction of the genomes of many eukaryotes (Table 1, Table 2).30,31 This class includes satellite DNA (very highly repetitive, tandemly repeated sequences), minisatellite and microsatellite sequences (moderately repetitive, tandemly repeated sequences), the new megasatellites (moderately repetitive, tandem repeats of larger size) and transposable or mobile elements (moderately repetitive, dispersed sequences that can move from site to site; see Table 2).When first discovered, they did not seem to confer any benefit to the host organism, as their ability to move about the genome and/or cause recombination between different homologous copies has often resulted in deleterious mutation and disease. We now know that at least some of these sequences carry out important functions. Satellite sequences The functionality of a sequence of 2 or 3 bp repeated a thousand or so times is not immediately apparent. In addition, the lengths and compositions of these repetitions often vary wildly Figure 3. Comparison of integrated mobile DNA sequence structures. between species, between organisms of the same species, or even between cells of the same organism. But greater understanding has come as scientists realize how DNA acts not only as the information source for the cell, but also as the library in which it is housed. 32 It is beginning to be seen that the dispensability of sequences is not an indicator of their non-functionality, and that in many cases, repetitive sequences tend to fill functions collectively rather than individually.Satellite sequences vary in their repeat size and in their array size (Table

2). Microsatellites are the smallest, at a repeat size of as little as 2 bp, and the newly discovered megasatellite sequences, which actually can contain ORFs, are 4–10 kb long. 33 The actual sequence repeated differs from species to species, and repeats can differ slightly from one another. The number in an array can vary between individuals, which is why forensic DNA fingerprinting techniques use mini- and microsatellite differences to identify individuals.

Table 2. Types of eukaryotic repetitive DNA sequences.

Functions of satellite sequences The first recognised function of these types of sequences was in organising the centromeres, the constricted sites on each chromosome where the chromosomes attach to cellular tethers and are pulled apart during meiosis and mitosis. These sequences help condense the DNA region they are in into heterochromatin*.One hypothesis of the collective functionality of repeat sequences is that long stretches of noncoding sequences act as tethers, permitting placement of groups of genes into different zones in the cell nucleus.19 Transcriptionally inactive heterochromatin and the heterochromatin-like telomeric sequences (sequences at the end of chromosomes), may associate their respective chromatin segments much of the time with the nuclear periphery. Very long runs of gene-poor, AT-rich isochores*, would be the tethers that permit the gene-rich, GC-rich isochores to distribute themselves into the appropriate nuclear zones for transcription and RNA processing.The importance of the sequences of satellite DNA is reflected when these sequences are mutated. A mutation in a minisatellite just after the end of the Harvey ras gene (which encodes a growth regulatory protein) may contribute to as many as 10% of all cases of breast, colorectal and bladder cancer, and acute leukemia. The mutant minisatellites Figure 4. Mutations in minisatellite DNA can bind a transcriptional regulatory factor,34 which causes an abnormal result in cancer. Mutated satellite DNA near increase in transcription of the Harvey ras gene (Figure 4). the Harvey rasgene (a major regulator of cell Retroviruses* and retroelements* growth) can bind a protein that These ‘class I mobile elements’ reproduce themselves through an RNA increasesras activity. intermediate which, in a reversal of the usual DNA to RNA transcription,

is reverse transcribed to DNA by the reverse transcriptase* enzyme encoded on intact elements. One of the remarkable findings of the human genome project is that a high percentage (35.40%) of human nuclear DNA consists of dispersed retroelements (Table 1).35 Short and long interspersed elements, SINEs and LINEs, make up the majority of this class of DNA, with Alu and LINE-1 (L1), respectively, being most abundant in humans.36 L1 elements encode their own reverse transcriptase, that probably is also responsible for the spread of SINEs, which lack this enzyme. HIV-1, the AIDS virus, human endogenous retroviruses* (HERVs), and solitary long terminal repeats (LTRs*) apparently derived from HERVs, are also part of this class of retroelements (Figure 3, Table 2).Most eukaryotic retrotransposons* move only sporadically in the genome. An exception is the hybrid dysgenesis seen in Drosophila, where if flies containing a retrotransposon are mated to flies not containing the particular retrotransposon, the element transposes with a high frequency, resulting in death or mutation of many of the progeny. Host factors, many not well characterized as yet, seem to keep the transposition rate in check (see below). Functions of retroelements Do these abundant elements have functions, or have hapless eukaryotic genomes been parasitized by selfish DNA? There are more and more examples of these elements performing important functions. One example is the Alu family. This 300-bp sequence (named for the enzyme used to identify it) occurs almost a million times in the human genome, up to 3.5% of the total DNA (Table 2). It is estimated, and has been seen in many cloned genes, that there are 4 or 5 Alu elements in every gene. Despite their number, they have been generally considered parasitic DNA, with occasional deleterious effects on the genome when they exercise their ability to retrotranspose to sites in and near genes, or recombine with each other abnormally. Such disruptions have caused neurofibromatosis, or elephant man’s disease. 16 Mutations in the Alusequence also have been associated with cancer. Alu sequences have been found to affect the functions of at least 8 different genes (Table 2).37,38 Though Alu sequences do have internal promoters for RNA polymerase III (an enzyme which transcribes genes encoding RNAs needed for translation of mRNA into protein), normally very little RNA is produced from all these Alu sequences. However, under certain stressful conditions such as a viral infection, these transcripts increase dramatically and affect protein synthesis levels to help the cell deal with the stress. 39 Thus, though individual Alu elements have a very weak effect, hundreds of thousands of them together can affect protein synthesis.Epigenetic control mechanisms, or modifications of gene activity that are due to modifications of the DNA itself and not its sequence (see below), are associated with repeats. A repeat-induced process involving L1 retroelements has been hypothesised for Xchromosome inactivation, which is necessary to maintain proper gene dosage in females, who have two X chromosomes (Table 2).40Endogenous retroviruses (that is, those that are obtained from inheritance rather than infection) can also affect gene expression. The LTRs of two such viruses provides the sequence signal for the polyadenylation* of the mRNA of two newly discovered human genes.41 An L1 repeat was found to provide the polyadenylation signal for the mouse thymidylate synthase gene. Retrotransposons were also seen to help in repairing chromosomal breaks in yeast. Retroelements modulate expression of many more genes.42 DNA transposons* DNA transposons, or ‘class II transposable elements’, move from place to place by replicative transposition (that increases the copy number) or by a simple cut-and-paste mechanism. Though in general not as common or in as high a copy number as retroelements, they are still found in most organisms. Examples are the Drosophila P elements, bacterial transposons such as Tn10 and Tn7, the Mu phage, and the ubiquitous mariner/Tc1 superfamily of transposons. The mariner/Tc1 family is the most widespread, being found in most insects, flatworms, nematodes, arthropods, ciliated protozoa, fungi and many vertebrates, including zebra fish, trout and humans.43 Copy number varies from two copies inDrosophila sechellia, to 17,000 in the horn fly Haematobia irritans, ing for 1% of the genome. The vast majority of them appear to have been inactivated by multiple mutations. The close homology between mariner/Tc1 elements found in species thought to have diverged 200 million years ago has fuelled the hypothesis that these elements can transfer horizontally (that is, not by normal inheritance) between different species, or even different phyla (see below). Again, the evolutionist gets to pick and choose from his smorgasbord of explanations when the data do not fit the evolutionary tree. Miniature inverted-repeat transposable elements (MITEs) A recently discovered third class of mobile elements is the miniature inverted-repeat transposable elements (MITEs). 44– 46 They are very small (125–500 bp), and have short terminal inverted repeats. They were first found in plants, but have also been found in nematodes, humans, mosquitoes and zebrafish.47–50 They are found in the thousands and tens of thousands per genome, and have been given colourful names (e.g. Tourist, Stowaway, Alien and Bigfoot) to reflect their apparent ability to move about in the genome. Their mechanism of transposition is still unknown, but they appear to be DNA elements that cannot move about on their own (non-autonomous). Though none seem to be presently active, they are believed to have been mobile in the recent past because of the high levels of sequence similarity between elements in a particular family, and the differences in insertion sites seen in closely related species. 51 MITEs are particularly interesting in of generating genetic variation in that they are preferentially associated with genes (see below).46,52 Effects of mobile and repetitive elements on gene expression Mobile elements and repetitive elements can alter the structure and regulate expression of the genome in several different ways. As described earlier, transposition can disrupt genes by direct insertional mutagenesis and can adversely affect transcription. Many retrotransposons have strong constitutive (always on) promoters that can cause inappropriate expression of downstream genes. If the promoter is in the opposite direction of the gene, RNA complementary to the mRNA of the gene can be made that can act as antisense RNA* that binds up the mRNA, affecting translation. Recombination between similar DNA strands is a necessary process for repair of DNA breaks and allele*shuffling between homologous chromosomes. But the presence of mobile and repetitive elements in inappropriate positions can result in recombination products that are Figure 5. Recombination between direct deleterious, such as translocations*, inversions*, and other chromosomal repeats causes the loss of the DNA between rearrangements (Figure 5). For example, it was shown that a widespread them. chromosomal inversion commonly seen in Drosophila buzzatii is caused by the recombination between two copies of a transposable element in opposite orientations.53 There can even be an exchange of DNA between non-homologous chromosomes: such as was seen in maize, in this case mediated by the recombination of one complete and one partial copy of the Ac (Activator) transposable element.54

Target site selection in mobile DNA Many of the retrotransposons and DNA transposons seem to have very little site-specificity in where they integrate.55 Integration sites for most mammalian and Drosophila retroelements appear to be distributed more or less randomly in the genome. Vertebrate retroviruses do have a general preference for insertion into regions with an open chromatin configuration.56 However, there are some specific ones that do show target selectivity.51 R2 is a non-LTR retrotransposon that inserts preferentially in the 28S ribosomal RNA genes of various insect species. Group II introns present in some yeast mitochondrial genes (genes carried in the energy-producing organelles in the cell), are mobile elements very similar to poly (A)-type retrotransposons. After copying themselves, they can reinsert precisely back into their spots between two exons. Their ability to move argues for their spread into various genes at some point in time. The yeast retrotransposons Tyl and Ty3, integrate preferentially upstream of genes transcribed by RNA polymerase III, which transcribes genes needed for protein synthesis.Very recently, evidence has been found that certain P elements* containing regulatory sequences from developmental genes, showed a high frequency of reinserting at the parent gene (homing) and preferential insertion at another site containing regulatory genes.57The first example known of a host using the movement of a retrotransposon to its advantage, was found in the telomere maintenance ofDrosophila. The telomeres, or chromosomal ends of Drosophila, are maintained differently than any other known organism. Two retroposons, HeTA and TART, are present in multiple copies on the telomeres, and will retropose specifically to the end of the telomere and heal a frayed chromosome.58 Observed regulation of mobile DNA Epigenetic mechanisms, or reversible but heritable changes in chromatin structure, are seen to play a role in regulating genes. Methylation of cytosine residues, modification of the DNA-binding histones, and production of antisense RNAs, are some of the mechanisms by which gene expression can be modified without permanent genetic change to the gene regulated.59 Methylation of the cytosine residues of DNA is used by the cell to turn off genes not currently needed. Cytosine methylation inactivates the promoters of most viruses and transposons (including retroviruses and Alu elements). In fact, transposons are so abundant, rich in G dinucleotides and heavily methylated, that we now know that the large majority of 5'-methylcytosine in the genome actually lies within these elements. 60 This prevents the movement of the elements under normal circumstances. Thus transposable elements that integrate into promoters of genes can alter gene expression patterns by attracting methylation or chromatin modifications to regulate the modified promoter. 53Drosophila, in general, are very vulnerable to mutation by mobile element activity. From 50–85% of all spontaneous mutations seen in the fruit fly are due to transposon insertions.53 But Drosophila does have one type of host control in the recently identified gene named flamenco.Flamenco normally acts to keep the gypsy retrotransposon in check. When flamenco is mutated, gypsy transposes at a high frequency in germ line (reproductive) cells.50 Criteria for identifying junk DNA There are several possible scenarios for the presence and function of the putative junk DNA sequences described above: They all perform designed functions in present day organisms in their present form and location, though current research has not revealed what those are as yet. This is unlikely, as it seems clear that in some individuals and species, the placement or particular sequence of one of a family of non-coding DNAs can lead to deleterious effects such as cancer and genetic disease. This would contradict the young age model of original perfect creation.All non-coding sequences could have been created with functions, but some have lost their functions due to purposeful limitations, and/or accumulation of mutations post-Fall. This would fit in with our observation of the rest of creation, where, though the perfection of design can be seen, it has become obscured by consequences of the Fall, allowing death and suffering to enter the world.There is the possibility that some of the elements, such as the mobile elements in particular, have never had designed functions. Rather, they are pieces of degenerate DNA affected by the Fall that randomly move about and mutate genomes, causing only deleterious effects.The ability of DNA sequences to rearrange and/or to move about in the genome or even between genomes, was originally a heretical idea for both evolutionist and creationist, but now is one that is strongly ed as being an integral part of gene regulation. Many systems utilizing similar recombination and rearrangement mechanisms are necessary for important cellular functions, such as the process of DNA repair, rearrangement of DNA segments to form the genes for the thousands of different antibodies, the yeast mating type switching system, the flagellar switching system of Salmonella, and the antigen switching system of the malaria parasite. Therefore, the second scenario seems the most likely.A working list of criteria needs to be developed to attempt to identify DNA sequences that may actually fit the category of junk DNA. The presence of some junk DNA would be expected due to the fallen state of genomes. True junk DNA may have one or more of the following characteristics: The DNA element is present within another gene, insertionally inactivating it. The DNA element is not found at that location in other within the same species. The effects of the presence of the element, if known, are deleterious, e.g. lead to cancer, genetic disease, etc. The element can be deleted without any observed ill effects on the organism or many generations of its descendants. The sequence of the element closely matches that of a mobile element, or contains a mobile element sequence. For example, pseudogenes have many of these junk DNA characteristics, though their transformation into junk DNA may in some cases have been intentionally arranged by the designer for the purpose of rapid diversification of created kinds. The AGEing theory and diversification There are, as described above, instances of functions for transposable DNAs, but until recently there has not been a particular purpose ascribed to repetitive and mobile elements as a group. A new hypothesis formulated by genomicist and creationist Wood addresses the past and present functions of mobile and repetitive DNA. 61Since these elements are capable of rapid change of the genome, and can even be transmitted horizontally between species, he proposes that they were designed to move about or recombine in the genomes of organisms to allow the rapid intrabaraminic diversification seen in the 500 years or so after the Flood. He sees their role as being designed to act for a limited period of time, after which they would be inactivated by mutation or repression by other regulatory elements. He proposes that such elements should be renamed Altruistic Genetic Elements (AGEs) to emphasize that their purpose is different than that proposed for ‘selfish’ DNA.The AGEs are hypothesised to work by activating dormant genes or inactivating active genes, or by horizontally transferring genetic information between species or possibly baramins with AGEs in the form of mobile elements. The phenotypic changes would be primarily cosmetic, such as variations in size or coloration, or would involve activation of a complex of genes needed to utilize a new environmental niche, like the Arctic fox’s adaptation to cold. There is a need for creationists to explain how a holobaramin such as the cat family, 62 could diversify into the many species of cats that were present even in Job’s time in just a few thousand years or possibly a few hundred years. Currently observed genetic mechanisms and natural selection are far too slow to explain this rapid speciation. A limited time period of AGE activity could explain how this rapid diversification could occur.If, for example, the proposed AGEs were at work in the diversification of the equines, we have the testable predication that differences in size, morphology and coloration could be traced back to the genetic level by mobile or repetitive DNA elements located near genes controlling coloration.

Pseudogenes and relic retroviral sequences could then be the result of the action of an AGE gone wrong after its designed activity began to fail. The AGEing theory could also solve the ‘founding pair’ problem—that is, when a rare macromutation occurs in an individual such that it cannot successfully hybridise with its parental species, this mutation is lost unless it can mate with another animal with the same mutation.For this proposed AGEing process to work, at least three things must be observed in putative AGEs: They must show site specificity in where they insert, or evidence that they had such specificity in the past.Transmission of AGEs between organisms horizontally and into germline DNA is required.We should see AGEs associated with genes affecting size, morphology, coloration, and specialised environmental adaptation rather than housekeeping genes.As for the first requirement, though many mobile elements are not specific in their target sites, there are examples of those that are, as discussed above. Since AGE movement is supposed to have occurred largely in the past, we might expect to see only a few with the intact capability.As for the second requirement, horizontal transmission*, the evidence for that occurring has become very strong,63 and in the case of the P and gypsy elements in Drosophila, such transmission has actually been observed occurring between species. Originally, no wild-caught D. melanogaster contained the P element and laboratory stocks collected 60 years ago reflected this. Then gradually, more and more wild-caught flies contained the element originally found in D. willistoni, until now all wild flies even in remote locations contain this element. 64Recently, it was also shown that the copia retrotransposon from D. melanogaster was transferred to D. willistoni (probably via a parasitic mite).65,66 There was also a report that gypsy-free fruit flies permissive for transposition of the gypsy retroposon could incorporate gypsy into their germline DNA when larvae were fed on extract of infected pupae. 67 There is no obvious evidence pointing to a functional change mediated by these horizontal transfers, but the principle is there.As for the third requirement, are there any examples known now of mobile or repetitive elements that can cause these types of phenotypic changes? In bacteria, there are many examples of transfers of antibiotic resistance mediated by transposons, 68 and the horizontal transfer of genes, though in general prokaryotes have comparatively little ‘junk’ DNA. Some evolutionary researchers now propose that mobile elements may be involved in speciation. Mobility of a retroelement was activated in a cross between two wallaby species, though the hybridisation resulted in only sterile males. 69 In maize, the original studies of Nobel Prize winner Barbara McClintock demonstrated that the activity of the transposons in different corn kernel cells could be followed by their effects on corn kernel coloration. In plants, there is additional strong evidence that movement of mobile elements in the past has altered gene expression. Although retrotransposon sequences, for example, are seldom found near genes in animals, recent analyses of plant mobile element insertion sites have revealed the presence of degenerate retrotransposon insertions adjacent to many normal plant genes that act as regulatory elements. 70 In addition to retrotransposons, MITEs are also found adjacent to many plant genes, where they also often provide regulatory sequences necessary for transcription.71 Plants, as well as animals, would have had to adjust to the drastically-altered post-Flood world. Other, more dramatic examples may exist, and further research will hopefully reveal them. Why debunk ‘junk’ DNA? What is the relevance to creation science, and to people in general, of a better understanding of the function of these DNA elements? Because of the publicity surrounding the Human Genome Project, there is increasing general interest in how our genomes work, and what exactly they look like. There is more and more emphasis being placed on discovering our evolutionary history through DNA, not fossils.The fact that functions are being found for junk DNAs fits in well with creation science, but was not predicted by evolutionary theory, though of course the theory is being adjusted again to accommodate the data. The intricate flexibility and specificity of these ‘junk’ DNA sequences are a strong testimony to a designer who plans and provides for the future of his creation. Glossary Allele Antisense RNA

one of several alternate forms of a gene occupying a given locus on a chromosome. Return to text. RNA made by copying the other DNA strand in a coding segment in the opposite direction; this RNA will bind to the mRNA made from the coding or sense strand. Return to text. Baramin the creationist term for an original created kind; not synonymous with species. Organisms within the same baramin may be of different species but can cross-hybridise, like the horse and the donkey.Return to text. Complementary two strands of DNA or RNA are said to be complementary when they can form base pairs (A-T, GC) with each other, e.g. AATTCC and TTAAGG. Return to text. Chromatin the complex of DNA and protein in the nucleus of the interphase cell. Return to text. Euchromatin the less condensed chromatin in the nucleus that is more transcriptionally active than the heterochromatin.Return to text. Eukaryote an organism with an organized nucleus. Return to text . Haploid half the set of the chromosome pairs; contains one copy of each chromosome pair and one of the sex chromosomes; characteristic of gametes (sperm and egg cells). Return to text. Heterochromatin regions of the genome that are in a highly condensed state and are not usually transcribed. Constitutive hetereochromatin is always in this condensed, inactive state, contains no genes, and is usually found at the centromeres and teleomeres. Facultative heterochromatin is condensed only in certain cell types, or at certain developmental stages when the genes contained in it need to be turned off. Return to text. Histones a family of basic proteins found tightly associated with DNA in all eukaryotic nuclei; their binding forms a bead structure called a nucleosome. Return to text. Horizontal when mobile elements or viruses are transferred between individuals by infection rather than by transmission inheritance (vertical transmission). Return to text. Human endogenousretroviruses that have become part of the human genome in the past by insertion into the germline retroviruses (HERVs) cells. Return to text . Hybridisation the pairing of single-stranded complementary RNA and/or DNA strands to give an RNA-DNA or DNA-DNA hybrid.Return to text. Inversion occurs when recombination between DNA segments causes the DNA between them to be flipped into the opposite orientation at the same chromosomal locus. Return to text. Isochore LTR

an approximately 300 kb segment of DNA whose bp composition is uniform above a 3 kb level, for example 67% A-T bp. This is believed to enable a certain level of co-regulation of all the DNA in the isochore. Return to text . long terminal repeat; the longer, more complex repeated sequences at the ends of some mobile elements, which are required for them to transpose. Return to text.

ORF

open reading frame; a stretch of DNA or RNA that contains of series of triplet codons coding for amino acids, without any protein termination codons, that is potentially translatable into protein. Return to text. P elements DNA transposons found in fruit fly species that often have a high level of mobility. Return to text. Promoter a region of DNA involved in binding of RNA polymerase to initiate transcription. Return to text. Poly-(A) tail a sequence of adenine residues added to the 3’ end of a mRNA after transcription in the process called polyadenylation; believed to help stabilize mRNAs from being degraded. Return to text. Pseudogene a gene that has been inactivated in the past by an insertion or deletion of DNA. Return to text. Prokaryote an organism that lacks an organized nucleus, and has its DNA mostly in a single molecule; a bacterium. Return to text. Processed a gene that has been apparently reverse-transcribed from its mRNA back into DNA and reinserted pseudogene into a chromosome. It thus lacks its introns, has a poly-A tail, and often is bounded by the characteristic direct repeats associated with transposition. Return to text. Retroelement any sequence that transposes through an RNA intermediate. Return to text. Retrotransposons mobile elements that encode reverse transcriptase. Transpose through an RNA intermediate. Classed into LTR-containing and poly (A)containing: LTR-containing—similar to proviral form of vertebrate retroviruses and usually have 2 ORFs, gag and pol (protease, integrase, reverse transcriptase, RNase H), e.g. Gypsy and tom. Poly (A)—containing retroelements or retroposons lack LTRs and have a 3’ A-rich region. Have 2 ORFs, gag and pol. Some elements such as L1 and the I Factor of Drosophila, contain a reverse transcriptase. L1 is found in yeast and humans. Return to text . Retrovirus a virus using RNA as its information storage system rather than DNA, integrates into host DNA as part of its lifecycle in a way very similar to retrotransposons, but also has additional genes that code for its packaging into virus particles for infection of other hosts. Return to text. Reverse transcriptase an enzyme found in retroelements that will make a complementary DNA strand from an RNA template. Return to text. Splicing two exons, or coding regions on a messenger RNA, are ed together when the intron (noncoding segment) between them is removed. Return to text . Translation the synthesis of protein on the messenger RNA template. Return to text. Translocation of a chromosome describes a rearrangement in which part of a chromosome is detached by breakage and then becomes attached to some other chromosome. Return to text. Transcription synthesis of RNA on the DNA template. Return to text . Transposase the enzyme that cuts the target DNA and splices in the transposing sequence; called the integrase in retroelements. Transposon any DNA sequence that can move about the genome, either by replicating itself, or by a cut-andpaste mechanism. In its simplest form, it is a transposase gene (see above) surrounded by a sequence on either side repeated directly or in inverse form, e.g. ATTGCGC and CGCGTTA are inverted repeats. Return to text . Triplet codon three nucleotides in an RNA or DNA that signal the insertion of a particular amino acid or termination signal; e.g. AUG would be the ‘code word’ for methionine. Return to text. UTR untranslated region; the parts of a messenger RNA before the first exon (‘5 prime’ UTR) and after the last exon (‘3 prime’ UTR) that are not translated into protein (non-coding). Return to text. Acknowledgements The author wishes to thank Dr. Todd C. Wood for providing unpublished information on his AGEing theory and his rice genome research. Thanks also to the editor for helpful discussions, information and patience with revisions. The slow, painful death of junk DNA by Robert W. Carter So-called “junk DNA” has fallen on hard times. Once the poster child of evolutionary theory, its status has been increasingly challenged over the past several years. Functions for junk DNA have been cited at other places on this website 1 and in the Journal of Creation2. In The Great Dothan Creation Evolution Debate,3 my opponent’s main argument, to which he returned again and again, rested on junk DNA. I warned that this was an argument from silence, that ‘form follows function’, and that this was akin to the old vestigial organ argument (and thus is easily falsifiable once functions are found). We did not have to wait long, however, because a new study has brought the notion of junk DNA closer to the dustbin of discarded evolutionary speculations. Faulkner et al. (2009)4 have put junk DNA on the run by claiming that retrotransposons (supposedly the remains of ancient viruses that inserted themselves into the genomes of humans and other species) are highly functional after all. Background Based on the work of J.B.S. Haldane (Haldane 1957) 5 and others, who showed that natural selection cannot possibly select for millions of new mutations over the course of human evolution, Kimura (1968)6 developed the idea of “Neutral Evolution”. If “Haldane’s Dilemma”7 was correct, the majority of DNA must be non-functional. It should be free to mutate over time without needing to be shaped by natural selection. In this way, natural selection could act on the important bits and neutral evolution could act randomly on the rest. Since natural selection will not act on neutral traits, which do not affect survival or reproduction, neutral evolution can proceed through random drift without any inherent ‘cost of

selection’.8 The term “junk DNA” originated with Ohno (1972),9 who based his idea squarely on the idea of Neutral Evolution. To Ohno and other scientists of his time, the vast spaces between protein-coding genes were just useless DNA whose only function was to separate genes along a chromosome. Can you see how the idea of junk DNA came about? It is a necessary mathematical extrapolation. It was invented to solve a theoretical evolutionary dilemma. Without it, evolution runs into insurmountable mathematical difficulties.To recap for emphasis: Junk DNA is not just a label that was tacked on to some DNA that seemed to have no function; it is something that is required by evolution. Mathematically, there is too much variation, too much DNA to mutate, and too few generations in which to get it all done. This was the essence of Haldane’s work. Without junk DNA, evolutionary theory cannot currently explain how everything works mathematically. Think about it; in the evolutionary model there have only been 3–6 million years since humans and chimps diverged. With average human generation times of 20–30 years, this gives them only 100,000 to 300,000 generations to fix the millions of mutations that separate humans and chimps. This includes at least 35 million single letter differences, 10 over 90 million base pairs of non-shared DNA,10nearly 700 extra genes in humans (about 6% not shared with chimpanzees),11 and tens of thousands of chromosomal rearrangements. Also, the chimp genome is about 13% larger12 than that of humans, but mostly due to the heterochromatin that caps the chromosome telomeres. All this has to happen in a very short amount of evolutionary time. They don’t have enough time, even after discounting the functionality of over 95% of the genome—but their position becomes grave if junk DNA turns out to be functional. Every new function found for Junk DNA makes the evolutionists’ case that much more difficult.One of the important classes of “junk DNA” is retrotransposons, which were thought to be leftovers from ancient virus infections where bits of DNA from the viruses had been randomly inserted into the DNA of humans (for example).The idea that huge stretches of human DNA are useless junk left over from evolution is itself having to be progressively junked.Enter Faulkner et al. (2009). Working in human and mouse, they discovered that between 6 and 30% of RNAs13 start within retrotransposons. Their distribution is clearly not random. This was a shock in itself, but they added that these RNAs are generally tissue-specific, as if there were different classes of retrotransposons involved in regulating gene expression in different tissues. From the start, their conclusions do not seem to the idea that retrotransposons are evolutionary junk, but it gets better from there. It turns out that retrotransposons coincide with gene-dense regions and occur in pronounced clusters within the genome, emphasizing the non-random distribution pattern. When they occur upstream of protein coding genes, they provide an abundance of alternative start sites for transcription, producing abundant alternative mRNAs and non-coding RNAs. On the downstream end, over one quarter of RefSeq (protein-coding) genes14 have a retrotransposon in their 3’ UTRs,15 and these reduce the amount of protein synthesized. They concluded that these 3’ UTRs are the site of intense transcriptional regulation. This is hardly something one would expect from junk DNA! Based on the distribution of retrotransposons, they identified a whopping 23,000 candidate regulatory regions within the genome. In addition, they found 2,000 examples of bidirectional transcription caused by the presence of retrotransposons (where the DNA is “read” in both directions, not just one direction, which is thought to be the norm).At one point Faulkner et al. try to downplay their results. They point out that only some retrotransposons contain active promoters and that only some of these are functional. They do not advocate a universal function for retrotransposons. However, as Faulkner et al. also point out, retrotransposons are highly abundant, with thousands of retrotransposon promoters immediately adjacent to protein coding genes, influencing their regulation and, they assume, their evolution. They concluded that retrotransposons have a key influence on transcription genome-wide, that they are “multifaceted regulators of the functional output of the mammalian transcriptome”, that they are “a pervasive source of transcription and transcriptional regulation”, and that they “must be considered in future studies of the genome as a ‘transcription machine’.”These results are stunning. With genome regulation becoming more and more complicated, and with more and more of the genome being demonstrated to be functional, one wonders how long evolutionists can hold to the idea of junk DNA? However, hold on to it they must, for without it they lose one of their best arguments. But they just lost one of their favorite pieces of evidence: the presence of ancient deactivated viruses in the genome. Rather than being functionless vestigial remnants of our past, retrotransposons turn out to be functionally integrated into the amazingly complex regulatory apparatus of mammalian genomes!I’d like to point out that young-earth creationists do not require the entire genome to be highlyfunctional. While I suspect that direct and indirect controls of transcription will eventually be found for most of it, there may be very large stretches of the genome that just add temporal structure to the functional parts. Think of them as scaffolding in a three-dimensional genomic skyscraper. Even these portions will be functional (because of a need for structure), though they may not contribute directly to genome regulation, and their sequence specificity might be very weak. We’ll have to wait to see how it all works out in the end. For now, let us take heart that one more weak link in the evolutionary line of arguments has been exposed. No joy for junkies by Don Batten Before any sequencing of DNA had been done, evolutionists decided that fully 99% of the human DNA must be inert or ‘junk’. They came to this conclusion because, according to the calculations of population geneticists, if much more than 1% of the DNA sequence of creatures such as humans actually mattered, then ‘error catastrophe’ would have resulted, because natural selection could not have eliminated the large number of harmful mutations.1When the DNA sequencing turned up ‘only’ about 35,000 proteincoding genes in humans, the evolutionists seemed vindicated, except that we already knew that DNA codes for more than just proteins. For example, the transfer-RNAs and ribosomal RNA are coded on the DNA. And various segments of DNA-coded RNA were being implicated as co-factors in various chemical reactions and in gene activation or suppression. But what else does all that DNA do?Bit by bit, the idea of ‘junk’ DNA has been unravelling. There have been reviews and notes in Journal of Creation2–5covering some of the exciting developments.Recently, a large chunk of the remaining ‘junk’ has been implicated in the control of embryo development. Scientists at the Jackson

Laboratory, Maine, USA, found that a type of transposable element (TE), a major class of supposed ‘junk’ or ‘parasitic’ DNA, activates during embryo development in mice.6 In a commentary on this work, Ricky James commented:‘Therefore, more than one third of the mouse and human genomes, previously thought to be non-functional, may play some role in the regulation of gene expression.’7Note that this ‘non-coding’ DNA only seems to function during egg and embryo development, so studying TEs in other cells would not reveal their function. This might explain why the functions of non-coding DNA have been so elusive.These developments underline, once again, how evolutionary premises impede the progress of science. In the past, evolutionary notions led to over 100 human features being labeled ‘vestigial’, or leftovers of our supposed animal ancestry.8 This was based on the similarity of these features to ones found in animals, combined with the lack of knowledge about what the organs did. The lack of logic is astonishing: ‘since we don’t know what the organs do, they must be useless’. The same evolutionary ‘logic’ has been applied to the DNA: ‘we don’t know what most of it does, so it must do nothing’. So it is labelled ‘junk’, ‘pseudogenes’, ‘parasitic’, ‘retroviral inserts’, etc.Thankfully, not everyone bought this idea. In the late 1980s, New Zealand–born Australian immunologist Malcolm Simons recognized patterns, or order, in the non-coding DNA that indicated to him that the code must have a function, but others ridiculed the idea. 9 In the mid-1990s, he patented the non-coding DNA (95%) of all organisms on Earth. The company he founded, Genetic Technologies, now reaps licence fees from all technologies being developed to cure disease that involve the non-coding DNA. It’s quite controversial, of course, paying such licence fees. And since factors involved in all sorts of diseases, such as breast cancer, Crohn’s disease, Alzheimer’s, heart disease, ovarian and skin cancer, are being found in the ‘junk’, Genetic Technologies is doing quite well.10There’s much gold to be mined from the junk, it would seem.Leading geneticist Prof. John Mattick of the University of Queensland in Brisbane, Australia, has proposed that the non-coding DNA was part of a sophisticated ‘operating system’, with ample justification.11,12 Some critics rejected this on the grounds that such a system could not have evolved! Mattick recently said that ‘the failure to recognise the implications of the non-coding DNA will go down as the biggest mistake in the history of molecular biology’. 9 This mistake can be attributed to an evolutionary approach to biology.Creationists have long argued that ‘junk’ DNA is nothing of the sort. For example, Carl Wieland, Creation Ministries International (Australia), wrote, ‘Creationists have long suspected that this “junk DNA” will turn out to have a function.’ 13 Although there might be a small amount of non-functional DNA due to damaging mutations that have occurred, it is inconceivable that most of the human DNA would be created as having no function. Large scale function for ‘endogenous retroviruses’ by Shaun Doyle Endogenous retroviruses (ERVs) are some of the most cited evidences for evolution. They are part of the suite of ‘junk DNA’ that supposedly comprised the vast majority of our DNA. ERVs are said to be parasitic retroviral DNA sequences that infected our genome long ago and have stayed there ever since. These short DNA strands are found throughout the human genome, and make up about 5% of the DNA,1 or about 10% of the total amount of DNA that is classified as transposable elements (i.e. 50%). 2However, the term ‘endogenous retrovirus’ is a bit of a misnomer. There are numerous instances where small transposable elements thought to be endogenous retroviruses have been found to have functions, which invalidates the ‘random retrovirus insertion’ claim. For instance, studies of embryo development in mice suggest that transposable elements (of which ERVs are a subset) control embryo development. Transposable elements seem to be involved in controlling the sequence and level of gene expression during development, by moving to/from the sites of gene control.3Moreover, researchers have recently identified an important function for a large proportion of the human genome that has been labelled as ERVs. They act as promoters, starting transcription at alternative starting points, which enables different RNA transcripts to be formed from the same DNA sequence.‘We report the existence of 51,197 ERV-derived promoter sequences that initiate transcription within the human genome, including 1,743 cases where transcription is initiated from ERV sequences that are located in gene proximal promoter or 5’ untranslated regions (UTRs).’4 And, ‘Our analysis revealed that retroviral sequences in the human genome encode tens-of-thousands of active promoters; transcribed ERV sequences correspond to 1.16% of the human genome sequence and PET tags that capture transcripts initiated from ERVs cover 22.4% of the genome.’ 5So we’re not just talking about a small scale phenomenon. These ERVs aid transcription in over one fifth of the human genome! ‘These data illustrate the potential of retroviral sequences to regulate human transcription on a large scale consistent with a substantial effect of ERVs on the function and evolution of the human genome.’ 3 This again debunks the idea that 98% of the human genome is junk, and it makes the inserted evolutionary spin look like a tacked-on nod to the evolutionary establishment. These results the conclusions of the ENCODE project, which found that at least 93% of DNA was transcribed into RNA.Evolutionists have used shared mistakes in ‘junk DNA’ as ‘proof’ that humans and chimps have a common ancestor. However, if the similar sequences are functional, which they are progressively proving to be, their argument evaporates.It seems that evolutionist Dr John Mattick, director of the Institute for Molecular Bioscience at the University of Queensland, Brisbane, Australia, was spot on in his assessment of the gravity of the ‘junk DNA’ error:‘The failure to recognize the full implications of this—particularly the possibility that the intervening noncoding sequences may be transmitting parallel information … may well go down as one of the biggest mistakes in the history of molecular biology.’ 6Both creationists7 and ID proponents8 predicted that transposable elements, such as ‘endogenous retroviruses’, would have a function. In 2000, creationist molecular biologist Linda Walkup proposed that transposable elements could be created to facilitate variation (adaptation) within the created kinds.7If the ‘junk DNA’ is not junk, then it puts a big spanner in the work of molecular taxonomists, who assumed that ‘junk DNA’ was free to mutate at random, unconstrained by the requirements of functionality. As Williams points out:‘The molecular taxonomists, who have been drawing up evolutionary histories (“phylogenies”) for nearly every kind of life, are going to have to undo all their years of “junk DNA”-based historical reconstructions and wait for the full implications to emerge before they try again.’9

Hox (homeobox) Genes—Evolution’s Saviour? by Don Batten Some evolutionists hailed homeobox or hox genes as the saviour of evolution soon after they were discovered. They seemed to fit into the Gouldian mode of evolution (punctuated equilibrium) because a small mutation in a hox gene could have profound effects on an organism. However, further research has not born out the evolutionists’ hopes. Dr Christian Schwabe, the non-creationist sceptic of Darwinian evolution from the Medical University of South Carolina (Dept. of Biochemistry and Molecular Biology), What is the REAL message of the patterns wrote: of life? ‘Control genes like homeotic genes may be the target of mutations that would The Biotic Message conceivably change phenotypes, but one must that, the more Walter ReMine central one makes changes in a complex system, the more severe the peripheral consequences become. … Homeotic changes induced This book scientifically fights in Drosophilagenes have led only to monstrosities, and most experimenters evolutionists on their , do not expect to see a bee arise from their Drosophila constructs.’ (Mini on their issues, using their Review: Schwabe, C., 1994. Theoretical limitations of molecular testimony, and their ground phylogenetics and the evolution of relaxins. Comp. Biochem. rules. It dismantles many Physiol.107B:167–177).Research in the six years since Schwabe wrote this evolutionary illusions, and offers a new has only born out his statement. Changes to homeotic genes cause creation theory of biology: Life was monstrosities (two heads, a leg where an eye should be, etc.); they do not designed to shout that it had only ONE change an amphibian into a reptile, for example. And the mutations do not designer, and to resist all other add any information, they just cause existing information to be mis-directed to explanations. 538 pages, hardbound. produce a fruit-fly leg on the fruit-fly head instead of on the correct body segment, for example.Evolutionists, of course, use the ubiquity of hox genes See also review by Dr Don Batten in their argument for common ancestry (‘Look, all these creatures share these ORDER YOUR COPY TODAY genes, so all creatures must have had a common ancestor’). However, commonality of such features is to be expected with their origin from the same (supremely) intelligent designer. All such homology arguments are only arguments for evolution when one excludes, a priori, origins by design. Indeed many of the patterns we see do not fit common ancestry. For example, the discontinuity of distribution of hemoglobin-like proteins, which are found in a few bacteria, molluscs, insects, and vertebrates. One could also note features such as vivipary, thermoregulation (some fish and mammals), eye designs, etc. For more detail, see The Biotic Message. Hox Hype Has Macro-evolution Been Proven? By David A. DeWitt, Ph.D Associate Professor of Biology, and Associate Director, Creation Studies at Liberty University From the hype of the press release, it would seem that evolution was finally proven once and for all and the creationists should just give up and go home. But far from refuting creation, the scientific evidence is completely consistent with creation!The press release from UCSD said in part:‘Biologists at the University of California, San Diego have uncovered the first genetic evidence that explains how large-scale alterations to body plans were accomplished during the early evolution of animals…. The achievement is a landmark in evolutionary biology, not only because it shows how new animal body plans could arise from a simple genetic mutation, but because it effectively answers a major criticism creationists had long leveled against evolution—the absence of a genetic mechanism that could permit animals to introduce radical new body designs.’Evolutionary biologists believe that the six-legged insect body plan evolved from crustacean-like ancestors (including creatures like shrimp) that lost the large number of legs. 1 Such a radical change would require mutation(s) that result in the suppression of leg development. McGinnis and coworkers believed that they found the mutation and the gene responsible for this change. However, careful examination of their efforts reveals that the situation is much more complicated.The scientists were investigating Ubx, a Hox gene which suppresses leg development in flies. Hox genes are master control switches that control the body plan. Specific Hox genes may control where the head forms, where limbs form, or a tail or even wings. These master switches work like circuit breakers and either turn on or turn off an array of other genes. Hox genes can be expressed in abnormal locations and either prevent development of structures or promote their development in very unusual places. For example Pax-6 expression controls the development of eyes. A fly with abnormal expression could form an eye on a leg, the antenna or even abdomen. 2The researchers found that the Ubx gene from a fly completely prevented leg development while the same gene from Artemia, a brine shrimp, only suppressed leg development 15%. They then mutated the Artemia Ubx gene and found that this version was much more effective at blocking leg formation. They postulated that such a mutation probably occurred in the crustaceans that were the ancestors of six-legged insects.3The fact that scientists can significantly alter the body plan does not prove macro-evolution nor does it refute creation. Successful macro-evolution requires the addition of NEW information and NEW genes that produce NEW proteins that are found in NEW organs and systems. For example, a single mutation that might prevent legs from forming is much different from a mutation that produces legs in the first place. Making a leg would require a large number of different genes present simultaneously. Moreover, where do the wings come from? Just because an organism loses a few legs doesn’t convert a shrimp-like creature into a fly. Since crustaceans don’t have wings, where does the information come from to make wings in flies?Having the wings themselves is not even enough. Researchers in another study have found that the subcellular location of metabolic enzymes is important for the functional muscle contraction required for flight. 4 Indeed, the metabolic enzymes must be in very close proximity with the cytoskeletal proteins that are involved in muscle contraction. If the enzymes are not in the exact location in which they are needed within the cell, the flies cannot fly. This study bears out the fact that ‘the presence of active enzymes in the cell is not sufficient for muscle function; colocalization of the enzymes is required.’ It also ‘…requires a highly organized cellular system.’Therefore, changes in body plan—no matter how dramatic—do not automatically prove macro-evolution. Losing structures, or misplacing their development, should not be equated with the increased information that is needed to form novel structures and cellular systems.

HOW DOES GENETICS POINT TO DESIGN Cell systems—what’s really under the hood continues to drop jaws By Brian Thomas Two 2009 papers summarized recent discoveries of utterly unforeseen intricacy, adaptability, robustness and precision in regulating gene expression, even in “simple” cells. Gene expression in eukaryotic cells I conservatively counted 24 recently discovered mechanisms that help regulate gene expression in eukaryotic cells, as reviewed by Moore and Proudfoot.1 Here are just a few of them. Figure 1. Widely regarded as the simplest genome, Mycoplasma gene expression is instead far more complicated than expected. It performs functions that had been considered the sole domain of higher eukaryotes. For example, DNA is transcribed in both the sense and antisense directions, indicating that valuable genetic information is double-stacked. RNA transcripts undergo post-translational modifications, single enzymes have more than one application, and when certain metabolic breakdowns occur, the cell is able to formulate a workaround solution. Illustration after. sciencemag.orgChromatin is not loosely wadded DNA inside cellular nuclei. Instead, it is very precisely organized, with specific portions dynamically looped outward. Each loop is associated with a separate nuclear pore, and can retract to a storage position when appropriate. Robust and efficient machinery ensures that the correct portions of chromatin are unspooled from nearer the center of the nucleus to an appropriate nuclear pore. Each pore is extremely active, with a host of interacting regulatory RNA’s, proteins, and ribonucleoproteins.2 These send and receive communications from and toward the farthest ends of the RNA and protein manufacturing processes.RNA Polymerase does not typically transcribe DNA in fluid space, but is attached to a cadre of proteins associated with each nuclear pore. This way, the rapidly emerging RNA transcript is already proximal to the pore, through which much of it will exit to the cytoplasm. Further, cell biologists have determined that the first copy of a transcript is like a practice run. This first, rough draft RNA transcript either serves as a quality control run, so that its integrity is ensured prior to full manufacture and export from the nucleus, as a primer for the total set of transcript processing machinery to be properly set, as a chemical communicator providing information to downstream processes, or all three. Warming up for transcription In addition, extracellular messages are transferred from the cell membrane to the nuclear pore sites via biochemical cascades, and these influence whether or not a gene region will switch from being transcribed into these rough ‘abortive transcripts’, or into full-length, properly marked and exported transcripts. It appears that transcription machinery is constantly transcribing in an ‘idle’ mode, but when the correct switches are tripped, the machinery fully engages. In full production mode, RNA transcripts often become marked for translation to proteins. Some of the switching messengers are proteins that are temporarily restrained by other proteins, which in turn can release them upon detection of certain cell signals carried by yet more precisely interacting biochemicals. For example, even sugar moieties riding on proteins have been found to act as a “safety switch that regulates the microswitches” which fine tune protein expression during cell division.3 Full-on eukaryotic transcription runs super-fast When all systems are ‘go’, transcription proceeds with “fully processive elongation of the full body of the gene.” 1 Inside the nucleus, the relevant DNA is pulled, like a loop of magnetic tape, across a nuclear pore. Some of the proteins involved in this action are named Set1PAF, Spt6, FACT, Chd1, along with other histone proteins. This way, the emerging transcript is under the constant watchful attention of a wide array of sensory, quality control, marking, and transporting machinery, all kept near the pore by precise chemical interactions specified by exactly arranged biomolecular sizes, shapes, charges, and polarities.It was known that transcripts in eukaryotic cells undergo cut-and-pasting as well as splicing. It is now known that this occurs simultaneously with manufacture, and requires a separate host of proteins. However, those pre-mRNA splicing proteins directly interact with the RNA polymerase assemblage, which all works together to react to ‘pause-sites’ in the gene it is transcribing. RNA polymerase acts like a ‘molecular juggernaut’,1 streaming RNA’s out as though through a jet engine. It must be slowed down in order for cutting and splicing machinery to have opportunity to insert. Since not all DNA pause sites become RNA cut sites, and since the alternative combinations of cut and spliced mRNA transcripts can specify a wide variety of regulatory or catalytic RNA’s and proteins from just one ‘gene’, 4 it is apparent that somehow precise communication occurs to discern which pause sites will result in cuts.In yeast, a model eukaryote, the THO/TREX protein complex serves three roles: one in transcription, one in “transcript-dependent recombination”, and one in mRNA export.1 And it does these while in constant communication with machine parts that are involved in transcript initiation as well as parts involved in slowing and stopping transcription. It is therefore one of many proteins and protein complexes that are being discovered with multiple functions—a clear sign of elegant engineering. Process flow management in translation The emerging RNA transcript then gets labeled with specific protein markers. The markers had already been gathered to the nuclear pore site, and are presented to the nascent transcript just inside the nucleus. The immediacy of labeling thus is vital. It guards against the dangers of having naked RNAs in the nucleus, as described below. The markers, too, serve multiple purposes. The more splices in the transcript, the more markers are attached, and this eventually causes more efficient translation because a transcript thus bedecked is more likely to have some surface exposed to cytoplasmic proteins vital to translation. The markers also signal watchdog nuclear pore proteins to expedite the transcript’s export.These same

watchdog proteins also serve to prevent naked transcripts from re-entering the nucleus. This is vital, for bits of RNA naturally anneal to unzipped DNA. If this happened, it would quickly create havoc in the nucleus by both generating mutations and gumming up the many nuclear processes that depend on accurate DNA recognition, clamping, spooling, unwinding, and other processes.After export, the cytoplasmic machinery links each transcript to other machines. Some of these shepherd the transcript toward a ribosome. Each time a transcript has been thus shepherded, some of its markers are removed, with most being lost after its first round of translation. Eventually the transcript becomes naked and difficult for translational machinery to detect, and subject to degradation. In this way, the freshest and highest quality transcripts are by far most translated by the ribosome. Eukaryotic gene expression is astonishing Effective quality control mechanisms constantly cull corrupt transcripts. For example, if a transcript did not have the correct signal sequence attached when it was first formed, due to gene mutation or an error in processing, the compromised molecule would have been recognized immediately at the nuclear pore, and degraded by RNase enzymes. This ensures that downstream processes are not gummed up with useless transcripts. Quality control is critical to forming the correct products in the needed amounts, and at appropriate paces.Other systems produce a stockpile of quality transcripts in strategic pockets within the cytoplasm. This way, there can be “a tightly controlled burst of the desired [protein] product.”1There is no indication that the discovery pace of more mind-bogglingly brilliant cell processes will slow down anytime soon. If none of the above made sense, then let the reader be edified by the glowing research summary:“At every point along the way, multifunctional proteins and [ribonucleoprotein] complexes facilitate communication between upstream and downstream steps, providing both feedforward and information essential for proper coordination of what can only be described as an intricate and astonishing web of regulation.”1 The ‘simple’ Mycoplasma Mycoplasma pneumoniae bacteria, long considered the simplest prokaryote, can no longer be described thus. It is a parasitic bacterium that (M. pneumonia causes walking pneumonia) has a reduced genome size. It relies on its host for certain nutrients that its ancestors apparently were able to manufacture. Thus, it has undergone significant genomic decay. How Mycoplasma bacteria really work The authors of a paper in Science endeavored to investigate “how a cell actually accomplishes” necessary processes using the most basic subject of study.5 But they ran into a juggernaut of layered information-rich complexity that inspired their assessment:“Together, these findings suggest the presence of a highly structured, multifaceted regulatory machinery, which is unexpected because bacteria with small genomes contain relatively few transcription factors … revealing that there is no such a thing as a ‘simple’ bacterium.”5Specifically, evolutionists Ochman and Raghavan cited research that found in many cases the ‘sense’ strand of protein-coding genes is transcribed, the complementary or ‘anti-sense’ strand is also transcribed. The resulting ‘sense mRNA’ is eventually translated to protein, and the resulting ‘antisense mRNA’ binds to the sense mRNA to make a double stranded RNA. This slows its path toward translation, and is thus an important speed regulator. This was previously only known to occur in eukaryotes. Mycoplasma cells have eukaryotic complexity In other experiments, different environmental growth conditions caused different lengths and segments of genomic DNA to become transcribed. This implies a suite of chemical communication cascades from the cell wall inward, as well as the ability to make alternate products from one gene. This, too, was a surprise, only known in eukaryotes.Like eukaryotic cells, these ‘simplest’ among prokaryotes have multifunctional proteins which can be used in different metabolic pathways as backup machines. Other data strongly suggests that newly manufactured proteins can be altered by other cellular machinery. Termed ‘post-translational modification’, this was taught dogmatically in my 1998 graduate biochemistry courses as exclusive to eukaryotes.Also shocking was the discovery that over 90% of Mycoplasma proteins are involved in protein complexes, again like eukaryotes. Another genome-wide survey found indirect evidence of tight gene expression regulation, but nobody yet knows the mechanism for it.They finally argue that because Mycoplasma is still alive even after such reduction in quality and quantity of its genome, it must have “an underlying eukaryote-like cellular organization replete with intricate regulatory networks and innovative pathways.”5 Where did Mycoplasma get all this in the first place? These authors then bravely ask, “How did these remarkable layers of gene regulation and the highly promiscuous [multifunctional] behavior of proteins in M. pneumoniae arise?”4 But they instead explain that:“ … the reduced efficacy of selection that operates on the genomes of host-dependent bacteria … reductions in long-term effective population size [from the bottleneck that occurred when the bacteria first became host-dependent, and] the accumulation and fixation of deleterious mutations in seemingly beneficial genes due to genetic drift, [together cause a] reducing genome size.” 5If selection, bottlenecks, and mutations only reduced the genome, then these processes are no help at all. What in nature expanded the genome with ingeniously useful data that the remarkably robust yet genomically truncated Mycoplasma retains plenty of? Conclusion At every level, scientists have uncovered more information. That information takes the form of three-dimensional shapes, electronic and charge configurations, as well as raw coding sequence information. Communication pathways, routines and subroutines, prioritizing, quality control, and process regulation plans are all stunningly effective and strikingly small.More indepth knowledge of these fantastically complicated cell features demands greater faith from naturalists in the belief that laws of chemistry built cells. The more informational structures that are found, the greater the gap between the organization in living system parts and the disorganization found in nonliving chemicals.A reminder of some inferences about information would seem appropriate here. First, wherever precise regulation of processes due to expertly engineered machines and codes are seen coming into existence, they always comes from persons. Stated negatively, these machines and codes are never observed to originate from natural laws. Therefore, it is most parsimonious to infer that wherever similar machines, processes, and codes are found, they, too, were not derived by nature, but instead by a person or persons.Second, “ … like spoken languages, biological language is irreducibly complex and yet without physical substance. It comes complete with symbols, meanings for those symbols, and a grammatical structure for their interpretation. Remove any one of these three fundamental features, and the informational system is lost. Physics has nothing to do with symbols or grammar, and therefore nothing to do with the origin of life, which cannot exist without its coded information.”6 If run-of-the-mill information always comes from a mind, then this cellular information, being extraordinary, came from a mastermind.

Meta-information An impossible conundrum for evolution by Alex Williams Published: 30 August 2007(GMT+10) Cell division, once thought of as a fairly simple thing, is now known to be an incredibly complex, orchestrated affair that shouts ‘intelligent design’. New genetic information? Evolutionists have never been able to give a satisfactory answer to the problem of where the new information comes from that evolution requires for turning a microbe into a myxomycete or a maze-mastering mammal. Their best guess is gene duplication (which gives them an extra length of DNA, but it contains no new information) followed by random mutations that are supposed to turn the duplicated information into something new and useful.They have no direct experimental evidence for this claim (and there is much against it 1), so they have to rely on indirect evidence such as the so-called ‘gene families’. Some genes are similar in both structure and function to other genes, and evolutionists point to these and say they originated by chance copying and mutation from some common ancestral gene. But this is just evolutionary speculation; it is not experimental evidence.The globin gene family is a favourite example. Hemoglobin carries oxygen in our blood and can be made up of different combinations of different kinds of globin proteins. For example, hemoglobin in human fetal blood contains a different combination of globins to that in post-natal blood. Evolutionists claim this resulted from an original globin molecule that duplicated in an early blood-using animal and mutated to form a family of different kinds of globins, which then allowed the diversification of complexity in oxygen-using processes that we see in the animal world today. 2But this example is far better explained by intelligent design.3 The human baby in his or her mother’s womb has to compete for the oxygen in its mother’s blood supply with the demand for oxygen from two other sources: the placenta that feeds it, and from the mother’s womb that surrounds it. So the fetal hemoglobin has to have, amongst other things, a higher affinity for oxygen than the mother’s hemoglobin. In contrast, when the baby is born and can draw oxygen from the air in its own lungs, it no longer has any competition so it requires a different kind of oxygen-uptake system. A wise designer would ensure that the hemoglobin could change its form and function to cater for these very different conditions, and integrate this change into the other vast complexities of the almost miraculous reproductive process. The idea that such complex interactive changes could all occur by chance is rather hard to accept. Information about Information But the problem of information origin in biology is far bigger than most people realize. Information by itself is useless unless the cell knows how to use it. Evolution not only requires new information, it also requires extra new information about how to use that new information.Information about information is called meta-information. We can see how it works in making a cake. If you want to make a cake, you need a recipe that contains: (a) a list of ingredients, and (b) instructions on how to mix and cook the ingredients to produce the desired outcome. The list of ingredients is the primary information, and the instructions on what to do with the ingredients is the meta-information.The human genome contains an enormous amount of information, far more than we ever (until recently) imagined. 4 But we now know that most of it is not primary information (protein-coding genes) but meta-information—the information that cells need to have in order to turn those protein-coding genes into a functional human being and maintain and reproduce that functional being. This meta-information is stored and used in a variety of ways:DNA consists of a double-helix—two long-chain molecules twisted around one another. Each strand consists of a chain of four different kinds of nucleotide molecules (the shorthand symbols are T, A, G and C). About 3% of this in humans consists of protein-coding genes and the other 97% appears to be regulatory meta-information.DNA is an information-storage molecule, like a closed book. This stored information is put to use by being copied onto RNA molecules, and the RNA molecules put the DNA information into action in the cell. For every molecule of protein-producing RNA (primary information), there are about 50 molecules of regulatory RNA (meta-information).Down the sides of the DNA double-helix, several different kinds of chemical chains are attached in patterns that code meta-information for turning unspecialized embryonic stem cells into the specialized cells that are needed in fingers, feet, toenails and tail-bones etc.DNA is a very long thin molecule. If we unwound one set of human chromosomes, the DNA would be about 2 metres long. To pack it up into the very tiny nucleus inside the very tiny human cell, it is coiled up in four different levels of chromatin structure into 46 chromosomes. This coiling chromatin structure also contains yet further levels of meta-information . The first level (the histone code) codes information about the cell’s history (i.e. it is a cell memory). 5,6 The three further levels of coiling code further information, some of which is described below, and there is no doubt more that we have yet to unravel.The amount of meta-information in the human genome is thus truly enormous compared with the amount of primary gene-coding information. Self-replicating molecules? In his monumental work, The Ancestor’s Tale,7 Richard Dawkins traced the supposed ancestry of humanity back through all the evolutionary ages to the very first supposed common ancestor of all life. He supposed this original ancestor to have been an RNA-type of life form, although he itted ignorance of the precise details.8 His choice of an original RNA life form is well-founded because RNA is the only known molecule that can do all of the three basic functions of life: (a) store coded information, (b) combine with itself and other RNAs to create molecular machines, and (c) self-replicate (but only in a very limited manner under very special circumstances).However, recent studies showing how living cells actually replicate have made this ‘RNA world’ concept ludicrously unrealistic.A central problem in cell division (that is, what living cells actually do, as opposed to Dawkins’ imagined self-replication) is that a large proportion of the whole genome is required for the normal operation of the cell—probably at least 50% in unspecialized body cells and up to 70–80% in complex liver and brain cells. When it comes time for a cell to divide, not only does the DNA have to continue to sustain normal cell operations, it also has to sustain the extra activity associated with cell division.

This creates a huge logistic problem—how to avoid clashes between the transcription machinery (which needs to continually copy information for ongoing use in the cell) and the replication machinery (which needs to unzip the whole of the DNA double-helix and replicate a ‘zipped’ copy back onto each of the separated strands).The cell’s solution to this logistics nightmare is truly astonishing.9 Replication does not begin at any one point, but at thousands of different points. But of these thousands of potential start points, only a subset are used in any one cell cycle—different subsets are used at different times and places. Can you see how this might solve the logistics problem?A full understanding is yet to emerge because the system is so complex; however, some progress has been made:The large set of potential replication start sites is not essential, but optional. In early embryogenesis, for example, before any transcription begins, the whole genome replicates numerous times without any reference to the special set of potential start sites.The pattern of replication in the late embryo and adult is tissue-specific. This suggests that cells in a particular tissue cooperate by coordinating replication so that while part of the DNA in one cell is being replicated, the corresponding part in a neighbouring cell is being transcribed. Transcripts can thus be shared so that normal functions can be maintained throughout the tissue while different parts of the DNA are being replicated.DNA that is transcribed early in the cell division cycle is also replicated in the early stage (but the transcription and replication machines are carefully kept apart). The early transcribed DNA is that which is needed most often in cell function. The correlation between transcription and replication in this early phase allows the cell to minimize the ‘downtime’ in transcription of the most urgent supplies while replication takes place.There is a ‘pecking order’ of control. Preparation for replication may take place at thousands of different locations, but once replication does begin at a particular site, it suppresses replication at nearby sites so that only one copy of the DNA is made. If transcription happens to occur nearby, replication is suppressed until transcription is completed. This clearly demonstrates that keeping the cell alive and functioning properly takes precedence over cell division.There is a built-in error correction system called the ‘cell-cycle checkpoints’. If replication proceeds without any problems, correction is not needed. However, if too many replication events occur at once the potential for conflict between transcription and regulation increases, and/or it may indicate that some replicators have stalled because of errors. Once the threshold number is exceeded, the checkpoint system is activated, the whole process is slowed down, and errors are corrected. If too much damage occurs, the daughter cells will be mutant, or the cell’s self-destruct mechanism (the apoptosome) will be activated to dismantle the cell and recycle its components. An obvious benefit of the pattern of replication initiation being never the same from one cell division to the next is that it minimizes the effect of any errors that are not corrected. The impossible conundrum Now comes the impossible conundrum. Keeping in mind the cake analogy, lets recall that the vast majority of information in humans is not ingredient-level information (code for proteins) but meta-information—instructions for using the ingredients to make, maintain and reproduce functional human beings.Evolutionists say that all this information arose by random mutations, but this is not possible. Random events are, by definition, independent of one another. But meta-information is, by definition, totally dependent upon the information to which it relates. It would be quite non-sensical to take the cooking instructions for making a cake and apply them to the assembly of, say, a child’s plastic toy (if nothing else, the baking stage would reduce the toy to a mangled mess). Cake-cooking instructions only have meaning when applied to cake-making ingredients. So too, the logistics solution to the cell division problem is only relevant to the problem of cell division. If we applied the logistics solution to the problem of mate attraction via pheromones (scent) in moths it would not work. All the vast amount of meta-information in human beings only has meaning when applied to the gene content of the human genome.Even if we granted that the first biological information came into existence by a random process, the metainformation needed to use that information could not come into existence by the same random (independent) process because meta-information is inextricably dependentupon the information that it relates to.There is thus no possible random (mutation) solution to this conundrum. Can natural selection save the day? No. There are at least 100 (and probably many more) bits of meta-information in the human genome for every bit of primary (protein-coding gene) information. An organism that has to manufacture, maintain, and drag around with it a mountain of useless information while waiting for a chance correlation of relevance to occur so that something useful can happen, is an organism that natural selection is going to select against, not favour! Moreover, an organism that can survive long enough to accumulate a mountain of useless information is an organism that does not need useless information—it must already have all the information it needs to survive!What kind of organism already has all the information it needs to survive? There is only one answer—an organism that was designed in the beginning with all that it needs to survive. Splicing and dicing the human genome Scientists begin to unravel the splicing code by Robert W. Carter Published: 1 July 2010(GMT+10) What separates the genomes of simple organisms like sea anemones and jellyfish from humans? Humans have approximately the same number of protein coding genes as these lowly creatures,1 yet we are much more complex organisms. Ignoring the spiritual aspects of humanity, this complexity difference must be coded within our genomes, but where? Since we share many genes with many simpler organisms, the answer does not lie in gene content alone. Rather, the differences are in the non-coding portions of the genome (the so-called “junk DNA”2) and in the way the genes are used to create proteins.Several decades ago, the “one gene-one enzyme” hypothesis was in vogue. It seemed straightforward that a single protein gene coded for a single protein. In prokaryotic organisms (bacteria), this was easy to show. The known bacterial genes had a defined starting and stopping place and the DNA letters in between spelled out a discrete amino acid sequence. The eukaryotes (organisms with a nucleus; everything from yeast, to plants, to humans) do not have a simple gene structure. Our protein genes are broken up into a series of “exons” (the parts that code for protein) and “introns” (non-coding intervening sequences). To make a protein, the gene is first transcribed into RNA, then the introns are spliced out, the exons are stitched together, and the remainder is translated into protein. Even though complex, the one gene-one enzyme hypothesis was still applied to eukaryotic protein genes.Over time, however, it was realized that life was not so simple, especially for the eukaryotes. The one gene-one enzyme hypothesis was particularly troubling for the higher (more complex) eukaryotes. For example, the approximately 20,000-25,000 protein-coding genes in the human genome3 are used to create 100,000-300,000 distinct proteins (the actual number is uncertain). The low number of genes in the human genome was troubling for several reasons. 4 First, this means that we did not have that many more genes than organisms much simpler than us. Second, we needed a way to create many proteins from few genes and nobody knew how this could be done on such a large scale. And third, the complexity of the genomic computer program ratcheted up to even more uncomfortable levels for those who thought we arose through random chance.Even before Human Genome

Project5 was complete, we knew that some proteins are manufactured through a process called “alternate splicing”, where exons from different locations in the genome are combined to create many different proteins. From the ENCODE project,6 we learned that alternate splicing is so pervasive that the definition of the word “gene” is currently under debate.7 Thus, the one gene-one enzyme hypothesis turned out to be a gross oversimplification. However, the word and the concept of a “gene” is so useful that for the rest of this article I will be referring to “genes” in the classic sense as a contiguous stretch of DNA with a starting and ending location and a set of introns and exons that could potentially be transcribed, spliced, and translated into a single protein. Each gene, however is made of parts that can be recombined with parts from other genes in different locations in the genome to create proteins not coded by any specific gene.Alternate splicing is a brilliant design concept that allows for a streamlined genetic program that takes up a fraction of the space compared to a program that coded for each protein independently. But this added complexity comes at a price. It has been conservatively estimated that each intron adds the same amount of complexity as approximately 30 additional DNA letters.8 Thus, the “mutation target” for a gene is increased for each intron added. Consider that the average protein-coding gene has 7-10 introns and that the total length of introns is often longer than the total length of protein coding DNA, and one can see why this is a problem. It takes a lot to maintain such a system and the complexity makes it difficult for naturalistic theories of origins. In fact, a sizeable proportion of human genetic disease has been attributed to mutations within intronexon splice sites.9 Introns are typically included in the junk DNA category, but they have specific sequences at the head and tail ends that tell the splicing mechanism where to cut, etc., so they are not without function. (Exons also have splice signals at their ends. Thus, some of the information for splicing out the introns is found within the protein-coding portion of the genome. The protein-coding sections code for both protein sequence and splicing patterns at the same time!)The ENCODE project made the significant discovery that nearly all of the genome was turned into RNA at some point in the life of a cell and that multiple overlapping RNAs were often created from the same stretch of DNA. This was a tremendous blow to junk DNA theorists.10However, perhaps more importantly, the ENCODE results also documented an amazing amount of alternate splicing. So, here we were, knowing that a huge portion of the genome is active and that the protein-coding portions were being used in complex combinations, but we still did not know how it all came together. Because of this, scientists have been looking for a “splicing code” within the genome that controls the slicing and dicing of the protein genes. This splicing code must for 1) the complex combinations of exons needed to create hundreds of thousands of proteins from tens of thousands of protein genes, 2) the variation in splicing from cell to cell needed to for the different proteins expressed in different cell types, and 3) changes in splicing patterns over time as the organism proceeds from fertilized egg to adult (since not all genes are active at all stages in the life cycle). All this information must be coded in the genome, but it also cannot interfere with the protein-coding domains. Thus, most of this information must reside within the introns and in the spaces between genes.A paper recently appeared in Nature where the authors claimed to have discovered the beginning of the splicing code. What they found is a marvel of complexity. Science labs across the world have been generating tremendous amounts of data and they were able to capitalize on this new knowledge in a massive data mining exercise. Specifically, vast databases have been compiled that tell us which genes are active in different cell lines and at different stages of development. We also know of many DNA-binding factors and their specific sequence targets (usually a short string of very precise letters that are targeted by proteins with whimsical names like “Star”, “Nova”, and “Quaking-like”). With this knowledge, they were able to approach the issue statistically to document significant features that help to control alternate splicing. They found many “motifs” (short DNA words of 5-10 letters each) before and after many exons that were strongly associated with different cell types. In all, they could explain 60% of the alternate splicing patterns found in the human genome just by the presence or absence of these motifs. Many of the motifs were known previously and are sites for known DNA-binding proteins. Many other motifs were new to science.The median number of tissue-specific motifs associated with splicing, per exon, ranged from 12 for the central nervous system and 19 for embryo. 11 There were additional tissue-independent features associated with most or all exons and additional and abundant short motifs that were not considered in the above counts. This means the splicing code is complex and that complex combinations of instructions are needed to control how the many exons combine to produce the multitude of proteins found in the human body.They also discovered features related to splicing much farther away from the protein-coding regions than they expected. Because of technical limitations, most studies on transcription regulation have historically focused on a few dozen letters immediately upstream or downstream of a target sequence. Here, they document features much further into non-coding regions than previously known (up to 300 letters away). Thus, even more junk DNA has been subsumed into the functional DNA category!But this is only the beginning. They have only scratched the surface and have already discovered amazing complexity. They only managed a prediction accuracy of 60%. Therefore, much remains to be discovered. Where is the missing information? Perhaps it will be found deeper into the non-coding DNA. Perhaps, because they did not consider the 3-D architecture of the DNA within the nucleus, additional features may be discovered much farther away or even on different chromosomes! The possibilities are endless and we will certainly update you as more is learned.There is one final implication of this work I would like to discuss. There are many “pseudogenes” in the genome that look like functional genes but have “mutations” that prevent them from being turned into proteins. The presence of pseudogenes has been an enigma since their discovery, but the idea has generally been used to attack creationists and other advocates of design. I believe the arguments are spurious12 and we have written much about them in prior articles. 13 Even though functions have been found for many pseudogenes, it is true that, if transcribed and spliced, a pseudogene cannot be translated into a protein. However, now that we are aware of alternate splicing, future work may show that many of the pseudogene exons are incorporated into functional proteins. If so, the entire pseudogene argument will collapse like a house of cards. But, only time will tell.For now, let us be amazed at the amazingly engineered human genome. The genetic computer program is, to date, unsured by any human technology. The wisdom and foresight that went into it is nothing short of stunning. He engineered a string of DNA as long as a person is tall that could withstand thousands of errors (mutations), adapt to changing environments (through self-modifying code that turns different genes on and off, depending on conditions), and that can be packed into a microscopic cell without forming knots! Now we learn that his program is a wonder of data compression and efficiency. It is more sophisticated than anything we have ever contemplated. Genetics: no friend of evolution A highly qualified biologist tells it like it is. by Lane Lester Genetics and evolution have been enemies from the beginning of both concepts. Gregor Mendel, the father of genetics, and Charles Darwin, the father of modern evolution, were contemporaries. At the same time that Darwin was claiming that creatures could change into other creatures, Mendel was showing that even individual characteristics remain constant. While Darwin’s ideas were based on erroneous and untested ideas about inheritance, Mendel’s conclusions were based on careful experimentation. Only by ignoring the total implications of modern genetics has it been possible to maintain the

fiction of evolution.To help us develop a new biology based on creation rather than evolution, let us sample some of the evidence from genetics, arranged under the four sources of variation: environment, recombination, mutation, and creation. Environment This refers to all of the external factors which influence a creature during its lifetime. For example, one person may have darker skin than another simply because she is exposed to more sunshine. Or another may have larger muscles because he exercises more. Such environmentally-caused variations generally have no importance to the history of life, because they cease to exist when their owners die; they are not ed on. In the middle 1800s, some scientists believed that variations caused by the environment could be inherited. Charles Darwin accepted this fallacy, and it no doubt made it easier for him to believe that one creature could change into another. He thus explained the origin of the giraffe’s long neck in part through ‘the inherited effects of the increased use of parts’. 1 In seasons of limited food supply, Darwin reasoned, giraffes would stretch their necks for the high leaves, supposedly resulting in longer necks being ed on to their offspring. Recombination This involves shuffling the genes and is the reason that children resemble their parents very closely but are not exactly like either one. The discovery of the principles of recombination was Gregor Mendel’s great contribution to the science of genetics. Mendel showed that while traits might be hidden for a generation they were not usually lost, and when new traits appeared it was because their genetic factors had been there all along. Recombination makes it possible for there to be limited variation within the created kinds. But it is limited because virtually all of the variations are produced by a reshuffling of the genes that are already there.For example, from 1800, plant breeders sought to increase the sugar content of the sugar beet. And they were very successful. Over some 75 years of selective breeding it was possible to increase the sugar content from 6% to 17%. But there the improvement stopped, and further selection did not increase the sugar content. Why? Because all of the genes for sugar production had been gathered into a single variety and no further increase was possible. Among the creatures Darwin observed on the Galápagos islands were a group of land birds, the finches. In this single group, we can see wide variation in appearance and in life-style. Darwin provided what I believe to be an essentially correct interpretation of how the finches came to be the way they are. A few individuals were probably blown to the islands from the South American mainland, and today’s finches are descendants of those pioneers. However, while Darwin saw the finches as an example of evolution, we can now recognize them merely as the result of recombination within a single created kind. The pioneer finches brought with them enough genetic variability to be sorted out into the varieties we see today.2 Mutation Now to consider the third source of variation, mutation. Mutations are mistakes in the genetic copying process. Each living cell has intricate molecular machinery designed for accurately copying DNA, the genetic molecule. But as in other copying processes mistakes do occur, although not very often. Once in every 10,000–100,000 copies, a gene will Photo by Ken Ham contain a mistake. The cell has machinery for correcting these mistakes, but some mutations still slip through. What kinds of changes are produced by mutations? Some have no effect at all, or produce so small a change that they have In a fallen world, predators like this tiger, by culling the no appreciable effect on the creature. But many more defective animals, may serve to slow genetic mutations have a significant effect on their deterioration by screening out the effects of mutation. owners. Based on the creation model, what kind of effect would we expect from random mutations, from genetic mistakes? We would expect virtually all of those which make a difference to be harmful, to make the creatures that possess them less successful than before. And this prediction is borne out most convincingly. Some examples help to illustrate The ‘naked rooster’ this.Geneticists began breeding the fruit fly, Drosophila melanogaster, soon after the turn of the century, mutation—no feathers and since 1910 when the first mutation was reported, some 3,000 mutations have been identified. 3 All of are produced. Such the mutations are harmful or harmless; none of them produce a more successful fruit fly—exactly as mutational defects predicted by the creation model.Is there, then, no such thing as a beneficial mutation? Yes, there is. A may rarely be beneficial mutation is simply one that makes it possible for its possessors to contribute more offspring to ‘beneficial’ (e.g. if a future generations than do those creatures that lack the mutation.Darwin called attention to wingless breeder were to select beetles on the island of Madeira. For a beetle living on a windy island, wings can be a definite this type to prevent disadvantage, because creatures in flight are more likely to be blown into the sea. Mutations producing the having to pluck preloss of flight could be helpful. The sightless cave fish would be similar. Eyes are quite vulnerable to injury, roasting?) but never and a creature that lives in pitch dark would benefit from mutations that would replace the eye with scaradd anything new. like tissue, reducing that vulnerability. In the world of light, having no eyes would be a terrible handicap, There is no mutation but is no disadvantage in a dark cave. While these mutations produce a drastic and beneficial change, it is which shows how important to notice that they always involve loss of information and never gain. One never observes the feathers or anything reverse occurring, namely wings or eyes being produced on creatures which never had the information to similar arose. produce them. Natural selection is the obvious fact that some varieties of creatures are going to be more successful than others, and so they will contribute more offspring to future generations. A favourite example of natural section is the peppered moth of England,Biston betularia. As far as anyone knows, this moth has always existed in two basic varieties, speckled and solid black. In pre-industrial England, many of the tree trunks were light in colour. This provided a camouflage for the speckled variety, and the birds tended to prey more heavily on the black variety. Moth collections showed many more speckled than black ones. When the Industrial Age came to England, pollution darkened the tree trunks, so the black variety was hidden, and the speckled variety was conspicuous. Soon there were many more black moths than speckled [Ed. note: see Goodbye, peppered moths for more information].As populations encounter changing environments, such as that described above or as the result of migration into a new area, natural selection favours the combinations of traits which will make the creature more successful in its new environment. This might be considered as the positive role of natural selection. The negative role of natural selection is seen in eliminating or minimizing harmful mutations when they occur. Creation

The first three sources of variation are woefully inadequate to for the diversity of life we see on earth today. An essential feature of the creation model is the placement of considerable genetic variety in each created kind at the beginning. Only thus can we explain the possible origin of horses, donkeys, and zebras from the same kind; of lions, tigers, and leopards from the same kind; of some 118 varieties of the domestic dog, as well as jackals, wolves and coyotes from the same kind. As each kind obeyed the designer`s command to be fruitful and multiply, the chance processes of recombination and the more purposeful process of natural selection caused each kind to subdivide into the vast array we now see. Astonishing DNA complexity uncovered by Alex Williams Because of evolutionary notions of our origin, our DNA was supposed to be mostly ‘junk’, leftovers of our animal ancestry. This has proven to be yet another evolutionary impediment to scientific progress. Photo sxc.hu Published: 20 June 2007(GMT+10) When the Human Genome Project published its first draft of the human genome in 2003, they already knew certain things in advance. These included: Coding segments (genes that coded for proteins) were a minor component of the total amount of DNA in each cell. It was embarrassing to find that we have only about as many genes as mice (about 25,000) which constitute only about 3% of the entire genome.The non-coding sections (i.e. the remaining 97%) were nearly all of unknown function. Many called it ‘junk DNA’; they thought it was the miscopied and mutation-riddled left-overs abandoned by our ancestors over millions of years. Molecular taxonomists routinely use this ‘junk DNA’ as a ‘molecular clock’—a silent record of mutations that have been undisturbed by natural selection for millions of years because it does not do anything. They have constructed elaborate evolutionary histories for all different kinds of life from it.Genes were known to be functional segments of DNA (exons) interspersed with non-functional segments (introns) of unknown purpose. When the gene is copied (transcribed into RNA) and then translated into protein the introns are spliced out and the exons are ed up to produce the functional gene.Copying (transcription) of the gene began at a specially marked START position, and ended at a special STOP sign.Gene switches (the molecules involved are collectively called transcription factors) were located on the chromosome adjacent to the START end of the gene.Transcription proceeds one way, from the START end to the STOP end.Genes were scattered throughout the chromosomes, somewhat like beads on a string, although some areas were gene-rich and others gene-poor.DNA is a double helix molecule, somewhat like a coiled zipper. Each strand of the DNA zipper is the complement of the other—as on a clothing zipper, one side has a lump that fits into a cavity on the other strand. Only one side of the DNA ‘zipper’ (called the ‘sense’ strand) makes the correct protein sequence. The complementary strand is called the ‘anti-sense’ strand. The sense strand is like an electrical extension cord where the ‘female’ end is safe to leave open until an appliance is attached, but the protruding ‘male’ end is active and for safety’s sake only works when plugged into a ‘female’ socket. Thus, protein production usually only comes from copying the sense strand, not the anti-sense strand. The anti-sense strand provides a template for copying the sense strand in a way that a photographic negative is used to produce a positive print. Some exceptions to this rule were known (i.e. that in some cases anti-sense strands were used to make protein) but no one expected the whole anti-sense strand to be transcribed.This whole structure of understanding has now been turned on its head. A project called ENCODE recently reported an intensive study of the transcripts (copies of RNA produced from the DNA) of just 1% of the human genome. 1,2 Their findings include the following inferences:About 93% of the genome is transcribed (not 3%, as expected). Further study with more wideranging methods may raise this figure to 100%. Because much energy and coordination is required for transcription this means that probably the whole genome is used by the cell and there is no such thing as ‘junk DNA’.Exons are not genespecific but are modules that can be ed to many different RNA transcripts. One exon (i.e. one part of one gene) can be used in combination with up to 33 different genes located on 14 different chromosomes. This means that one exon can specify one part shared in common by many different proteins.There is no ‘beads on a string’ linear arrangement of genes, but rather an interleaved structure of overlapping segments, with typically 5, 7, 9 or more transcripts coming from the one ‘gene’. Not just one strand, but both strands (sense and anti-sense) of the DNA are fully transcribed. Transcription proceeds not just one way but both backwards and forwards. Transcription factors can be tens or hundreds of thousands of base-pairs away from the gene that they control, even on different chromosomes. There is not just one START site, but many, in each particular gene region. There is not just one transcription triggering (switching) system for each region, but many. The authors conclude: ‘An interleaved genomic organization poses important mechanistic challenges for the cell. One involves the [use of] the same DNA molecules for multiple functions. The overlap of functionally important sequence motifs must be resolved in time and space for this organization to work properly. Another challenge is the need to compartmentalize RNA or mask RNAs that could potentially form long double-stranded regions, to prevent RNA-RNA interactions that could prompt apoptosis [programmed cell death].’This concern for the safety of so many RNA molecules being produced in such a small space is well-founded. RNA is a long single-strand molecule not unlike a long piece of sticky-tape—it will stick to any nearby surface, including itself! Unless properly coordinated, it will all scrunch up into a sticky mess.These results are so astonishing, so shocking, that it is going to take an awful lot more work to untangle what is really going on in cells. And the molecular taxonomists, who have been drawing up evolutionary histories (‘phylogenies’) for everything, are going to have to undo all their years of ‘junk DNA’-based historical reconstructions and wait for the full implications to emerge before they try again. One of the supposedly ‘knock-down’ arguments that humans have a common ancestor with chimpanzees is shared ‘nonfunctional’ DNA coding. That argument just got thrown out the window.

Astonishing DNA complexity update by Alex Williams

Published: 3 July 2007 (GMT+10) Recently we reported astonishing new discoveries about the complexity of the information content stored in the DNA molecule. 1Notably, the 97% of the human DNA that does not code for protein is not leftover ‘junk DNA’ from our evolutionary past, as previously thought, but is virtually all being actively used right now in our cells.Here are a few more exciting details from the ENCODE (Encyclopedia of DNA Elements) pilot project report.2 As a help in understanding this, DNA is a very stable molecule ideal for storing information. In contrast, RNA is a very active (and unstable) molecule and does lots of work in our cells. To use the stored information on our DNA, our cells copy the information onto RNA transcripts that then do the work as instructed by that information.Traditional ‘beads-on-a-string’ type genes do form the basis of the proteinproducing code, even though much greater complexity has now been uncovered. Genes found in the ENCODE project differ only about 2% from the existing catalogue of known protein-coding genes.We reported previously that the transcripts overlap the gene regions, but the overlaps are huge compared to the size of the genes. On average, the transcripts are 10 to 50 times the size of the gene region, overlapping on both sides. And as many as 20% of transcripts range up to more than 100 times the size of the gene region. This would be like photocopying a page in a book and having to get information from 10, 50 or even 100 other pages in order to use the information on that page.The untranslated regions (now called UTRs, rather than ‘junk’) are farmore important than the translated regions (the genes), as measured by the number of DNA bases appearing in RNA transcripts. Genic regions are transcribed on average in five different overlapping and interleaved ways, while UTRs are transcribed on average in seven different overlapping and interleaved ways. Since there are about 33 times as many bases in UTRs than in genic regions, that makes the ‘junk’ about 50 times more activethan the genes.Transcription activity can best be predicted by just one factor, the way that the DNA is packaged into chromosomes. The DNA is coiled around protein globules called histones, then coiled again into a rope-like structure, then super-coiled in two stages around scaffold proteins to produce the thick chromosomes that we see under the microscope. This suggests that DNA information normally exists in a form similar to a closed book—all the coiling prevents the coded information from coming into with the translation machinery. When the cell wants some information it opens a particular page, ‘photocopies’ the information, then closes the book again. Recent other work 3 shows that this is physically accomplished as follows:The chromosomes in each cell are stored in the membrane-bound nucleus. The nuclear membrane has about 2000 pores in it, through which molecules can be ed in and out. The required chromosome is brought near to one of these nuclear pores. The section of DNA to be transcribed is placed in front of the pore. The supercoil is unwound to expose the transcription region. The histone coils are twisted so as to expose the required copying site. The double-helix of the DNA is unzipped to expose the coded information. The DNA is grasped into a loop by the enzymes that do the copying, and this loop is copied onto an RNA transcript. The transcript is then checked for accuracy (and is degraded and recycled if it is faulty). The RNA transcript is then specially tagged for export, and is exported through the pore and carried to wherever it is needed in the cell.The ‘book’ of DNA information is then closed by a reversal of the coiling process and movement of the chromosome away from the nuclear pore region.The most surprising result, according to the ENCODE authors, is that 95% of the functional transcripts (genic and UTR transcripts with at least one known function) show no sign of selection pressure (i.e. they are not noticeably conserved and are mutating at the average rate). This contradicts Charles Darwin’s theory that natural selection is the major cause of our evolution. It also creates an interesting paradox: cell architecture, machinery and metabolic cycles are all highly conserved (e.g. the human insulin gene has been put into bacteria to produce human insulin on an industrial scale), while most of the chromosomal information is freely mutating. How could this state of affairs be maintained for the supposed 3.8 billion years since bacteria first evolved? A better answer might be that life is only thousands, not billions of years old. It also looks like cells, not genes, are in control of life—the direct opposite of what neo-Darwinists have long assumed. Evidence for the design of life: part 1—Genetic redundancy by Peter Borger Knockout strategies have demonstrated that the function of many genes cannot be studied by disrupting them in model organisms because the inactivation of these genes does not lead to a phenotypic effect. For living systems, this peculiar phenomenon of genetic redundancy seems to be the rule rather than the exception. Genetic redundancy is now defined as the situation in which the disruption of a gene is selectively neutral. Biology shows us that 1) two or more genes in an organism can often substitute for each other, 2) some genes are just there in a silent state. Inactivation of such redundant genes does not jeopardize the individual’s reproductive success and has no effect on survival of the species. Genetic redundancy is the big surprise of modern biology. Because there is no association between redundant genes and genetic duplications, and because redundant genes do not mutate faster than essential genes, redundancy therefore brings down more than one pillar of contemporary evolutionary thinking.

Figure 1. To create a mouse knockout for a particular gene, a selectable marker is integrated in the gene of interest in an embryonic stem cell. The marker disrupts (knocks out) the gene of interest. The manipulated embryonic stem cell is then

injected into a mouse oocyte and transplanted back into the uterus of pseudo-pregnant mouse. Offspring carrying the interrupted gene can be sorted out by screening for the presence of the selection marker. It is now fairly easy to obtain animals in which both copies are interrupted through selective breeding. Mendel’s law of independent segregation assures that crossbreeding littermates will produce individuals that lack both genes.The discovery of the primary rules governing biology in the second half of the 20th century paved the way for a more fundamental understanding of the complexity of life. One of the spin-offs of this knowledge has been the development of sophisticated techniques to elucidate the function of proteins. When molecular biologists want to know the function of a particular human protein they genetically modify a laboratory mouse so that it lacks the corresponding gene (for the laboratory procedure see figure 1). Mice that have both alleles of a gene interrupted cannot produce the corresponding protein—they are called knockouts. Theoretically, the phenotype of a mouse lacking specific genetic information could provide essential information about the function of the gene. Over the years, thousands of knockouts have been generated. The knockout-strategy has helped elucidate the functions of hundreds of genes and has contributed immensely to our biological knowledge. However, there has been one unexpected surprise—the no-phenotype knockout. This is unexpected, because according to the Darwinian paradigm, all genes should have a selectable advantage. Hence, knockouts should have measurable, detectable phenotypes. The nophenotype knockouts demonstrate that genes can be disrupted without—or with only minor—detectable effects on the phenotype. Many genes seem to have no measurable function! This is known as genetic redundancy and it is one of the big surprises of modern biology. Molecular switches One of the most intriguing examples of genetic redundancy is found in the SRC gene family. This family comprises a group of eight genes that code for eight distinct proteins all with a function that is technically known as tyrosine kinase. SRC proteins attach phosphate groups to other proteins that contain the amino acid tyrosine in a specific amino acid context. The result of this attachment is that the protein becomes activated; it is switched on, and can hence down information in a signalling cascade. Four closely related of the family are named SRC, YES, FYN and FGR, and the other related are known as BLK, HCK, LCK and LYN. Both families are so-called ‘nuclear receptors’, and transmit signals from the exterior of the cell to the nucleus, the operation centre where the information present in the genes is transcribed into messenger RNA. The proteins of the SRC gene family operate as molecular switches that regulate growth and differentiation of cells. When a cell is triggered to proliferate, tyrosine kinase proteins are transiently switched on, and then immediately switched off.The SRC gene family is among the most notorious genes known to man, since they cause cancer as a consequence of single point mutations. A point mutation is a change in a DNA sequence that alters only one single nucleotide—a DNA letter—of the entire gene. When the point mutation is not on a silent position, it will cause the organism’s protein-making machines to incorporate a wrong amino acid. The consequence of the point mutation is that the organism now produces a protein that cannot be switched off. Mutated SRC genes are of particular danger because they will permanently activate signalling cascades that induce cell proliferation: the signal that tells cells to divide is permanently switched on. The result is uncontrolled proliferation of cells—cancer. The growth-promoting point mutations cannot be overcome by allelic compensation because a normal protein cannot help to switch off the mutated protein.Despite the SRC protein being expressed in many tissues and cell types, mice in which the SRC gene has been knocked out are still viable. The only obvious characteristic of the knockout is the absence of two front teeth due to osteoporosis. In contrast, there are essentially no point mutations allowed in the SRC protein without severe phenotypic consequences. Amino acid changing point mutations in most, presumably all, of the SRC genes can lead to uncontrolled cellular replication. 1 Knockout mice models have been generated to reveal the functions of all the of the SRC gene family. Four out of eight knockouts did not have a detectable phenotype. Despite their cancer-inducing properties, half of the SRCgenes appear to be redundant. Standard evolutionary theory tells us that redundant gene family originated through gene duplications. Duplicated genes are truly redundant and as such they are expected to reduce to a single functional copy over time through the accumulation of mutations that damage the duplicated genes. Such mutations can be frame-shift mutations that introduce premature stop signals, which are recognized by the cellular translation-machines to terminate protein synthesis. The existence of the SRC gene family has been explained as follows:‘In the redundant gene family of SRC-like proteins, many, perhaps almost all point mutations that damage the protein also cause deleterious phenotypes and kill the organism. The genetic redundancy cannot decay away through the accumulation of point mutations.’ 1This scenario implies that the SRC genes are destined to reside in the genome forever. Point mutations that immediately kill raise an intriguing origin question. If the SRC genes are really so potently harmful that point mutations induce cancer, how could this extended gene family come into existence through gene duplication and diversify through mutations in the first place? After the first duplication, neither of the genes is allowed to change because it will invoke a lethal phenotype and kill the organism through cancer. Amino acid changing mutations in the SRC genes will permanently be selected against. The same holds true for the third, fourth and additional gene duplication. New gene copies are only allowed to mutate at neutral sites that do not replace amino acid in the protein. Otherwise the organism will die from tumours. Because of this ‘purifying’ selection mechanism, the duplicates should remain as they are. Yet the proteins of the SRC family are distinctly different, only sharing 60–80% of their sequences. Redundancy—the rule not the exception In 1964, a ‘knockout’ cross-country skier won two gold medals during the Winter Olympics in Innsbruck. In true Olympic tradition, Eero Maentyranta’s 15 and 30 km success was surrounded by controversy. Tests showed that he had 15% more red blood cells than normal subjects and Eero was accused of using doping to increase his level of red blood cells. Yet no trace of blood doping could be found. In 1964 nobody knew, but modern biology showed Maentyranta had a mutated EPO gene, which codes for erythropoietin, a messenger protein that tells the bone marrow to increase the production of red blood cells. To increase red blood levels, EPO binds to the EPO receptor that generates two opposite signals: one to instruct bone marrow cells to become red blood cells (the on-switch) and one to reduce production of red blood cells (the off-switch). This auto-regulatory mechanism assures a balanced production of red blood cells. In 1993, it turned out that the Olympic medallist had a mutation that knocked out the off-switch.2 The EPO receptor of the Finnish athlete generated a normal activation signal, but not the deactivating one. People can do well without the off-switch.In humans, the muscle-fiber-producing ACTN3 gene can also be missed entirely and without consequences for fitness.3 Humans can also do without the GULO gene,4 the gene coding for caspase 12,5 the CCR5gene6 and some of the GST genes that are involved in the detoxification of polycyclic aromatic hydrocarbons present in cigarette smoke. 7 All these genes can be found inactivated in entire human populations (GULO, caspase 12) or subpopulations thereof. The Douc Langur (Pygathrix nemaeus), an Asian leaf-eating Colobine monkey, is the natural no-phenotype knockout for the angiogenin gene that codes a small protein that stimulates the formation of blood vessels. 8 Bacterial genomes can be reduced by over 9% without selective disadvantages on minimal medium, 9 and mice in which 3 megabases of conserved DNA was erased showed no signs of reduced survival and there was no indication of overt pathology. 10 Fewer than 2% of approximately 200 Arabidopsis thaliana (Mouse-Ear Cress) knockouts displayed significant phenotypic alterations. Many of

the knockouts did not affect plant morphology even in the presence of severe physiological defects.11 In the nematode worm Caenorhabditis elegans a surprising 89% of single-copy and 96% of duplicate genes show no detectable phenotypic effect when they are knocked out.12 Prion proteins are thought to have a function in learning processes, but when they are misfolded they can cause bovine spongiform encephalitis (BSE) or Kreutzfeld–Jacob disease. In order to make BSE resistant cows, a knockout breed has been created lacking the prion protein. A thorough health assessment of this knockout breed revealed only small differences from wild-type animals. Apparently, cows can thrive very well without the prion protein.13 Research on histone H1 genes, once believed to be indispensable for DNA condensation, suggest that any individual H1 subtype is not necessary for mouse development, and that loss of even two subtypes is tolerated if a normal H1-to-nucleosome stoichiometry is maintained.14 Even complete highly specialized cells can be redundant. A strain of laboratory mouse, named WBB6F1, lacks a specific type of blood cells known as mast cells. The reported no-phenotype knockouts are probably only the tip of the iceberg. As reported in Nature below, few knockout organisms in which no phenotype could be traced ever see the light of day:‘ … a lot of those things [no-phenotype knockouts] you don’t hear about. No-phenotype knockouts are negative results, and as such they are usually not reported in scientific journals; because they do not have news value. To address the problem, the journal Molecular and Cellular Biology has since 1999 a section given over to knockout and other mutant mice that seem perfectly normal.’ 15So how are genes, cells and organisms supposed to have evolved without selective constraints? If organisms can do without complete cells, it would be outlandish to assert that natural selection was the driving force shaping those cells. Two decades of knockout experiments has made it clear that genetic redundancy is a major characteristic of all studied life forms. Paradigm lost Genetic redundancy falsifies several evolutionary hypotheses. Firstly, truly redundant genes are impossible paradoxes because natural selection cannot prevent the accumulation of harmful mutations in these genes. Hence, natural selection cannot prevent redundancies from being lost. Secondly, redundant genes do not evolve (mutate) any faster than essential genes. If protein evolution is due in large part to neutral and slightly deleterious amino acid substitutions, then the incidence of such mutations should be greater in proteins that contribute less to individual reproductive success. The rationale for this prediction is that non-essential proteins should be subject to weaker purifying selection and should accumulate mildly deleterious substitutions more rapidly. This argument, which was presented over twenty years ago, is fundamental to many theoretical applications of evolutionary theory, but despite intense scientific scrutiny the prediction has not been confirmed. In contrast, a systematic analysis of mouse genes has shown that essential genes do not evolve more slowly than nonessential ones.16 Likewise, E. coli proteins that operate in huge redundant networks can tolerate just as many mutations as unique single-copy proteins,17 and scientists comparing the human and chimpanzee genomes found that non-functional pseudogenes, which can be considered as redundancies, have similar percentages of nucleotide substitutions as do essential protein-coding genes.18 Thirdly, as discussed in more detail below, several recent biology studies have provided evidence that genetic redundancy is not associated with gene duplications. What does the evolutionary paradigm say? An important question that needs to be addressed is—can we understand genetic redundancy from Darwin’s natural selection perspective? How can genetic redundancy be maintained in the genome without natural selection acting upon it continually? How did organisms evolve genes that are not subject to natural selection? First, let’s look at how it is thought genetic redundancies arise. Susumo Ohno’s influential 1970 book, Evolution by Gene Duplication, deals with this idea.19 Sometimes, during cell divisions, a gene or longer stretch of biological information is duplicated. If duplication occurs in germ line cells and become inheritable, the exact same gene may be present twofold in the genome of the offspring—a genetic back-up. Ohno argues that gene and genome duplications are the principal forces that drive the increasing complexity of Darwinian evolution, referring to the evolution from microbes to microbiologists. He proposes that duplications of genetic material provide genetic redundancies which are then free to accumulate mutations and adopt novel biological functions. Duplicated DNA elements are not subject to natural selection and are free to transform into novel genes. With time, he argues, a duplicated gene will diverge with respect to expression characteristics or function due to accumulated (point) mutations in the regulatory and coding segments of the duplicate. Duplicates transforming into novel genes with a selective advantage will certainly be favored by natural selection. Meanwhile, the genetic redundancy will protect old functions as new ones arise, hence reducing the lethality of mutations. Ohno estimates that for every novel gene to arise through duplication, about ten redundant copies must the ranks of functionless DNA base sequence.20 Diversification of duplicated genetic material is now the accepted standard evolutionary idea on how genomes gain useful information. Ohno’s idea of evolution through duplication also provides an explanation for the no-phenotype knockouts: if genes duplicate fairly often, it is then reasonable to expect some level of redundancy in most genomes, because duplicates provide an organism with back-up genes. As long as duplicates do not change too much, they may substitute for each other. If one is lost, or inactivated, the other one takes over. Hence, Ohno’s theory predicts an association between genetic redundancy and gene duplication. The evolutionary paradigm is wrong Figure 2. A very simple scheme of a small robust network comprised of A–E, where several nodes are redundant. Some biologists have looked into this matter specifically using the wealth of genetic data available for Saccharomyces cerevisiae—the common baker’s yeast. A surprising 60% ofSaccharomyces’ genes could be inactivated without producing a phenotype. In 1999, Winzeler and co-workers reported in Science that only 9% of the non-essential genes ofSaccharomyces have sequence similarities with other genes present in the yeast’s genome and could thus be the result of duplication events.21 Most redundant genes ofSaccharomyces are not related to genes in the yeast’s genome, which suggests that genetic duplications cannot explain genetic redundancy. In 2000, Andreas Wagner confirmed Winzeler’s original findings that weak or no-effect (i.e. non-essential and redundant) genes are no more likely to have paralogous —that is, duplicated—genes within the yeast genome than genes that do result in a defined phenotype when they are knocked out. Wagner concluded that the robustness of mutant strains cannot be caused by gene duplication and redundancy, but is more likely due to the interactions between unrelated genes. 22 More recent studies have shown that cooperating networks of unrelated genes contribute significantly more to robustness than gene copy number.23 Redundant genes are proposed to have originated in gene duplications, but we do not find a link between genetic redundancy, and duplicated genes in the genomes. Gene duplication is not a major contributor to genetic redundancy, and the robust genetic networks found in organisms cannot be explained. The predicted association between

genetic redundancy and gene duplication is non-existent. Ohno’s interesting idea of evolution by gene duplication therefore cannot be right. The non-linearity of biology The no-phenotype knockouts can only be explained by taking into the non-linearity of biochemical systems. It is ironic that standard wall charts of biochemical reactions show hundreds of coupled reactions working together in networks, while graduate students are tacitly encouraged to think in of linear cause and effect. The linear cause-and-effect thinking in ancient Greek philosophy was adopted by nineteenth century European scholars, and is still dominating most fields of science, including biology. We cannot understand that genetic redundancy and biological robustness in linear of single causality, where A causes B causes C causes D causes E. Biological systems do not work like that. Biological systems are designed as redundant scale-free networks. In a scale-free network the distribution of node linkage follows a power law in that it contains many nodes with a low number of links, few nodes with many links and very few nodes with a high number of links. A scale-free network is very much like the Golden Orb’s web: individual nodes are not essential for letting the system function as a whole. The internet is another example of a robust scale-free network: the major part of the websites makes only a few links, a lesser fraction make an intermediate number of links, and a minor part makes the majority of links. Usually hundreds of routers routinely malfunction on the Internet at any moment, but the network rarely suffers major disruptions. As many as 80% of randomly selected Internet routers can fail, but the remaining ones will still form a compact cluster in which there will still be a path between any two nodes. 24 Likewise, we rarely notice the consequences of thousands of errors that routinely occur in our cells. Scale free networks Genes never operate alone but in redundant scale-free networks with an incredible level of buffering capacity. In a simple non-linear biological system—presented in figure 2—with nodes A through E, A may cause B, but A also causes D independent of B and C. This very simple network of only five nodes demonstrates robustness due to redundancy of B and C. If A fails to make the link with D, there are still B and C to make the connection. Extended networks composed of hundreds of interconnected proteins ensure that if one network becomes inactivated by a mutation, essential pathways will then not be shut down immediately. A network of cooperating proteins that can substitute for or by each other’s functions makes a biological system robust. It is hard to imagine how selection acts on individual nodes of a scale-free, redundant system. Complex engineered systems rely on scale-free networks that can incorporate small failures in order to prevent larger failures. In a sense, cooperating scale-free networks provide systems with an anti-chaos module which is required for stability and strength. Scale-free genetic and protein networks are an intrinsic, engineered characteristic of genomes and may explain why genetic redundancy is so widespread among organisms. Genetic networks usually serve to stabilize and fine-tune the complex regulatory mechanisms of living systems. They control homeostasis, regulate the maintenance of genomes and provide regulatory on gene expression. An overlap in the functions of proteins also ensures that a cell does not have to respond with only ‘on’ or ‘off’ in a particular biochemical process, but instead may operate somewhere in between.Most genes in the human genome are involved in regulatory networks that detect and process information in order to keep the cell informed about its environment. The proteins operating in these networks come as large gene families with overlapping functions. In a cascade of activation and deactivation of signalling proteins, external messages are transported to the nucleus with information about what is going on outside so it can respond adequately. If one of the interactions disappears, this will not immediately disturb the balance of life. The buffering capacity present in redundant genetic networks also provides the robustness that allows living systems to propagate in time. In a linear system, one detrimental mutation would immediately disable the system as a whole: the strength of a chain is determined by its weakest link. Interacting biological networks, where parallel and converging links independently convey the same or similar information, almost never fail. The Golden Orb’s web only crumbles when an entire spoke is obliterated in a crash with a Dragonfly, an event that will hardly ever happen. Biological systems operate as a spider’s web: many interacting and interwoven nodes produce robust genetic networks and are responsible for genetic redundancy.23 Conclusion Genetic redundancy is an amazing property of genomes and has only recently become evident as a result of negative knockout experiments. Protein-coding genes and highly conserved regions can be eliminated from the genome of model organisms without a detectable effect on fitness. There is no association between redundant genes and gene duplications, and redundant genes do not mutate faster than essential genes. Genetic redundancy stands as an unequivocal challenge to the standard evolutionary paradigm, as it questions the importance of Darwin’s selection mechanism as a major force in the evolution of genes. It is also important to realize that redundant genes cannot have resided in the genome for millions of years, because natural selection, a conservative force, cannot prevent their destruction due to debilitating mutations. Mainstream biologists who are educated in the Darwinian framework are unable to understand the existence of genes without natural selection. This is clear from a statement in Nature a few years ago by Mario Cappecchi, a pioneer in the development of knockout technology:‘I don’t believe that there is a single [knockout] mouse that does not have a phenotype. We just aren’t asking the right questions.’15The right question to be asked is: is the evolutionary paradigm wrong? My answer is yes, it is. Current naturalistic theories do not explain what scientists observe in the genomes. Genetic redundancy is the actual key to help us understand the robustness of organisms and also their built-in flexibility to rapidly adapt to different environments. In part 2 of this series of articles, I will explain genetic redundancy in the context of baranomes, the multipurpose genomes baramins were originally designed with in order to rapidly spread to all the corners and crevices of the earth. The design of life: part 3—an introduction to variation-inducing genetic elements by Peter Borger The inheritance of traits is determined by genes: long stretches of DNA that are ed down from generation to generation. Usually, genes consist of a coding part and a non-coding regulatory part. The coding part of the gene determines the functional output, whereas the non-coding portion contains switches and units that determine when, where and how much of the functional output should be generated. Point-mutations in the coding part are predominantly neutral or slightly detrimental genetic noise that accumulates in the genome, whereas point-mutations in the regulatory part of DNA units can induce variation with respect to the amount of output. Previously, in part 2, I argued that created kinds were frontloaded with baranomes: that is, pluripotent genomes with an ability to induce variation from within. The output of (morpho)genetic algorithms present in the baranome can readily be modulated by variation-inducing genetic elements (VIGEs). VIGEs are frontloaded genetic elements normally referred to as endogenous retroviruses, insertion sequences, LINEs, SINEs, micro-satellites, transposons, insertion sequences, and the like. In the present report,

these transposable and repetitive DNA sequences are redefined as VIGEs, which solves the RNA virus paradox. The (morpho)genetic algorithms were designed in such way that VIGEs easily integrated into it and became a part of it, hence making the program explicit.The variation that Darwin saw in pigeons can be explained with the activation or deactivation of existing genetic sequences for feather production in different parts of the body. This gives no basis for asserting that pigeons could change into something which is not a pigeon.In order to fight off invading bugs and parasites, higher organisms have an elaborate mechanism that induces variation in immunological defence systems. One particular type of immune cells (B cells) produces defence proteins known as immunoglobulins. Immunoglobulins are very sticky; they bind to intruders as biological tags and mark them as ‘alien’. Other cells of the immune system then recognize the intruder, and a destruction cascade is activated. To have a tag available for every possible alien intruder, millions of B cells have their own highly specific gene for immunoglobulin production. In the genome there is only limited storage space for biological information, so how can there be millions of genes? Well, there aren’t. Immunoglobulin genes are assembled from several pre-existing DNA sequences that can be independently put together. The part of the immunoglobulin that does the ‘alien’ recognition contains several domains which are each highly variable. Every single B cell forms a unique immunoglobulin gene by picking from several short pre-existing DNA sequences. We also observe that later generations of immunoglobulins are more specific than the earlier generations, in the sense that they bind more tightly to invading microorganisms. Binding affinity to an invader is equivalent to recognition of that invader. And the better the immune system is able to recognize an intruder, the better it is able to clear it. The increased specificity is due to somatic mutations deliberately introduced in the genes of the immunoglobulins. A mechanism to rapidly induce mutations in immunoglobulin genes is present in the B cell genome. This mechanism ensures that the recognition pattern specified by the genes becomes increasingly specific for the intruder. This ability to recognize and defeat all potential microorganisms is characteristic of the immune systems of higher organisms, including humans. The genomes contain all the necessary biological information required to induce variation from within. A flexible genome is required to effectively ward off diseases and parasitic infections. B cells don’t wait for mutations to happen; they generate the necessary mutations themselves. Darwin revisited Previously, in part 2,1 I argued that organisms are equipped with flexible, highly adaptable, pluripotent, multipurpose genomes. Organisms are able to conquer the world through adaptive radiation of baranomes. But how do baranomes unleash information? Do organisms have to wait for selectable mutations to occur in order to rapidly invade and occupy novel ecological niches? Or were the baranomes of created kinds equipped with mechanisms to rapidly induce mutations, similar to the variation generated by B cells? Let’s turn to Darwin’s The Origin of Species, where we will find some clues. Darwin wrote quite extensively on variation, and in particular on the variation of feather patterns in pigeons: Box 1. Common names of some well-known variation-inducing genetic elements (VIGEs) in prokaryotes (bacteria) and eukaryotes (yeast, plants, insects and mammals). ‘Some facts in regard to the colouring of pigeons well deserve consideration. The rock-pigeon is of a slaty-blue, and has a white rump (the Indian sub-species, C. intermedia of Strickland, having it bluish); the tail has a terminal dark bar, with the bases of the outer feathers externally edged with white; the wings have two black bars; some semi-domestic breeds and some apparently truly wild breeds have, besides the two black bars, the wings chequered with black. These several marks do not occur together in any other species of the whole family. Now, in every one of the domestic breeds, taking thoroughly well-bred birds, all the above marks, even to the white edging of the outer tail-feathers, sometimes concur perfectly developed. Moreover, when two birds belonging to two distinct breeds are crossed, neither of which is blue or has any of the above specified marks, the mongrel offspring are very apt suddenly to acquire these characters; for instance, I crossed some uniformly white fantails with some uniformly black barbs, and they produced mottled brown and black birds; these I again crossed together, and one grandchild of the pure white fantail and pure black barb was of as beautiful a blue colour, with the white rump, double black wing-bar, and barred and white-edged tail-feathers, as any wild rock pigeon! We can understand these facts, on the well-known principle of reversion to the ancestral characters, if all the domestic breeds have descended from the rock-pigeon.’ 2Darwin argues— and correctly so—that all domestic pigeon breeds have descended from the rock-pigeon. He even knew, as demonstrated above, how to breed the rock-pigeon from several distinct pigeon races following a breeding pattern. Darwin describes a breeding algorithmfor pigeons, to obtain the ancestor to all pigeons! But does he also describe an algorithm for breeding turkeys from pigeons? No. Darwin doesn’t know such an algorithm. If he had found an algorithm for breeding ducks or magpies from pigeon genomes, he would have had solid evidence in favour of his proposal On The Origin of Species Through the Preservation of Favoured Races. His breeding experiments led him to discover ‘the principle of reversion to ancestral characters’, but contrary to common Darwinian wisdom, it is also the falsifying observation to his proposal for the origin of species. The observation that pigeons bring forth pigeons, and nothing else but pigeons, is not exactly the evidence needed to argue for the common descent of all birds. On the contrary! Darwin’s breeding experiments demonstrated that a pigeon is a pigeon is a pigeon. Characteristics and traits within single species of pigeons may vary tremendously, but he always started and ended with pigeons. Breeding experiments have always shown, without exception, that novel and distinct bird species do not arrive through artificial selection. Even Darwin argues that there is no doubt that all varieties of ducks and rabbits have descended from the common wild duck and rabbit. 3 From the variation Darwin observed in wild and domesticated populations, it does not follow that rabbits and ducks have some hypothetical common ancestor in a fuzzy distant past. Darwin observed inborn, innate variation that already existed in the genomes of the pigeons and it only had to be activated or expressed.From the excerpt above, we may even get an impression of how it works. A genetic algorithm for making feathers (a feather program) is part of the pigeon’s genome and is present in every single cell. The feather program is present in billions of pigeon cells, but it is NOT active in all those cells. Feathers are only formed when the program is activated. The feather program is silent in cells where it should normally not operate. Activation of the feather program in the wrong cells may often be incompatible with life, but sometimes it may produce pigeons with (reversed) feathers on the feet. The program may be derepressed or activated through a mechanism that operates in the pigeon’s genome. Whether feathers appear on the feet or on the head, and whether they appear normal or reversed is merely a matter of activation and regulation of the feather program. But Darwin didn’t know about silent genomic programs or how they could become active. He didn’t know about gene regulation and molecular switches. Darwin did not know anything about genes and genomes. Analogous variation The idea that Darwin had been working on for over two decades prior to the publication of Origin, his idée fixe, was how organic change (i.e. variation) present in populations might explain how novel species came into being. Unchanging, stable

species is not what Darwin had in mind. He pondered the riddles of variation; he thought about laws and principles associated with the process of variation and believed he could disclose them by the study of the formation of new breeds. Drawing from what he knew about pigeon breeding and equine varieties, Darwin describes some of his ideas about the ‘laws of variation’ in chapter five of Origin:‘Distinct species present analogous variations; and a variety of one species often assumes some of the characters of an allied species, or reverts to some of the characters of an early progenitor. These propositions will be most readily understood by looking to our domestic races. The most distinct breeds of pigeons, in countries most widely apart, present sub-varieties with reversed feathers on the head and feathers on the feet, characters not possessed by the aboriginal rock-pigeon; these then are analogous variations in two or more distinct races.’ 4Darwin describes that the exact same traits can appear in distinct breeds of pigeons and—importantly—these traits appeared independently in ‘countries most widely apart’. If several breeds arrive with the same characteristics independently, it is unlikely they do so because of chance. Rather, the pigeon genomes may activate or derepress the same feather program independently. The effect is that distinct breeds ‘in countries most widely apart’ acquire the same characteristics. Over and over the same traits appear in separated populations of organisms as the result of mutations ‘from within’. Animal breeders like exuberant patterns and rarities; that is exactly what they are looking for to select. Aberrant traits that are normally under stringent negative selection, as might be the case for the pigeon’s reversed feathers, may readily become visible as soon as the selective pressure is relieved; that is, when organisms are reared and fed in the protective environment of captivity. Darwin called the phenomenon of independent acquisition of the same traits analogous variation. It is a common phenomenon well known to breeders, and Darwin easily found more examples of analogous variation:‘The frequent presence of fourteen or even sixteen tail-feathers in the pouter, may be considered as a variation representing the normal structure of another race, the fantail. I presume that no one will doubt that all such analogous variations are due to the several races of the pigeon having inherited from a common parent the same constitution and tendency to variation, when acted on by similar unknown influences. In the vegetable kingdom we have a case of analogous variation, in the enlarged stems, or roots as commonly called, of the Swedish turnip and Ruta baga [sic] plants which several botanists rank as varieties produced by cultivation from a common parent: if this be not so, the case will then be one of analogous variation in two so-called distinct species; and to these a third may be added, namely, the common turnip. According to the ordinary view of each species having been independently created, we should have to attribute this similarity in the enlarged stems of these three plants, not to the vera causa of community of descent, and a consequent tendency to vary in a like manner, but to three separate yet closely related acts of creation.’ 5Analogous variation originates in the genome. Through rearrangement and/or transposition of DNA elements, previously silent (cryptic) traits can be activated. The underlying molecular mechanism can’t be merely random; if it were, then Darwin, and other breeders, would not have observed the expression of the same traits independently of each other. A more contemporary translation of analogous variation would benonrandom (or: non-stochastic) variation, and it implies some sort of mechanism. Reversions In the excerpt above, Darwin also describes what he calls reversions. By this term he meant traits that are present in ancestors, then disappear in first generation offspring, and then reappear in subsequent generations. Darwin acknowledged that unknown laws of inheritance must exist, but still he talks about ‘the proportion of blood’. Reversions are easily explained as traits present on separate chromosomes, and the inheritance of such traits is best understood from Gregor Mendel’s inheritance laws. Through Mendel’s discovery of the genetic laws that underlie the inheritance of traits associated with chromosome segregation (a hallmark of sexual reproduction), Mendel gave us a quantum theory of inheritance. He found that traits are always inherited in well-defined and predictable proportions, and do not just come and go. Darwin’s ‘reversions’ are traits that reappear in later generations due to the inheritance of the same genes (alleles) from both parents.5 Darwin didn’t know about Mendel’s laws of inheritance, neither did he know about how variation is generated in genomes. What Darwin described inOrigin, however, is that variation in offspring is a rule of biology. What Darwin described in isolated species (whether domesticated breeds or island-bound birds) was the result of a burst of abundant speciation resulting from multipurpose genomes. Variant breeds of pigeons are the phenotypes of a rearranged multipurpose pigeon genome. The Galápagos finches (with their distinct beaks and body sizes) are the phenotypes of a rearranged multipurpose finch genome. Where does the variation stem from in populations of Galápagos finches?Darwin was well aware of the profound lack of knowledge on the origin of variation, and did not exclude mechanisms or laws to drive biological variation:‘I have hitherto sometimes spoken as if the variations so common and multiform in organic beings under domestication, and in a lesser degree in those in a state of nature had been due to chance. This, of course, is a wholly incorrect expression, but it serves to acknowledge plainly our ignorance of the cause of each particular variation.’ 6Since Darwin’s days, almost all corners of the living cell have been explored and our biological knowledge has expanded greatly. Through a vast library of data generated by new research in biology, we now have the answers to many questions of a biological nature that had puzzled Darwin. We may also have the answer to ‘the cause of each particular variation’, although we may not be aware of it (yet). That is not because it is hidden between billions of other books and hard to find. No, it is because of the Darwinian paradigm. The mechanism(s) that drive biological variations have been elucidated but are not yet recognized as such.One of the findings of the new biology was that the DNA of most (if not all) organisms contains jumping genetic elements. The mainstream opinion is that these elements are the remnants of ancient invasions of RNA viruses. RNA viruses are a class of viruses that use RNA molecule(s) for information storage. Some of them, such as influenza and HIV, pose an increasing threat to human health. Are virus invasions responsible for all the beautiful intricate complexity of organic beings? Is a virus a creator? Most likely it is not. Otherwise why would we pump billions of research dollars into research to fight off viruses? Could it be that mainstream science is mistaken? The RNA virus paradox Here is one good reason for believing that mainstream science is indeed mistaken: the RNA virus paradox. It has been proposed that these RNA viruses have a long evolutionary history, appearing with, or perhaps before, the first cellular life forms.7 Molecular genetic analyses have demonstrated that genomes, including those of humans and primates, are riddled with ‘endogenous retroviruses’ (ERVs), which are currently explained as the remnants of ancient RNA virus-invasions. RNA virus origin can be estimated using homologous genes found in both ERVs and modern RNA virus families. By using the best estimates for rates of evolutionary change (i.e. nucleotide substitution) and assuming an approximate molecular clock,8,9 the families of RNA viruses found today ‘could only have appeared very recently, probably not more than about 50,000 years ago’.10 These data imply that present-day RNA viruses may have originated much more recently than our own species. The implication of a recent origin of RNA viruses and the presence of genomic ERVs poses an apparent paradox that has to be resolved. I will argue, in order to resolve the paradox, we should abstain from the mainstream idea that ERVs are remnants of ancient RNA virus invasions.Solving the RNA paradox can only be accomplished by asking questions. First, we have to ask ourselves, What do scientists mean when they refer to genetic elements as endogenous retroviruses (ERVs)? In addition, we have to ask, How do ERVs behave, and what—if any—are their functions? ERVs have been extensively studied in microorganisms, such as baker’s yeast (Saccharomices cerivisiae) and the common gut

bacterium Escherichia coli. Most of our knowledge on the mechanisms of transposition of ERVs comes from those two organisms. In yeast, the ERV known as Ty is flanked by long terminal repeats and specifies two genes, gag and pol, which are similar to genes found in free operating RNA viruses. This is the main argument why scientists believe RNA viruses and ERVs are evolutionarily closely related. The long terminal repeats enable the ERV to insert into the host’s DNA. The transposition and integration is a stringently regulated process and seems to be target or site-specific. 11,12 During the transpositions of an ERV, the host’s RNA polymerase II makes an RNA template, which is polyadenylated to become messenger RNA. Thegag and pol mRNAs are translated and cleaved into several individual proteins. The gag gene specifies a polyprotein that is cleaved into three proteins, which form a capsid-like structure surrounding the ERV’s RNA. We may ask here: why is a capsid involved? It should be noted that single stranded RNA molecules are very sticky nucleotide polymers and the capsid may prevent the ERV from sticking at wrong places. The capsid may also be required to direct the ERV to the right spots in the genome. The pol polyprotein is cleaved into four enzymes: protease, reverse transcriptase, RNase and integrase. Protease cleaves the polyproteins into the individual proteins and then the RNA and proteins are packed into a retrovirus-like particle. Reverse transcriptase forms a single-stranded DNA molecule from the ERV RNA template, whereas RNase removes the RNA. The DNA is then circularized and the complementary DNA strand is synthesized to create a double-stranded, circular copy of the ERV, which is then integrated into a new site in the host’s genomic DNA by integrase’s activity. This intricate mechanism for transposition of ERVs seems to be irreducibly complex (and thus a sign of intelligent design) since all ERVs and RNA viruses use the same or similar genetic components. Variation-inducing genetic elements (VIGEs). What can the function, if any, of ERVs be? If we follow the mainstream opinion, ERVs integrated into the genomes a very long time ago as viral infections. Currently, ERVs are not particularly helpful. They merely hop around in the genome as selfish genetic elements that serve no function in particular. They are mainly upsetting the genome. Long ago, however, RNA viruses are alleged to have significantly contributed to evolution by helping to shape the genome.It’s hard to imagine this story to be true, and not only because of the RNA virus paradox. Modern viruses usually do not integrate into the DNA of the germ line-cells; that is, the genes of an RNA virus don’t usually become a part of the heritable material of the infected host. If we obey the uniformitarian principle, we are allowed to argue: ‘What currently doesn’t happen didn’t happen a long time ago, either’. To answer the question raised above, we must start finding out more about some biological characteristics of a less complicated jumping genetic element, the so-called insertion-sequence (IS) element. IS elements are DNA transposons abundantly present in the genomes of bacteria. IS elements share an important characteristic with ERVs: transposition. Genome shuffling takes place in bacteria so frequently that we can hardly speak of a specific gene order. The shuffling of pre-existing genetic elements may unleash cryptic information instantly as the result of position effects. Shuffling seems to be an important mechanism to generate variation. But what is the mechanism for genome shuffling? The answer to this question comes unexpectedly from evolutionary experiments, in which genetic diversity (‘evolutionary change’) was determined between reproducing populations of E. coli. During the breeding experiment, which ran for two decades, it was observed that the number and location of IS (‘insertion sequence’) elements dramatically changed in evolving populations, whereas point mutations were not abundant.13After 10,000 generations of bacteria, the genomic changes were mostly due to duplication and transposition of IS elements. A straightforward conclusion would thus be that jumping genetic elements, such as the IS elements, were designed to deliberately generate variation—variation that might be useful to the organism. In 2004, Lenski, one of the co-authors of the studies, demonstrated that the IS elements indeed generate fitness-increasing mutations.14 In E. coli bacteria IS elements activate cryptic—or silent—catabolic operons: a set of genetic programs for food digestion. It has been reported that IS element transposition overcomes reproductive stress situations by activating cryptic operons, so that the organism can switch to another source of food. IS elements do so in a regulated manner, transposing at a higher rate in starving cells than in growing cells. In at least one case, IS elements activated a cryptic operon during starvation only if the substrate for that operon was present in the environment. 15It is clear that in Lenski’s experiments, IS elements did not evolve over night. Rather, the IS elements reside in the genome of the original strain. During the two decades of breeding, the IS elements duplicated and jumped from location to location. There was ample opportunity to shuffle genes and regulatory sequences, and plenty of time for the IS elements to integrate into genes or to simply redirect regulatory patterns of gene expression. Microorganisms may thus induce variation simply through shuffling the order of genes and put old genes in new contexts: variation through position effects that can be inherited and propagated in time. It’s hardly an exaggeration to state that jumping genetic elements specified by the bacterium’s genome generated the new phenotypes.Transposition of IS elements is mostly characterized by local hopping, meaning that novel insertions are usually in the proximity of the previous insertion and may be a more-or-less random phenomenon; the site of integration isn’t sequence dependent. Bacteria have a restricted set of genes and they divide almost indefinitely. Therefore, sequencedependent insertion and stringent regulation of transposition may not be required for IS-induced reshuffling of bacterial genomes; in a population of billions of microorganisms all possible chromosomal rearrangements may occur due to stochastic processes. In ‘higher’ organisms the order of genes in the chromosomes is more important, but there is no reason to exclude jumping genetic elements as a factor affecting the expression of genetic programs through position effects. Transposable elements may therefore be a class of variation-inducing genetic elements (VIGEs) in ‘higher’ organisms. Indeed, ERVs, LINEs and SINEs resemble IS elements in bacteria in that they are able to transpose. In fact, these elements may be responsible for a large part of the variability observed in higher organisms and may even be responsible for adaptive phenotypes. The genomic transposition of VIGEs is not just a random process. As observed for Ty elements in yeast, integration of all VIGEs may originally have been designed as site or sequence specific. It should be noted that VIGEs might qualify as redundant genetic elements, of which the control over translocation may have deteriorated over time. VIGEs in humans Mobile genetic elements make up a considerable part of the eukaryotic genome and have the ability to integrate into the genome at a new site within their cell of origin. Mobile genetic elements of several classes make up more than one third of the human genome.Human endogenous retroviruses (ERVs) are, as with yeast ERVs, first transcribed into RNA molecules as if they were genuine coding genes. Each RNA is then transformed into a double stranded RNA-DNA hybrid through the action of reverse transcriptase, an enzyme specified by the retrotransposon itself. The hybrid molecule is then inserted back into the genome at an entirely different location. The result of this copy-paste mechanism is two identical copies at different locations in the genome. More than 300,000 sequences that classify as ERVs have been found in the human genome, which is about 8% of the entire human DNA.16

Figure 1. Variation-inducing genetic elements (VIGEs) are found throughout all biological domains, ranging from bacteria to mammals. In yeast, insects and mammals we observe similar designs. (Homologous sequences are indicated by the same colour). Long terminal repeats retrotransposons (LTR retrotransposons) are transcribed into RNA and then reverse transcribed into a RNA-DNA hybrid and reinserted into the genome. LTRs and retroviruses are very similar in structure. Both contain gag and pol genes (figure 1), which encode a viral particle coat (GAG), reverse transcriptase (RT), ribonuclease H (RH) and integrase (IN). These genes provide proteins for the conversion of RNA into complementary DNA and facilitate insertion into the genome. Examples of LTR retrotransposons are human endogenous retroviruses (HERVs). Unlike RNA retroviruses, LTR retrotransposons lack envelope proteins that facilitate movements between cells.Non-LTR retrotransposons, such as long interspersed elements (LINEs), are long stretches (4,000–6,000 nucleotides) of reverse transcribed RNA molecules. LINEs have two open reading frames: one encoding an endonuclease and reverse transcriptase, the other a nucleic acid binding protein (figure 1). There are approximately 900,000 LINEs in the human genome, i.e. about 21% of the entire human DNA. LINEs are found in the human genome in very high copy numbers (up to 250,000).17Short interspersed elements (SINEs) constitute another class of VIGEs that may use an RNA intermediate for transposition. SINEs do not specify their own reverse transcriptase and therefore they are retroposons by definition. They may be mobilized for transposition by using the enzymatic activity of LINEs. About one million SINEs make up another 11% of the human genome. They are found in all higher organisms, including plants, insects and mammals. The most common SINEs in humans are Alu elements. Alu elements are usually around 300 nucleotides long, and are made up of repeating units of only three nucleotides. Some Alu elements secondarily acquired the genes necessary to hop around in the genome, probably though recombination with LINEs. Others simply duplicate or delete by means of unequal crossovers during cell divisions. More than one million copies of Alu elements, often interspersed with each other, are found in the human genome, mostly in the non-coding sections. Many Alu-like elements, however, have been found in the introns of genes; others have been observed between genes in the part responsible for gene regulation and still others are located within the coding part of genes. In this way SINEs affect the expression of genes and induce variation. Alu elements are often mediators of unequal homologous recombinations and duplications.18 Figure 2. Schematic view of the central role VIGEs may play to generate variation, adaptations and speciation events. Lower part: VIGEs may directly modulate the output of (morpho)genetic algorithms due to position effects. Upper part: VIGEs that are located on different chromosomes may be the result of speciation events, because their homologous sequences facilitate chromosomal translocations and other major karyotype rearrangements.Repetitive triplet sequences (RTSs) present in the coding regions of proteins are a class of VIGEs that cannot actively transpose. RTSs are usually found as an intrinsic part of the coding region of proteins. For instance, RTSs can be formed by a tract of glycine (GGC), proline (CCG), or alanine (GCC). Usually RTSs form a loop in the messenger (m)RNA that provides a docking site for chaperone molecules or proteins involved in the mRNA translation. RTSs may increase or decrease in length through slippery DNA polymerases during DNA replication. Conclusions and outlook Now that we have redefined ERVs as a specific class of VIGEs, which were present in the genomes from the day they were created, it is not difficult to see how RNA viruses came into being. RNA viruses have emerged from VIGEs. ERVs, LINEs and SINEs are the genetic ancestors of RNA viruses. Darwinists are wrong in promoting ERVs as remnants of invasions of RNA viruses; it is the other way around. In my opinion, this view is ed by several recent observations. RNA viruses contain functional genetic elements that help them to reproduce like a molecular parasite. Usually, an RNA virus contains only a handful of genes. Human Immunodeficiency virus (HIV), the agent that causes AIDS, contains only eight or nine genes. Where did these genes come from? An RNA world? From space? The most parsimonious answer is: the RNA viruses got their genes from their hosts.The Rous arcoma virus (RSV), which has the ability to cause tumours, has only 4 genes: gag, pol, envand src. In addition, the virus is flanked by a set of repeat sequences that facilitate integration and promote replication. Gag, pol and env are genes commonly present in ERVs. The src gene of RSV is a modified hostderived src gene that normally functions as a tyrosine kinase—a molecular regulator that can be switched on and off in order to control cell proliferation. In the virus, the regulator has been reduced to an on-switch only that induces uncontrolled cell proliferation. The src gene is not necessary for the survival of RSV, and RSV particles can be isolated that have only the gag, pol and env genes. These have perfectly normal life cycles, but do not cause tumours in their host. It is clear the virus picked up the src gene from the host. Why wouldn’t the whole vector be derived from the host? VIGEs may easily pick up genes or parts thereof as the result of an accidental polymerase II read-through. This will increase the genetic content of the VIGE because the gene located next to the VIGE will also be incorporated. An improper excision of VIGEs may also include extra genetic information. Imagine for instance HERV-K, a well-known human-specific endogenous retrovirus, transposing itself to a location in the genome where it sits next to thesrc gene. If in the next round of transposition a part of the src gene was accidentally added to the genes of HERV-K, it has already transformed into a fully formed RSV (see figure 3). It can be demonstrated that most RNA viruses are built of genetic information directly related to that of their hosts.

Figure 3. RNA viruses originate from VIGEs through the uptake of host genes. In the controlled and regulated context of the host DNA, genes and VIGEs are harmless. A combination of a few genes integrated in VIGEs may start an uncontrolled replication of VIGEs. In this way, VIGEs may take up genes that serve to form the virus envelope (to wrap up the RNA molecule derived from the VIGE) and genes that enable them to leave and re-enter host cells. Once VIGEs become full-blown shuttle vectors between hosts, they act as virulent, devastating and uncontrolled replicators. Hence, harmless VIGEs may degenerated into molecular parasites in a similar way normally harmless cells turn into tumors once they lose the power to control cell replication. VIGEs are on the basis of RNA viruses, not the other way around. The scheme outlined here shows how the Rous sarcoma virus (RSV) may have formed from a VIGE that integrated the env gene and part of the src gene (a proto-oncogene: for details see text).The outer membranes of influenza viruses, for instance, are built of hemagglutinin and neuraminidase molecules. Neuraminidase is a protein that can also be found in the genomes of higher ‘host’ organisms, where it serves the function to modify glycopeptides and oligosaccharides. In humans, neuraminidase deficiency leads to neurodegenerative lysosomal storage disorders: sialidosis and galactosialidosis.19 Even so-called orphan genes, genes that are only found in viruses, can usually be found in the host genomes. Where? In VIGEs!To become a shuttle-vector between organisms, all that is required is to have the right tools to penetrate and evade the defenses of the host cell. HIV, for instance, acquired part of the gene of the host’s defence system (the gp120 core) that binds to the human beta-chemokine receptor CCR5.20These observations make it plausible that all RNA viruses have their origin in the genomes of living cells through recombination of host’s DNA elements (genes, promoters, enhancers). Every now and then such an ‘unfortunate’ recombination produces a molecular replicator: it is the birth of a new virus. Once the virus escapes the genome and acquires a way to re-enter cells, it has become a fully formed infectious agent. It has long been known that bacteria use genes acquired from bacteriophages—i.e. bacterial viruses that insert their DNA temporarily or even permanently into the genome of their host—to gain reproductive advantage in a particular environment. Indeed, work reaching back decades has shown that prophage (the integrated virus) genes are responsible for producing the primary toxins associated with diseases such as diphtheria, scarlet fever, food poisoning, botulism and cholera. Diseases are secondary entropy-facilitated phenomena. Virologists usually explain the evolution of viruses as recombination: that is, a mixing of pre-existing viruses, a reshuffling and recombination of genes. 21 In bacteria, viruses may therefore be recombined from plasmids carrying survival genes and/or transposable genetic elements, such as IS elements. Discussion Where did all the big, small and intermediate noses come from? Why are people tall, short, fat or slim? What makes morphogenetic programs explicit? The answer may be VIGEs. It may turn out that the created kinds were designed with baranomes that had an ability to induce variation from within. This radical view implies that the baranome of man may have been designed to contain only one morphogenetic algorithm for making a nose. But the program was implicit. The program was designed in such way that a VIGE easily integrated into it, becoming a part of it, hence making the program explicit. Most inheritable variation we observe within the human population may be due to VIGEs—Elements that affect morphogenetic and other programs of baranomes. It should be noted that a huge part of the genomic sequences are ‘redundant’ adaptors, spacers, duplicators, etc., which can be removed from the genome without major affects on reproductive success (fitness). In bacteria, VIGEs have been coined IS elements; in plants they are known as transposons; and in animals, they are called ERVs, LINEs, SINEs, and microsatellites. What these elements are particularly good at is inducing genomic variation. It is the copy number of VIGEs and their position in the genome that determine gene expression and the phenotype of the organism. Therefore, these transposable and repetitive elements should be renamed after their function: variation-inducing genetic elements. VIGEs explain the variations Darwin referred to as ‘due to chance’.I will address the details of a few specific classes of VIGEs and argue why modern genomes are literally riddled with VIGEs in a future article. With the realization that RNA viruses have emerged from VIGEs the RNA paradox is solved. For many mainstream scientists this solution will be bothersome because VIGEs were frontloaded elements of the baranomes of created kinds and that implies a young age for their common ancestor and that all life is of recent origin. The design of life: part 4—variation-inducing genetic elements and their function by Peter Borger Endogenous retroviruses (ERVs) are claimed to be the selfish remnants of ancient RNA viruses that invaded the cells of organisms millions of years ago and now merely free-ride the genome in order to be replicated. This selfish gene thinking still dominates the public scene, but well-informed biologists know that the view among researchers is rapidly changing. Increasingly, ancient RNA viruses and their remnants are being thought of as having played (and still do) a significant role in protein evolution, gene structure, and transcriptional regulation. As argued in part 3 of this series of articles, ERVs may be the executors of genetic variation, and qualify as specifically designed variation-inducing genetic elements (VIGEs) responsible for variation in higher organisms. VIGEs induce variation by duplication, transposition, and may even rearrange chromosomes. This extraordinary claim requires extraordinary scientific , which is present throughout this paper. In addition, the VIGE hypothesis may be a framework to understand the origin of diseases and explain rapid speciation events through facilitated chromosome swapping.The idea that mobile genetic elements are involved in creating variation is not new. Barbara McClintock, who discovered the first mobile genetic elements in maize, was also the first to recognize the true nature of such jumping genetic elements. In 1956, she suggested that transposons (as she coined them) function as molecular switches that could help determine when nearby genes turn on and off. Her key insight was that all living systems have mechanisms available to restructure and repair the chromosomes. When it was discovered that more than half of the human genome consists of (remnants of) mobile elements, McClintock’s ideas were revived and further developed by Roy Britten and Eric Davidson.1 It is only recently that we have begun to understand the power of VIGEs (variation-inducing genetic elements) as genetic regulators and switches. A team of investigators lead by Haussler recently provided direct evidence that even when a short interspersed nucleotide element (SINE) lands at some distance from a gene, it can take on a regulatory role with powerful regulatory functions.2‘Haussler and his colleagues then looked at a particular example—a copy of the ultra-conserved element that is near a gene called Islet 1 (ISL1). ISL1 produces a protein that helps control the growth and differentiation of motor neurons. In the laboratory of Edward Rubin at the University of California, Berkeley, postdoctoral fellow Nadav Ahituv combined the human version of the LF-SINE sequence with a “reporter” gene that would

produce an easily recognizable protein if the LF-SINE were serving as its on-off switch. He then injected the resulting DNA into the nuclei of fertilized mouse eggs. Eleven days later, he examined the mouse embryos to see whether and where the reporter gene was switched on. Sure enough, the gene was active in the embryos’ developing nervous systems, as would be expected if the LF-SINE copy were regulating the activity of ISL1.’3This excerpt shows that some functions of SINEs are easily uncovered because they are directly affecting the expression of a particular gene. However, most functions of SINEs may not be as easily detected as described of above, because they can integrate in gene deserts—regions of the genome where the chromosomes are devoid of any recognizable protein-coding genes—or they may only subtly affect expression of morphogenetic programs. Gene expression patterns largely determine how cells behave and determine the morphology of organisms. VIGEs integrated in such genetic programs will change expression patterns of genes that will result in different cellular behaviour and morphology. Whether the ultimate effect on the phenotype of the organism can be predicted, however, remains to be established. This is largely due to the fact that we still do not know what morphogenetic algorithms look like. Of course, biologists have argued that evolution and development are determined by homeobox (HOX) genes, but HOX genes are merely executors of developmental (or morphogenetic) programs; they are not the programs themselves.In another study by the same group, thousands of short identical DNA sequences that are scattered throughout the human genome were analyzed. Many of those sequences were located in gene deserts, which are in fact so clogged with regulatory DNA elements that they have recently been renamed regulatory jungles. But what do they regulate? The answer could be morphogenesis. Most of the short DNA elements cluster near genes that play a decisive role during an organism’s first weeks after conception. The elements help to orchestrate an intricate choreography of ‘when-and-where’ developmental genes are switched on and off as the organism lays out its body plan. These elements may provide a sort of blueprint for how to build the animal. The exact mechanism as to how such sequences may function as a plan to build an animal is not entirely clear, but the DNA elements are particularly abundant near genes that help cells to stick together. That ‘stickiness’ is important in an organism’s early life phase because these genes help cells to migrate to the right location and to form into organs and tissues of the correct shape. The 10,402 short DNA sequences studied by Bejerano are derived from transposable genetic elements—retrotransposons that duplicate themselves and hop around the genome. Apparently, transposable genetic elements are not what they have been mistakenly thought to be: mess makers. Indeed, the view that transposable elements are just bad stuff is rapidly changing. In an interview with Science Daily, Bejerano says: ‘We used to think they were mostly messing things up. Here is a case where they are actually useful.’4 The genome is literally littered with thousands of transposable elements. The word is that ‘when ancient retroviruses slipped bits of their DNA into the primate genome millions of years ago, they successfully preserved their own genetic legacy.’ 5 It is hard to imagine that they all have functions, but their presence could certainly determine or fine-tune the output of nearby genes. In this way they may create subtle, but novel, variation. Bejerano and Haussler’s research has already identified a handful of transposons that serve as regulatory elements, but it is not clear how common the phenomenon might be. The 2007 study showed that the phenomenon may be a general one: ‘Now we’ve shown that transposons may be a major vehicle for evolutionary novelty.’ 4 The new findings indeed show that, in many cases, transposable elements function as regulators of gene output, but major vehicles for evolution from microbe to man they are not. The transposition of jumping genetic elements may certainly affect gene expression patterns, but it does not follow that they produce new genetic information. Considering the biological data, it seems reasonable that transposable elements are present in the genome to deliberately induce biological variation. Transposable elements thus qualify as variation-inducing genetic elements (VIGEs), and by leaving copies, they make sure the new variation is heritable. The transposable elements present in regulatory jungles do not produce new biological information, but they induce variation in the genetic algorithms and may underlie rapid adaptive radiation from uncommitted pluripotent genomes. The regulatory jungles may provide an active reservoir of VIGEs that put existing genes in new regulatory environments. Regulated activity of VIGEs The chromosome of the E. coli strain K12 includes three cryptic operons (linear genetic programs that encode programs to metabolize three alternative sugars): one for cellobiose, one for arbutin and one for salicin. The organization of those operons is like a normal substrate-induced bacterial operon; but the operons themselves are abnormal in that they are cryptic (silent) in wild-type strains. Even in the presence of alternative sugars the operons are not activated, which indicates that these bacteria don’t readily use alternative sugars. Unused cryptic operons are redundant genetic programs that are not observed by natural selection:‘As cryptic genes are not expressed to make any positive contribution to the fitness of the organism, it is expected that they would eventually be lost due to the accumulation of inactivating mutations. … Cryptic genes would thus be expected to be rare in natural populations. This, however, is not the case. Over 90% of natural isolates of E. coli carry cryptic genes for the utilization of beta-glucoside sugars. … These cryptic operons can all be activated by IS [insertion-sequence] elements, and when so activated allow E. colito utilize beta-glucoside sugars as sole carbon and energy sources.’6The excerpt shows that operons are kept inactive by repressors; that is, proteins that sit on the DNA of the operon to ward off the nanomachines responsible for gene expression. Operons will only be active in bacteria that don’t have a functional gene coding for the repressors. Disrupting the repressor gene releases the cryptic programs. That’s where the VIGEs come in. The transposition and integration of an IS element into the silencer elements is the mutational event that activates the cryptic operon. Usually, the lack of an appropriate carbon and energy source triggers transposition of IS elements. The transposition of IS elements appears to be regulated by starvation, and the integration in the repressor gene is not utterly random. For instance, position 472 in the ebgR gene in the ebg operon of E. coli is a hotspot for integration of IS elements, but only under starvation conditions. VIGEs may thus accumulate and integrate at well-defined positions in the genome; this indicates a site-specific mechanism.In the fruit fly, some non-LTR (long terminal repeats retrotransposons) integrate at very specific sites, but some others have been shown to integrate more or less at random. The specificity is determined by endonucleases, enzymes that cut the DNA.7 Assuming VIGEs are part of a designed genome, we must expect that their transposition and activity can be controlled and regulated. To avoid deleterious effects on the host and retrotransposon, we may expect that the activity of VIGEs is regulated both by retrotransposon-and host-encoded factors. Indeed, the mechanism of transposition seems to be dictated by the species in which the VIGEs operate. Recent research has shown that in zebra fish the transposable element known as NLR integrant usually carries a few extra nucleotides at the far end of the sequence, but it is not expressed in human cells.8 This observation would argue for the involvement of host specific protein machinery in transposition—one more argument for the design origin of VIGEs.From the design perspective, we may expect that the activity of VIGEs used to be a tightly controlled process. This is because the genomes in which they operate also specify control factors: retroviral restriction factors. The restriction factors are proteins with the ability to bind to retroviral capsid proteins and target them for degradation. Several restriction factors have been identified, including Fv1, Trim5-alpha and Trim5-CypA.9 These factors share the common property of containing sequences that promote selfassociation: that is, they can assemble themselves. This fact, together with the observation that the restriction factors are encoded by unrelated genes, is clear evidence of purposeful design. Retroviral restriction factors play an important role in

innate immunity against invading RNA viruses. For instance, Trim5-alpha binds directly to the incoming retroviral capsid core and targets its premature disassembly or destruction. 10 In addition, some integrated VIGEs show evolutionary-tree deviations, indicating a sequence-specific integration/excision mechanism. For instance, Alu HS6 is present in human, gorilla and orangutan, but not in chimpanzee (see figure 1). This highly peculiar observation prompted the investigators to consider the possibility of the specific excision of this Alu element from the chimpanzee’s genome.11 Precise excision implies precise integration.

Figure 1. The Alu HS6 insertion sites in human, chimpanzee, gorilla, orangutan and owl monkey. Note the complete absence in chimpanzee and owl monkey of any evidence for an extraction site. This suggests a highly specific mechanism for integration and/or extraction. Alternatively, the sequences are a molecular falsification of the common descent of primates. Biologists specializing in synthetics at the Johns Hopkins University have built, from scratch, a LINE1-based retrotransposon —a genetic element capable of jumping around in the mouse genome. The man-made retrotransposon was designed to be a far more effective ‘jumper’ than natural retrotransposons; indeed, it inserts itself into many more places in the genome.12,13 Why do not all LINEs jump so effectively? The scientists that constructed the synthetic LINE changed the regulator sites used in transposition. Native LINE1 elements are relatively inactive in mice when they are introduced into the mouse genome as transgenes. The synthetic LINE1-based element, ORFeus, contains two synonymously recoded ORFs relative to mouse L1 and is far more active. This indicates that the integration and excision of native LINE1 elements are controlled and regulated by an as yet unknown mechanism.VIGEs qualify as redundant genetic elements that can simply be erased from the genome without fitness effects. As long as VIGEs do not upset critical genomic functions and do affect reproductive success of the carrier, they are selectively neutral. Therefore, not only VIGEs, but also the mechanisms by which they integrate, may readily wither and degrade due to accumulation of debilitating mutations. The control over integration and activity we observe today may be less stringent compared to how it was originally designed. The originally fine-tuned control for excision and transposition may have deteriorated over time and what is left today are more or less free moving elements that may predominantly cause havoc when they integrate in the wrong location. It is easy to understand how, for instance, endonucleases became less specific through mutations. This view may also explain why VIGEs are often found associated with heritable diseases. As long as VIGE activity and integration do not significantly affect the fitness of the organisms in which they operate, they are free to copy and paste themselves along the genome. Indeed, inactivating VIGEs have been observed in genes not immediately required for reproduction. The GULO gene, which qualifies as a redundant gene in populations with high vitamin C intake, has been hit several times by VIGEs and this may have contributed to pseudogenization of GULO in humans.14Over time, VIGEs may have become increasingly detrimental to the host’s genome. That is because information that regulates the integration and activity of VIGEs is subject to mutation. Some VIGEs have been associated with susceptibility or resistance to diseases. In asthma, increased susceptibility appears to be associated with microsatellite DNA instability (a term used for copy-number differences in repetitive DNA sequences). 15 Psoriasis is also associated with HERV expression.16 It should be clear that deregulated and uncontrolled VIGEs cause havoc when they integrate with and disrupt functional parts of genes.From the vantage of design, VIGE transpositions would make sense during meiosis, which is the process leading to the formation of gametes. Controlled activity of VIGEs during meiosis may be responsible for variation that can be ed on to the offspring. Although information is scant, it has been shown in fungi17 and plants18 that VIGEs become active during meiosis and even have mechanisms to silence deleterious bystandereffects, such as deleterious point mutations.17 This shows transposable elements function to induce genetic variation, providing the flexibility for populations to adapt successfully to environmental challenges. In chimpanzees, for instance, it has been documented that large blocks of compound repetitive DNA, which have demonstrated retrotransposon function, induce and prolong the bouquet stage in meiotic prophase and affect chiasm formations. 19 This may seem like a mouthful, but it merely means that these repetitive genetic elements facilitate sister-chromosome exchanges when reproductive cells (sperm and eggs) are being generated. Mammalian VIGEs, in particular Alu sequences, have the ability to induce genetic recombination and duplications and contribute to chromosomal rearrangements, and they may for the major part of variation observed in humans. The methylation pattern of Alu sequences possibly determine activity and/or serve as markers for genomic imprinting or in maintaining differences in male and female meiosis. 21 VIGEs and the human family When short triplet repeat units are present in the coding part of a gene, they may even have functional consequences. There is evidence that repeat units in the Runx2 gene formed the bent snout of the Bullterrier in a few generations.22 Likewise, in mice and dogs, having five or six toes is determined by a repeat unit in the Alx4 gene.23 These novel phenotypes can form almost over night, i.e. within one generation. Repetitive coding triplets that can be gained or lost provide another mechanism to generate (instant) variation. It should be noted that this mechanism leads to reversible genetic change, because a lost repetitive unit can readily be added back through duplication of a preexisting one, and vice versa. Therefore, the RTS mechanism may explain seasonal changes in beak size observed for Galapagos finches, adaptive phenotypes in Australian snakes and the ‘evolution’ of the Cichlid varieties in African lakes.If we accept the idea of deliberately designed VIGEs, we may also expect these elements to have played an important role in determining the variety of human phenotypes. In other words, human races are the result of the activity of VIGEs! Biologists used to think that our genomes all had the same basic structure—the same number of genes, in roughly the same order, with a few minor differences in the sequence of DNA bases. Now, technologies that compare whole human genomes are revealing that this picture is far from complete. Michael Wigler at Cold Spring Harbor Laboratory provided the first evidence that human genomes are strikingly variable: his group showed marked differences in the copy number of protein-coding genes.24 Apparently, some people have more copies of certain genes and, large-scale copy number polymorphisms (CNPs) (about 100 kilobases and greater) contribute substantially to genomic variation between individuals. 25 In addition, people not only carry different copy numbers of parts of our DNA they also have varying numbers of deletions, insertions and other major rearrangements in their genomes.In 2005, Evan Eichler of the University of Washington reported 297 locations in the genome where different individuals have different forms of major structural variations. At these spots some carry a major deletion, for example, or an extra hundred bases of DNA. Differences between individuals were found in the protein-coding genes; structural differences were also observed between individual genomes.26 From these and other studies we now know that every one of us shares only about 99% of our DNA with all the other people on Earth. 27 The difference is due to repetitive sequences that easily amplify or delete parts from the genome. With this, we have discovered another class of VIGEs. The highly variable repetitive sequences also explain why genetic screening methods are so reliable nowadays: they

detect copy-number differences and hence are capable of discriminating between the DNA of a father and his son. Yes, fathers and sons apparently differ at the level of VIGEs!A comparison of Asian and Caucasian people showed that 25% of more than 4,000 protein-coding genes had significantly different expression patterns. Some gene expression levels differed as much as twofold.28 The researchers commented that these findings ‘ … the idea that there are genetically determined characteristics that tend to be clustered in different ethnic groups.’ Some genes are simply not expressed at all, or are simply not present in the genomes. For instance, the gene UGT2B17 is deleted more often in Asians than in Caucasians, and has a mean expression level that was more than 20 times greater in Caucasians relative to Asians. How can such big differences be explained? Of course, single nucleotide polymorphisms (SNP; i.e. point mutations) in regulatory sequences could affect gene regulation patterns. It is not clear, however, ‘whether the SNPs themselves might be regulating gene expression or whether they travel together with other DNA that’s the regulator.’ We may also expect VIGEs to be responsible for differences observed between human races. VIGEs and chromosome 2 Human chromosome 2 looks as if it is the product of the fusion of two chromosomes that we find in chimpanzees as chromosome 12 and 13. Therefore, some Darwinists take human chromosome 2 as the ultimate evidence for common descent with chimpanzees. We know that a fusion of two ancestral chromosomes would have produced human chromosome 2 with two centromeres. Currently, human chromosome 2 has only one centromere, so there must be molecular evidence for remnants of the other. In 1982, Yunis and Prakash studied the putative fusion site of chromosome 2 with a technique known as fluorescence in situ hybridization (FISH) and reported signs of the expected centromere.29In 1991, another study also reported signs of the centromere.30 In 2005, after the complete sequencing of human chromosome 2, we would have expected full proof of the ancestor’s centromere. However, even after intense scrutiny there are still only signs of the centromere. If signs of the centromere were already observed in 1982, why can it not be proved in the 2005 sequence analysis? Apparently, the site mutated at such high speed it is no longer recognizable as a centromere:‘During the formation of human chromosome 2, one of the two centromeres became inactivated (2q21, which corresponds to the centromere of chromosome 13) and the centromeric structure quickly deteriorated’. 31Why would it quickly deteriorate? Why would this region deteriorate faster than neutral? A close up scrutiny in 2005 showed the region that has been interpreted as the ancestor’s centromere to be built from sequences present in 10 additional human chromosomes (1, 7, 9, 10, 13, 14, 15, 18, 21 and 22) as well as a variety of other genetic repeat elements that were already in place before the fusion occurred.31 The sequences interpreted as ‘ancient centromere’ are merely repetitive sequences and may actually qualify as (deregulated) VIGEs.The chimpanzee and human genome projects demonstrated that the fusion did not result in loss of protein coding genes. Instead, the human locus contains approximately 150,000 additional base pairs not found in chimpanzee chromosome 12 and 13 (now also known as 2A and 2B). This is remarkable: why would a fusion result in more DNA? We would rather have expected the opposite: the fusion would have left the fused product with less DNA, since loss of DNA sequences is easily explained. The fact that humans have a unique 150 kb intervening sequence indicates it may have been deliberately planned (or designed) into the human genome. It could also be proposed that the 150 kb DNA sequence demarcating the fusion site may have served as a particular kind of VIGE, an adaptor sequence for bringing the chromosomes together and facilitating the fusion in humans.Another remarkable observation is that in the fusion region we find an inactivated cobalamin synthetase (CBWD) gene. 32 Cobalamin synthetase is a protein that, in its active form, has the ability to synthesize vitamin B12 (a crucial cofactor in the biosynthesis of nucleotides, the building blocks of DNA and RNA molecules). Deficiency during pregnancy and/or early childhood results in severe neurological defects because of impaired development of the brain. The Darwinian assumption is that the cobalamin synthetase gene was donated by bacteria a long time ago and afterwards it was inactivated. Nowadays, humans must rely on microorganisms in the colon as well as dietary intake (a substantial part coming from meat and milk products) for their vitamin B12 supply. It is also noteworthy that humans have several copies of inactivated cobalamin-synthetase-like genes on a number of locations in the genome, whereas chimpanzees only have one inactivated cobalamin synthetase gene. That the fusion must have occurred after man and chimp ‘split’ is evident from the fact that the fusion is unique to humans:‘Because the fused chromosome is unique to humans and is fixed, the fusion must have occurred after the humanchimpanzee split, but before modern humans spread around the world, that is, between 6 and 1 million years ago.’ 32The molecular analyses show we are more unique than we ever thought we were, and this is in complete accordance with creation. Apparently the fusion of two human chromosomes that took place may have been the result of an intricate rearrangement or activation of repetitive genetic elements after the Fall (as part of, or executors of, the curse following the Fall) and inactivated the cobalamin synthetase gene. The inactivation of the gene may have reduced people’s longevity in a similar way as the inactivation of the GULO gene, which is crucial to vitamin C synthesis.14 Understanding the molecular properties of human chromosome 2 is no longer problematic if we simply accept that humans, like the great apes, were originally created with 48 chromosomes. Two of them fused to form chromosome 2 when mankind went through a severe bottleneck.33 And, as argued above, the fusion was mediated by VIGEs (see figure 2). Figure 2. Putative mechanism for how the human chromosome 2 formed through the fusion of two ancestral chromosomes p2 and q2, which are similar to chimpanzee chromosome 12 and 13). Like the great apes, originally the human baranome may have contained 48 chromosomes. A) Independent transposition events may have led to the integration of a relative small variation-inducing genetic element (VIGE). B) Extended duplication events of the VIGE may have resulted in rapid

expansion of the region in both p2 and q2, preparing it to become an ‘adapter sequence’ required for fusion. C) The expanded homologous regions align and facilitate the fusion of the chromosomes. The fusion region (2q21) and other parts of the modern human genome still shows the remnants of this catastrophic event that only occurred in humans: the cobalamin synthetase gene was inactivated and several inactive copies, which are not found in the chimpanzee, scattered throughout the genome. Speculative note: Before the great flood, and probably shortly after, a balancing dynamics of both 48 and 46 chromosomes may have been present in the human family. This may explain the two extreme cranial morphologies present in the human fossil record. The Homo erectus/Neandertal humans may have had a karyotype comprised of 48 chromosomes (non-fused p2 and q2), whereas the other humans had 46 (fused p2 and q2). The upside-down world The p53 protein is a mammalian transcription factor that functions as the main switch controlling whether cells divide or go into apoptosis (programmed cell death, which is sometimes required for severely damaged cells that may become tumours). Scientists have long wondered how p53 gained the ability to turn on and off more than 1200 genes related to cell division, DNA repair and programmed cell death. Without the p53 control system organisms would not function: all life would have died as bulky tumors.Biologists at the University of California now claim that ancient retroviruses helped p53 to become an important master gene regulator in primates.34 An RNA virus invaded the genome of our common ancestor, jumped into hundreds of new positions throughout the human genome and spread numerous copies of repetitive DNA sequences that allowed p53 to regulate many other genes, the team contends. Studies such as these prompted Darwinians to change their minds about jumping genetic elements. In other words, a randomly hopping ERV provided the human genome with carefully regulated decision-making machinery. The idea is beyond reasonable belief. Darwinists tend to mix things up. What really happened in the human genome is a read-through of polymerase II in a VIGE that was next to a gene that already contained a binding site for p53. Or maybe the VIGE was excised improperly, taking a bit of a flanking gene containing the p53 binding site. Next, the modified VIGE amplified, transposed, amplified and so on. That explains this family of transposons. A similar story can be told for the syncytin gene, which encodes a protein of the mammalian placenta that helps the fertilized egg to become embedded in the uterus wall. Since syncytin has also been found on a transposable element, 35 mammals are alleged to have obtained the gene from an RNA virus that infected a mammalian ancestor millions of years ago. It is more likely, however, that syncytin was captured by a VIGE.In bacteria it is often observed that genes that convey a specific advantageous character are transmitted via plasmids. Plasmids often contain genes for alternative metabolic routes or genes that provide resistance to antibiotics, and they replicate independently from the host’s genome. Plasmids easily shuttle between microorganisms via a DNA uptake-process known as transformation (or horizontal gene transfer). The uptake of plasmids is regulated and controlled, and is DNA sequence dependent. The result of DNA transformations is rapid adaptation to, for instance, antibiotics. Likewise, viruses replicate independently from the genomic DNA, leaving many copies and easily transferring from one organism to another. Viruses are not plasmids, although some viruses may have a similar function in higher organisms as do plasmids in bacteria: they may be able to aid in rapid adaptations to changing environments. It has been observed that a virus can indeed transfer an adaptive phenotype. The virus that is present in the fungus (Curvularia protuberata), can induce heat resistance in tropical panic grass (Dichanthelium lanuginosum), allowing both organisms to grow at high soil temperatures in Yellowstone National Park. This shows that ‘viruses’ still provide strategies for rapid adaptation.‘Fungal isolates cured of the virus are unable to confer heat tolerance, but heat tolerance is restored after the virus is reintroduced. The virus-infected fungus confers heat tolerance not only to its native monocot host but also to a eudicot host, which suggests that the underlying mechanism involves pathways conserved between these two groups of plants.’36In fruit flies, wing pigmentation depends on a gene known as yellow. The gene exists in the genome of all individual fruit flies, but in some it is not active. By analysing the genetic origin of the spots on fruit fly wings, researchers have discovered a molecular mechanism that explains how new patterns of pigmentation can emerge. The secret appears to be specific genetic elements that orchestrate where proteins are used in the construction of an insect’s body. The segments do not code for proteins, but rather regulate the nearby gene that specifies the pigmentation. As such, these regulatory DNA segments qualify as VIGEs. The researchers transferred the regulatory DNA segment from a spotted species (Drosophila biarmipes) into another species not expressing the spot (D. melanogaster), and attached the regulatory region to a gene for a fluorescent protein. They found that the fluorescent gene was expressed in the spot-free species in exactly the same patterns as the yellow gene is expressed in the spotted species. By comparing several spotted and spotfree species, the scientists established that mutation of a regulatory DNA segment led to the expression of the spotted trait. They discovered that in the species with spotted wings this regulatory segment has multiple binding sites for a protein that then activates the yellow gene. Spotless species do not have multiple binding sites. 37 The multiplicity of regulatory DNA segments may argue for an amplification mechanism or targeted integration of the regulatory sequence. That explains why the same pattern of pigmentation can emerge independently in distantly related species (Darwin’s analogous variation). The observed shuttle function of viruses leads me to pose an intriguing question: Were endogenous retroviruses originally designed to serve as shuttle-vectors to deliver messages from the soma to the germ-line? If yes, then it would put Lamarckian evolution in an entirely new perspective. Discussion The findings of the new biology demonstrate that mainstream scientists are wrong regarding the idea that transposable elements are the selfish remnants of ancient invasions by RNA viruses. Instead, RNA viruses originate from transposable elements that were designed as variation-inducing genetic elements (VIGEs). Created kinds were deliberately frontloaded with several types of controlled and regulated transposable elements to allow them to rapidly invade and adapt to all corners and crevices of the earth. Due to the redundant character of VIGEs, their controlled regulation may have readily deteriorated and some of them may now merely cause havoc. The VIGE hypothesis provides elegant explanations for several biological observations that may otherwise be difficult to interpret within the creationist framework, including the origin of diseases (RNA viruses) and chromosome rearrangements. The VIGE hypothesis may be a framework for extended creationist research programs. Some intriguing question can already be raised.Were VIGEs intentionally designed to cause diseases? No, they were not. It is conceivable that the transposition and integration of VIGEs is not entirely random. The transposition of VIGEs may have been originally present in the baranome as controlled and regulated elements and activated upon intrinsic or external triggers. To induce variation in offspring, triggers for the transposition of VIGEs could be released during meiosis, when the reproductive cells are being produced. The emergence of RNA viruses from VIGEs may be a result of the Fall, when we were cut of from the regenerating healing power of the designer.Why are some VIGEs located on the exact same position in primates and humans? Each original baranome must have had a limited number of VIGEs, some of which we still find on the same location in distinct species. In distinct baranomes, VIGEs may have been located on the exact same positions (the T-zero location), which then explains why some VIGEs such as ERVs, can be found in the same location in, for instance, primates and humans. In addition, sequence-dependent integration of VIGEs may also contribute to this observation.How could Bdelloid rotifers, a group of strictly asexually reproducing aquatic invertebrates, rapidly form novel species?Asexual production of progeny, as observed in Bdelloids, is found in over one

half of all eukaryotic phyla and is likely to contribute to adaptive changes, as suggested by recent evidence from both animals and plants.38 The Bdelloids may have been derived from pluripotent baranomes containing numerous DNA transposons and retro elements, including active LTR retrotransposons containing gag,pol, and env-like open reading frames.39 These elements are able to reshuffle the genomes and facilitate instant variation and speciation.Do we also observe remnants of DNA viruses in the mammalian genomes? If not, this s my idea that RNA viruses emerged from VIGEs, and implies DNA viruses have a different origin; probably, as with the Mimi-virus 40, they originated from degenerated bacteria.Why was a class of VIGEs designed with information for protein capsids? The capsid may have been acquired from the host’s genome or it may have been designed to prevent the RNA molecules from attaching themselves to, or finding, integrations sites. A very speculative idea may be that these VIGEs were designed to shuttle information from the soma to the germ-line. One thing is clear, however: creation researchers have loads of work to do. INFORMATION THEORY Refuting Evolution—Chapter 9 A handbook for students, parents, and teachers countering the latest arguments for evolution by Jonathan Sarfati, Ph.D., F.M. Is the design explanation legitimate? First published in Refuting Evolution, Chapter 9 As pointed out in previous chapters, Teaching about Evolution frequently dismisses creation as ‘unscientific’ and ‘religious.’ Creationists frequently point out that creation occurred in the past, so cannot be directly observed by experimental science —and that the same is true of large-scale evolution. But evolution or creation might conceivably have left some effects that can be observed. This chapter discusses the criteria that are used in everyday life to determine whether something has been designed, and applies them to the living world. The final section discusses whether design is a legitimate explanation for life’s complexity or whether naturalistic causes should be invoked a priori. How do we detect design? People detect intelligent design all the time. For example, if we find arrowheads on a desert island, we can assume they were made by someone, even if we cannot see the designer.1There is an obvious difference between writing by an intelligent person, e.g. Shakespeare’s plays, and a random letter sequence like WDLMNLTDTJBKWIRZREZLMQCOP.2 There is also an obvious difference between Shakespeare and a repetitive sequence like ABCDABCDABCD. The latter is an example oforder, which must be distinguished from Shakespeare, which is an example of specified complexity.We can also tell the difference between messages written in sand and the results of wave and wind action. The carved heads of the U.S. presidents on Mt Rushmore are clearly different from erosional features. Again, this is specified complexity. Erosion produces either irregular shapes or highly ordered shapes like sand dunes, but not presidents’ heads or writing.Another example is the SETI program (Search for Extraterrestrial Intelligence). This would be pointless if there was no way of determining whether a certain type of signal from outer space would be proof of an intelligent sender. The criterion is, again, a signal with a high level of specified complexity—this would prove that there was an intelligent sender, even if we had no other idea of the sender’s nature. But neither a random nor a repetitive sequence would be proof. Natural processes produce radio noise from outer space, while pulsars produce regular signals. Actually, pulsars were first mistaken for signals by people eager to believe in extraterrestrials, but this is because they mistook order for complexity. So evolutionists (as are nearly all SETI proponents) are prepared to use high specified complexity as proof of intelligence, when it suits their ideology. This shows once more how one’s biases and assumptions affect one’s interpretations of any data. .3 Life fits the design criterion Life is also characterized by high specified complexity. The leading evolutionary origin-of-life researcher, Leslie Orgel, confirmed this:Living things are distinguished by their specified complexity. Crystals such as granite fail to qualify as living because they lack complexity; mixtures of random polymers fail to qualify because they lack specificity. 4Unfortunately, a materialist like Orgel here refuses to make the connection between specified complexity and design, even though this is the precise criterion of design.To elaborate, a crystal is a repetitive arrangement of atoms, so is ordered. Such ordered structures usually have the lowest energy, so will form spontaneously at low enough temperatures. And the information of the crystals is already present in their building blocks; for example, directional forces between atoms. But proteins and DNA, the most important large molecules of life, are not ordered (in the sense of repetitive), but have high specified complexity. Without specification external to the system, i.e., the programmed machinery of living things or the intelligent direction of an organic chemist, there is no natural tendency to form such complex specified arrangements at all. When their building blocks are combined (and even this requires special conditions 5), a random sequence is the result. The difference between a crystal and DNA is like the difference between a book containing nothing but ABCD repeated and a book of Shakespeare. However, this doesn’t stop many evolutionists (ignorant of Orgel’s distinction) claiming that crystals prove that specified complexity can arise naturally—they merely prove that order can arise naturally, which no creationist contests.6 Information The design criterion may also be described in of information. Specified complexity means high information content. In formal , the information content of any arrangement is the size, in bits, of the shortest algorithm (program) required to generate that arrangement. A random sequence could be formed by a short program: Print any letter at random. Return to step 1. A repetitive sequence could be made by the program: Print ABCD. Return to step 1. But to print the plays of Shakespeare, a program would need to be large enough to print every letter in the right place.7 The information content of living things is far greater than that of Shakespeare’s writings. The atheist Richard Dawkins says: [T]here is enough information capacity in a single human cell to store the Encyclopaedia Britannica, all 30 volumes of it, three or four times over.8If it’s unreasonable to believe that an encyclopedia could have originated without intelligence, then it’s just as unreasonable to believe that life could have originated without intelligence.Even more amazingly, living things have by far the most compact information storage/retrieval system known. This stands to reason if a microscopic cell stores as much information as several sets of Encyclopaedia Britannica. To illustrate further, the amount of information that could be stored in a pinhead’s volume of DNA is staggering. It is the equivalent information content of a pile of paperback books 500 times as tall as the distance from earth to the moon, each with a different, yet specific content.9 Machinery in living things

On a practical level, information specifies the many parts needed to make machines work. Often, the removal of one part can disrupt the whole machine, so there is a minimum number of parts without which the machine will not work. Biochemist Michael Behe, in his book Darwin’s Black Box, calls this minimum number irreducible complexity.10 He gives the example of a very simple machine: a mousetrap. This would not work without a platform, holding bar, spring, hammer, and catch, all in the right place. If you remove just one part, it won’t work at all—you cannot reduce its complexity without destroying its function entirely.The thrust of Behe’s book is that many structures in living organisms show irreducible complexity, far in excess of a mousetrap or indeed any man-made machine. For example, he shows that even the simplest form of vision in any living creature requires a dazzling array of chemicals in the right places, as well as a system to transmit and process the information. The blood-clotting mechanism also has many different chemicals working together, so we won’t bleed to death from minor cuts, nor yet suffer from clotting of the entire system. A simple cell? Many people don’t realize that even the simplest cell is fantastically complex—even the simplest self-reproducing organism contains encyclopedic quantities of complex, specific information. Mycoplasma genitalium has the smallest known genome of any free-living organism, containing 482 genes comprising 580,000 base pairs11 (compare 3 billion base pairs in humans, as Teaching about Evolution states on page 42). Of course, these genes are functional only in the presence of pre-existing translational and replicating machinery, a cell membrane, etc. But Mycoplasma can only survive by parasitizing other more complex organisms, which provide many of the nutrients it cannot manufacture for itself. So evolutionists must postulate a more complex first living organism with even more genes.More recently, Eugene Koonin and others tried to calculate the bare minimum requirement for a living cell, and came up with a result of 256 genes. But they were doubtful whether such a hypothetical bug could survive, because such an organism could barely repair DNA damage, could no longer fine-tune the ability of its remaining genes, would lack the ability to digest complex compounds, and would need a comprehensive supply of organic nutrients in its environment.12Molecular biologist Michael Denton, writing as a non-creationist skeptic of Darwinian evolution, explains what is involved:Perhaps in no other area of modern biology is the challenge posed by the extreme complexity and ingenuity of biological adaptations more apparent than in the fascinating new molecular world of the cell … . To grasp the reality of life as it has been revealed by molecular biology, we must magnify a cell a thousand million times until it is twenty kilometers in diameter and resembles a giant airship large enough to cover a great city like London or New York. What we would then see would be an object of unparalleled complexity and adaptive design. On the surface of the cell we would see millions of openings, like the port holes of a vast space ship, opening and closing to allow a continual stream of materials to flow in and out. If we were to enter one of these openings we would find ourselves in a world of supreme technology and bewildering complexity.Is it really credible that random processes could have constructed a reality, the smallest element of which—a functional protein or gene—is complex beyond our own creative capacities, a reality which is the very antithesis of chance, which excels in every sense anything produced by the intelligence of man? Alongside the level of ingenuity and complexity exhibited by the molecular machinery of life, even our most advanced artifacts appear clumsy … .It would be an illusion to think that what we are aware of at present is any more than a fraction of the full extent of biological design. In practically every field of fundamental biological research ever-increasing levels of design and complexity are being revealed at an ever-accelerating rate.13For natural selection (differential reproduction) to start, there must be at least one self-reproducing entity. But as shown above, the production of even the simplest cell is beyond the reach of undirected chemical reactions. So it’s not surprising that Teaching about Evolutionomits any discussion of the origin of life, as can easily be seen from the index. However, this is part of the ‘General Theory of Evolution’ (molecules to man), 14 and is often called ‘chemical evolution.’ Indeed, the origin of the first self-reproducing system is recognized by many scientists as an unsolved problem for evolution, and thus evidence for a designer.15 The chemical hurdles that non-living matter must overcome to form life are insurmountable, as shown by many creationist writers. 16 Can mutations generate information? Even if we grant evolutionists the first cell, the problem of increasing the total information content remains. To go from the first cell to a human means finding a way to generate enormous amounts of information—billions of base pairs (‘letters’) worth. This includes the recipes to build eyes, nerves, skin, bones, muscles, blood, etc. In the section on variation and evolution, we showed that evolution relies on copying errors and natural selection to generate the required new information.However, the examples of ‘contemporary evolution’ presented byTeaching about Evolution are all losses of information.This is confirmed by the biophysicist Dr Lee Spetner, who taught information and communication theory at Johns Hopkins University:In this chapter I’ll bring several examples of evolution, [i.e., instances alleged to be examples of evolution] particularly mutations, and show that information is not increased. … But in all the reading I’ve done in the lifesciences literature, I’ve never found a mutation that added information.All point mutations that have been studied on the molecular level turn out to reduce the genetic information and not to increase it.The NDT [neo-Darwinian theory] is supposed to explain how the information of life has been built up by evolution. The essential biological difference between a human and a bacterium is in the information they contain. All other biological differences follow from that. The human genome has much more information than does the bacterial genome. Information cannot be built up by mutations that lose it. A business can’t make money by losing it a little at a time.17This is not to say that no mutation is ‘beneficial,’ that is, it helps the organism to survive. But as pointed out in chapter 2, even increased antibiotic and pesticide resistance is usually the result of loss of information, or sometimes a transfer of information—never the result of newinformation. Other beneficial mutations include wingless beetles on small desert islands—if beetles lose their wings and so can’t fly, the wind is less likely to blow them out to sea.18 Obviously, this has nothing to do with the origins of flight in the first place, which is what evolution is supposed to be about. Insect flight requires complicated movements to generate the patterns of vortices needed for lift—it took a sophisticated robot to simulate the motion.19 Would any evidence convince evolutionists? The famous British evolutionist (and Communist) J.B.S. Haldane claimed in 1949 that evolution could never produce ‘various mechanisms, such as the wheel and magnet, which would be useless till fairly perfect.’20 Therefore such machines in organisms would, in his opinion, prove evolution false. That is, evolution meets one criterion Teaching about Evolution claims is necessary for science, that there are tests that could conceivably prove it was wrong (the ‘falsifiability criterion’ of the eminent philosopher of science, Karl Popper).Recent discoveries have shown that there are indeed ‘wheels’ in living organisms. This includes the rotary motor that drives the flagellum of a bacterium, and the vital enzyme that makes ATP, the ‘energy currency’ of life.21 These molecular motors have indeed fulfilled one of Haldane’s criteria. Also,

turtles,22 monarch butterflies,23 and bacteria24 that use magnetic sensors for navigation seem to fulfil Haldane’s other criterion.I wonder whether Haldane would have had a change of heart if he had been alive to see these discoveries. Most evolutionists rule out intelligent design a priori, so the evidence, overwhelming as it is, would probably have no effect. Other marvels of design The genetic information in the DNA cannot be translated except with many different enzymes, which are themselves encoded. So the code cannot be translated except via products of translation, a vicious circle that ties evolutionary origin-oflife theories in knots.These include double-sieve enzymes to make sure the right amino acid is linked to the right tRNA. One sieve rejects amino acids too large, while the other rejects those too small. 25The genetic code that’s almost universal to life on earth is about the best possible, for protecting against errors.26 [See also DNA: marvellous messages or mostly mess?] The genetic code also has vital editing machinery that is itself encoded in the DNA. This shows that the system was fully functional from the beginning—another vicious circle for evolutionists. [See also Self-replicating enzymes?]Yet another vicious circle, and there are many more, is that the enzymes that make the amino acid histidine themselves contain histidine.The complex compound eyes of some types of trilobites (extinct and supposedly ‘primitive’ invertebrates) were amazingly designed. They comprised tubes that each pointed to a different spot on the horizon, and had special lenses that focused light from any distance. Some trilobites had a sophisticated lens design comprising a layer of calcite on top of a layer of chitin—materials with precisely the right refractive indices—and a wavy boundary between them of a precise mathematical shape.27 The Designer of these eyes is a Master Physicist, who applied what we now know as the physical laws of Fermat’s principle of least time, Snell’s law of refraction, Abbé’s sine law and birefringent optics.Lobster eyes are unique in being modeled on a perfect square with precise geometrical relationships of the units. NASA X-ray telescopes copied this design.28The amazing sonar system of dolphins was discussed in chapter 5. Many bats also have an exquisitely designed sonar system. The echolocation of fishing bats is able to detect a minnow’s fin, as fine as a human hair, extending only 2 mm above the water surface. This fine detection is possible because bats can distinguish ultra-sound echoes very close together. Man-made sonar can distinguish echoes 12 millionths of a second apart, although with ‘a lot of work this can be cut to 6 millionths to 8 millionths of a second.’ But bats ‘relatively easily’ distinguish ultra-sound echoes only 2 to 3 millionths of a second apart according to researcher James Simmons of Brown University. This means they can distinguish objects ‘just 3/10ths of a millimeter apart—about the width of a pen line on paper.’ 29The neural system of a leech uses trigonometric calculations to work out which muscles to move and by how much. 30From my own specialist field of vibrational spectroscopy: there is good evidence that our chemical-detecting sense (smell) works on the same quantum mechanical principles.31 Why should design be ‘unscientific’? The real reason for rejecting the creation explanation is the commitment to naturalism. As shown in chapter 1, evolutionists have turned science into a materialistic ‘game,’ and creation/design is excluded by their self-serving rules.32 Therefore, although Teaching about Evolutiondismisses creation science as ‘unscientific,’ this appears to be derived more from the rules of the game than from any evidence.Even some anti-creationist philosophers of science have strongly criticized the evolutionary scientific and legal establishment over these word games. They rightly point out that we should be more interested in whether creation is true or false than whether it meets some self-serving criteria for ‘science.’33Many of these word games are self-contradictory, so one must wonder whether their main purpose is to exclude creation at any cost, rather than for logical reasons. For example, Teaching about Evolution claims on page 55:The ideas of ‘creation science’ derive from the conviction that a intelligent designer created the universe—including humans and other living things—all at once in the relatively recent past. However, scientists from many fields have examined these ideas and have found them to be scientifically inable. For example, evidence for a very young earth is incompatible with many different methods of establishing the age of rocks. Furthermore, because the basic proposals of creation science are not subject to test and verification, these ideas do not meet the criteria for science.The Teaching about Evolution definition of creation science is almost right, although creationists following creationist assumptions would claim that different things were created on different days. However, Teaching about Evolution claims that the ideas of creation science have been examined and found unable, then they claim that the ‘basic proposals of creation science are not subject to test and verification.’ So how could its proposals have been examined (tested!) if they are not subject to test?Of course, it is not true that science has proved the earth to be billions of years old—see chapter 8.The historian and philosopher of science Stephen Meyer concluded:We have not yet encountered any good in principle reason to exclude design from science. Design seems just as scientific (or unscientific) as its evolutionary competitors … .An openness to empirical arguments for design is therefore a necessary condition of a fully rational historical biology. A rational historical biology must not only address the question, ‘Which materialistic or naturalistic evolutionary scenario provides the most adequate explanation of biological complexity?’ but also the question ‘Does a strictly materialistic evolutionary scenario or one involving intelligent agency or some other theory best explain the origin of biological complexity, given all relevant evidence?’ To insist otherwise is to insist that materialism holds a metaphysically privileged position. Since there seems no reason to concede that assumption, I see no reason to concede that origins theories must be strictly naturalistic.34 Scientific laws of information and their implications—part 1 by Werner Gitt The grand theory of atheistic evolution posits that matter and energy alone have given rise to all things, including biological systems. To hold true, this theory must attribute the existence of all information ultimately to the interaction of matter and energy without reference to an intelligent or conscious source. All biological systems depend upon information storage, transfer and interpretation for their operation. Thus the primary phenomenon that the theory of evolution must for is the origin of biological information. In this article it is argued that fundamental laws of information can be deduced from observations of the nature of information. These fundamental laws exclude the possibility that information, including biological information, can arise purely from matter and energy without reference to an intelligent agent. As such, these laws show that the grand theory of evolution cannot in principle for the most fundamental biological phenomenon. In addition, the laws here presented give positive ground for attributing the origin of biological information to the conscious, wilful action of a designer. The far-reaching implications of these laws are discussed. Figure 1. The five levels of information. To fully characterise the concept of information, five aspects must be considered—statistics, syntax, semantics,

pragmatics and apobetics. Information is represented (that is, formulated, transmitted, stored) as a language. From a stipulated alphabet, the individual symbols are assembled into words (code). From these words (each word having been assigned a meaning), sentences are formed according to the firmly defined rules of grammar (syntax). These sentences are the bearers of semantic information. Furthermore, the action intended/carried out (pragmatics) and the desired/achieved goal (apobetics) belong of necessity to the concept of information. All our observations confirm that each of the five levels is always pertinent for the sender as well as the receiver.In the communication age information has become fundamental to everyday life. However, there is no binding definition of information that is universally agreed upon by practitioners of engineering, information science, biology, linguistics or philosophy.There have been repeated attempts to grapple with the concept of information. The most sweeping formulation was recently put forward by a philosopher: “The entire universe is information.”1 Here we will set out in a new direction, by seeking a definition of information with which it is possible to formulate laws of nature.Because information itself is non-material, 2 this would be the first time that a law of nature (scientific law) has been formulated for such a mental entity. We will first establish a universal definition for information; then state the laws themselves; and, finally, we will draw eight comprehensive conclusions. What is a law of nature? If statements about the observable world can be consistently and repeatedly confirmed to be universally true, we refer to them as laws of nature. Laws of nature describe events, phenomena and occurrences that consistently and repeatedly take place. They are thus universally valid laws. They can be formulated for material entities in physics and chemistry (e.g. energy, momentum, electrical current, chemical reactions). Due to their explanatory power, laws of nature enjoy the highest level of confidence in science. The following attributes exhibited by laws of nature are especially significant:Laws of nature know no exceptions. This sentence is perhaps the most important one for our purposes. If dealing with a real (not merely supposed) natural law, then it cannot be circumvented or brought down. A law of nature is thus universally valid, and unchanging. Its hallmark is its immutability. A law of nature can, in principle, be refuted—a single contrary example would end its status as a natural law. Laws of nature are unchanging in time. Laws of nature can tell us whether a process being contemplated is even possible or not. This is a particularly important application of the laws of nature. Laws of nature exist prior to, and independent of, their discovery and formulation. They can be identified through research and then precisely formulated. Hypotheses, theories or models are fundamentally different. They are invented by people, not merely formulated by them. In the case of the laws of nature, for physical entities it is often, but not always, 3 possible to find a mathematical formulation in addition to a verbal one. In the case of the laws for non-material entities presented here, the current state of knowledge permits only verbal formulations. Nevertheless, these can be expressed just as strongly, and are just as binding, as all others. Laws of nature can always be successfully applied to unknown situations. Only thus was the journey to the moon, for example, possible. Due to their explanatory power, laws of nature enjoy the highest level of confidence in science. When we talk of the laws of nature, we usually mean the laws of physics (e.g. the second law of thermodynamics, the law of gravity, the law of magnetism, the law of nuclear interaction) and the laws of chemistry (e.g. Le Chatelier’s Principle of least restraint). All these laws are related exclusively to matter. But to claim that our world can be described solely in of material quantities is failing to acknowledge the extent of one’s perception. Unfortunately many scientists follow this philosophy of materialism (e.g. Dawkins, Küppers, Eigen 4), remaining within this self-imposed boundary of insight. But our world also includes non-material concepts such as information, will and consciousness. This article (described more comprehensively in ref. 1) attempts, for the first time, also to formulate laws of nature for non-material quantities. The same scientific procedures used for identifying laws of nature are also used for identifying laws governing non-material entities. Additionally, these laws exhibit the same attributes as listed above for the laws of nature. Therefore they fulfil the same conditions as the laws of nature for material quantities, and possessing, consequently, a similar power of inference. Alex Williams describes this concept as a “revolutionary new understanding of information”. 5 In an in-depth personal discussion with Dr Bob Compton (Idaho, U.S.A.), he proposed to name the laws of nature on information the “Scientific Laws of Information (SLI)” in order to distinguish them from the physical laws. This positive suggestion is to be taken seriously since it takes of the shortcomings of the materialistic view. I have therefore decided to use the term here. What is information? Information is not a property of matter! The American mathematician Norbert Wiener made the oft-cited statement: “Information is information, neither matter nor energy.”6 With this he acknowledged a very significant thing: information is not a material entity. Let me clarify this important property of information with an example. Imagine a sandy stretch of beach. With my finger I write a number of sentences in the sand. The content of the information can be understood. Now I erase the information by smoothing out the sand. Then I write other sentence in the sand. In doing so I am using the same matter as before to display this information. Despite this erasing and rewriting, displaying and destroying varying amounts of information, the mass of the sand did not alter at any time. The information itself is thus massless. A similar thought experiment involving the hard drive of a computer quickly leads to the same conclusion.Norbert Wiener has told us what information is not; the question of what information really is, then, will be answered in this article.Because information is a non-material entity, its origin is likewise not explicable by material processes. What causes information to come into existence at all—what is the initiating factor? What causes us to write a letter, a postcard, a note of congratulations, a diary entry or a file note? The most important prerequisite for the construction of information is our own will, or that of the person who assigned the task to us. Information always depends upon the will of a sender who issues the information. Information is not constant; it can be deliberately increased and can be distorted or destroyed (e.g. through disturbances in transmission). In summary: Information arises only through will (intention and purpose). A definition of universal information Technical used in science are sometimes also used in everyday language (e.g. energy, information). However, if one wants to formulate laws of nature, then the entities to which they apply must be unambiguous and clear cut. So one always needs to define such entities very precisely. In scientific usage, the meaning of a term is in most cases considerably more narrowly stated than its range of meaning in everyday usage (i.e. it is a subset of). In this way, a definition does more than just assign a meaning; it also acts to contain or restrict that meaning. A good “natural-law” definition is one that enables us to exclude all those domains (realms) in which laws of nature are not applicable. The more clearly one can establish the domain of definition, the more precise (and furthermore certain) the conclusions which can be drawn.Example—energy: In everyday language we use the word energy in a wide range of meanings and situations. If someone does something with great diligence, persistence and focused intensity, we might say he “applies his whole energy” to the task. But the same word is used in physics to refer to a natural law, the law of energy. In such a context, it becomes necessary to substantially

narrow the range of meaning. Thus physics defines energy as the capacity to do work, which is force x distance.7 An additional degree of precision is added by specifying that the force must be calculated in the direction of the distance. With this, one has come to an unambiguous definition and has simultaneously left behind all other meanings in common usage. Information: namely an encoded, symbolically represented message conveying expected action and intended purpose. The same must now be done for the concept of information. We have to say, very clearly, what information is in our naturallaw sense. We need criteria in order to be able unequivocally to determine if an unknown system belongs within the domain of our definition or not. The following definition permits a secure allocation in all cases:Information is always present when all the following five hierarchical levels are observed in a system: statistics, syntax, semantics, pragmatics and apobetics.If this applies to a system in question, then we can be certain that the system falls within the domain of our definition of information. It therefore follows that for this system all four laws of nature about information will apply. The five levels of universal information (figure 1) Statistics. In considering a book, a computer program or the genome of a human being we can ask the following questions: How many letters, numbers and words does the entire text consist of? How many individual letters of the alphabet (e.g. a, b, c … z for the Roman alphabet, or G, C, A and T for the DNA alphabet) are utilized? What is the frequency of occurrence of certain letters and words? To answer such questions it is irrelevant whether the text contains anything meaningful, is pure nonsense, or just randomly ordered sequences of symbols or words. Such investigations do not concern themselves with the content; they involve purely statistical aspects. All of this belongs to the first and thus bottom level of information: the level of statistics. The statistics level can be seen as the bridge between the material and the non-material world. (This is the level on which Claude E. Shannon developed his well-known mathematical concept of information.8) Figure 2. The first five verses of Genesis 1 written in a special code. Syntax. If we look at a text in any particular language, we see that only certain combinations of letters form permissible words of that particular language. This is determined by a pre-existing, wilful, convention. All other conceivable combinations do not belong to that language’s vocabulary. Syntax encomes all of the structural characteristics of the way information is represented. This second level involves only the symbol system itself (the code) and the rules by which symbols and chains of symbols are combined (grammar, vocabulary). This is independent of any particular interpretation of the code.Semantics. Sequences of symbols and syntactic rules form the necessary pre-conditions for the representation of information. But the critical issue concerning information transmission is not the particular code chosen, nor the size, number or form of the letters—nor even the method of transmission. It is, rather, the semantics (Greek: semantikós = significant meaning), i.e. the message it contains—the proposition, the sense, the meaning.Information itself is never the actual object or act, neither is it a relationship (event or idea), but encoded symbols merely represent that which is discussed. Symbols of extremely different nature play a substitutionary role with regard to the reality or a system of thought. Information is always an abstract representation of something quite different. For example, the symbols in today’s newspaper represent an event that happened yesterday; this event is not contemporaneous; moreover, it might have happened in another country and is not at all present where and when the information is transmitted. The genetic words in a DNA molecule represent the specific amino acids that will be used at a later stage for synthesis of protein molecules. The symbols of figure 2 represent what happened on day 1 .Pragmatics. Information invites action. In this context it is irrelevant whether the receiver of information acts in the manner desired by the sender of the information, or reacts in the opposite way, or doesn’t do anything at all. Every transmission of information is nevertheless associated with the expectation, from the side of the sender, of generating a particular result or effect on the receiver. Even the shortest advertising slogan for a washing powder is intended to result in the receiver carrying out the action of purchasing this particular brand in preference to others. We have thus reached a completely new level at which information operates, which we call pragmatics (Greek pragma = action, doing). The sender is also involved in action to further his desired outcome (more sales/profit), e.g. deg the best message (semantics) and transmitting it as widely as possible in newspapers, TV, etc.Apobetics. We have already recognized that for any given information the sender is pursuing a goal. We have now reached the last and highest level at which information operates: namely, apobetics (the aspect of information concerned with the goal, the result itself). In linguistic analogy to the previous descriptions the author has here introduced the term “apobetics” (from the Greek apobeinon = result, consequence). The outcome on the receiver’s side is predicated upon the goal demanded/desired by the sender—that is, the plan or conception. The apobetics aspect of information is the most important of the five levels because it concerns the question of the outcome intended by the sender.In his outstanding articles “Inheritance of biological information” 5, Alex Williams has explained this five-level concept by applying it to biological information. Using the last four of the five levels, we developed an unambiguous definition of information: namely an encoded, symbolically represented message conveying expected action and intended purpose. We term any entity meeting the requirements of this definition as “universal information” (UI). Scientific laws of information (SLI) In the following we will describe the four most important laws of nature about information.9 SLI-110

A material entity cannot generate a non-material entity In our common experience we observe that an apple tree bears apples, a pear tree yields pears, and a thistle brings forth thistle seeds. Similarly, horses give birth to foals, cows to calves and women to human babies. Likewise, we can observe that something which is itself solely material never creates anything non-material. The universally observable finding of SLI– 1 can now be couched in somewhat more specialized form by arriving at SLI–2. SLI-2 Universal information is a non-material fundamental entity The materialistic worldview has widely infiltrated the natural sciences such that it has become the ruling paradigm. However, this is an unjustified dogma. The reality in which we live is divisible into two fundamentally distinguishable realms: namely, the material and the non-material. Matter involves mass, which is weighable in a gravitational field. In contrast, all nonmaterial entities (e.g. information, consciousness, intelligence and will) are massless and thus have zero weight. Information is always based on an idea; it is thus also massless and does not arise from physical or chemical processes. Information is also not correlated with matter in the same way as energy, momentum or electricity is. However, information is stored, transmitted and expressed through matter and energy. The distinction between material and non-material entities Necessary Condition (NC): That a non-material entity must be massless (NC: m = 0) is indeed a necessary condition, but it is not sufficient to assign it as non-material. To be precise, the “sufficient condition” must also be met.Sufficient Condition (SC): An observed entity can be judged to be “non-material” if it has no physical or chemical correlation with matter. This is always the case if the following four conditions are met: SC1: The entity has no physical or chemical interaction with matter. SC2: The entity is not a property of matter. SC3: The entity does not originate in pure matter. SC4: The entity is not correlated with matter. Photons are massless particles and they are a good contrast to the SC because they do interact with matter and can originate from and be correlated with matter.Information always depends on an idea; it is massless and does not originate from a physical or chemical process.11 The necessary condition (NC: m = 0) and also all four sufficient conditions (SC1 to SC4) are also fulfilled, and therefore universal information is a non-material entity. The fact that it requires matter for storage and transportation does not turn it into matter. Thus we can state:Universal Information is a non-material entity because it fulfils both necessary conditions: it is massless; and, it is neither physically nor chemically correlated with matter.Occasionally it is claimed that it is a physical (and thereby a material) entity. But as presented under SLI-1, information is clearly a non-material entity.There is another very powerful justification for stating that information cannot be a physical quantity. The SI System of units has seven base units: mass, length, electric current, temperature, amount of substance, luminous intensity and time. All physical quantities can be expressed in of one of these base units (e.g. area = length x length) or by a combination (by multiplication or division) of several base units (e.g. momentum = mass x length / time). This is not possible in the case of information and therefore information is not a physical magnitude! SLI-3 Universal information cannot be created by statistical processes The grand theory of evolution would gain some empirical if it could be demonstrated, in a real experiment, that information could arise from matter left to itself without the addition of intelligence. Despite the most intensive worldwide efforts this has never been observed. To date, evolutionary theoreticians have only been able to offer computer simulations that depend upon principles of design and the operation of pre-determined information. These simulations do not correspond to reality because the theoreticians smuggle their own information into the simulations. SLI-4 Universal information can only be produced by an intelligent sender The question here is: What is an intelligent sender? Several attributes are required to define an intelligent sender. Definition D1: An intelligent sender as mentioned in SLI-4 is conscious has a will of its own12 is creative thinks autonomously acts purposefully SLI-4 is a very general law from which several more specific laws may be derived. We know the Maxwell equations from physics. They describe, in a brilliant generalization, the relationship between changing electric and magnetic fields. But for most practical applications these equations are far too complex and cumbersome and for this reason we use more specific formulations, such as Ohm’s Law, Coulomb’s Law or the induction law. Similarly, in the following section we will present four more specific formulations of SLI-4 (SLI-4a to 4d) that are easier to use for our practical conclusions. SLI-4a Every code is based upon a mutual agreement between sender and receiverThe essential characteristic of a code symbol (character) is that it was at one point in time freely defined. The set of symbols so created represents all allowed symbols (by definition). They are structured in such a way as to fulfil, as well as possible, their designated purpose (e.g. a script for the blind such as Braille must be sufficiently palpable; musical symbols must be able to describe the duration and pitch of the notes; chemical symbols must be able to designate all the elements). An observed signal may give the impression that it is composed of symbols, but if it can be shown that the signal is a physical or chemical property of the system then the fundamental “free mutual agreement” attribute is missing and the signal is not a symbol according to our definition.13 SLI-4b There is no new universal information without an intelligent sender The process of the formation of new information (as opposed to simply copied information) always depends upon intelligence and free will. A sequence of characters are selected from an available, freely defined set of symbols such that the resulting string of characters represents (all five levels of) information. Since this cannot be achieved by a random process, there must always be an intelligent sender. One important aspect of this is the application of will, so that we may also say: Information cannot be created without a will. SLI-4c Every information transmission chain can be traced back to an intelligent sender 14It is useful to distinguish here between the original and the intermediate sender. We mean by the original sender the author of the information, and he must always be an individual equipped with intelligence and a will. If, after the original sender, there follows a machine-aided

chain consisting of several links, the last link in the chain might be mistaken for the originator of the message. Since this link is onlyapparently the sender, we call this the intermediate sender (but it is not the original one!).The original sender is often not visible: in many cases the author of the information is not or no longer visible. It is not in contradiction to the requirement of observability when the author of historical documents is no longer visible—in such a case he was, however, observable once upon a time. Sometimes the information received has been carried via several intermediate links. Here, too, there must have been an intelligent author at the beginning of the chain. Take the example of a car radio: we receive audible information from the loud speakers, but these are not the actual source; neither is the transmission tower that also belongs to the transmission chain. An author (an intelligent originator) who created the information is at the head of the chain. In general we can say that there is an intelligent author at the beginning of every information transmission chain.The actual (intermediate) sender may not be an individual: we could gain the impression that, in systems with machine-aided intermediate links, that the last observed member is the sender:The of a car auto-wash can only trace the wash program back to the computer—but the computer is only the intermediatesender; the original sender (the programmer) is nowhere to be seen.The internet-surfer sees all kinds of information on his screen, but his home computer is not the original sender, but rather someone who is perhaps at other end of the world has thought out the information and put it on the internet.It is by no means different in the case of the DNA molecule. The genetic information is read off a material substrate, but this substrate is not the original sender; rather, it is only the intermediate sender.It may seem obvious that the last member of the chain is the sender because it seems to be the only discernible possibility. But it is never the case in a system with machine-aided intermediate links that the last member is the original sender (= author of the information)—it is an intermediate sender. This intermediate sender may not be an individual, but rather only part of a machine that was created by an intelligence. Individuals can on information they have received and in so doing act as intermediate senders. However, they are in actuality only intermediate senders if they do not modify the information. If an intermediate changes the information, he may then be considered the original sender of a new piece of information.Even in the special case where the information was not transmitted via intermediaries, the author may remain invisible. We find in Egyptian tombs or on the obelisks numerous hieroglyphic texts, but the authors are nowhere to be found. No one would conclude that there had been no author. SLI-4d Attributing meaning to a set of symbols is an intellectual process requiring intelligenceWe have now defined the five levels (statistics, syntax, semantics, pragmatics and apobetics) at which universal information operates. Using SLI-4d we can make the following general observation: these five aspects are relevant for both the sender and the receiver.Origin of information: SLI-4d describes our experience of how any information comes into being. Firstly, we draw on a set of symbols (characters) that have been defined according to SLI-4a. Then we use one symbol after another from the set to create units of information (e.g. words, sentences). This is not a random process, but requires the application of intelligence. The sender has knowledge of the language he is using and he knows which symbols he needs in order to create his intended meaning. Furthermore, the connection between any given symbol and meaning is not originally determined by laws of physics or energy. For example, there is nothing physically about the three letters “d, o, g” that necessarily originally caused it to be associated with man’s much loved pet. The fact that there are other words for “dog” in other languages demonstrates that the association between a word and its meaning is mental rather than physical/energetic. In other words, the original generation of information is an intellectual process.Finally, we make three remarks that have fundamental significance:Remark R1: Technical and biological machines can store, transmit, decode and translate information without understanding the meaning and purpose.Remark R2: Information is the non-material basis for all technological systems and for all biological systems.There are numerous systems that do not possess their own intelligence but nevertheless can transfer or store information or steer processes. Some such systems are inanimate (e.g. networked computers, process controls in a chemical factory, automatic production lines, car auto-wash, robots); others are animate (e.g. cell processes controlled by information, bee waggle dance).It is important to recognize that biological information differs from humanly generated information in three essential ways:In living systems we find the highest known information density. 15The programs in living systems obviously exhibit an extremely high degree of sophistication. No scientist can explain the program that produces an insect that looks like a withered leaf. No biologist understands the secret of an orchid blossom that is formed and coloured like a female wasp … and smells like one, too. We are able to think, feel, desire, believe and hope. We can handle a complex thing such as language, but we are aeons away from understanding the information control process that develop the brain in the embryo. Biological information displays a sophistication that is unparalleled in human information.No matter how ingenious human inventions and programs may be, it is always possible for others to understand the underlying ideas. For example, during World War II, the English succeeded, after considerable effort, in understanding completely the German “Enigma” coding machine which had fallen into their hands. From then on it was possible to decode German radio messages. However, most of the ingenious ideas and programs we find in living organisms are hardly, or at best only partly, understood by us at all. To make an exact replica is impossible.Remark R3: The storage and transmission of information requires a material medium.Imagine a piece of information written on a blackboard. Now wipe the board with a duster. The information has vanished, even though all the particles of chalk are still present. The chalk in this case was the necessary material medium but the information was represented by theparticular arrangement of the particles. And this arrangement did not come about by chance—it had a mental origin. The same information could have been stored/transmitted in Indian smoke signals through the arrangement of puffs of smoke, or in a computer’s memory through magnetized domains. One could even line up an array of massive rocks into a Morse code pattern. So, clearly, the amount or type of matter upon which the information resides is not the issue. Even though information requires a material substrate for storage/transmission, information is not a property of matter. In the same way, the information in living things resides on the DNA molecule. But it is no more an inherent property of the physics and chemistry of DNA than the blackboard’s message was an intrinsic property of chalk. Conclusion All these four laws of nature about information have arisen from observations in the real world. None of them has been falsified by way of an observable process or experiment.The grand theory of atheistic evolution must attribute the origin of all information ultimately to the interaction of matter and energy, without reference to an intelligent or conscious source. A central claim of atheistic evolution must therefore be that the macro-evolutionary processes that generate biological information are fundamentally different from all other known information-generating processes. However, the natural laws described here apply equally in animate and inanimate systems and demonstrate this claim to be both false and absurd.

Implications of the scientific laws of information—part 2

by Werner Gitt In the past there were so-called perpetual motion experts. These were inventors and tinkerers who wanted to build a machine that would run continuously without the supply of energy. The discovery of the law of conservation of energy (a law of nature) brought all efforts to solve this challenge to a halt because aperpetuum mobile is an impossible machine. Such a machine will never be built, as the laws of nature make it impossible. Evolution could only occur if the possibility existed that information could arise by itself out of matter. Those who believe that evolution is a plausible concept believe in a “perpetuum mobile of information”. If there were laws of nature that preclude a perpetuum mobile of this kind, the theory of evolution would be disproved. Such laws of nature actually exist, and I have presented these at many universities throughout of the world. The concept of this theory of information is explained in the first article (part I) in this issue. There I enumerated four scientific laws of information arising from observations in the real world. None of them has been falsified by way of an observable process or experiment. In this article, eight far-reaching conclusions will be drawn. Eight comprehensive conclusions Having firmly established the domain of our definition of information in part 1, and familiarized ourselves with the laws of nature about information derived from experience—known as scientific laws of information (SLI; see figure 1)—we can now zero in on effectively applying them. Hereafter the term “information” will be used when referring to universal information. There are eight very far-reaching conclusions that answer fundamental questions. All scientific thought and practice reaches a limit beyond which science is inherently unable to take us. This situation is no exception. But some of our questions involve matters beyond this limiting boundary and so to successfully transcend it we need a higher source of knowledge. We will proceed in the following sequential manner: Set out the (briefly formulated) conclusion itself. SLI-1: A material entity cannot generate a non-material entity. SLI-2: Universal information is a non-material fundamental entity. SLI-3: Universal information cannot be created by statistical processes. SLI-4: Universal information can only be produced by an intelligent sender. 4a: Every code is based upon a mutual agreement between sender and receiver. 4b: There is no new universal information without an intelligent sender. 4c: Every information transmission chain can be traced back to an intelligent sender. 4d: Attributing meaning to a set of symbols is an intellectual process requiring intelligence. Figure 1. The four most important laws of nature about information known as scientific laws of information (SLI) 1. A Designer exists; refutation of atheism Because it can be established that all forms of life contain a code (DNA, RNA), as well as all of the other levels of information, we are within the domain of our definition of information. We can therefore conclude that: • There must be an intelligent sender! [Applying SLI-4] Basis for this conclusion Because there has never been a process in the material world, demonstrable through observation or experiment, in which information has arisen by without prior intelligence, then that also must be valid for all the information present in living things. Furthermore, what we do observe about information—namely that it intrinsically depends upon an original act of intelligence to construct it, as defined by SLI-4d—excludes the possibility of information coming from non-intelligence. Thus SLI-4b requires here, too, an intelligent author who “wrote” the programs. Conclusion 1 is therefore also a refutation of atheism. The top of figure 2 outlines the realm that is, in principle, inaccessible to natural science; namely: Who is the message sender? To answer that the sender cannot exist because the methods of human science (scientific boundary) cannot perceive him, both misapplies science and is untenable according to the laws of information. The requirement that there must be a personal sender exercising his own free will cannot be relinquished. 2. There is only one designer , who is all knowing and eternal The information encoded in DNA far exceeds all our current technologies. Hence, no human being could possibly qualify as the sender, who must therefore be sought outside of our visible world. We can conclude that: There is only one sender, who must not only be exceptionally intelligent but must possess an infinitely large amount of information and intelligence, i.e. he must be omniscient all knowing), and beyond that must also be eternal. [Applying SLI-1, SLI-2, SLI-4b] Basis for this conclusion Figure 2. The origin of life. If one considers living things as unknown systems that can be analysed with the help of natural laws, then one finds all five levels of the definition of information: statistics (here left off for simplicity), syntax, semantics, pragmatics and apobetics. In accordance with the natural laws of information, the origin of any information requires a sender equipped with intelligence and will. The fact that the sender in this case is not observable is not in contradiction to these laws. In a huge library with thousands of volumes, the authors are also not visible; but no one would maintain that there was no author for all this information. According to SLI-4b, at the beginning of every chain of information there is an intelligent sender. When one applies this to biological information, then here, too, there must an intelligent author of the information. In DNA molecules we find the

highest density of information known to us.1 Because of SLI-1, no conceivable processes in the material realm qualify as the source of this information. Humans, who can, of course, generate information (e.g. letters, books), are also obviously excluded as the source of this biological information. This leaves only a sender who operated outside of our normal physical world. After a lecture at a university about biological information and the necessary sender, a young lady student said to me: “I can tell where you were heading when you spoke of an intelligent sender—you meant designer . I can accept that as far as it goes; without a sender, that is, without a designer, it wouldn’t work. But who informed him so that He could program the DNA molecules?” Two explanations spring to mind: Explanation a): Imagine that this designer was considerably more intelligent than we are, but nevertheless limited. Let’s assume furthermore that he had so much intelligence (thus information) at his disposal that he was able to program all biological systems. The obvious question then is: who gave him this information and who taught him? This would require a higher information-giver I1, that is, a “super-designer”, who knew more than the designer. If I1 knew more than the desiner, but was also limited, then he would in turn require an information-giver I 2—i.e. a “super-super-designer”. So this line of reasoning leads to an extension of this series—I3, I4 … to Iinfinity. One would require an infinite number of designers, such that in this long chain every n 1 th deity always knew more than the n th. Only once one reached the I infinity super-super-super … . designer , could we say such a designer would be unlimited and all knowing. However, traversing an infinite is impossible (whether it is a temporal, spatial or, as in this example, an ontological infinity) and so this explanation is unsatisfactory. Explanation b): It is more simple and satisfying to assume only a single sender—a prime mover, an ultimate designer. But then one would need to also assume that such a designer is infinitely intelligent and in command of an infinite amount of information. So he must be all knowing(omniscient).Which of the explanations a) and b) is correct? Both are logically equivalent. Thus we must make a decision that is not derived from the SLI based on the following considerations. In reality, there is no such thing as an actual infinite number of anything. The number of atoms in the universe is unimaginably vast, but nevertheless finite, and thus in principle able to be counted. The total number of people, ants, or grains of wheat that have ever existed is also vast, but finite. Although infinity is a useful mathematical abstraction, the fact is that in reality there can be no such thing as an infinite number of anything that can be reached by counting for long enough. Thus explanation a) fails the test of plausibility, leaving only explanation b). That means there is only one sender. But this one sender must therefore be all knowing. This conclusion is a consequence of consistently applying the laws of nature about information. What does it mean that the designer (the author of biological information, the designer), is infinite? It means that for Him there is no question that He cannot answer, and He knows all things. Not merely about present and the past; even the future is not hidden from Him. But if He knows all things—even beyond all restrictions of time—then He Himself must be eternal. 3. The designer is immensely powerful Because the sender: • ingeniously encoded the information into the DNA molecules, • must have designed the complex bio-machinery that decodes the information and carries out all the processes of biosynthesis, and • created all the details of the original construction and reproductive capacities of all living things, We can conclude that: • The sender accomplished his purpose and, therefore, he must be powerful. Basis for this conclusion In conclusion 2, we determined on the basis of laws of nature that the sender must be all knowing and eternal. Now we consider the question of the extent of His power. “Power” encomes all that which would be described under headings such as strength, creativity, capability and might. Power of this sort is absolutely necessary in order to have created all living things.Because of His infinite knowledge, the sender knows, for example, how DNA molecules can be programmed. But this knowledge is not sufficient to fashion such molecules in the first place. 3 Taking the step from mere knowledge to practical application requires the capacity to be able to build all the necessary biomachinery in the first place. Research enables us to observe these “hardware systems”. But we do not see them come about other than through a coordinated process of cellular replication which requires the same biomachinery to transmit and carry out the replication programs. Thus they had to originally be constructed by the sender. He had the task of creating the immense variety of all the basic biological types (created kinds), including the construction specifications for their biological machinery. There are no physio-chemical tendencies in raw matter for complex information-bearing molecules to form spontaneously. Without creative power, life would not have been possible.The obvious question here is the same as in conclusion 2: who gave Him this power? This would require a higher power-giver, P1, that is, a “super-designer”, who has more than the desiner. If we proceed as shown before according to explanation a) and b), we come to the conclusion that the sender must be all powerful. 4. The designer is non-material Because information is a non-material fundamental entity, it cannot originate from a material one. We can therefore conclude that: The sender must have a non-material component (spirit) to his nature. [Applying SLI-1, SLI-2] Basis for this conclusion Unaided matter has never been observed to generate information in the natural-law sense, (i.e. with all five levels: statistics, syntax, semantics, pragmatics, apobetics). Information is a non-material entity and therefore requires for its origin a nonmaterial source. We have already reasoned our way to some characteristics of the sender. Now we have a further one; he must be of a non-material nature, or at least must possess a non-material component to his nature. 5. No human being without a soul: refutation of materialism Because people have the ability to create information, this cannot originate from our material portion (body). We can therefore conclude that: Each person must have a non-material component (spirit, soul). [Applying SLI-1, SLI-2] Basis for this conclusion Evolutionary biology is locked into an exclusively materialistic paradigm. Reductionism (in which explanations are limited exclusively to the realm of the material) has been elevated to a fundamental principle within the evolutionary paradigm. With the aid of the laws of information, materialism may be refuted as follows: We all have the capacity to create new information. We can put our thoughts down in letters, essays and books, or carry on creative conversations and give lectures. 5 In the process, we are producing a non-material entity, namely information. (The fact that we need a material substrate to store and transfer information has no bearing on the nature of information itself.) From this we can draw a very important conclusion: namely that besides our material body we must have a non-material component. The philosophy of materialism, which found its strongest expression in Marxism-Leninism and communism, can now be scientifically refuted with the help of the scientific laws about information.

6. Big bang is impossible Since information is a non-material entity, the assertion that the universe arose solely from matter and energy (scientific materialism) is demonstrably false.6 [Applying SL1-2] Basis for this conclusion It is widely asserted today that the universe owes its origin to a primeval explosion in which only matter and energy was available. Everything that we experience, observe and measure in our world is, according to this view, solely the result of these two physical entities. Energy is clearly a material entity, since it is correlated with matter through Einstein’s mass/energy equivalence relationship E = mc2. Is this “big bang theory” just as refutable as a perpetual motion machine? Answer: YES, with the help of the scientific laws about information. In our world we find an abundance of information such as in the cells of all living things. According to SLI-1, information is a non-material entity and therefore cannot possibly have arisen from unaided matter and energy. Thus the common big bang worldview is false. 7. No evolution Since biological information (the fundamental component of all life) originates only from an intelligent sender, and all theories of chemical and biological evolution require that information must have originated solely from matter and energy (no sender), we conclude that: All theories or concepts of chemical and biological evolution (macroevolution) are false. [Applying SLI-1, SLI-2, SLI-4b, SLI-4d] Basis for this conclusion Judging by its worldwide following, evolution has become probably the most widespread teaching of our time. In accordance with its basic precepts, we see an ongoing attempt to explain all life on a purely physical/chemical plane (reductionism). The reductionists prefer to think of a seamless transition from the non-living to the living. 7 With the help of the laws of information we can reach a comprehensive and fundamental conclusion: the idea of macroevolution—i.e. the journey from chemicals to primordial cell to man—is false. Information is a fundamental and absolutely necessary factor for all living things. But all information—and living systems are not excluded—must necessarily have a non-material source. The evolutionary model, in the light of the laws of information, shows itself to be an “intellectual perpetual motion machine”.Now the question arises: where do we find the sender of the information stored within the DNA molecules? We don’t observe him, so did this information somehow come about in a molecular biological fashion?The answer is the same as that in the following cases: Consider the wealth of information preserved in Egypt in hieroglyphics. Not a single stone allows us to see any part of the sender. We only find these “footprints” of his or her existence chiselled into stone. But no one would claim that this information arose without a sender and without a mental concept.In the case of two connected computers exchanging information and setting off certain processes, there is also no trace of a sender. However, all the information concerned also arose at some point from the thought processes of one (or more) programmers.8The information in DNA molecules is transferred to RNA molecules; this occurs in an analogous fashion to a computer transferring information to another computer. In the cell, an exceptionally complex system of biomachinery is at work which translates the programmed commands in an ingenious fashion. But we see nothing of the sender. However, to ignore him would be a scientifically untenable reductionism.We shouldn’t be surprised to find that the programs devised by the sender of biological information are much more ingenious than all of our human programs. After all, we are here dealing with (as already explained in conclusion 2) a sender of infinite intelligence. The desiner’s program is so ingeniously conceived that it even permits a wide range of adaptations to new circumstances. In biology, such processes are referred to as “microevolution”. However, they have nothing to do with an actual evolutionary process in the way this word is normally used, but are properly understood as “parameter optimizations” within the same kind. In brief: The laws of information exclude a macro-evolution of the sort envisaged by the general theory of evolution. By contrast, microevolutionary processes (= programmed genetic variation), with their frequently wide-ranging adaptive processes within a kind, are explicable with the help of ingenious programs instituted by the designer. 8. No life from pure matter Because the distinguishing characteristic of life is a non-material entity (namely information) matter cannot have given rise to it. From this we conclude that: There is no process inherent within matter alone that leads from non-living chemicals to life. No purely material processes, whether on the earth or elsewhere in the universe, can give rise to life. [Applying SLI-1] Basis for this conclusion Proponents of evolutionary theory assert that “Life is a purely material phenomenon, which will arise whenever the right conditions are present.” However, the most universal and distinguishing characteristic of life—information—is of a nonmaterial nature. Thus we can apply scientific law SLI-1, which says: “A purely material entity cannot generate a non-material entity.”Figure 3 shows an ant with a microchip. Microchips are the storage elements of present-day computers and they represent matter plus information. The ant contains one material part (matter) and two non-material parts (information and life).We repeatedly hear of the discovery of water somewhere in our planetary system (e.g. on Jupiter’s moon Europa), or that carbon-containing substances have been found somewhere in our galaxy. These announcements are promptly followed by speculations that life could have developed there. This repeatedly reinforces the impression that so long as the necessary chemical elements or molecules are present on some astronomical body, and certain astronomical/physical conditions are fulfilled, one can more or less count on life being there. But as we have shown with the help of two laws, this is impossible. Even under the very best chemical conditions, accompanied by optimal physical conditions, there would still be no hope of life developing.Figure 3. Ant carrying a microchip. Both the ant and the microchip contain information, a non-material entity, that cannot be generated by a material entity and which points to intelligent, creative input. The ant, moreover, contains two non-material parts: information and life. (From: ‘Werkbild Philips’, with the kind permission of ‘Valvo Unternehmensbereich Bauelemente’, of Philips GmbH, Hamburg).Since the phenomenon of life ultimately requires something non-material, every kind of living

thing required a mind as its ultimate initiator. The four Australian scientists Don Batten, Ken Ham, Jonathan Sarfati and Carl Wieland thus correctly state: “Without intelligent, creative input, lifeless chemicals cannot form themselves into living things. The idea that they can is the theory of spontaneous generation, disproved by the great creationist founder of microbiology, Louis Pasteur.”9 With this new type of approach, applying the laws of information, Conclusions 7 and 8 have both shown us that we can exclude the spontaneous origin of life in matter. Conclusion No one has ever observed water flowing uphill. Why are there no exceptions to this? Because there is a law of nature that universally excludes this process from happening. Many plausible arguments have been raised against the teachings of atheism, materialism, evolution and the big bang worldview. But if it is possible to find scientific laws that contradict these ideas, then, since scientific laws have the highest degree of scientific credibility possible, we will have scientifically falsified them. We will have done so just as effectively as the way in which perpetual motion machines (those which supposedly run forever without any energy from outside) have been shown to be impossible through the application of scientific laws. This is precisely what we have demonstrated in this paper. We have presented four scientific laws about information. 10 From these we can generate comprehensive conclusions about te designer, the origin of life, and humanity. With the help of laws of information we have been able to refute all of the following: The purely materialistic approach in the natural sciences. All current notions of evolution (chemical, biological). Materialism (e.g. man as purely matter plus energy). The big bang as the cause of this universe. Atheism. Variation, information and the created kind by Dr Carl Wieland Summary All observed biological changes involve only conservation or decay of the underlying genetic information. Thus we do not observe any sort of evolution in the sense in which the word is generally understood. For reasons of logic, practicality and strategy, it is suggested that we: Avoid the use of the term ‘microevolution’. Rethink our use of the whole concept of ‘variation within kind’. Avoid taxonomic definitions of the created kind in favour of one which is overtly axiomatic. Most popular literature on evolution more or less implies that since we see small changes going on today in successive generations of living things, we only have to extend this in time and we will see the types of changes which have caused single-cell-to-man evolution. Creationists are thus seen as drawing some sort of imaginary ‘Maginot line’, and saying in effect ‘this much variation we will allow but no more—call it microevolution or variation within kind.’ When a creationist says that, after all, mosquitoes are not seen turning into elephants or moths, this is regarded as a simplistic retreat. Such a criticism is not without some justification, because the neo-Darwinist can rightly say that he would not expect to see that sort of change in his lifetime either. The post-neo-Darwinist may say that our sample of geologic time is too small to be sure of seeing a ‘hopeful monster’ or any sort of significant saltational change.Another reason why the creationist position often appears as one of weakness is that we are perceived as itting variation only because of being forced to do so by observation, then simply escaping the implications of variation by saying it does not go far enough. And we appear to redraw our ‘Maginot line’ depending on how much variation is demonstrated. It will be shown shortly, though, that this is a caricature of the creationist position, and that the limits to variation arise from basic informational considerations at the genetic level. The created kinds Observed variation does appear to have limits. It is tempting to use this fact to show that there are created kinds, and that variation is only within the limits of such kinds.However, the argument is circular and thus vulnerable. Since creationists by definition regard all variation as ‘within the limits of the created kind’ (see for example the statement of belief of the Creation Research Society of the USA), how can we then use observations to prove that variation is within the limits of the kind? To put it another way—of course we have never observed variation ‘across the kind’, since whatever two varieties descend from a common source, they are regarded as the same kind. It is no wonder that evolutionists are keen to press us for an exact definition of the created kind, since only then does our claim of ‘variation is only within the kind’ become nontautologous and scientifically falsifiable.Circular reasoning does not invalidate the concept of created kinds, however. In the same way, natural selection is also only capable of a circular definition (those who survive are the fittest, and the fittest are the ones who survive), but it is nevertheless a logical, easily observable concept. All we are saying is that arguments which are inherently circular cannot be invoked as independent proof of the kinds.When I claim that such independent proof may not be possible by the very nature of things, this statement is in no way a ‘cop out’. For instance, let us say we happened upon the remnants of an island which had exploded, leaving behind the debris of rocks, trees, sand, etc. It may be impossible in principle to reconstruct the original positions of the pieces in relation to each other before the explosion. This does not, however, mean that it is not possible to deduce with a great degree of confidence that the current state of the debris is consistent with that sort of an explosion which was recorded for us by eyewitness testimony, rather than arising by some other mechanism.In like manner, we can show that the observations of the living world are highly consistent with the ly described concept of original created kinds, and inconsistent with the idea of evolution. This is best done by focusing on the underlying genetic/informational basis of all biological change. This is more realistic and more revealing than focusing on the degree or extent of morphological change.The issue is qualitative, not quantitative. It is not that the train has had insufficient time to go far enough—it is heading in the wrong direction. The limits to variation—observed or unobserved—will come about inevitably because gene pools run out of ‘functionally efficient’ genetic information (or ‘teleonomic’ information). A full understanding of this eliminates the image of the desperately backpedalling creationist, redrawing his line of last resistance depending on what new observations are made on the appearance of new varieties.It also defuses the whole issue of ‘micro’ and ‘macro’ evolution. I believe it is better for creationists to avoid these confusing and misleading altogether. The word ‘evolution’ generally conveys the meaning of the sort of change which will ultimately be able to convert a protozoon into a man or a reptile into a bird, and so on. I hope to show that in of that sort of meaning, we do not see any evolution at all. By saying ‘we accept micro but not macroevolution’ we risk reinforcing the perception that the issue is about the amount of change, which it is not. It is about the type of change.This is not merely petty semantics, but of real psychological and tactical significance. Of course one can say that ‘microevolution’ occurs when this word is defined in a certain fashion, but the impact of the word, the meaning it conveys, is such as to make it unwise to persevere with this unnecessary concessional statement. Microevolution, that is, a change, no matter how small, which is unequivocally the right sort of change to ultimately cause real, informationally ‘uphill’ change, has never been observed.In any case, leading biologists are themselves now coming to the conclusion that ‘macroevolution’ is not just ‘microevolution’ [using their

terminology] extended over time. In November 1980 a conference of some of the world’s leading evolutionary biologists, billed as ‘historic’, was held at the Chicago Field Museum of Natural History on the topic of ‘macroevolution’. Reporting on the conference in the journal Science, Roger Lewin wrote:The central question of the Chicago conference was whether the mechanisms underlying microevolution can be extrapolated to explain the phenomena of macroevolution. At the risk of doing violence to the positions of some of the people at the meeting, the answer can be given as a clear, No. 1Francisco Ayala (Associate Professor of Genetics, University of California), was quoted as saying:… but I am now convinced from what the paleontologists say that small changes do not accumulate.2The fact that this article reaches essentially the same conclusion in the following pages can thus hardly cause it to be regarded as radical. Nevertheless, the vast majority of even well-educated people still persist in ignorance of this. That is, they believe that ‘Big Change = Small Change x Millions of Years.’ The concept of information The letters on this [printed] page—that is, the matter making up the ink and paper—all obey the laws of physics and chemistry, but these laws are not responsible for the information they carry. Information may depend on matter for its storage, transmission and retrieval, but is not a property of it. The ideas expressed in this article, for instance, originated in mind and were imposed on the matter. Living things also carry tremendous volumes of information on their biological molecules—again, this information is not a property of their chemistry, not a part of matter and the physical laws per se. It results from the order—from the way in which the letters of the cell’s genetic ‘alphabet’ are arranged. This order has to be imposed on these molecules from outside their own properties. Living things this information on from generation to generation. The base sequences of the DNA molecule effectively spell out a genetic ‘blue-print’ which determines the ultimate properties of the organism. In the final analysis, inherited biological variations are expressions of the variations in this information. Genes can be regarded as ‘sentences’ of hereditary information written in the DNA ‘language’.Imagine now the first population of living things on the evolutionist’s ‘primitive earth’. This so-called ‘simple cell’ would, of course, have a lot of genetic information, but vastly less than the information in only one of its present-day descendant gene pools, e.g., man. The evolutionist proposes that this ‘telegram’ has given rise to ‘encyclopedias’ of meaningful, useful genetic sentences. (See later for discussion of ‘meaning’ and ‘usefulness’ in a biological sense.) Thus he must for the origin with time of these new and meaningful sentences. His only ultimate source for these is mutation.3Going back to the analogy of the printed page, the information in a living creature’s genes is copied during reproduction, analogous to the way in which an automatic typewriter reproduces information over and over. A mutation is an accident, a mistake, a ‘typing error’. Although most such changes are acknowledged to be harmful or meaningless, evolutionists propose that occasionally one is useful in a particular environmental context and hence its possessor has a better chance of survival/reproduction. By looking now at the informational basis for other mechanisms of biological variation, it will be seen why these are not the source of new sentences and therefore why the evolutionist generally relies on mutation of one sort or another in his scheme of things. 1. Mendelian variation This is the mechanism responsible for most of the new varieties which we see from breeding experiments and from reasonable inferences in nature. Sexual reproduction allows packets of information to be combined in many different ways, but will not produce any new packets or sentences. For example, when the many varieties of dog were bred from a ‘mongrel’ stock, this was achieved by selecting desired traits in successive generations, such that the genes or sentences for these traits became isolated into certain lines. Although some of these sentences may have been ‘hidden from view’ in the original stock, they were already present in that population. (We are disregarding mutation for the moment, since such new varieties may arise independently of any new mutations in the gene pool. Some dogs undoubtedly have mutant characteristics.)This sort of variation can only occur if there is a storehouse of such sentences available to choose from. Natural (or artificial) selection can explain the survival of the fittest but not the arrival of the fittest, which is the real question. These Mendelian variations tell us nothing about how the genetic information in the present stock arose. Hence, it is not the sort of change required to demonstrate ‘upward’ evolution—there has been no addition of new and useful ‘sentences’. And this is in spite of the fact that it is possible to observe many new varieties in this way—even new species. If you define a species as a freely interbreeding natural unit, it is easy to see how new species could arise without any ‘uphill’ change. That is, without the addition of any new information coding for any new functional complexity. For example, mutation could introduce a defect which served as a genetic barrier, or simple physical differences, such as the sizes of Great Dane and Chihuahua, could make interbreeding impossible in nature.It is a little surprising to still see the occasional creationist literature clinging to the concept that no new species have ever been observed. Even if this were true, and there is some suggestion that it has actually been observed, there are instances of ‘clines’ in field observations which make it virtually certain that two now-isolated (reproductively) species have arisen from the same ancestral gene pool. Yet the very same creationists who seem reluctant to make that sort of ission would be quite happy to agree with the rest of us that the various species within what may be regarded as the ‘dog’ kind, including perhaps wolves, foxes, jackals, coyotes and the domestic dog, have arisen from a single ancestral kind. So why may this no longer be permitted to be happening under present-day observations? It is not only scientifically unnecessary, but it sets up a ‘straw man’ in the sense that any definite observation of a new species arising is used as a further lever with which to criticize creationists.What we see in the process of artificial selection or breeding giving rise to new varieties, is a thinning-out of the information in the parent stock, a reduction in the genetic potential for further variation. If you try and breed a Chihuahua from a Great Dane population or vice versa, you will find that your population lacks the necessary ‘sentences’. This is because, as each variety was selected out, the genes it carried were not representative of the entire gene pool.What appeared to be a dramatic example of change with the appearance of apparently new traits thus turns out, when its genetic basis is understood, to be an overall downward movement in informational . The number of sentences carried by each subgroup is reduced thus making it less likely to survive future environmental changes. Extrapolating that sort of process forward in time does not lead to upwards evolution, but ultimately to extinction with the appearance of evermore-informationally-depleted populations. 2. Polyploidy Again, no sentences appear which did not previously exist. This is the multiplication (‘photocopying’) of information already present. 3. Hybridizatlon Again, no new sentences. This is the mingling of two sets of information already present. 4. Mutation Since mutations are basically accidents, it is not surprising that they are observed to be largely harmful, lethal or meaningless to the function or survival of an organism. Random changes in a highly ordered code introduce ‘noise’ and chaos, not meaning, function and complexity, which tend to be lost. However, it is conceivable that in a complex world, occasionally a ‘destructive’ change will have a limited usefulness. For example, if we knock out a sentence such that there is a decrease in leg length in sheep (and there is such a mutation), this is useful to stop them jumping over the farmer’s fence. A beetle on a lonely, wind-swept island may have a mutation which causes it to lose or corrupt the information coding for

wing manufacture; hence its wingless successors will not be so easily blown out to sea and will thus have a selective advantage. Eyeless fish in caves, some cases of antibiotic resistance—the handful of cases of mutations which are quite ‘beneficial’—do notinvolve the sort of increase in functional complexity which evolutionary theory demands. Nor would one expect this to be possible from a random change.At this point some will argue that the ‘useful’, ‘meaningful’, ‘functional’, etc. are misused. They claim that if some change gives survival value then by definition it has biological ‘meaning’ and usefulness. But this assumes that living systems do nothing but survive—when in fact they and their subsystems carry out projects and have specific functions. That is, they carry teleonomic information. This is one of the essential differences between living objects and non-living ones (apart from machines). These projects do not always give rise to survival/reproductive advantages—in fact, they may have very little to do with survival, but are carried out very efficiently. The Darwinian assumption is always made, of course, that at some time in the organism’s evolutionary history, the project had survival/reproductive value. (For example, the archer-fish with its highly-skilled ‘hobby’ of shooting down bugs which it does not require for survival at the present time.) However, since these are nontestable assumptions, it is legitimate to talk about genetic information in a teleonomic sense, in isolation from any possible survival value.The gene pools of today carry vast quantities of information coding for the performance of projects and functions which do not exist in the theoretical ‘primeval cell’. Hence, in order to protozoon-to-man evolution, one must be able to point to instances where mutation has added a new ‘sentence’ or gene coding for a new project or function. This is so regardless of one’s assumptions on the survival value of any project or function.We do not know of a single mutation giving such an increase in functional complexity. Probabilistic considerations would seem to preclude this in any case, or at least make it an exceedingly rare event, far too rare to salvage evolution even over the assumed multibillion year time span.To illustrate further—the molecule haemoglobin in man carries out its project of transporting and delivering oxygen in red cells in a functionally efficient manner. A gene or ‘sentence’ exists which codes for the production of haemoglobin. There is a known mutation (actually three separate ones, giving the same result) in which only one letter in the sentence has been accidentally replaced by another. If you inherit this change from both parents, you will be seriously ill with a disease called sickle cell anaemia and will not survive for very long. Yet evolutionists frequently use this as an example of a ‘beneficial mutation’. This is because if you inherit it from only one parent, your red cells will be affected, but not seriously enough to affect your survival—just enough to prevent the malaria parasite from using them as an effective host. Hence, you will be more immune to malaria and better able to survive in malaria-infested areas. This shows us how a functionally efficienthaemoglobin molecule became a functionally crippled haemoglobin molecule. The mutation-caused gene for this disease is maintained at high levels in malaria-endemic regions by this incidental phenomenon of heterozygote superiority. Its damaging effect in a proportion of offspring is balanced by the protection it gives against malaria. It is decidedly not an ‘upward’ change. We have not seen a new, efficient oxygen transport mechanism or its beginnings evolve. We have not seen the haemoglobin transport mechanism improved.One more loose but possibly useful analogy. Let us say an undercover agent is engaged in sending a daily reassuring telegram from enemy territory. The text says ‘the enemy is not attacking today’. One day an accident occurs in transmission and the word ‘not’ is lost. This is very likely going to be a harmful change, perhaps even triggering a nuclear war by mistake. But perhaps, in a freak situation, it could turn out to be useful (for example, by testing the fail-safe mechanisms involved). But this does not mean that it is the sort of change required to begin to convert the telegram into an encyclopedia.The very small number of ‘beneficial’ mutations actually observed are simply the wrong kind of change for evolution—we do not see the addition of new sentences which carry meaning and information. Again surprisingly, one often reads creationist works which insist that there is no such thing as a beneficial mutation. If benefit is defined purely in survival , then we would not expect this to be true in all instances, and in fact it is not—that is, there are indeed ‘beneficial’ mutations in that sense only.Information depends on order, and since all of our observations and our understanding of entropy tells us that in a natural, spontaneous, unguided and unprogrammed process order will decrease, the same will be true of information. The physicist and communications engineer should not be surprised at the realisation that biological processes involve no increases in useful or functional (teleonomic) information and complexity. In fact, the net result of any biological process involving transmission of information (i.e., all hereditary variation) is conservation or loss of that genetic information.This points back directly to the creation of the information, supernaturally, in the beginning. It is completely in harmony with the young age concept of a world made ‘very good’ as a balanced, functioning whole, with decay only subsequent to the Fall. This is the reason why there are inevitable limits to variation, why the creationist does not have to worry about how many new ‘species’ the future may bring—because there is a limit to the amount of functionally efficient genetic information present, and natural processes such as mutation cannot add to this original storehouse.Notice that since organisms were created to migrate out from a central point at least once and fill empty ecological niches, as well as having to cope with a decaying and changing environment, they would require considerable variation potential. Without this built-in genetic flexibility, most populations would not be present today. Hence the concept of biological change is in a sense predicted by the young age model, not something forced upon it only because such change has occurred. The created kind The originally created information was not in the form of one ‘super species’ from which all of today’s populations have split off by this ‘thinning out’ process, but was created as a number of distinct gene pools. Each group of sexually reproducing organisms had at least two . Thus,Each original group began with a built-in amount of genetic information which is the raw material for virtually all subsequent useful variation.Each original group was presumably genetically and reproductively isolated from other such groups, yet was able to interbreed within its own group. Hence the original kinds would truly have earned the modern biological definition of ‘species’. 4 We saw in our dog example that such ‘species’ can split into two or more distinct subgroups which can then diverge (without adding anything new) and can end up with the characteristics of ‘species’ themselves—that is, reproductively isolated from each other but freely interbreeding among themselves. The more variability in the original gene pool, the more easily can such new groups arise. However, each ‘splitting’ reduces the potential for further change and hence even this is limited. All the descendants of such an original kind which was once a species, may then end up being classified together in a much higher taxonomic category—e.g., family.

Take a hypothetical created kind A—truly a biological ‘species’ with perhaps a tremendous genetic potential. See Figure 1. Note that A may even continue as an unchanged group, as may any of the subgroups. Splitting off of daughter populations does not necessarily mean extinction of the parent population. In the case of man, the original group has not diverged sufficiently to produce new species.Hence, D1, D2, D3, E1, E2, E3, P1, P2, Q1, Q2, Q3 and Q4 are all different species, reproductively isolated. But all the functionally efficient genetic information they contain was present in A. (They presumably carry some mutational defects as well).Let us assume that the original kind A has become extinct, and also the populations X, B, C, D, E, P and Q. (But not D1, D2, etc.) If X carried some of the original information in A, which is not represented in B or C, then that information is lost forever. Hence, in spite of the fact that there are many ‘new species’ which were not originally present, we would have witnessed conservation of most of the information, loss of some, and nothing new added apart from mutations (harmful defects or just meaningless ‘noise’ in the genetic information). All of which is the wrong sort of informational change if one is trying to demonstrate protozoon-to-man evolution.Classifications above species are more or less arbitrary groupings of convenience, based generally on similarities and differences of structure. It is conceivable that today, D1, D2 and D3 could be classified as species belonging to one genus, and E1, E2 and E3 as species in another genus, for example. It could also be that the groups B and C were sufficiently different such that their descendants would today be in different families. We begin to see some of the Figure 1. The ‘splitting off’ of daughter populations from problems facing a creationist who tries to delineate today’s an original created kind. representatives of the created kinds.Creatures may be Click here for larger image. classified in the same family, for example, on the basis of similarities due to common design while in fact they belong to two totally different created kinds. This should sound a note of caution against using morphology alone, as well as pointing out the potential folly of saying ‘in this case, the baramin is the family; in this case, it is the genus, etc.’ (Baramin is an accepted creationist term for ‘created kind’.)There is no easy solution as yet to the problem of establishing each of these genetic relationships—in fact, we will probably never be able to know them all with certainty. Interbreeding, in vitro fertilization experiments, etc. may suggest hip of the same baramin but lack of such genetic compatibility does not prove that two groups are not in the same kind. (See earlier discussion—genetic barriers could arise via mutational deterioration.) However, newer insights, enabling us to make direct comparisons between species via DNA sequencing, open up an entirely new research horizon. (Although the question of where the funding for such extensive research will come from in an evolution-dominated society remains enigmatic.)What then do we say to an evolutionist who understandably presses us for a definition of a created kind or identification of same today? I suggest the following for consideration:Groups of living organisms belong in the same created kind if they have descended from the same ancestral gene pool.To talk of ‘fixity of kinds’ in relation to any present-day variants thus also becomes redundant—no new kinds can appear by definition.Besides being a simple and obvious definition, it is axiomatic. Thus it is as unashamedly circular as a rolled-up armadillo and just as impregnable, deflecting attention, quite properly, to the real issue of genetic change.The question is not—what is a baramin, is it a species, a family or a genus? Rather, the question is—which of today’s populations are related to each other by this form of common descent, and are thus of the same created kind? Notice that this is vastly removed from the evolutionist’s notion of common descent. As the creationist looks back in time along a line of descent, he sees an expansion of the gene pool. As the evolutionist does likewise, he sees a contraction. As with all taxonomic questions, common sense will probably continue to play the greatest part. For instance, it is conceivable (though not necessarily so) that crocodiles and alligators both descended from the same ancestral gene pool which contained all their functionally efficient genes, but not really conceivable that crocodiles, alligators and ostriches had a common ancestral pool which carried the genes for all three! ARE THERE EVOLUTIONARY PROCESSES THAT LEAD TO INFORMTION INCREAS? Bears across the world … Bears are some of the most amazing creatures! by Paula Weston and Carl Wieland From the thick stomach lining of the panda and the partially webbed paws of the polar bear, to the insect-sucking muzzle of the sloth bear, bears provide a fascinating example of the variety of specialized characteristics existing within one family.The bear family (Ursidae) consists of eight species, four of which are contained in the Ursus group: the brown bear, American black bear, Asiatic black bear and polar bear. Even within this group (known as a genus) the variation is wide.The brown and American black bears are mainly vegetarians with appropriate dental features for crushing plant material. However, the first has claws suited to digging while the other has claws more suitable for climbing. The Asiatic black bear, which also has claws for climbing, is an opportunistic omnivorous feeder (eating meat and plants as available).1The polar bear, however, has some amazing features which allow it to function perfectly in its cold, wet environment. Much heavier than the above bears, it has two distinct hair types, one long and one short, which effectively is like having two coats. By increasing buoyancy, this helps it to swim, as does its long neck and the partial webbing between its toes. Its fur-covered foot pads provide better traction on the ice. Almost exclusively a meat eater (with teeth to suit such a diet), the polar bear also has a large stomach capacity for sporadic (opportunistic) feeding.The sun bears and sloth bears (also included in the Ursus group by many scientists) also have as many differences as similarities. The sun bear is omnivorous, with sharp, sickle-like claws suited for tree climbing, while the sloth bear (possessing claws for both digging and tree climbing) has an unusual head and dental structure perfect for eating its main food source, termites. The sloth bear’s long muzzle has protrusible lips and nostrils which it can close—these two features allow it to create a vacuum tube to suck up the termites.

The giant panda, like the polar bear, has very specialized features necessary for survival, including powerful jaws and special molars for crushing plants, and an oesophagus (gullet) with a tough, horny lining to protect the bear from splinters when it eats bamboo, its primary source of food. The panda’s stomach also has a thick, muscular lining to protect it from bamboo fragments.While both evolutionists and creationists consider these specialized characteristics to be adaptations to the environment through natural selection, the two camps are poles apart as to how most of this variation came about in the first place.Evolutionists believe that the genetic (hereditary) information (which supplies the ‘recipe’ to construct such specialized features in the developing embryo) all arose by an accumulation of copying errors (mutations). Any ‘good’ errors which helped the creature to survive were ed on. In this way, they believe that these design features are all the result of these copying mistakes, accumulated by selection over millions of years.Creationists, however, while accepting that all of today’s bears probably descended from a single bear kind, 2 do not believe that the information in the ‘recipes’ for all these design features arose by chance. No-one has ever observed any biological process adding information!A better explanation is that virtually all the necessary information was already there in the genetic makeup of the first bears, a population created with vast genetic potential for variation.This doesn’t mean that all of the features of today’s bears would have been on obvious display back then. A simple example would be the way in which mongrel dogs obviously had the potential to develop all the different breeds we see today. Thus, there was no actual poodle to be seen among mongrel dogs hundreds of years ago, but by looking closely at many of them, one would have seen at least some of the individual features found in today’s poodles popping up here and there.Similarly, it is unlikely that there were polar bears before the Flood—however, since much of the information for their specialized features was already there, some of these features, in lesser form, would have also been apparent in a few individuals from time to time.It takes selection (natural or artificial) to concentrate and enhance these features—however, this does not create anything really new, no new design information. If there were no genetic potential in the bear family to grow really thick fur, then no bears would ever have inhabited the Arctic.However, it is likely that not all the features for today’s bears would have been coded for directly in the genes of the original bear kind. Mutations, genetic copying mistakes which cause defects, may on rare occasions be helpful, even though they are still defects, corruptions or losses of information. Thus, the polar bear’s partly webbed feet may have come from a mutation which prevented the toes from dividing properly during its embryonic development. This defect would give it an advantage in swimming, which would make it easier to survive as a hunter of seals among ice floes.Thus, bears carrying this defect would be more likely to it on to their offspring—but only in that environment. However, since mutations are always informationally downhill, there is a limit to the ability of this mechanism to cause adaptive features to arise. It will never turn fur into feathers, for example. 3After the Flood, when dramatic climate and environment changes occurred, there was suddenly a large number of ‘empty’ niches, and as the first pair multiplied, groups of their descendants found new habitats. Only those whose predominant characteristics were suitable for that environment thrived and bred. 4 In this way, it would not need millions of years for a new variety (even a new species) to arise.For example, of the first bears forced to exist on bamboo, only those exhibiting the genetic information for a stronger oesophagus and stomach lining would have survived in each generation. Animals without these features would not have lived to produce offspring, thus reducing the gene pool as only the surviving animals interbred. Thus these characteristics became more prominent in that group. This is more reasonable than assuming that this group had to wait for the right mutations to come along, over thousands or millions of years, to provide those vital features. Notice how such new species will be more specialised; be better adapted to a particular habitat; and have less genetic information than the original group. (See the box (below) for a simple example of how information is lost as creatures adapt). It makes a great deal of sense the original kinds of creatures to be created as very robust groups, possessing the ability to vary and adapt to changing environments. Summary Creationists accept that the design features we see in modern animals are largely the result of original created design, expressed and ‘fine-tuned’ to fit the environment by subsequent adaptation, through natural selection in a fallen world of death and struggle. If, as seems probable from fossil evidence, there were no ice-caps before the Flood, there would have been no polar bears at that time. The wisdom of the designer is revealed in providing the original organisms with the potential to adapt so as to be ‘fit’ for a wide range of habitats and lifestyles. The bear family, with its incredible variation, provides clear evidence of an intelligent designer.

How information is lost when creatures adapt to their environment In the example on the right (simplified for illustration), a single gene pair is shown under each bear as coming in two possible forms. One form of the gene (L) carries instructions for long fur, the other (S) for short fur.In row 1, we start with medium-furred animals (LS) interbreeding. Each of the offspring of these bears can get one of either gene from each parent to make up their two genes. In row 2, we see that the resultant offspring can have either short (SS), medium (LS) or long (LL) fur. Now imagine the climate cooling drastically (as in the post-Flood ice age). Only those with long fur survive to give rise to the next generation (line 3). So from then on, all the bears will be a new, long-furred variety. Note that: They are now adapted to their environment. They are now more specialized than their ancestors on row 1. This has occurred through natural selection. There have been no new genes added In fact, genes have been lost from the population—i.e. there has been a loss of genetic information, the opposite of what microbe-toman evolution needs in order to be credible. Now the population is less able to adapt to future environmental changes—were the climate to become hot, there is no genetic information for short fur, so the bears would probably overheat. Polar bears: correcting past blunders … In 1979, this magazine, then called Ex Nihilo, reported (2(2):18) that the hairs of polar bears were transparent and, like fibreoptic cables, ‘piped’ light energy down to the bear’s skin to keep it warm. The information was from a secular source, and of course we had no polar bear hairs to test.Now a recent author who has tested their hair points out that this idea, which has been repeated over and over in secular science journals and reports, is actually a myth. 6The polar bear’s hairs are not some unique fibre-optic substance (which come to think of it would actually have been tough to explain if all bears came recently from one kind, as most creationists currently think), but are made of ordinary keratin, just like the hair of all other mammals. This emphasizes the fact that all scientific claims are tentative and fallible, no matter who makes them.Another erroneous statement about polar bears, which has appeared in some anti-Darwinian literature, is that natural selection can have nothing to do with the polar bear’s white coat, since the bear has no predators.However, this is not the case, as it is obvious that of the first bears to reach the snowbound regions, those with lighter coats would have had an advantage.By being camouflaged against the snow, they would have had more chance of being able to sneak up on their prey undetected. Thus, especially where food was scarce, whiter bears would have been more likely to survive and on their genes.

Was Dawkins Stumped? Frog to a Prince critics refuted again Published: 12 April 2008(GMT+10) This week we feature a critical from JW, whose complaint relates to CMI’s videoclip of Richard Dawkins being stumped by a question about genetic information, which features on our DVD From a Frog to a Prince (see raw footage with subtitles, right).We like to publish critical s regularly, and our policy is to choose the best-articulated and most well-reasoned critical available. But regrettably, few of the multitudinous critical emails we receive are cogent and logical, with most tending toward the ‘mangled diatribe’ end of the literary spectrum. JW’s email below is mildly representative in this regard. Although JW’s contribution breaks our rules against unsubstantiated allegations, etc., her comments give us the opportunity to confront the prolific accusations made against us in relation to our Richard Dawkins interview, and also to address some common misthinking regarding religion. We have answered previous critics in Skeptics choke on Frog: Was Dawkins caught on the hop? But we still receive a lot of abuse and slander in relation to our Dawkins interview, much of it revolving around incorrect s of the sequence of events that occurred during the interview. For a precise analysis and timeline of exactly what took place, see our Dawkins Interview Timeline (below). J.W. writes: sxc.hu I’ve seen the raw footage of the so called “stumping Richard Hawkins” [sic] fiasco. You are liars! You didn’t “stump” him. He gave a brilliant and true answer!!! Must you really lie to try to satisfy your followers??? Andrew Lamb responds: I’ve seen the raw footage of the so called “stumping Richard Hawkins” fiasco.

An excerpt of CMI’s raw footage of our Richard Dawkins interview was posted online in April 2007 on a secular website. The excerpt is that in which Richard Dawkins responds to the question, ‘Can you give an example of a genetic mutation or an evolutionary process which can be seen to increase the information in the genome?’, a question that he was asked on two separate occasions on the day.Encouragingly, in the year that has ed since then there have been almost half a million viewings of this video, by people from around the world. That’s several hundred thousand people who have witnessed for themselves the utter inability of evolution’s leading apologist to for genetic information.A shortened version of this appears in our popular Frog to a Prince DVD, which incidentally now has subtitles in ten languages. You are liars! You didn’t “stump” him. He gave a brilliant and true answer!!! We did not lie. The ‘Richard Dawkins Stumped…’ title given to our raw footage clip on that secular website is accurate. Dawkins was stumped, as shown by the fact that he tried to think of an answer, but eventually responded with comments that did not address the question.A few of the things Dawkins said were true, e.g. ‘fish are modern animals’. But even then, they don’t qualify as true answers since they hadnothing to do with the question asked.Also, much of what he said was not true, e.g. his comment that ‘They [fish] are descended from ancestors which we’re descended from’. From the true eyewitness of history we know that humans have always been humans, and did not descend from some other kind of creature, and there are no facts of science to demonstrate that they have, only the fanciful story-telling of evolution theorists. Must you really lie to try to satisfy your followers??? Your comment here implies that you think there is something wrong with lying. But if evolution were true, it would not be possible to show logically that lying is ‘bad’. Rather ‘good’ and ‘bad’ would just be matters of opinion, not matters of objective reality. Evolutionary beliefs provide no objective basis to justify traits like honesty. Dawkins Interview Timeline

The above timeline is of the Richard Dawkins interview that formed the basis of CMI’s video From a Frog to a Prince (click on it to see high-resolution version). From a Frog to a Prince recording timeline resolves questions This timeline, based on the main camera sound track of the interview, reconciles the three s of the interview, i.e. the published s of Richard Dawkins and Gillian Brown, and the unpublished of Philip Hohnen, given in personal correspondence with CMI during 2001–2003. There seemed to be discrepancies between the three s, but our timeline is consistent with all three s and with the audio tape. The key to resolving the apparent inconsistencies is the realization that: Dawkins was questioned about information twice, first by Hohnen (A on timeline), after which the interview was interrupted, with Dawkins upset, and later by Brown (K), from behind the camera, when Dawkins had no ready answer.Dawkins’ anger erupted at the first occasion, when he suspected he might be speaking to creationists. This is what Dawkins recalled and gave as an excuse for his silence following the question on the video, which was asked some time later when Dawkins was already aware that he was speaking with creationists. In his recollection, Professor Dawkins conflated these two events.After Philip Hohnen had been on a tour of the house with Mrs Dawkins (Lalla Ward) (section D on timeline), and then negotiated with Richard Dawkins (E), the latter agreed to make a statement for recording. In his statement (G, J) Dawkins candidly itted that evolution had to explain the information in living things and he claimed that mutations, aided by natural selection, created all the information. These very pro-evolution statements are on the video, just as Dawkins had wanted. After these confident assertions, Gillian Brown, from her position behind the camera, slipped in the question asking for an actual example of an evolutionary process that can be observed to increase the information in the genome (K). It would have been churlish of Dawkins not to try to answer this, in the light of the confident spiel he had just given. His look (on the video) of puzzlement, even consternation, had nothing to do with discovering the nature of the interview (this discovery happened much earlier). The fact that he failed to answer the question, even given time to think, should have been sufficient for any fair-minded observer to see that the silence (L) following the asking of the question revealed a lack of an answer, not a rising tide of anger, etc., as claimed by Dawkins.There was a period (D–E on the timeline) which was perceived differently by the three participants, in part because they were actually doing different things at the time (e.g. Philip Hohnen was being given a guided tour of the house by Mrs Dawkins). When Hohnen returned from the tour, he did not see any evidence of a rapprochement between Dawkins and Brown. Hohnen then negotiated with Dawkins for a continuation of the videoing, with Dawkins agreeing to give a statement. This timeline harmonizes the recollections of all three persons and shows that the video producer did not manufacture Dawkins’ silence and nor was Dawkins’ silence due to a rising tide of anger over discovering that he was being interviewed by creationists (this had happened earlier). Hohnen recalls that they parted in good humour. The segment where Dawkins fails

to answer the information question is fair (in fact the period of silent puzzlement was considerably shortened on the Frog to a Prince video).It may be argued that Brown pushed the boundaries by asking the question at all when she had agreed for Dawkins to make a statement. However, it was a question begging to be asked after Dawkins’ confident speech about the adequacies of natural processes in creating new information. Philip Hohnen has checked the timeline, and vouches for its accuracy. Explanatory notes to timeline Creation Ministries International have an audio tape (we may also have the actual video recording, but it is not currently locatable) of the latter part of the interview, starting from the point at which Dawkins expressed his suspicions (B). This audio tape comprises the sound track from the main video camera. (Another video camera was also running during much of the interview.) A copy of this same audio tape was sent to the anticreationist Glenn Morton, who had previously been sceptical of our . After seeing this copy, Morton declared ‘I will state categorically that the audio tape of the interview 100% s Gillian Brown’s contention that Dawkins couldn’t answer the question.’The green (lightly shaded) segments of the timeline above represent periods covered on the audio tape. The red (darkly shaded) segments represent periods not covered on the audio tape.The two occurrences of double slashes // in the timeline’s text boxes represent breaks in recording.Dawkins’ oft-discussed ‘11-second pause’ is represented in this timeline by segments L and M, and is referred to on this chart by the term ‘silence’, rather than the usual term ‘pause’ in order to differentiate between this and the recording pauses. It is 11 seconds from the end of GB’s question until RD’s audible intake of breath, and 19 seconds in total from the end of GB’s question until the pause in recording (O). That is, L, M and N together comprise 19 seconds. There is approximately seven seconds of silence between RD’s audible intake of breath and his request to stop. In period O on this chart, i.e. after GB asked the info question and RD requested a stop, there was no speaking by anybody until GB said ‘Now recording’ and RD began speaking again with ‘Ok. There’s a popular misunderstanding …’. The adaptation of bacteria to feeding on nylon waste by Don Batten by Don Batten In 1975, Japanese scientists discovered bacteria that could live on the waste products of nylon manufacture as their only source of carbon and nitrogen.1 Two species, Flavobacterium sp. K172 and Pseudomonas sp. NK87, were identified that degrade nylon compounds.Much research has flowed from this discovery to elucidate the mechanism for the apparently novel ability of these bacteria.2 Three enzymes are involved in Flavobacterium K172: F-EI, F-EII and F-EIII, and two in PseudomonasNK87: P-EI and P-EII. None of these has been found to have any catalytic activity towards naturally occurring amide compounds, suggesting that the enzymes are completely new, not just modified existing enzymes. Indeed no homology has been found with known enzymes. The genes for these enzymes are located on plasmids: 3 plasmid pOAD2 in Flavobacterium and on two plasmids, pNAD2 and pNAD6, in Pseudomonas.Apologists for materialism latched onto these findings as an example of evolution of new information by random mutations and natural selection, for example, Thwaites in 1985.4 Thwaites’ claims have been repeated by many, without updating or critical evaluation, since. Is the evidence consistent with random mutations generating the new genes? Thwaites claimed that the new enzyme arose through a frame shift mutation. He based this on a research paper published the previous year where this was suggested. 5 If this were the case, the production of an enzyme would indeed be a fortuitous result, attributable to “pure chance”. However, there are good reasons to doubt the claim that this is an example of random mutations and natural selection generating new enzymes, quite aside from the extreme improbability of such coming about by chance.6Evidence against the evolutionary explanation includes:There are five transposable elements on the pOAD2 plasmid. When activated, transposase enzymes coded therein cause genetic recombination. Externally imposed stress such as high temperature, exposure to a poison, or starvation can activate transposases. The presence of the transposases in such numbers on the plasmid suggests that the plasmid is designed to adapt when the bacterium is under stress.All five transposable elements are identical, with 764 base pairs (bp) each. This comprises over eight percent of the plasmid. How could random mutations produce three new catalytic/degradative genes (coding for EI, EII and EIII) without at least some changes being made to the transposable elements? Negoro speculated that the transposable elements must have been a “late addition” to the plasmids to not have changed. But there is no evidence for this, other than the circular reasoning that supposedly random mutations generated the three enzymes and so they would have changed the transposase genes if they had been in the plasmid all along. Furthermore, the adaptation to nylon digestion does not take very long (see point 5 below), so the addition of the transposable elements afterwards cannot be seriously entertained.All three types of nylon degrading genes appear on plasmids and only on plasmids. None appear on the main bacterial chromosomes of either Flavobacterium or Pseudomonas. This does not look like some random origin of these genes—the chance of this happening is low. If the genome of Flavobacterium is about two million bp,7 and the pOAD2 plasmid comprises 45,519 bp, and if there were say 5 pOAD2 plasmids per cell (~10% of the total chromosomal DNA), then the chance of getting all three of the genes on the pOAD2 plasmid would be about 0.0015. If we add the probability of the nylon degrading genes of Pseudomonas also only being on plasmids, the probability falls to 2.3 x 10 -6. If the enzymes developed in the independent laboratory-controlled adaptation experiments (see point 5, below) also resulted in enzyme activity on plasmids (almost certainly, but not yet determined), then attributing the development of the adaptive enzymes purely to chance mutations becomes even more implausible.The antisense DNA strand of the four nylon genes investigated in Flavobacterium and Pseudomonas lacks any stop codons.8 This is most remarkable in a total of 1,535 bases. The probability of this happening by chance in all four antisense sequences is about 1 in 10 12. Furthermore, the EII gene in Pseudomonas is clearly not phylogenetically related to the EII genes of Flavobacterium, so the lack of stop codons in the antisense strands of all genes cannot be due to any commonality in the genes themselves (or in their ancestry). Also, the wild-type pOAD2 plasmid is not necessary for the normal growth of Flavobacterium, so functionality in the wild-type parent DNA sequences would appear not to be a factor in keeping the reading frames open in the genes themselves, let alone the antisense strands. Some statements by Yomo et al., express their consternation: “These results imply that there may be some unknown mechanism behind the evolution of these genes for nylon oligomerdegrading enzymes. “The presence of a long NSF (non-stop frame) in the antisense strand seems to be a rare case, but it may be due to the unusual characteristics of the genes or plasmids for nylon oligomer degradation. “Accordingly, the actual existence of these NSFs leads us to speculate that some special mechanism exists in the regions of these genes.” It looks like recombination of codons (base pair triplets), not single base pairs, has occurred between the start and stop codons for each sequence. This would be about the simplest way that the antisense strand could be protected from stop codon generation. The mechanism for such a recombination is unknown, but it is highly likely that the transposase genes

are involved.Interestingly, Yomo et al. also show that it is highly unlikely that any of these genes arose through a frame shift mutation, because such mutations (forward or reverse) would have generated lots of stop codons. This nullifies the claim of Thwaites that a functional gene arose from a purely random process (an accident).The Japanese researchers demonstrated that nylon degrading ability can be obtained de novo in laboratory cultures of Pseudomonas aeruginosa [strain] POA, which initially had no enzymes capable of degrading nylon oligomers.9 This was achieved in a mere nine days! The rapidity of this adaptation suggests a special mechanism for such adaptation, not something as haphazard as random mutations and selection.The researchers have not been able to ascertain any putative ancestral gene to the nylon-degrading genes. They represent a new gene family. This seems to rule out gene duplications as a source of the raw material for the new genes.8 P. aeruginosa is renowned for its ability to adapt to unusual food sources—such as toluene, naphthalene, camphor, salicylates and alkanes. These abilities reside on plasmids known as TOL, NAH, CAM, SAL and OCT respectively.2Significantly, they do not reside on the chromosome (many examples of antibiotic resistance also reside on plasmids).The chromosome of P. aeruginosa has 6.3 million base pairs, which makes it one of the largest bacterial genomes sequenced. Being a large genome means that only a relatively low mutation rate can be tolerated within the actual chromosome, otherwise error catastrophe would result. There is no way that normal mutations in the chromosome could generate a new enzyme in nine days and hypermutation of the chromosome itself would result in non-viable bacteria. Plasmids seem to be adaptive elements designed to make bacteria capable of adaptation to new situations while maintaining the integrity of the main chromosome. Stasis in bacteria P. aeruginosa was first named by Schroeter in 1872. 10 It still has the same features that identify it as such. So, despite being so ubiquitous, so prolific and so rapidly adaptable, this bacterium has not evolved into a different type of bacterium. Note that the number of bacterial generations possible in over 130 years is huge—equivalent to tens of millions of years of human generations, encoming the origin of the putative common ancestor of ape and man, according to the evolutionary story, indeed perhaps even all primates. And yet the bacterium shows no evidence of directional change—stasis rules, not progressive evolution. This alone should cast doubt on the evolutionary paradigm.Flavobacterium was first named in 1889 and it likewise still has the same characteristics as originally described.It seems clear that plasmids are designed features of bacteria that enable adaptation to new food sources or the degradation of toxins. The details of just how they do this remains to be elucidated. The results so far clearly suggest that these adaptations did not come about by chance mutations, but by some designed mechanism. This mechanism might be analogous to the way that vertebrates rapidly generate novel effective antibodies with hypermutation in B-cell maturation, which does not lend credibility to the grand scheme of neoDarwinian evolution.11 Further research will, I expect, show that there is a sophisticated, irreducibly complex, molecular system involved in plasmid-based adaptation—the evidence strongly suggests that such a system exists. This system will once again, as the black box becomes illuminated, speak of intelligent creation, not chance. Understanding this adaptation system could well lead to a breakthrough in disease control, because specific inhibitors of the adaptation machinery could protect antibiotics from the development of plasmid-based resistance in the target pathogenic microbes. New plant colours—is this new information? CMI scientist answers a skeptic 11 July 2000 One skeptic believes that he has found an example of ‘new information’ arising by mutations and natural selection. Could he be correct? Question/statements from skeptic Since I have some background in genetics and plant breeding, I can tell you that the entire field of plant breeding is based on ‘new information’ arising from random mutations. New traits do appear, at the molecular and morphological level new proteins, new pigments, etc. These are novelties.Two parents with blue eyes will generally produce children with blue eyes, and likewise two plants with white flowers will generally produce new plants with white flowers, but sometimes that seedlings with red or purple flower turns up, not because a recessive allele has been revealed, but because a mutation has altered an existing pigment or biochemical pathway to produce something entirely new, that has never existed before. This is NEW INFORMATION.As an example, there is nothing like an ear of corn in any other species of grass. It seems to be entirely unique in the plant kingdom. And yet there are three or four species of grass, very similar to corn in their overall growth, but with typical grass-like reproductive organs. The funny thing is, they will breed with corn to produce fully fertile offspring. It is clear that a combination of mutation and selection has produced in corn an unusual and entirely novel structure from a very typical grass— in other words, NEW INFORMATION. Response by Don Batten, Ph.D. The question comes from someone who does not understand the concept of information. The appearance of a ‘new trait’ does not have to involve the addition of information via the DNA coding. In fact, as bioinformatics expert Dr Lee Spetner has demonstrated (in his book, Not by Chance, Judaica Press), such is so unlikely that it could never be the basis for the increased information needed for molecules-to-man evolution. Information content is measured not by the number of traits, but by what is called the specified complexity of a base sequence or protein amino acid sequence. A mutation, being a random change in highly specified information contained in the nucleic acid base sequence, could almost never do anything but scramble the information; that is, reduce the information.Now sometimes such a loss of information results in a new trait —for example, purple or red flowers where there were only blue ones before. This would have to be studied at the DNA base sequence level (or amino acid sequence in the enzyme producing the pigment, or the pigment itself) to show this. For example, a blue pigment could be changed into a red or purple pigment by loss of a side-chain from the basic pigment molecule. Such a change would involve a loss of specified complexity and therefore a loss of information. Even an informationally neutral change could be responsible—this is not to be confused with Kimura’s neutral mutation, which has nothing to do with the concept of information, only the effect on survival. Even a change of one amino acid in a protein, not altering information content, can alter energy levels in such a way as to change the visible absorption spectrum, e.g. by reducing the number of consecutive conjugated bonds. And a small change in pH can have a large effect on color (this effect was overlooked by a group of molecular biologists who managed to get the gene for the blue pigment in hydrangeas into a rose—the rose was not blue, although the pigment was manufactured, because the cell pH was not the same as a hydrangea’s!).Of the many hundreds of antibiotic, herbicide and insecticide resistance mechanisms studied at a biochemical level, none involve addition of specified complexity in the DNA. Although some are ‘new traits’ due to mutations, all involve loss of information. An example is the loss of control over the production of an enzyme that happens to break down penicillin in Staphylococcus aureus, resulting in the production of greatly increased amounts of the enzyme and thus conferring resistance to penicillin. Another mode of antibiotic resistance due to mutation is decreased effectiveness of a membrane transport protein so that the antibiotic is no longer taken up by the cell (but the normal function of the transporter is also

impaired and the bacterium is less fit to survive in the wild). However, much antibiotic resistance seems to be acquired by the transfer of plasmids from other species of bacteria via conjugation, which of course does not explain the ultimate origin of the information.What about the corn story? The questioner is probably correct about the species of grass and the origin of corn. I have no problem with that. Creationists would say that the species that interbreed with corn (maize) are of the same created kind (see Ligers and wholphins? What next?, Q&A: Speciation). However, until the biochemical/genetic basis of the difference between maize and its wild relatives is determined, it cannot be said that the maize inflorescence is due to new information. Loss of information in some base sequences responsible for early steps in inflorescence development could easily for such seemingly large differences.It must be noted (again) that creationists do not say that mutations are always harmful, just that they are almost invariably a loss of information (i.e. specified complexity). Sometimes a loss of information can be beneficial, but it is a loss of information. For example, loss of function of wings in the flightless cormorant in the Galápagos Islands, which can now dive better than its flying cousins, or flightless beetles on a windswept island that are better off because they are less likely to be blown into the sea—see Beetle bloopers.Evolution needs swags of new information, if a microbe really did change into a man over several billion years. The additional new information would take nearly a thousand books of 500 pages each to print the sequence. Random changes cannot for a page, or even a sentence, of this, let alone ing for all of it. The evolutionist has an incredible faith! Further reading: In the Beginning Was Information by Dr Werner Gitt (an information scientist in ). The Mystery of Life’s Origin by Thaxton, Bradley and Olsen—these are thermodynamics experts and they deal with the origin of information from a thermodynamics point of view, showing the impossibility of natural processes creating the information in living things. See also Q&A: Information Theory. Is antibiotic resistance really due to increase in information? 22 October 2001; reposted and updated 11 November 2006 In 2001, the responses by Dr Jonathan Sarfati to the PBS Evolution propaganda series induced mainly favorable responses [and were later incorporated into the book Refuting Evolution 2, right]. Order online This , from Mikko Ilmari N. of Finland, criticises the responses to the PBS series on Online chapter index ostensibly scientific grounds. He accuses CMI of bias, falsehood, and misinformation, but fails to back up his points.The only issue he does attempt to back up is a claim of information increase that caused increased resistance to antibiotics. But this once again fails to understand the key relationship between information and specified complexity. Once again, supposed evidence for evolution turns out to be better explained by the Creation/Fall model. His letter is printed with point-by-point responses by Dr Jonathan Sarfati (the author of the PBS responses) interspersed as per normal email fashion. MIN’s letter includes quotes from the PBS rebuttal, which are double-indented. Ellipses (…) at the end of one of the paragraphs signal that a mid-sentence comment follows, not an omission. Just noticed that your ministries have, by assistance of Australian creationist Jonathan Sarfati, responded to the PBS-TV seriesEvolution. The Australian creationist Jonathan Sarfati was not just offering assistance; it was part of his (my) job, since I’m part of Creation Ministries International. The responses have got multiple omissions and scientific errors, … Really? Let’s see if that claim stands up to scrutiny. No special problems. I just noticed that [CMI] has provided misinformation in its PBS-“rebuttals”, and I suspect that reason for doing so is [CMI’s] fundamentalist-Christian bias, strictly requiring separately created species, young earth and many other features with which, [CMI’s] personnel sure is also familiar with. As covered above, CMI staff are not the only ones with biases. It’s just a convenient excuse to avoid having to actually refute the scientific evidence for a young Earth. Note also, as shown in Q&A: Speciation, we do not believe that every one of today’s species was separately created. Rather we predict rapid speciation within a created kind, not requiring any new genetic information but instead recombinations of already existing information and information-losing mutations. I’ll take Sarfati’s writings of poison newts as an example: (from [this page], actually) Poison newt The program moves to Oregon, where there were mysterious deaths of campers, with newts found in their sleeping bags. It turns out that these Rough-skinned Newts (Taricha granulosa) secrete a deadly toxin from their skin glands, so powerful that even a pinhead can kill an adult human. They are the deadliest salamanders on Earth. So scientists investigated why this newt should have such a deadly toxin. Up to this point, still OK. They theorized that a predator was driving this ‘evolution’, and they found that the Common Garter Snake (Thamnophis sirtalis) was the newt’s only predator. Most snakes will be killed, but the Common Garter Snake just loses muscle control for a few hours, which could of course have serious consequences. Here the Evolution-program makes a good point how scientific research of evolution can be done, with satisfying results, indeed. And as I pointed out, the assumption of goo-to-you evolution was unnecessary and in fact is irrelevant—this is perfectly well explained by the Creation/Fall model. Note that the creationist Edward Blyth talked about natural selection 25 years before Darwin wrote Origin. But the newts were also driving the ‘evolution’ of the snakes-they also had various degrees of resistance to the newt toxin. Are their conclusions correct? Yes, they are probably correct that the predators and prey are driving each other’s changes, and that they are the result of mutations and natural selection. Although this might surprise the ill-informed anti-creationist, this shouldn’t be so surprising to anyone who understands the young age model. Why the involvement of mutations and natural selection should surprise so-called “ill-informed anti-creationists”? Because they present a caricature of creationism that pretends that we believe in fixity of species. So is this proof of particles-to-people evolution? Not at all. There is no proof that the changes increase genetic information. In fact, the reverse seems to be true. [CMI’s] text slips into obvious falsehoods. The main point of the Evolution-program here is that (a) other species form large part of the environment of one species, … Since when did we deny this? The problem is, this has nothing to do with particles-to-people evolution. So where is the ‘obvious falsehood’?

… (b) mutations, recombinations and natural selection is the clue how the species absorbs information from it's environment thru generations following each other. This is gobbledygook. There is no information from the environment to absorb! One wonders what meaning you assign to the term information. I have a fair idea where you picked up this nonsense, and the source of this misinformation is refuted in detail by the article The Problem of Information for the Theory of Evolution <www.trueorigin.org/dawkinfo.asp>. (As a side point, it is very important to notice that this increase of information in a species does not conflict the Second Law of Thermodynamics, as life on planet Earth is energetically open system.) As a Ph.D. physical chemist, needing no instruction in thermodynamics, I’m always amused by anticreationists, mainly biologists and geologists, who think they know something about this topic, when they obviously don’t. As I point out in The Second Law of Thermodynamics Answers to Critics, an open system is necessary but not sufficient for an increase in information content. Since the PBS episode provides no explanation of the poison’s activity, it’s fair to propose a possible scenario (it would be hypocritical to object, since evolutionists often produce far more hypothetical ‘just-so’ stories): suppose the poison normally reacts with a particular neurotransmitter to produce something that halts all nerve impulses, resulting in death. But if the snake had a mutation reducing production of this the neurotransmitter, so the poison has fewer targets to act upon. Another possibility is a mutation altering its precise structure so that its shape no longer matches the protein. Either way, the poison would be less effective. But either reduced production of the neurotransmitter or a less precise shape, slow nerve impulses, meaning that muscle movement is slower. Rather than producing these “just-so” stories and trying to dig an excuse to do so from “evolutionists”, … This was perfectly legitimate given the available information. It is far more legitimate than the evolutionary just-so stories that you evidently tolerate, because my explanation of an information-losing mutation is based on the observed fact that the more resistant snakes suffer from a disability. … could [CMI] PLEASE make a note that protein structures can be examined to see if these more-effective poisons actually show loss of information or less-complicated structures than less-effective poisons. Indeed they can be, and in every case they have shown a reduced specificity, which may be beneficial. So please provide actual evidence—patronising assertions are unimpressive. Indeed, I have come across the similar kind of (creationist) claim than yours about antibiotic resistence earlier. Finnish creationist Dr. Pekka Reinikainen claimed that bacteria with better antibiotic resistence always show having less information or simpler structure. I haven’t heard of Dr Reinikainen, but from the limited amount of information you provide, he seems to know what he’s talking about. An article from a popular science magazine, concerning this antibiotic-resistence showed that Reinikainen had it wrong. Increase of information and new structural complexity has been observed in not just some, but in fact, many cases. As will be shown, you have failed to demonstrate this in even one case! You would benefit by reading Dr Spetner’s book (Not by chance!) and his more detailed explanations of information in of specified complexity (Part 1 <www.trueorigin.org/spetner1.asp> & Part 2<www.trueorigin.org/spetner2.asp>)—True Origins site, also hyperlinked on Q&A: Information. The original magazine (which is not at hand now) was a Finnish popular scientific magazine Tiede 2000 i.e. Science 2000. It had some non-technical examples of antibiotic resistance which however showed clearly that in many cases we cannot honestly call the evolution of antibiotic resistance, "a loss of information". Instead, I have put (as an attachment) an article by Petrosino, Cantu and Palzkoll, titled “β-Lactamases: protein evolution in real time” This was Trends in Microbiology 6(8):323–327, August 1998. Some bacteria produce β-Lactamases to destroy β-Lactam antibiotics, which include penicillin. You may “judge” it and check if it’s always about “loss of information” as frequently claimed by some creationists. (Or maybe you accept increased information by evolution in this case without any further problems … your original article was about poisonous newts, indeed.) Right, I read this paper as you requested. But despite its title, it does not your points, but ours! For example, one mechanism featured in the article was acquisition of genes from other bacteria. I.e. the genes already existed—hopefully it should be obvious that this is irrelevant to the origin of these genes in the first place, which is what goo-to-you evolution is supposed to explain! The other clue is the statement ‘many of the mutations located around the active site pocket result in increased catalytic activity for hydrolysis of extended-spectrum substrates.’ Mutations far from the active site also increase extended spectrum catalysis. This provided an advantage to the bacteria containing these mutations, because they could destroy more types of antibiotics. But here was yet another example of an information loss conferring an advantage. To understand this properly, it’s necessary to realize enzymes are usually tuned very precisely to only onetype of molecule (the substrate), and this fine-tuning is necessary for living cells to function. Mutationsreduce specificity and hence would reduce the effectiveness of its primary function, but would enable it to degrade other substrates too. But this loss of specificity means loss of information content. Dr Spetner analyzes this with rigorous mathematics using standard definitions of information. He presents the two extremes:An enzyme has activity for only one substrate out of n possible ones and zero for the others— here the information gain is log2n.The second is where there is no discrimination between any of the substrates—here the information gain is zero.Real enzymes are somewhere in between, and Dr Spetner shows how to calculate their information. As explained above, living organisms require enzymes to do a specific job, so their information content is very close to the maximum in case 1. Quite close to the other extreme Comparison of ribitol, xylitol and arabitolactivities of wild are ordinary acids or alkalis, which hydrolyse many compounds. and mutant ribitol dehydrogenase (from Lee These have wonderful extended-spectrum catalytic activity, but Spetner, True Origins website). are not specific, so have low information content, so would be useless for the precise control required for biological reactions. All observed mutations reduce the specificity and trend towards the second extreme case. The trend described in the βLactamases is just the same as that described in ribitol dehydrogenase, the enzyme some bacteria use to metabolize ribitol,

a derivative of a type of sugar (left). That is, the mutant acquired the new ability to metabolize xylitol, so it was thought to be an example of new information arising, and that it could trend towards a highly specific xylitol dehydrogenase. But on further inspection, it turned out not only toreduce its ability to perform its original specific function of metabolizing ribitol, but also to increase the ability to synthesize lots of other things, including arabitol. The trend is towards loss of specificity and producing an ordinary broad-spectrum catalyst, i.e. from case 1 to case 2. A graph of wild v. mutant β-Lactamase activity on various antibiotics would be essentially the same as this graph of wild v. mutant ribitol dehydrogenase activity on the different types of sugars.In conclusion, there is nothing to any information gain at all. But evolution posits that the information content of the simplest living organisms, the mycoplasma with 580,000 ‘letters’ (482 genes), was increased to, say, the 3 billion letters equivalent in man. If this were so, we should be able to observe plenty of examples of information gain without intelligent input. But we have yet to observe even one, including the example you cited. WHAT IS THE DIFFERENCES BETWEEN ORDER AND COMPLEXITY The treasures of the snow Do pretty crystals prove that organization can arise spontaneously? by Martin Tampier Snow crystals are some of the most beautiful shapes that nature has to offer, and no two flakes are alike. Many evolutionists have tried to claim the order of a crystal forming due to atomic structures as proof for “something coming out of nothing”, due simply to natural laws. But closer examination of this argument shows it does not hold up to scientific scrutiny. Modern snowflake research Several scientists are trying to grow their own crystals to understand and direct their development. Applications of this research reach way beyond meteorology, with the aim of controlling the growth of other crystals, such as silicon structures, for the semiconductor industry. [Snowflake] shape is due to the properties of their building blocks, the water molecules (H 2O). So why do snow crystals form this shape? Does it require special design? No, their shape is due to the properties of their building blocks, the water molecules (H 2O). These are bent and polar (i.e. with positively and negatively charged ends). When they come together in solid form, they tend to form the lowest-energy structure they can, 1 which is crystals with hexagonal (six-fold) symmetry.2 By contrast, carbon dioxide (CO2), a linear and more symmetrical molecule, forms cubic crystals in its solid form (“dry ice”).We now know that not only temperature, but also humidity influences crystal formation and shape. The beautiful six-legged star-like crystals grow in air warmer than -3°C. Between -3°C and -10°C, snow falls as little prisms. Between -10°C and -22°C, it is little stars again, and below that, prisms once more. Nevertheless, scientists still cannot tell exactly why snow crystal shapes change so much with temperature. These shapes depend on how water vapour molecules are incorporated into the growing ice crystal, and the physical processes governing crystal growth are complex and not well understood yet.3 Snowflakes—proof of evolution?4 Photo by Martin Tampier Sometimes evolutionists claim that snowflakes show that order can arise from disorder, and more complex structures from simple ones, based purely on the inherent physical properties of matter. Therefore, the reasoning goes, life could have arisen from simple molecules that organize themselves in a way that ultimately leads to more complex structures, and eventually the first living cell.5But crystals are nothing like a living cell. Formed by the withdrawal of heat from water, they are dead structures that contain no more information than is in their component parts, the water molecules. Life forms, on the other hand, came into Fun stuff existence, evolutionists An excellent snowflake website is believe, through the addition of heat energy to some postulated primordial soup. Not www.snowcrystals.com. only are these processes very different, but life requires the emergence of new You can and use many information (a code) in order to take over the functions of organization and snowflake photos to create your reproduction of a cell. There is therefore no analogy between snow crystals and the own calendar, greeting card or far, far greater complexity of living organisms. other present. Apart from More importantly, the organization in proteins and DNA is not caused by the beautiful photos, the site will tell properties of the constituent amino acids and nucleotides themselves, any more you just about everything you than forces between ink molecules make them up into letters and words. ever wanted to know about Michael Polanyi (1891–1976), a former chairman of physical chemistry at the snowflakes. University of Manchester (UK) who turned to philosophy, confirmed this: “As the arrangement of a printed page is extraneous to the chemistry of the printed page, so is the base sequence in a DNA molecule extraneous to the chemical forces at work in the DNA molecule. It is this physical indeterminacy of the sequence that produces the improbability of occurrence of any particular sequence and thereby enables it to have a meaning—a meaning that has a mathematically determinate information content …”.6Snow crystals are not direct evidence for creation, either. Nevertheless, the philosophical argument can be made that a universe without a designer cannot logically be expected to create such order out of disorder.7 So when we observe order and design in the universe, as exemplified by the six-cornered snowflake, doesn’t this demand a designer who supplies this order and design?8Of course, the physical properties of water are known to be necessary preconditions for life to exist on Earth, which testifies to a designer who conceived the universe and its physical laws as conducive to life. 9 For example, snow forms an insulating layer on the ground that protects plants and animals below it from the much harsher temperatures above. But whereas this could have been achieved with very simple shapes, such as round or square disks, the lavish beauty and variety in snow crystals shows the designer`s loving creativity in making snow not only very useful,

but also wonderful to look at! As even evolutionists it, “One could almost convince oneself that snowflakes constitute a demonstration of supernatural power.”5 No two alike? Actually, smaller snowflakes that take the shape of hexagonal prisms look pretty much the same. On the other hand, larger, star-shaped crystals are all different. To understand why, think of how many different ways 15 books can be arranged on a bookshelf. You have 15 choices for the first book, 14 for the second, 13 for the third, etc. The total number of possibilities is thus 15 × 14 × 13 … (15!), or over a trillion ways to arrange those books. Crystals can easily have 100 or more features that can be recombined in different ways—leading to at least a staggering 10158 different possibilities. This is 1070 times the number of atoms in the entire universe!1 Adapted from www.its.caltech.edu/~atomic/snowcrystals/alike/alike.htm.

The Snowflake Man from Vermont Astronomer Johannes Kepler seems to have been the first scientist to examine snow crystals. He wrote a booklet on the subject in 1611.1 But the real ‘Snowflake Man’ was Wilson Alwyn Bentley, born 1865 in Vermont, USA. Bentley was the first to photograph snowflakes.2 He published more than 5,000 photographs, and wrote numerous articles on snow, rain, dew and other natural phenomena related to water and precipitation.WA Bentley was the first to photograph snowflakes. He dedicated his life to studying snow, dew and rain and although he was a farmer without formal scientific training, he was years ahead of his time with his meteorological hypotheses.Bentley relates that it was his mother who instilled the love of scientific investigation into him: he was home schooled until he was 14 years old, and in his quest for learning he even read an encyclopedia! ‘It was my mother that made it possible for me, at fifteen, to begin the work to which I have devoted my life. She had a small microscope, which she had used in her school teaching. When the other boys of my age were playing with popguns and sling-shots, I was absorbed in studying things under this microscope: drops of water, tiny fragments of stone, a feather dropped from a bird’s wing, a delicately veined petal from some flower. But always, from the very beginning, it was snowflakes that fascinated me most.’Bentley knew nothing about photography and for the longest time could not manage to take pictures of snowflakes. But through persistence and learning by trial and error he learned how to work rapidly before the ice crystal changed shape, how to use transmitted light by pointing the camera to the sky, and how to get sharpness of detail on the crystal by using a large f-stop. Finally, during a January snowstorm in 1885, he obtained the first photomicrographs ever taken of an ice crystal.He kept detailed meteorological records, and pondered over the meaning of the shapes and sizes of the crystals and why they often varied from one storm to the next. Starting in 1898, he published his findings in scientific journals. Bentley greatly contributed to what is today common knowledge, i.e. that temperature changes and movements in the storm clouds impact on the form and type of the crystals formed. With his research, he was years ahead of the meteorological thinking of his time.Bentley loved people, but was misunderstood by them, and the scientific world appreciated (or caught up with) the value of his work only much later. When he convened a meeting in his hometown to present on his work, only six people attended.One of his National Geographic (Jan. 1923) articles, ‘The magic beauty of snow and dew’, is accompanied by over 100 photomicrographs of ice crystals, frost patterns, and dew. 3 Although his photos were sold for jewellery and other purposes, Bentley did not become rich through his work. But he said that he would not change places with Ford or Rockefeller: he felt he was serving the Great Designer; capturing the evanescent loveliness which, but for him, would be unappreciated—even unseen by most of his fellow men. And with that role he was content. When he died of pneumonia in 1931, his obituary read, ‘Truly, greatness blooms in quiet corners and flourishes under strange circumstances. For Wilson Bentley was a greater man than many a millionaire who lives in luxury of which the ‘Snowflake Man’ never dreamed.’ Creation question: Snowflakes Editor’s note: As Creation magazine has been continuously Chilling Facts published since 1978, we are publishing some of the articles from Snow covers about 23 per cent of the Earth's the archives for historical interest, such as this. For teaching and surface—permanently or temporarily. sharing purposes, readers are advised to supplement these The lowest air temperature ever recorded was at historic articles with more up-to-date ones available by Vostok II in Antarctica, 3,420 metres (11,218 feet) searching creation.com. above sea level. The temperature dropped to Q:‘Snowflakes show beautiful design patterns, which appear highly -88.3 degrees Celsius (-127 degrees ordered, and which arise by themselves under simple freezing Fahrenheit).The size and shape of snow crystals conditions. Since this shows order arising from disorder, doesn’t depend mainly on the temperature of their this mean that the ordered patterns of complex life could arise from formation and the amount of water vapour simpler chemicals?’ However, there is no tendency for simple organic molecules to available at deposition. At temperatures between 0 A: In themselves form fact, there isinto no parallel the precise between sequences the two needed issues attoall. form To put the and 3 degrees Celsius, thin hexagonal plates it simply, water long-chain information-bearing forming snowflakes molecules is 'doing found whatincomes living naturally', systems. form. Between -3 and -5 degrees, needles form. At given isthe That because properties the properties of the system. of theThere 'finished is no product' need for are any not -25 to -30 degrees, the crystal shape is hollow external information programmed in the components or programming of thetosystem. be added It takes to the thesystem— addition prism. thesome of existing extra properties information—either of the waterbymolecule an intelligent and the mind atmospheric at work or conditions a programmed are machine. enough to What give would risebe inevitably analogous to snowflake-type is if you saw a patterns. doily crocheted into the pattern of a snowflake. There is no natural, spontaneous tendency for the components of the system (for example, wool or cotton fibres) to assume that shape. The pattern has to be imposed by external information—either by the operation of mind or a programmed machine.So whenever you see a snowflake doily, you instinctively recognize this fact and see it as the result of creation, as you should when you contemplate a section of a chromosome—the raw ingredients are not sufficient without a source of information. In living things, that information has come from the parent organism (a programmed mechanism) which arose from its parent which arose.... You might find that the doily has been crocheted by a programmed machine in a factory, which might itself have been built by another machine—but eventually that information had to arise in amind. A snowflake pattern as water freezes may appear beautiful, but it is not the same thing at all, because no external programming or information has to be applied.A similar issue (sometimes raised by evolutionists who should know better) is that of salt crystal formation as a warm 1. ABCABCABCABCABCABCABC 2. A CAT SAT ON THE MAT Both are 'ordered', but only type 2 resembles the ordering in, say, a protein molecule. Chop the first sequence in half, and the two halves are essentially the same. Break a crystal of salt in two, and you see the same effect. Chop a protein (for

example haemoglobin) molecule in half and you no longer have haemoglobin—the two halves don't resemble one another. That is because the ordering is like that in the type 2 example above—chop that sentence in half and it loses all its meaning. To put it another way, as a salt crystal grows and grows, it is like continuing the type 1 sequence above. The sequence gets longer, the crystal gets bigger (simply more of the same), but not more complex. For simple organisms to become more complex (or simple chemicals to become a living thing) would be like the type 2 sentence becoming a whole story about cats, for example. CONCLUSION To compare snowflake or salt crystal formation to any assumed evolutionary growth in complexity is like comparing chalk with cheese. Examining the two simply highlights the need for external information before biological order will arise—which is a strong argument for creation. HOW DOES INFORMATION THEORY CREATION? Information, science and biology by Werner Gitt Summary Energy and matter are considered to be basic universal quantities. However, the concept of information has become just as fundamental and far-reaching, justifying its categorisation as the third fundamental quantity. One of the intrinsic characteristics of life is information. A rigorous analysis of the characteristics of information demonstrates that living things intrinsically reflect both the mind and will of their designer. Information confronts us at every turn both in technological and in natural systems: in data processing, in communications engineering, in control engineering, in the natural languages, in biological communications systems, and in information processes in living cells. Thus, information has rightly become known as the third fundamental, universal quantity. Hand in hand with the rapid developments in computer technology, a new field of study—that of information science—has attained a significance that could hardly have been foreseen only two or three decades ago. In addition, information has become an interdisciplinary concept of undisputed central importance to fields such as technology, biology and linguistics. The concept of information therefore requires a thorough discussion, particularly with regard to its definition, with understanding of its basic characteristic features and the establishment of empirical principles. This paper is intended to make a contribution to such a discussion. Information: a statistical study With his (1948) paper entitled ‘A Mathematical Theory of Communication’, Claude E. Shannon was the first to devise a mathematical definition of the concept of information. His measure of information which is given in bits (binary digits), possessed the advantage of allowing quantitative statements to be made about relationships that had previously defied precise mathematical description. This method has an evident drawback, however: information according to Shannon does not relate to the qualitative nature of the data, but confines itself to one particular aspect that is of special significance for its technological transmission and storage. Shannon completely ignores whether a text is meaningful, comprehensible, correct, incorrect or meaningless. Equally excluded are the important questions as to where the information comes from (transmitter) and for whom it is intended (receiver). As far as Shannon’s concept of information is concerned, it is entirely irrelevant whether a series of letters represents an exceptionally significant and meaningful text or whether it has come about by throwing dice. Yes, paradoxical though it may sound, considered from the point of view of information theory, a random sequence of letters possesses the maximum information content, whereas a text of equal length, although linguistically meaningful, is assigned a lower value.The definition of information according to Shannon is limited to just one aspect of information, namely its property of expressing something new: information content is defined in of newness. This does not mean a new idea, a new thought or a new item of information—that would involve a semantic aspect—but relates merely to the greater surprise effect that is caused by a less common symbol. Information thus becomes a measure of the improbability of an event. A very improbable symbol is therefore assigned correspondingly high information content.Before a source of symbols (not a source of information!) generates a symbol, uncertainty exists as to which particular symbol will emerge from the available supply of symbols (for example, an alphabet). Only after the symbol has been generated is the uncertainty eliminated. According to Shannon, therefore, the following applies: information is the uncertainty that is eliminated by the appearance of the symbol in question. Since Shannon is interested only in the probability of occurrence of the symbols, he addresses himself merely to the statistical dimension of information. His concept of information is thus confined to a non-semantic aspect. According to Shannon, information content is defined such that three conditions must be fulfilled: Summation condition: The information contents of mutually independent symbols (or chains or symbols) should be capable of addition. The summation condition views information as something quantitative. Probability condition: The information content to be ascribed to a symbol (or to a chain of symbols) should rise as the level of surprise increases. The surprise effect of the less common ‘z’ (low probability) is greater than that of the more frequent ‘e’ (high probability). It follows from this that the information content of a symbol should increase as its probability decreases. The bit as a unit of information: In the simplest case, when the supply of symbols consists of just two symbols, which, moreover, occur with equal frequency, the information content of one of these symbols should be assigned a unit of precisely 1 bit. The following empirical principle can be derived from this: Theorem 1: The statistical information content of a chain of symbols is a quantitative concept. It is given in bits (binary digits).According to Shannon’s definition, the information content of a single item of information (an item of information in this context merely means a symbol, character, syllable, or word) is a measure of the uncertainty existing prior to its reception. Since the probability of its occurrence may only assume values between 0 and 1, the numerical value of the information content is always positive. The information content of a plurality of items of information (for example, characters) results (according to the summation condition) from the summation of the values of the individual items of information. This yields an important characteristic of information according to Shannon: Theorem 2: According to Shannon’s theory, a disturbed signal generally contains more information than an undisturbed signal, because, in comparison with the undisturbed transmission, it originates from a larger quantity of possible alternatives. Shannon’s theory also states that information content increases directly with the number of symbols. How inappropriately such a relationship describes actual information content becomes apparent from the following situation: If someone uses many words to say virtually nothing, then, according to Shannon, in accordance with the large number of letters, this utterance is assigned a very high information content, whereas the utterance of another person, who is skilled in expressing succinctly that which is essential, is ascribed only a very low information content.Furthermore, in its equation of information content, Shannon’s theory uses the factor of entropy to take of the different frequency distributions of the letters.

Entropy thus represents a generalised but specific feature of the language used. Given an equal number of symbols (for example, languages that use the Latin alphabet), one language will have a higher entropy value than another language if its frequency distribution is closer to a uniform distribution. Entropy assumes its maximum value in the extreme case of uniform distribution. Symbols: a look at their average information content If the individual symbols of a long sequence of symbols are not equally probable (for example, text), what is of interest is the average information content for each symbol in this sequence as well as the average value over the entire language. When this theory is applied to the various code systems, the average information content for one symbol results as follows: In the German language: I = 4.113 bits/letter In the English language: I = 4.046 bits/letter In the dual system: I = 1 bit/digit In the decimal system: I = 3.32 bits/digit In the DNA molecule: I = 2 bits/nucleotide The highest information density The highest information density known to us is that of the DNA (deoxyribonucleic acid) molecules of living cells. This chemical storage medium is 2 nm in diameter and has a 3.4 nm helix pitch (see Figure 1). This results in a volume of 10.68 x 10-21 cm3 per spiral. Each spiral contains ten chemical letters (nucleotides), resulting in a volumetric information density of 0.94 x 1021 letters/cm3. In the genetic alphabet, the DNA molecules contain only the four nucleotide bases, that is, adenine, thymine, guanine and cytosine. The information content of such a letter is 2 bits/nucleotide. Thus, the statistical information density is 1.88 x 1021 bits/cm3.Proteins are the basic substances that compose living organisms and include, inter alia, such important compounds as enzymes, antibodies, haemoglobins and hormones. These important substances are both organand species-specific. In the human body alone, there are at least 50,000 different proteins performing important functions. Their structures must be coded just as effectively as the chemical processes in the cells, in which synthesis must take place with the required dosage in accordance with an optimised technology. It is known that all the proteins occurring in living organisms are composed of a total of just 20 different chemical building blocks (amino acids). The precise sequence of these individual building blocks is of exceptional significance for life and must therefore be carefully defined. This is done with the aid of the genetic code. Shannon’s information theory makes it possible to determine the smallest number of letters that must be combined to form a word in order to allow unambiguous identification of all amino acids. With 20 amino acids, the average information content is 4.32 bits/amino acid. If words are made up of two letters (doublets), with 4 bits/word, these contain too little information. Quartets would have 8 bits/word and would be too complex. According to information theory, words of three letters (triplets) having 6 bits/word are sufficient and are therefore the most economical method of coding. Binary coding with two chemical letters is also, in principle, conceivable. This however, would require a quintet to represent each amino acid and would be 67 per cent less economical than the use of triplets.

Figure 1. The DNA molecule—the universal storage medium of natural systems. A short section of a strand of the double helix with sugar-phosphate chain reveals its chemical structure (left). The schematic representation of the double helix (right) shows the base pairs coupled by hydrogen bridges (in a plane perpendicular to the helical axis). Computer chips and natural storage media Figures 1, 2 and 3 show three different storage technologies: the DNA molecule, the core memory, and the microchip. Let’s take a look at these. Core memory: Earlier core memories were capable of storing 4,096 bits in an area of 6,400 mm 2 (see Figure 2). This corresponds to an area storage density of 0.64 bits/mm 2. With a core diameter of 1.24 mm (storage volume 7,936 mm 3), a volumetric storage density of 0.52 bits/mm3 is obtained.

Figure 2. Detail of the TR440 computer’s core-memory matrix (Manufacturer: Computer Gesellschaft Konstanz). 1-Mbit DRAM: The innovative leap from the core memory to the semiconductor memory is expressed in striking figures in of storage density; present-day 1-Mbit DRAMs (see Figure 3) permit the storage of 1,048,576 bits in an area of approximately 50 mm2, corresponding to an area storage density of 21,000 bits/mm 2. With a thickness of approximately 0.5 mm, we thus obtain a volumetric storage density of 42,000 bits/mm 3. The megachip sures the core memory in of area storage density by a factor of 32,800 and in of volumetric storage density by a factor of 81,000.

Figure 3. The 1-Mbit DRAM—a dynamic random-access memory for 1,048,576 bits. DNA molecule: The carriers of genetic information, which perform their biological functions throughout an entire life, are nucleic acids. All cellular organisms and many viruses employ DNAs that are twisted in an identical manner to form double helices; the remaining viruses employ single-stranded ribonucleic acids (RNA). The figures obtained from a comparison with man-made storage devices are nothing short of astronomical if one includes the DNA molecule (see Figure 1). In this super storage device, the storage density is exploited to the physico-chemical limit: its value for the DNA molecule is 45 x 1012 times that of the megachip. What is the explanation for this immense difference of 45 trillion between VLSI technology and natural systems? There are three decisive reasons:The DNA molecule uses genuine volumetric storage technology, whereas storage in computer devices is area-oriented. Even though the structures of the chips comprise several layers, their storage elements only have a two-dimensional orientation.Theoretically, one single molecule is sufficient to represent an information unit. This most economical of technologies has been implemented in the design of the DNA molecule. In spite of all research efforts on miniaturisation, industrial technology is still within the macroscopic range.Only two circuit states are possible in chips; this leads to exclusively binary codes. In the DNA molecule, there are four chemical symbols (see Figure 1); this permits a quaternary code in which one state already represents 2 bits.The knowledge currently stored in the libraries of the world is estimated at 1018 bits. If it were possible for this information to be stored in DNA molecules, 1 per cent of the volume of a pinhead would be sufficient for this purpose. If, on the other hand, this information were to be stored with the aid of megachips, we would need a pile higher than the distance between the earth and the moon. The five levels of information Shannon’s concept of information is adequate to deal with the storage and transmission of data, but it fails when trying to understand the qualitative nature of information.Theorem 3: Since Shannon’s definition of information relates exclusively to the statistical relationship of chains of symbols and completely ignores their semantic aspect, this concept of information is wholly unsuitable for the evaluation of chains of symbols conveying a meaning.In order to be able adequately to evaluate information and its processing in different systems, both animate and inanimate, we need to widen the concept of

information considerably beyond the bounds of Shannon’s theory. Figure 4 illustrates how information can be represented as well as the five levels that are necessary for understanding its qualitative nature. Level 1: statistics Shannon’s information theory is well suited to an understanding of the statistical aspect of information. This theory makes it possible to give a quantitative description of those characteristics of languages that are based intrinsically on frequencies. However, whether a chain of symbols has a meaning is not taken into consideration. Also, the question of grammatical correctness is completely excluded at this level. Level 2: syntax In chains of symbols conveying information, the stringing-together of symbols to form words as well as the ing of words to form sentences are subject to specific rules, which, for each language, are based on consciously established conventions. At the syntactical level, we require a supply of symbols (code system) in order to represent the information. Most written languages employ letters; however, an extremely wide range of conventions is in use for various purposes: Morse code, hieroglyphics, semaphore, musical notes, computer codes, genetic codes, figures in the dance of foraging bees, odour symbols in the pheromone languages of insects, and hand movements in sign language.The field of syntax involves the following questions: Which symbol combinations are defined characters of the language (code)? Which symbol combinations are defined words of the particular language (lexicon, spelling)? How should the words be positioned with respect to one another (sentence formation, word order, style)? How should they be ed together? And how can they be altered within the structure of a sentence (grammar)?

Figure 4. The five mandatory levels of information (middle) begin with statistics (at the lowest level). At the highest level is apobetics (purpose). The syntax of a language, therefore, comprises all the rules by which individual elements of language can or must be combined. The syntax of natural languages is of a much more complex structure than that of formalised or artificial languages. Syntactical rules in formalised languages must be complete and unambiguous, since, for example, a compiler has no way of referring back to the programmer’s semantic considerations. At the syntactical level of information, we can formulate several theorems to express empirical principles: Theorem 4: A code is an absolutely necessary condition for the representation of information. Theorem 5: The assignment of the symbol set is based on convention and constitutes a mental process. Theorem 6: Once the code has been freely defined by convention, this definition must be strictly observed thereafter. Theorem 7: The code used must be known both to the transmitter and receiver if the information is to be understood. Theorem 8: Only those structures that are based on a code can represent information (because of Theorem 4). This is a necessary, but still inadequate, condition for the existence of information. These theorems already allow fundamental statements to be made at the level of the code. If, for example, a basic code is found in any system, it can be concluded that the system originates from a mental concept. Level 3: semantics Chains of symbols and syntactical rules form the necessary precondition for the representation of information. The decisive aspect of a transmitted item of information, however, is not the selected code, the size, number or form of the letters, or the method of transmission (script, optical, acoustic, electrical, tactile or olfactory signals), but the message it contains, what it says and what it means (semantics). This central aspect of information plays no part in its storage and transmission. The price of a telegram depends not on the importance of its contents but merely on the number of words. What is of prime interest to both sender and recipient, however, is the meaning; indeed, it is the meaning that turns a chain of symbols into an item of information. It is in the nature of every item of information that it is emitted by someone and directed at someone. Wherever information occurs, there is always a transmitter and a receiver. Since no information can exist without semantics, we can state: Theorem 9: Only that which contains semantics is information. According to a much-quoted statement by Norbert Wiener, the founder of cybernetics and information theory, information cannot be of a physical nature:‘Information is information, neither matter nor energy. No materialism that fails to take of this can survive the present day.’The Dortmund information scientist Werner Strombach emphasises the nonmaterial nature of information when he defines it as ‘an appearance of order at the level of reflective consciousness.’ Semantic information, therefore, defies a mechanistic approach. Accordingly, a computer is only ‘a syntactical device’ (Zemanek) which knows no semantic categories. Consequently, we must distinguish between data and knowledge, between algorithmically conditioned branches in a programme and deliberate decisions, between comparative extraction and

association, between determination of values and understanding of meanings, between formal processes in a decision tree and individual selection, between consequences of operations in a computer and creative thought processes, between accumulation of data and learning processes. A computer can do the former; this is where its strengths, its application areas, but also its limits lie. Meanings always represent mental concepts; we can therefore further state: Theorem 10: Each item of information needs, if it is traced back to the beginning of the transmission chain, a mental source (transmitter).Theorems 9 and 10 basically link information to a transmitter (intelligent information source). Whether the information is understood by a receiver or not does nothing to change its existence. Even before they were deciphered the inscriptions in Egyptian obelisks were clearly regarded as information, since they obviously did not originate from a random process. Before the discovery of the Rosetta Stone (1799), the semantics of these hieroglyphics was beyond the comprehension of any contemporary person (receiver); nevertheless, these symbols still represented information.All suitable formant devices (linguistic configurations) that are capable of expressing meanings (mental substrates, thoughts, contents of consciousness) are termed languages. It is only by means of language that information may be transmitted and stored on physical carriers. The information itself is entirely invariant, both with regard to change of transmission system (acoustic, optical, electrical) and also of storage system (brain, book, computer system, magnetic tape). The reason for this invariance lies in its non-material nature. We distinguish between different kinds of languages: Natural languages: at present, there are approximately 5,100 living languages on earth. Artificial or sign languages: Esperanto, sign language, semaphore, traffic signs. Artificial (formal) languages: logical and mathematical calculations, chemical symbols, shorthand, algorithmic languages, programming languages.Specialist languages in engineering: building plans, design plans, block diagrams, bonding diagrams, circuit diagrams in electrical engineering, hydraulics, pneumatics.Special languages in the living world: genetic language, the foraging-bee dance, pheromone languages, hormone language, signal system in a spider’s web, dolphin language, instincts (for example, flight of birds, migration of salmon).Common to all languages is that these formant devices use defined systems of symbols whose individual elements operate with fixed, uniquely agreed rules and semantic correspondences. Every language has units (for example, morphemes, lexemes, phrases and whole sentences in natural languages) that act as semantic elements (formatives). Meanings are correspondences between the formatives, within a language, and imply a unique semantic assignment between transmitter and receiver.Any communication process between transmitter and receiver consists of the formulation and comprehension of the sememes (sema = sign) in one and the same language. In the formulation process, the thoughts of the transmitter generate the transmissible information by means of a formant device (language). In the comprehension process, the combination of symbols is analysed and imaged as corresponding thoughts in the receiver. Level 4: pragmatics Up to the level of semantics, the question of the objective pursued by the transmitter in sending information is not relevant. Every transfer of information is, however, performed with the intention of producing a particular result in the receiver. To achieve the intended result, the transmitter considers how the receiver can be made to satisfy his planned objective. This intentional aspect is expressed by the term pragmatics. In language, sentences are not simply strung together; rather, they represent a formulation of requests, complaints, questions, inquiries, instructions, exhortations, threats and commands, which are intended to trigger a specific action in the receiver. Strombach defines information as a structure that produces a change in a receiving system. By this, he stresses the important aspect of action. In order to cover the wide variety of types of action, we may differentiate between:Modes of action without any degree of freedom (rigid, indispensable, unambiguous, program-controlled), such as program runs in computers, machine translation of natural languages, mechanised manufacturing operations, the development of biological cells, the functions of organs;Modes of action with a limited degree of freedom, such as the translation of natural languages by humans and instinctive actions (patterns of behaviour in the animal kingdom);Modes of action with the maximum degree of freedom (flexible, creative, original; only in humans), for example, acquired behaviour (social deportment, activities involving manual skills), reasoned actions, intuitive actions and intelligent actions based on free will.All these modes of action on the part of the receiver are invariably based on information that has been previously designed by the transmitter for the intended purpose. Level 5: apobetics The final and highest level of information is purpose. The concept of apobetics has been introduced for this reason by linguistic analogy with the previous definitions. The result at the receiving end is based atthe transmitting end on the purpose, the objective, the plan, or the design. The apobetic aspect of information is the most important one, because it inquires into the objective pursued by the transmitter. The following question can be asked with regard to all items of information: Why is the transmitter transmitting this information at all? What result does he/she/it wish to achieve in the receiver? The following examples are intended to deal somewhat more fully with this aspect:Computer programmes are target-oriented in their design (for example, the solving of a system of equations, the inversion of matrices, system tools).With its song, the male bird would like to gain the attention of the female or to lay claim to a particular territory.With the advertising slogan for a detergent, the manufacturer would like to persuade the receiver to decide in favour of its product.Humans are endowed with the gift of natural language; they can thus enter into communication and can formulate objectives. We can now formulate some further theorems: Theorem 11: The apobetic aspect of information is the most important, because it embraces the objective of the transmitter. The entire effort involved in the four lower levels is necessary only as a means to an end in order to achieve this objective. Theorem 12: The five aspects of information apply both at the transmitter and receiver ends. They always involve an interaction between transmitter and receiver (see Figure 4). Theorem 13: The individual aspects of information are linked to one another in such a manner that the lower levels are always a prerequisite for the realisation of higher levels. Theorem 14: The apobetic aspect may sometimes largely coincide with the pragmatic aspect. It is, however, possible in principle to separate the two. Having completed these considerations, we are in a position to formulate conditions that allow us to distinguish between information and non-information. Two necessary conditions (NCs; to be satisfied simultaneously) must be met if information is to exist: NC1: A code system must exist. NC2: The chain of symbols must contain semantics. Sufficient conditions (SCs) for the existence of information are: SC1: It must be possible to discern the ulterior intention at the semantic, pragmatic and apobetic levels (example: Karl v. Frisch analysed the dance of foraging beesand, in conformance with our model, ascertained the levels of semantics, pragmatics and apobetics. In this case, information is unambiguously present).

SC2: A sequence of symbols does not represent information if it is based on randomness. According to G.J. Chaitin, an American informatics expert, randomness cannot, in principle, be proven; in this case, therefore, communication about the originating cause is necessary.The above information theorems not only play a role in technological applications, they also embrace all otherwise occurring information (for example, computer technology, linguistics, living organisms). Information in living organisms Life confronts us in an exceptional variety of forms; for all its simplicity, even a monocellular organism is more complex and purposeful in its design than any product of human invention. Although matter and energy are necessary fundamental properties of life, they do not in themselves imply any basic differentiation between animate and inanimate systems. One of the prime characteristics of all living organisms, however, is the information they contain for all operational processes (performance of all life functions, genetic information for reproduction). Braitenberg, a German cybernetist, has submitted evidence ‘that information is an intrinsic part of the essential nature of life.’ The transmission of information plays a fundamental role in everything that lives. When insects transmit pollen from flower blossoms, (genetic) information is essentially transmitted; the matter involved in this process is insignificant. Although this in no way provides a complete description of life as yet, it touches upon an extremely crucial factor.Without a doubt, the most complex information processing system in existence is the human body. If we take all human information processes together, that is, conscious ones (language, information-controlled functions of the organs, hormone system), this involves the processing of 10 24 bits daily. This astronomically high figure is higher by a factor of 1,000,000 than the total human knowledge of 10 18 bits stored in all the world’s libraries. The concept of information On the basis of Shannon’s information theory, which can now be regarded as being mathematically complete, we have extended the concept of information as far as the fifth level. The most important empirical principles relating to the concept of information have been defined in the form of theorems. Here is a brief summary of them:1 No information can exist without a code. No code can exist without a free and deliberate convention. No information can exist without the five hierarchical levels: statistics, syntax, semantics, pragmatics and apobetics. No information can exist in purely statistical processes. No information can exist without a transmitter. No information chain can exist without a mental origin. No information can exist without an initial mental source; that is, information is, by its nature, a mental and not a material quantity. No information can exist without a will. The marvellous ‘message molecule’ by Carl Wieland When someone sends a message, something rather fascinating and mysterious gets ed along. Let's say Alphonse in Alsace wants to send the message, 'Ned, the war is over. Al'. He dictates it to a friend; the message has begun as patterns of air compression (spoken words). His friend puts it down as ink on paper and mails it to another, who puts it in a fax machine. The machine transfers the message into a coded pattern of electrical impulses, which are sent down a phone line and received at a remote Indian outpost where it is printed out in letters once again. Here the person who reads the fax lights a campfire and sends the same message as a pattern of smoke signals. Old Ned in Nevada, miles away, looks up and gets the exact message that was meant for him. Nothing physical has been transmitted; not a single atom or molecule of any substance travelled from Alsace to Nevada, yet it is obvious thatsomething travelled all the way.This elusive something is called information. It is obviously not a material thing, since no matter has been transmitted. Yet it seems to need matter on which to 'ride' during its journey. This is true whether the message is in Turkish, Tamil or Tagalog. The matter on which information travels can change, without the information having to change. Air molecules being compressed in sound waves; ink and paper; electrons travelling down phone wires, semaphore signals—whatever—all involve material mediums used to transmit information, but the medium is not the information.This fascinating thing called information is the key to understanding what makes life different from dead matter. It is the Achilles' heel of all materialist explanations of life, which say that life is nothing more than matter obeying the laws of physics and chemistry. Life is more than just physics and chemistry; living things carry vast amounts of information.Some might argue that a sheet of paper carrying a written message is nothing more than ink and paper obeying the laws of physics and chemistry. But ink and paper unaided do not write messages—minds do. The alphabetical letters in a Scrabble® kit do not constitute information until someone puts them into a special sequence—mind is needed to get information. You can program a machine to arrange Scrabble® letters into a message, but a mind had to write the program for the machine.How is the information for life carried? How is the message which spells out the recipe that makes a frog, rather than a frangipani tree, sent from one generation to the next? How is it stored? What matter does it 'ride' on? The answer is the marvellous 'message molecule' called DNA. This molecule is like a long rope or string of beads, which is tightly coiled up inside the centre of every cell of your body. This is the molecule that carries the programs of life, the information which is transmitted from each generation to the next. *Some people think that DNA is alive—this is wrong. DNA is a dead molecule. It can't copy itself—you need the machinery of a living cell to make copies of a DNA molecule. It may seem as if DNA is the information in your body. Not so—the DNA is simply the carrier of the message, the 'medium' on which the message is written. In the same way, Scrabble® letters are not information until the message is 'imposed' on them from the 'outside'. Think of DNA as a chain of such alphabet letters linked together, with a large variety of different ways in which this can happen. Unless they are ed in the right sequence, no usable message will result, even though it is still DNA.Now to read the message, you need a pre-existing language code or convention, as well as machinery to translate it. All of that machinery exists in the cell. Like man-made machinery, it does not arise by itself from the properties of the raw materials. If you just throw the basic raw ingredients for a living cell together, without information nothing will happen. Machines and programs do not come from the laws of physics and chemistry by themselves. Why? Because they reflect information, and information has never been observed to come about by unaided, raw matter plus time and chance. Information is the very opposite of chance—if you want to arrange letters into a sequence to spell a message, a particular order has to be imposed on the matter.When living things reproduce, they transmit information from one generation to the next. This information, travelling on the DNA from mother and from father, is the 'instruction manual' which enables the machinery in a fertilized egg cell to construct, from raw materials, the new living organism—a fantastic feat. This is in a new combination so that children are not exactly like their parents, although the information itself, which is expressed in the make-up of those children, was there all along in both parents. That is, the deck was reshuffled, but no new cards were added.Just how much space does DNA need to store its information? The technological achievements of humankind in storing information seem sensational. Imagine how much information is stored on a videotape of a movie, for example—you can hold it all in one hand. Yet compared to this, the feat of information

miniaturization performed by DNA is nothing short of mind-blowing. For a given amount of information, the room needed to store it on DNA is about a trillionth of that for information on videotape—i.e. it is a million million times more efficient at storing information.1How much information is contained in the DNA code which describes you? Estimates vary widely. Using simple analogies, based upon the storage space in DNA, they range from 500 large library books of small-type information, to more than 100 complete 30 volume encyclopaedia sets. When you think about it, even that is probably not enough to specify the intricate construction of even the human brain, with its trillions of precise connections. There are probably higherlevel information storage and multiplication systems in the body that we have not even dreamed of yet—there are many more marvellous mysteries waiting to be discovered about the designer`s handiwork.Not only is the way in which DNA is encoded highly efficient—even more space is saved by the way in which it is tightly coiled up. According to genetics expert Professor Jérôme Lejeune, all the information required to specify the exact make-up of every unique human being on Earth could be stored in a volume of DNA no bigger than a couple of aspirin tablets! 2 If you took the DNA from one single cell in your body (an amount of matter so small you would need a microscope to see it) and unravelled it, it would stretch to two metres!This becomes truly sensational when you consider that there are 75 to 100 trillion cells in the body. Taking the lower figure, it means that if we stretched out all of the DNA in one human body 3 and ed it end to end, it would stretch to a distance of 150 billion kilometres (around 94 billion miles). How long is this? It would stretch right around the Earth's equator three-and-a-half million times! It is a thousand times as far as from the Earth to the sun. If you were to shine a torch along that distance, it would take the light, travelling at 300,000 kilometres (186,000 miles) every second, five-and-a-half days to get there.But the really sensational thing is the way in which the information carried on DNA in all living things points directly to intelligent, supernatural creation, by straightforward, scientific logic, as follows: Observations 1. The coded information used in the construction of living things is transferred from pre-existing messages (programs), which are themselves transmitted from pre-existing messages. 2. During this transfer, the fate of the information follows the dictates of message/information theory and common sense. That is, it either stays the same, or decreases (mutational loss, genetic drift, species extinction) but seldom, probably never, is it seen to increase in any informationally meaningful sense. Deduction from observation No. 2 3. Were we to look back in time along the line of any living population, e.g. humans (the information in their genetic programs) we would see an overall pattern of gradual increase the further back we go. Axiom 4. No population can be infinitely old, nor contain infinite information. Therefore: Deduction from points 3 and 4 5. There had to be a point in time in which the first program arose without a pre-existing program—i.e. the first of that type had no parents. Further observation 6. Information and messages only ever originate in mind or in pre-existing messages. Never, ever are they seen to arise from spontaneous, unguided natural law and natural processes. Conclusion The programs in those first representatives of each type of organism must have originated not in natural law, but in mind. This is totally consistent with the model, which teaches us that the programs for each of the original 'kind' populations, with all of their vast variation potential, arose from the mind of a designer at a point in time, by creation. These messages, written in intricate coded language, could not have written themselves, as far as real, observational science can tell us. Once the first messages were written, they also contained instructions to make machinery with which to transmit those messages 'on down the line'. DNA, this marvellous 'message molecule', carries that special, non-material something called information, down through many generations, from its origin in the mind of a designer. More or less information? / Has a recent experiment proved creation? Published: 17 February 2007 (GMT+10) Photo by José A. Warletta, from www.sxc.hu One of the most important creationist arguments concerns information. Understanding this issue deflects many anticreationist equivocations, calling any change ‘evolution’. That is, no creationist denies that things change, and even speciate, but nearly all the cited changes do not involve the increase in information content required for microbes-to-man evolution, but go in the wrong direction. See one illustration: How information is lost when creatures adapt to their environment.This week’s comes from Casey P who picked up from a website a vexatious question about how to define information. The evolutionist who first posed that question erred by presupposing a simplistic definition, while Andrew Lamb’s reply shows that there are more levels of information needed to understand its role in biology.The second addresses questions on a recent article about a research scientist whose work supposedly proves creation. However,Jonathan Sarfati had replied to a similar query in 1999 about the same phenomenon, and it is updated below. How do we define information in biology? Photo by Dacho Dachovic, from www.sxc.hu

I’m curious to know perhaps you could fill me in on this. Which one has the most information, and what exactly are these two sequences? Sequence 1: cag tgt ctt ggg ttc tcg cct gac tac Thanks for your help here. God bless. Casey P gag acg cgt ttg tct tta cag gtc ctc ggc cag cac Dear Mr P Thank you for your email of 17 January, submitted via ctt aga caa gca ccc ggg acg cac ctt tca gtg ggc our website. In response to creationist arguments about genetic act cat aat ggc gga gta cca agg agg cac ggt cca information, some evolutionists disingenuously object that since there is no one measure of information ttg ttt tcg ggc cgg cat tgc tca tct ctt gag att content applicable to all situations, therefore genetic information doesn’t exist! But even hardened atheists like the eugenicistRichard Dawkins recognize that DNA tcc ata ctt Sequence 2: tgg agt tct aag aca gta caa ctc tgc contains information. In fact there is a burgeoning new field of science called bio-informatics, which is all about genetic information. gac cgt gct ggg gta gcc act tct ggc cta atc tac With respect to the two sequences you presented, one would need to know their functions before it would be gtt aca gaa aat ttg agg ttg cgc ggt gtc ctc gtt possible to consider making a comparison about which sequence carried more information. If their functions agg cac aca cgg gtg gaa tgg ggg tct ctt acc aaa (assuming they were not just gobbledygook) were dissimilar, then it would be fairly meaningless to attempt ggg ctg ccg tat cag gta cga cgt agg tat tgc cgt a comparison of information content. For example if one was a genetic sequence coding for an enzyme, and the gat aga ctg other a genetic sequence coding for a structural protein, then to ask which has the most information would be as meaningless as asking, say, ‘which has more information—60 grams worth of apple or 60 grams worth of orange’. If the meaning/function is similar, then an information-content comparison may be possible. Consider the following two sequences: She has a yellow vehicle. She has a yellow car. Both are English sentences. The first is 25 characters long, and the second is 21 characters long. The first sentence has more characters, but the second sentence has more information, because it is more specific (cars being just one of scores of different types of vehicle), andspecificity is one measure of information content. Specificity only relates to the purpose of the information, not to the way it is expressed or the size of the message when it is expressed in some particular way/language.There are five levels of information content (after Information, Science and Biology by Dr Werner Gitt, information scientist): statistics (symbols and their frequencies) syntax (patterns of arrangement of symbols) semantics (meaning) pragmatics (function/result/outcome) apobetics (purpose/plan/design) Specificity relates to the pragmatics or apobetics level. Gitt’s Theorem 9 states that ‘Only that which contains semantics is information’. This is a crucial point. Many evolutionists err by restricting information measurement to the statistical level, or to ‘Shannon information’. So-called ‘Shannon information’ is not a measure of information per se, but merely a measure of the minimum number of characters/units needed to represent a sequence, regardless of whether the sequence is meaningful or not. Gobbledygook can have more ‘Shannon information’ than a sentence in English.So, if the two sequences you presented were composed randomly, then it is highly unlikely that either contains any information. However, for argument’s sake, I will assume that they may be meaningful, and compare them.The two sequences both contain the same amount of statistical information, 240 characters worth, when represented in text.Both sequences appear the same at the syntactical level, i.e. both consist of 60 spaced triplets composed of the symbols c, a, t, and g.At the semantic level, I recognize that these letter triplets are the same as ones used to represent triplets of DNA bases that code for particular amino acids. Since all 64 possible triplets have a meaning in the DNA code, and since neither sequence contains any of the three ‘stop codes’ (taa, tga, tag), it follows that both sequences could be regarded as having the same amount of information at the semantic level, since, if processed by the appropriate genetic machinery, both sequences could probably produce a segment of protein 60 amino acids in length. However, when it comes to the pragmatics level, as far as I can determine (being unable to locate these sequences in a gene library such asNCBI’s Entrez Nucleotides) both sequences apparently carry the same amount of meaningful

information—zilch.At the apobetics level, I have no idea what outcomes would result from processing of the two sequences. Conceivably, at one extreme, they could result in production of an enzyme that kills the cell, or even a toxin that kills the organism to which the cell belongs. At the other extreme, they could (for all I know) prevent aging, thus extending the lifespan—I have no idea. Indeed, one of the most intractable problems in molecular biology is computing the final protein configuration from an amino acid sequence (see a current project).Note also that each creature has its own unique set of cellular machinery, so the outcomes that result from the reading of these genetic sequences could be very different depending on which organism’s genetic machinery reads them. For example the genetic sequence found in the HIV virus is harmless when read by the cellular machinery in ape’s cells, but ultimately lethal when read by human cellular machinery— very different outcomes at the apobetics level from the same genetic sequence. Also, there are some organisms with slightly different genetic codes, so the same semantic information would be read differently resulting in different pragmatic and apobetic information.The final protein configuration that results from a particular DNA sequence is mainly determined by cellular machines of a type calledchaperonins, which influence protein folding. Without chaperonins, an important protein might mis-fold into a deadly prion. This is the likely cause of the fatal brain conditions Creutzfeldt–Jakob disease and bovine spongiform encephalopathy (BSE) aka mad cow disease (Discoveries that undermine the one gene → one protein idea).I hope this helps. We have many articles on our website on the issue of information in living organisms. They can be found listed under the topic ‘Information Theory’ in the Frequently Asked Questions index on this website. Yours sincerely Andrew Lamb Information Officer How is information content measured? New plant colours—is this new information? Is antibiotic resistance really due to increase in information? The Problem of Information for the Theory of Evolution: Has Dawkins really solved it? Life’s irreducible structure—Part 1: autopoiesis by Alex Williams The commonly cited case for intelligent design appeals to: (a) the irreducible complexity of (b) some aspects of life. But complex arguments invite complex refutations (valid or otherwise), and the claim that only someaspects of life are irreducibly complex implies that others are not, and so the average person remains unconvinced. Here I use another principle— autopoiesis (self-making)—to show that all aspects of life lie beyond the reach of naturalistic explanations. Autopoiesis provides a compelling case for intelligent design in three stages: (i) autopoiesis is universal in all living things, which makes it a pre-requisite for life, not an end product of natural selection; (ii) the inversely-causal, information-driven, structured hierarchy of autopoiesis is not reducible to the laws of physics and chemistry; and (iii) there is an unbridgeable abyss between the dirty, mass-action chemistry of the natural environmental and the perfectly-pure, single-molecule precision of biochemistry. Naturalistic objections to these propositions are considered in Part II of this article. Snowflake photos by Kenneth G. Libbrecht. Figure 1. Reducible structure. Snowflakes (left) occur in hexagonal shapes because water crystallizes into ice in a hexagonal pattern (right). Snowflake structure can therefore be reduced to (explained in of) ice crystal structure. Crystal formation is spontaneous in a cooling environment. The energetic vapour molecules are locked into solid bonds with the release of heat to the environment, thus increasing overall entropy in accord with the second law of thermodynamics.The commonly cited case for intelligent design (ID) goes as follows: ‘some biological systems are so complex that they can only function when all of their components are present, so that the system could not have evolved from a simpler assemblage that did not contain the full machinery.’ 1 This definition is what biochemist Michael Behe calledirreducible complexity in his popular book Darwin’s Black Box2 where he pointed to examples such as the bloodclotting cascade and the proton-driven molecular motor in the bacterial flagellum. However, because Behe appealed to complexity, many equally complex rebuttals have been put forward, 3 and because he claimed that only some of the aspects of life were irreducibly complex, he thereby implied that the majority of living structure was open to naturalistic explanation. As a result of these two factors, the concept of intelligent design remains controversial and unproven in popular understanding.In this article, I shall argue that all aspects of life point to intelligent design, based on what European polymath Professor Michael Polanyi FRS, in his 1968 article in Science called ‘Life’s Irreducible Structure.’4 Polanyi argued that living organisms have a machine-like structure that cannot be explained by (or reduced to) the physics and chemistry of the molecules of which they consist. This concept is simpler, and broader in its application, than Behe’s concept of irreducible complexity, and it applies to all of life, not just to some of it. The nature and origin of biological design Biologists universally ire the wonder of the beautiful ‘designs’ evident in living organisms, and they often recoil in revulsion at the horrible ‘designs’ exhibited by parasites and predators in ensuring the survival of themselves and their species. But to a Darwinist, these are only ‘apparent designs’—the end result of millions of years of tinkering by mutation and fine tuning by natural selection. They do not point to a cosmic Designer, only to a long and ‘blind’ process of survival of the fittest.5 For a Darwinist, the same must also apply to the origin of life—it must be an emergent property of matter. An emergent property of a system is some special arrangement that is not usually observed, but may arise through natural causes under the right environmental conditions. For example, the vortex of a tornado is an emergent property of atmospheric movements and temperature gradients. Accordingly, evolutionists seek endlessly for those special environmental conditions that may have launched the first round of carbon-based macromolecules 6 on their long journey towards life. Should they ever find those unique environmental conditions, they would then be able to explain life in of physics and chemistry. That is, life could then be reduced to the known laws of physics, chemistry and environmental

conditions.However, Polanyi argued that the form and function of the various parts of living organisms cannot be reduced to (or explained in of) the laws of physics and chemistry, and so life exhibits irreducible structure. He did not speculate on the origin of life, arguing only that scientists should be willing to recognize the impossible when they see it:‘The recognition of certain basic impossibilities has laid the foundations of some major principles of physics and chemistry; similarly, recognition of the impossibility of understanding living things in of physics and chemistry, far from setting limits to our understanding of life, will guide it in the right direction.’7 Reducible and irreducible structures To understand Polanyi’s concept of irreducible structure, we must first look at reducible structure. The snowflakes in figure 1 illustrate reducible structure.Meteorologists have recognized about eighty different basic snowflake shapes, and subtle variations on these themes add to the mix to produce a virtually infinite variety of actual shapes. Yet they all arise from just one kind of molecule—water. How is this possible? Figure 2. Irreducible structure. The silver coins (left) have properties of flatness, roundness and impressions on faces and rims, that cannot be explained in of the crystalline state of silver (close packed cubes) or its natural occurrence as native silver (right).When water freezes, its crystals take the form of a hexagonal prism. Crystals then grow by ing prism to prism. The elaborate branching patterns of snowflakes arise from the statistical fact that a molecule of water vapour in the air is most likely to up to its nearest surface. Any protruding bump will thus tend to grow more quickly than the surrounding crystal area because it will be the nearest surface to the most vapour molecules.8 There are six ‘bumps’ (corners) on a hexagonal prism, so growth will occur most rapidly from these, producing the observed six-armed pattern.Snowflakes have a reducible structure because you can produce them with a little bit of vapour or with a lot. They can be large or small. Any one water molecule is as good as any other water molecule in forming them. Nothing goes wrong if you add or subtract one or more water molecules from them. You can build them up one step at a time, using any and every available water molecule. The patterns can thus all be explained by (reduced to) the physics and chemistry of water and the atmospheric conditions. Figure 3. Common irreducibly structured machine components: lever (A), cogwheel (B) and coiled spring (C). All are made of metal, but their detailed structure and function cannot be reduced to (explained by) the properties of the metal they are made of.To now understand irreducible structure, consider a silver coin.Silver is found naturally in copper, lead, zinc, nickel and gold ores—and rarely, in an almost pure form called ‘native silver’. Figure 2 shows the back and front of two vintage silver coins, together with a nugget of the rare native form of silver. The crystal structure of solid silver consists of closely packed cubes. The main body of the native silver nugget has the familiar lustre of the pure metal, and it has taken on a shape that reflects the available space when it was precipitated from groundwater solution. The black encrustations are very fine crystals of silver that continued to grow when the rate of deposition diminished after the main load of silver had been deposited out of solution.Unlike the case of the beautifully structured snowflakes, there is no natural process here that could turn the closely packed cubes of solid silver into round, flat discs with images of men, animals and writing on them. Adding more or less silver cannot produce the roundness, flatness and image-bearing properties of the coins, and looking for special environmental conditions would be futile because we recognize that the patterns are man-made. The coin structure is therefore irreducible to the physics and chemistry of silver, and was clearly imposed upon the silver by some intelligent external agent (in this case, humans).Whatever the explanation, however, the irreducibility of the coin structure to the properties of its component silver constitutes what I shall call a ‘Polanyi impossibility’. That is, Polanyi identified this kind of irreducibility as a naturalistic impossibility, and argued that it should be recognized as such by the scientific community, so I am simply attaching his name to the principle.Polanyi pointed to the machine-like structures that exist in living organisms. Figure 3 gives three examples of common machine components: a lever, a cogwheel and a coiled spring. Just as the structure and function of these common machine components cannot be explained in of the metal they are made of, so the structure and function of the parallel components in life cannot be reduced to the properties of the carbon, hydrogen, oxygen, nitrogen, phosphorus, sulphur and trace elements that they are made of. There are endless examples of such irreducible structures in living systems, but they all work under a unifying principle called ‘autopoiesis’. Autopoiesis defined Autopoiesis literally means ‘self-making’ (from the Greek auto for self, and the verb poiéō meaning ‘I make’ or ‘I do’) and it refers to the unique ability of a living organism to continually repair and maintain itself—ultimately to the point of reproducing itself—using energy and raw materials from its environment. In contrast, an allopoietic system (from the Greek allo for other) such as a car factory, uses energy and raw materials to produce an organized structure (a car) which is something other than itself (a factory). 9Autopoiesis is a unique and amazing property of life—there is nothing else like it in the known universe. It is made up of a hierarchy of irreducibly structured levels. These include: (i) components with perfectly pure composition, (ii) components with highly specific structure, (iii) components that are functionally integrated, (iv) comprehensively regulated information-driven processes, and (v) inversely-causal meta-informational strategies for individual and species survival (these will be explained shortly). Each level is built upon, but cannot be explained in of, the level below it. And between the base level (perfectly pure composition) and the natural environment, there is an

unbridgeable abyss. The enormously complex details are still beyond our current knowledge and understanding, but I will illustrate the main points using an analogy with a vacuum cleaner. A vacuum cleaner analogy My mother was excited when my father bought our first electric vacuum cleaner in 1953. It consisted of a motor and housing, exhaust fan, dust bag, and a flexible hose with various end pieces. Our current machine uses a cyclone filter and follows me around on two wheels rather than on sliders as did my mother’s original one. My next version might be the small robotic machine that runs around the room all by itself until its battery runs out. If I could afford it, perhaps I might buy the more expensive version that automatically senses battery run-down and returns to its induction housing for battery recharge. Notice the hierarchy of control systems here. The original machine required an operator and some physical effort to pull the machine in the required direction. The transition to two wheels allows the machine to trail behind the operator with little effort, and the cyclone filter eliminates the messy dust bag. The next transition to on-board robotic control requires no effort at all by the operator, except to initiate the action to begin with and to take the machine back to the power source for recharge when it has run down. And the next transition to automatic sensing of power run-down and return-to-base control mechanism requires no effort at all by the operator once the initial program is set up to tell the machine when to do its work. If we now continue this analogy to reach the living condition of autopoiesis, the next step would be to install an on-board power generation system that could use various organic, chemical or light sources from the environment as raw material. Next, install a sensory and information processing system that could determine the state of both the external and internal environments (the dirtiness of the floor and the condition of the vacuum cleaner) and make decisions about where to expend effort and how to avoid hazards, but within the operating range of the available resources. Then, finally, the pièce de résistance, to install a meta-information (information about information) facility with the ability to automatically maintain and repair the life system, including the almost miraculous ability to reproduce itself—autopoiesis.Notice that each level of structure within the autopoietic hierarchy depends upon the level below it, but it cannot be explained in of that lower level. For example, the transition from out-sourced to on-board power generation depends upon there being an electric motor to run. An electric vacuum cleaner could sit in the cupboard forever without being able to rid itself of its dependence upon an outside source of power—it must be imposed from the level above, for it cannot come from the level below. Likewise, autopoiesis is useless if there is no vacuum cleaner to repair, maintain and reproduce. A vacuum cleaner without autopoietic capability could sit in the cupboard forever without ever attaining to the autopoietic stage—it must be imposed from the level above, as it cannot come from the level below.The autopoietic hierarchy is therefore structured in such a way that any kind of naturalistic transition from one level to a higher level would constitute a Polanyi impossibility. That is, the structure at level i is dependent upon the structure at level i-1 but cannot be explained by the structure at that level. So the structure at level i must have been imposed from level i or above. The naturalistic abyss Most origin-of-life researchers agree (at least in the more revealing parts of their writings) 10 that there is no naturalistic experimental evidence directly demonstrating a pathway from non-life to life. They continue their research, however, believing that it is just a matter of time before we discover that pathway. But by using the vacuum cleaner analogy, we can give a solid demonstration that the problem is a Polanyi impossibility right at the foundation—life is separated from non-life by an unbridgeable abyss. Dirty, mass-action environmental chemistry The ‘simple’ structure of the early vacuum cleaner is not simple at all. It is made of high-purity materials (aluminium, plastic, fabric, copper wire, steel plates etc) that are specifically structured for the job in hand and functionally integrated to achieve the designed task of sucking up dirt from the floor. Surprisingly, the dirt that it sucks up contains largely the same materials that the vacuum cleaner itself is made of—aluminium, iron and copper in the mineral grains of dirt, fabric fibres in the dust, and organic compounds in the varied debris of everyday home life. However, it is the difference in form and function of these otherwise similar materials that distinguishes the vacuum cleaner from the dirt on the floor. In the same way, it is the amazing form and function of life in a cell that separates it from the non-life in its environment.Naturalistic chemistry is invariably ‘dirty chemistry’ while life uses only ‘perfectly-pure chemistry’. I have chosen the word ‘dirty chemistry’ not in order to denigrate origin-of-life research, but because it is the term used by Nobel Prize winner Professor Christian de Duve, a leading atheist researcher in this field.11 Raw materials in the environment, such as air, water and soil, are invariably mixtures of many different chemicals. In ‘dirty chemistry’ experiments, contaminants are always present and cause annoying side reactions that spoil the hoped-for outcomes. As a result, researchers often tend to fudge the outcome by using artificially purified reagents. But even when given pure reagents to start with, naturalistic experiments typically produce what a recent evolutionist reviewer variously called ‘muck’, ‘goo’ and ‘gunk’ 12—which is actually toxic sludge. Even our best industrial chemical processes can only produce reagent purities in the order of 99.99%. To produce 100% purity in the laboratory requires very highly specialized equipment that can sort out single molecules from one another.Another crucial difference between environmental chemistry and life is that chemical reactions in a test tube follow the Law of Mass Action.13Large numbers of molecules are involved, and the rate of a reaction, together with its final outcome, can be predicted by assuming that each molecule behaves independently and each of the reactants has the same probability of interacting. In contrast, cells metabolize their reactants with single-molecule precision, and they control the rate and outcome of reactions, using enzymes and nano-scale-structured pathways, so that the result of a biochemical reaction can be totally different to that predicted by the Law of Mass Action. The autopoietic hierarchy Perfectly-pure, single-molecule-specific bio-chemistry The vacuum cleaner analogy breaks down before we get anywhere near life because the chemical composition of its components is nowhere near pure enough for life. The materials suitable for use in a vacuum cleaner can tolerate several percent of impurities and still produce adequate performance, but nothing less than 100% purity will work in the molecular machinery of the cell.One of the most famous examples is homochirality. Many carbon-based molecules have a property called ‘chirality’—they can exist in two forms that are mirror images of each other (like our left and right hands) called ‘enantiomers’. Living organisms generally use only one of these enantiomers (e.g. left-handed amino acids and right-handed sugars). In contrast, naturalistic experiments that produce amino acids and sugars always produce an approximately 50:50 mixture (called a ‘racemic’ mixture) of the left-and right-handed forms. The horrors of the thalidomide drug disaster resulted from this problem of chirality. The homochiral form of one kind had therapeutic benefits for pregnant women, but the other form caused shocking fetal abnormalities.The property of life that allows it to create such perfectly pure chemical components is its ability to manipulate single molecules one at a time. The assembly of proteins in ribosomes illustrates this single-molecule precision. The recipe for the protein structure is coded onto the DNA molecule. This is transcribed onto a messenger-RNA molecule which then takes it to a ribosome where a procession of transfer-RNA molecules each bring a single molecule of the next required amino acid for the ribosome to add on to the growing chain. The protein is built up one molecule at a time, and so the composition can be monitored and corrected if even a single error is made.

Specially structured molecules Life contains such a vast new world of molecular amazement that no one has yet plumbed the depths of it. We cannot hope to cover even a fraction of its wonders in a short article, so I will choose just one example. Proteins consist of long chains of amino acids linked together. There are 20 amino acids coded for in DNA, and proteins commonly contain hundreds or even thousands of amino acids. Cyclin B is an averaged-size protein, with 433 amino acids. It belongs to the ‘hedgehog’ group of signalling pathways which are essential for development in all metazoans. Now there are 20 433 (20 multiplied by itself 433 times) = 10563 (10 multiplied by itself 563 times) possible proteins that could be made from an arbitrary arrangement of 20 different kinds of amino acids in a chain of 433 units. The human body—the most complex known organism—contains somewhere between 105 (= 100,000) and 106 (=1,000,000) different proteins. So the probability (p) that an average-sized biologically useful protein could arise by a chance combination of 20 different amino acids is about p = 106 /10563 = 1/10557 . And this assumes that only L-amino acids are being used—i.e. perfect enantiomer purity.14For comparison, the chance of winning the lottery is about 1/10 6 per trial, and the chance of finding a needle in a haystack is about 1/10 11per trial. Even the whole universe only contains about 1080 atoms, so there are not even enough atoms to ensure the chance assembly of even a single average-sized biologically useful molecule. Out of all possible proteins, those we see in life are very highly specialized—they can do things that are naturally not possible. For example, some enzymes can do in one second what natural processes would take a billion years to do. 15 Just like the needle in the haystack. Out of all the infinite possible arrangements of iron alloy (steel) particles, only those with a long narrow shape, pointed at one end and with an eye-loop at the other end, will function as a needle. This structure does not arise from the properties of steel, but is imposed from outside. Water, water, everywhere There is an amazing paradox at the heart of biology. Water is essential to life, 16 but also toxic—it splits up polymers by a process called hydrolysis, and that is why we use it to wash with. Hydrolysis is a constant hazard to origin-of-life experiments, but it is never a problem in cells, even though cells are mostly water (typically 60–90%). In fact, special enzymes called hydrolases are required in order to get hydrolysis to occur at all in a cell. 17 Why the difference? Water in a test tube is free and active, but water in cells is highly structured, via a process called ‘hydrogen bonding’, and this waterstructure is comprehensively integrated with both the structure and function of all the cell’s macromolecules: ‘The hydrogen-bonding properties of water are crucial to [its] versatility, as they allow water to execute an intricate threedimensional “ballet”, exchanging partners while retaining complex order and enduring effects. Water can generate small active clusters and macroscopic assemblies, which can both transmit and receive information on different scales.’18 Water should actually be first on the list of molecules that need to be specially configured for life to function. Both the vast variety of specially structured macromolecules and their complementary hydrogen-bonded water structures are required at the same time. No origin-of-life experiment has ever addressed this problem. Functionally integrated molecular machines Figure 4. ATP synthase, a proton-powered molecular motor. Protons (+) from inside the cell (below) move through the stator mechanism embedded in the cell membrane and turn the rotor (top part) which adds inorganic phosphate (iP) to ADP to convert it to the high-energy state ATP.It is not enough to have specifically structured, ultra-pure molecules, they must also be integrated together into useful machinery. A can of stewed fruit is full of chemically pure and biologically useful molecules but it will never produce a living organism19 because the molecules have been disorganized in the cooking process. Cells contain an enormous array of useful molecular machinery. The average machine in a yeast cell contains 5 component proteins,20 and the most complex —the spliceosome, that orchestrates the reading of separated sections of genes— consists of about 300 proteins and several nucleic acids.21One of the more spectacular machines is the tiny proton-powered motor that produces the universal energy molecule ATP (adenosine tri-phosphate) illustrated in Figure 4. When the motor spins one way, it takes energy from digested food and converts it into the high-energy ATP, and when the motor spins the other way, it breaks down the ATP in such a way that its energy is available for use by other metabolic processes.22 Comprehensively regulated, information-driven metabolic functions It is still not enough to have spectacular molecular machinery—the various machines must be linked up into metabolic pathways and cycles that work towards an overall purpose. What purpose? This question is potentially far deeper than science can take us, but science certainly can ascertain that the immediate practical purpose of the amazing array of life structures is the survival of the individual and perpetuation of its species. 23 Although we are still unravelling the way cells work, a good idea of the multiplicity of metabolic pathways and cycles can be found in the BioCyc collection. The majority of organisms so far examined, from microbes to humans, have between 1,000 and 10,000 different metabolic pathways.24 Nothing ever happens on its own in a cell—something else always causes it, links with it or benefits or is affected by it. And all of these links are multi-step processes.All of these links are also ‘choreographed’ by information—a phenomenon that never occurs in the natural environment. At the bottom of the information hierarchy is the storage molecule—DNA. The double-helix of DNA is ‘just right’ for genetic information storage, and this ‘just right’ structure is beautifully matched by the elegance and efficiency of the code in which the cell’s information is written there. 25 But it is not enough even to have an elegant ‘just right’ information storage system—it must also contain information. And not just biologically relevant information, but brilliantly inventive strategies and tactics to guide living things through the extraordinary challenges they face in their seemingly miraculous achievements of metabolism and reproduction. Yet even ingenious strategies and tactics are not enough. Choreography requires an intricate and harmonious regulation of every aspect of life to make sure that the right things happen at the right time, and in the right sequence, otherwise chaos and death soon

follow.Recent discoveries show that biochemical molecules are constantly moving, and much of their amazing achievements are the result of choreographing all this constant and complex movement to accomplish things that static molecules could never achieve. Yet there is no spacious ‘dance floor’ on which to choreograph the intense and lightning-fast (up to a million events per second for a single reaction26) activity of metabolism. A cell is more like a crowded dressing room than a dance floor, and in a show with a cast of millions! Inversely causal meta-information The Law of Cause and Effect is one of the most fundamental in all of science. Every scientific experiment is based upon the assumption that the end result of the experiment will be caused by something that happens during the experiment. If the experimenter is clever enough, then he/she might be able to identify that cause and describe how it produced that particular result or effect.Causality always happens in a very specific order—the cause always comes before the effect.27 That is, event A must always precede eventB if A is to be considered as a possible cause of B. If we happened to observe that A occurred after B, then this would rule out A as a possible cause of B.In living systems however, we see the universal occurrence of inverse causality. That is, an event A is the cause of event B, but A exists or occurs after B. It is easier to understand the biological situation if we refer to examples from human affairs. In economics, for example, it occurs when behaviour now, such as an investment decision, is influenced by some future event, such as an anticipated profit or loss. In psychology, a condition that exists now, such as anxiety or paranoia, may be caused by some anticipated future event, such as harm to one’s person. In the field of occupational health and safety, workplace and environmental hazards can exert direct toxic effects upon workers (normal causality), but the anticipation or fear of potential future harm can also have an independently toxic effect (inverse causality).Darwinian philosopher of science Michael Ruse recently noted that inverse causality is a universal feature of life,28 and his example was that stegosaur plates begin forming in the embryo but only have a function in the adult—supposedly for temperature control. However most biologists avoid itting such things because it suggests that life might have purpose (a future goal), and this is strictly forbidden to materialists.The most important example of inverse causality in living organisms is, of course, autopoiesis. We still do not fully understand it, but we do understand the most important aspects. Fundamentally, it is meta-information—it is information about information. It is the information that you need to have in order to keep the information you want to have to stay alive, and to ensure the survival of your descendants and the perpetuation of your species.This last statement is the crux of this whole paper, so to illustrate its validity lets go back to the vacuum cleaner analogy. Let’s imagine that one lineage of vacuum cleaners managed to reach the robotic, energy-independent stage, but lacked autopoiesis, while a second makes it all the way to autopoiesis. What is the difference between these vacuum cleaners? Both will function very well for a time. But as the Second Law of Thermodynamics begins to take its toll, components will begin to wear out, vibrations will loosen connections, dust will gather and short circuit the electronics, blockages in the suction age will reduce cleaning efficiency, wheel axles will go rusty and make movement difficult, and so on. The former will eventually die and leave no descendants. The latter will repair itself, keep its components running smoothly and reproduce itself to ensure the perpetuation of its species.But what happens if the environment changes and endangers the often-delicate metabolic cycles that real organisms depend upon? Differential reproduction is the solution. Evolutionists from Darwin to Dawkins have taken this amazing ability for granted, but it cannot be overlooked. There are elaborate systems in place—for example, the diploid to haploid transition in meiosis, the often extraordinary embellishments and rituals of sexual encounters, the huge number of permutations and combinations provided for in recombination mechanisms—to provide offspring with variations from their parents that might prove of survival value. To complement these potentially dangerous deviations from the tried-and-true there are also firm conservation measures in place to protect the essential processes of life (e.g. the ability to read the DNA code and to translate it into metabolic action). None of this should ever be taken for granted.In summary, autopoiesis is the information—and associated abilities—that you need to have (repair, maintenance and differential reproduction) in order to keep the information that you want to have (e.g. vacuum cleaner functionality) alive and in good condition to ensure both your survival and that of your descendants. In a parallel way, my humanity is what I personally value, so my autopoietic capability is the repair, maintenance and differential reproductive capacity that I have to maintain my humanity and to share it with my descendants. The egg and sperm that produced me knew nothing of this, but the information was encoded there and only reached fruition six decades later as I sit here writing this—the inverse causality of autopoiesis. Summary There are three lines of reasoning pointing to the conclusion that autopoiesis provides a compelling case for the intelligent design of life. • If life began in some stepwise manner from a non-autopoietic beginning, then autopoiesis will be the end product of some long and blind process of accidents and natural selection. Such a result would mean that autopoiesis is not essential to life, so some organisms should exist that never attained it, and some organisms should have lost it by natural selection because they do not need it. However, autopoiesis is universal in all forms of life, so it must be essential. The argument from the Second Law of Thermodynamics as applied to the vacuum cleaner analogy also points to the same conclusion. Both arguments demonstrate that autopoiesis is required at thebeginning for life to even exist and perpetuate itself, and could not have turned up at the end of some long naturalistic process. This conclusion is consistent with the experimental finding that origin-of-life projects which begin without autopoiesis as a pre-requisite have proved universally futile in achieving even the first step towards life. • Each level of the autopoietic hierarchy is dependent upon the one below it, but is causally separated from it by a Polanyi impossibility. Autopoiesis therefore cannot be reduced to any sequence of naturalistic causes. • There is an unbridgeable abyss below the autopoietic hierarchy, between the dirty, mass-action chemistry of the natural environment and the perfect purity, the single-molecule precision, the structural specificity, and the inversely causal integration, regulation, repair, maintenance and differential reproduction of life. DAILY DNA INFORMATION Information Theory—part 1: overview of key ideas by Royal Truman The origin of information in nature cannot be explained if matter and energy is all there is. But the many, and often contradictory, meanings of information confound a clear analysis of why this is so. In this, the first of a four-part series, the key views about information theory by leading thinkers in the creation/evolution controversy are presented. In part 2, attention is drawn to various difficulties in the existing paradigms in use. Part 3 introduces the notion of replacing Information by Coded Information System (CIS) to resolve many difficulties. Part 4 completes the theoretical backbone of CIS theory,

showing how various conceptual frameworks can be integrated into this comprehensive model. The intention is to focus the discussion in the future on whether CISs can arise naturalistically. Intelligent beings design tools to help solve problems. These tools can be physical or intellectual, and can be used and reused to solve classes of problems.1 But creating separate tools for each kind of problem is usually inefficient. In nature many problems involving growth, reproduction and adjustment to changes are performed with information-based tools. These share the remarkable property that an almost endless range of intentions can be communicated via coded messages using the same sending, transmission and receiving equipment.All known life depends on information. But what is information and can it arise naturally? Naturalists deny the existence of anything beyond matter, energy, laws of nature and chance. But then where do will, choice, and information come from?In the creation science and intelligent design literature we find inconsistent or imprecise understandings about what is meant by ‘information’. We sometimes read that nature cannot create information. But in other places, that some, but not enough, information could be produced to explain the large amount observed today in nature.Suppose a species of bacteria can produce five similar variants of a protein which don’t work very well for some function, and another otherwise identical species produces only a single, highly tuned version. Which has more information?Consider a species of birds with white and grey . A catastrophe occurs and the few survivors only produce white offspring from now on. Has information increased or decreased?What about enzymes. Do they possess more information when able to act on several different substrates or when specific to only one?In the creation science and intelligent design literature we find inconsistent or imprecise understandings about what is meant by ‘information’. The influence of Shannon’s Theory of InformationMost of the experts debating the origin of information rely on the mathematical model of communication developed by the late Claude Shannon with its quantitative merits. 2–4 Shannon’s fame began with publication of his master’s thesis, which was called “possibly the most important, and also the most famous, master’s thesis of the century”. 5Messages are strings of symbols, like ‘10011101’, ‘ACCTGGTCAA’, and ‘go away’. All messages are composed of symbols taken from a coding alphabet. The English alphabet uses 26 symbols, the DNA code, four, and binary codes use two symbols.In Shannon’s model, one bit of information communicates a decision between two equiprobable choices and in general n bits between 2n equiprobable choices. Each symbol in an alphabet of s alternatives can provide log2s bits of information.Entropy, H, plays an important role in Shannon’s work. The entropy of a Source can be calculated by observing the frequency each symbol i is generated in messages: where log is to the base 2 and p is the probability of each symbol i appearing in a message. For example, if both symbols of an alphabet [0,1] are equiprobable, then eqn. (1) leads to: Maximum entropy results when the symbols are equiprobable, whereas zero entropy indicates that the same message is always produced. Maximum entropy indicates that we have no way of guessing which sequence of symbols will be produced. In English, letter frequencies differ, so entropy is not maximum. Even without understanding English, one can know that many messages will not be produced, such as sentences over a hundred letters long using only the letters z and q.6Equations for other kinds of entropy, each with special applications, exist in Shannon’s theory: t entropy, conditional entropy (equivocation), and mutual information.Shannon devotes much attention to calculating the Channel Capacity. This is the rate at which the initial message can be transmitted error-free in the presence of disturbing noise, and requires knowledge of the probability that each symbol i sent will arrive correctly or be corrupted into another symbol, j. These errorcorrection measures require special codes to be devised, with additional data accompanying the original message.There are many applications of Shannon’s theories, especially in data storage and transmission. 7 A more compact code could exist whenever the entropy of the messages is not maximum, and the theoretical limit to data compression obtained by recoding can be calculated.8 Specifically, if messages based on some alphabet are to be stored or transmitted and the frequency of each symbol is known, then the upper compression limit for a new code can be known. 9Hubert Yockey is a pioneer in applying Shannon’s theory to biology.10–14 His work and the mathematical calculations have been discussed in this journal.15 Once it was realized that the genetic code uses four nucleobases, abbreviated A, C, G, and T, in combinations of three to code for amino acids, the relevance of Information Theory became quickly apparent. Yockey used the mathematical formalism of Shannon’s work to evaluate the information of cytochrome c proteins, 15 selected due to the large number of sequence examples available. Many proteins are several times larger, or show far less tolerance to variability, as is the case of another example Yockey discusses:“The pea histone H3 and the chicken histone H3 differ at only three sites, showing almost no change in evolution since the common ancestor. Therefore histones have 122 invariant sites … the information content of an invariant site is 4.139 bits, so the information content of the histones is approximately 4.139 × 122, or 505 bits required just for the invariant sites to determine the histone molecule.” 16Yockey seems to believe the information was frontloaded on to DNA about four billion years ago in some primitive organism. This viewpoint is not elaborated on by him and is deduced primarily by his comments that Shannon’s Channel Capacity Theorem ensures transmission of the original message correctly.It is unfortunate that the mysterious allusions 17 to the Channel Capacity Theorem were not explained. In one part he wrote,“But once life has appeared, Shannon’s Channel Capacity Theorem (Section 5.3) assures us that genetic messages will not fade away and can indeed survive for 3.85 billion years without assistance from an Intelligent Designer.” 18 This is nonsense. The Channel Capacity Theorem only claims that it is theoretically possible to devise a code with enough redundancy and error-correction to transmit a message error-free. Increased redundancies (themselves subject to corruption) are needed as the demand for accuracy increases, and perfect accuracy is achieved only at the limit of infinite

low effective transmission of the intended error-free message. Whether this is even conceivable using mechanical or biological components is not addressed by the Channel Capacity Theorem. But the key point is that Yockey claims the theorem assures that the evolutionary message will not fade away. He confuses a mathematical ‘in principle’ notion with an implemented fact. He fails to show what the necessary error-correcting coding measures would be and that they have been actually implemented.In his latest edition, Yockey (or possibly an editor) was very hostile to the notion of an intelligent designer. Tragically, his comments on topics like Behe’s irreducible complexity suggests he does not understand what the term means. As one example, we read:“mRNA acts like the reading head on a Turing machine that moves along the DNA sequence to read off the genetic message to the proteasome. The fact the sequence has been read shows that it is not ‘irreducibly complex’ nor random. By the same token, Behe’s mouse trap is not ‘irreducibly complex’ or random.” 19The word information is used in many ways, which complicates the discussion as to its origin. Yockey’s work is often difficult to follow. Calculations which are easily understood and can be performed effortlessly with a spreadsheet or computer program are needlessly complicated by deriving poorly explained alternative formulations.20 Very problematic in his work is the difficulty in understanding his multiple uses of the word information. For example, the entropy of iso-1-cytochrome c sequences is called Information content.21 Then presumably the greater the randomness of these sequences, the higher the entropy and therefore the higher the information content, right? That makes no sense, and is the wrong conclusion. But why, since higher entropy of the Source (DNA) according to Shannon’s theory always indicates more information?I believe this is the source of much confusion in the creationist and Intelligent Design literature which criticizes Shannon’s approach as supposedly implying greater randomness always implies more information.Kirk Durston, a member of the Intelligent Design community, improves considerably on Yockey’s pioneering efforts. He correctly identifies the difference in entropy of all messages generated by a Source, H0, and the entropy of those messages which provide a particular function, H f, as the measure of interest. He calls this difference, H0–Hf, functional information.22 This difference in entropies is actually used by all those applying Shannon’s work to biological sequences, whether evolutionists or not, although this fact is not immediately apparent when reading their papers.Entropies are defined by eqn. (1), but Yockey’s approach has a conceptual flaw (and implied assumption) which destroys his justification for using Shannon’s Information Theory with protein sequence analysis.23 Truman already pointed out that Yockey’s quantitative results are obtained within little more than a rounding-off error with the same data, using much simpler standard probability calculations. 24The sum of the entropy contributions at each position of a protein leads to H f. To calculate these site entropies, Durston aligned all known primary sequences of a protein using the ClustalX program, and determined the proportion of each amino acid in the dataset, using eqn. (1). Large datasets were collected for 35 protein families and the bits of functional information, or Fits, were calculated. Twelve examples were found having over 500 Fits, or a proportion of <2˗500 = 3 × 10˗151 among random sequences. The highest value reported was for protein Flu PB2, with 2416 Fits.Durston’s calculations have one minor and one major weakness. To calculate H0, he assumed amino acids are equiprobable, which is not true. This effect is not very significant, but indeed H 0 is a little less random than he assumed. The other assumption is that of mutational context independence: that all mutations which are tolerated individually are also acceptable concurrently. This is not the case, as Durston knows, and the result is that the amount of entropy in Hf is much lower than he calculated. 15,25,26 The conclusion is that the protein families actually contain far more Fits of functional information, and represent a much lower subset among random sequences. This effect is counteracted somewhat by the fact that not all organisms which ever lived are represented in the dataset.Bio-physicist Lee Spetner, Ph.D. from MIT, is a leading information theoretician who wrote the book Not by Chance.27 He is a very lucid participant in Internet debates on evolution and information theory, and is adamant that evolutionary processes quantitatively won’t increase information. In his book, he wrote,“I don’t say it’s impossible for a mutation to add a little information. It’s just highly improbable on theoretical grounds. But in all the reading I’ve done in the life-sciences literature, I’ve never found a mutation that added information. The NDT says not only that such mutations must occur, they must also be probable enough for a long sequence of them to lead to macroevolution.” 28Within Shannon’s framework, it is correct that a random mutation could increase information content. However, one must not automatically conflate ‘more information content’ with good or useful.29,30Although Spetner says information could be in principle created or increased, Dr Werner Gitt, retired Director and Professor at the German Federal Institute of Physics and Technology, denies this:“Theorem 23: There is no known natural law through which matter can give rise to information, neither is any physical process or material phenomenon known that can do this.”31In his latest book, Gitt refines and explains his conclusions from a lifetime of research on information and its inseparable reliance on an intelligent source. 32 There are various manifestations of information: for example, the spider’s web; the diffraction pattern of butterfly wings; development of embryos; and an organplaying robot.33 He introduces the term ‘Universal Information’ 34 to minimize confusion with other usages of the word information:“Universal Information (UI) is a symbolically encoded, abstractly represented message conveying the expected actions(s) and the intended purposes(s). In this context, ‘message’ is meant to include instructions for carrying out a specific task or eliciting a specific response [emphasis added].”35Information must be encoded on a series of symbols which satisfy three Necessary Conditions (NC). These are conclusions, based on observation. NC1: A set of abstract symbols is required. NC2: The sequence of abstract symbols must be irregular. NC3: The symbols must be presented in a recognizable form, such as rows, columns, circles, spirals and so on. Gitt also concludes that UI is embedded in a five-level hierarchy with each level building upon the lower one: statistics (signal, number of symbols) cosyntics (set of symbols, grammar) semantics (meaning) pragmatics (action) apobetics (purpose, result). Gitt believes information is guided by immutable Scientific Laws of Information (SLIs). 36,37 Unless shown to be wrong, they deny a naturalist origin for information, and they are:38 SLI-1: Information is a non-material entity. SLI-2: A material entity cannot create a non-material entity. SLI-3: UI cannot be created by purely random processes. SLI-4: UI can only be created by an intelligent sender. SLI-4a: A code system requires an intelligent sender. SLI-4b: No new UI without an intelligent sender. SLI-4c: All senders that create UI have a non-material component. SLI-4d: Every UI transmission chain can be traced back to an original intelligent sender SLI-4e: Allocating meanings to, and determining meanings from, sequences of symbols are intellectual processes. SLI-5: The pragmatic attribute of UI requires a machine. SLI-5a: UI and creative power are required for the design and construction of all machines.

SLI-5b: A functioning machine means that UI is affecting the material domain. SLI-5c: Machines operate exclusively within the physical– chemical laws of matter. SLI-5d: Machines cause matter to function in specific ways. SLI-6: Existing UI is never increased over time by purely physical, chemical processes. These laws are inconsistent with the assumption stated by Nobel Prize winner and origin-of-life specialist Manfred Eigen: “The logic of life has its origin in physics and chemistry.” 39 The issue of information, the basis of genetics and morphology, has simply been ignored. On the other hand, Norbert Wiener, a leading pioneer in information theory, understood clearly that, “Information is information, neither matter nor energy. Any materialism that disregards this will not live to see another day.”40It is apparent that Gitt views Shannon’s model as inadequate to handle most aspects of information, and that he means something entirely different by the word ‘information’.Arch-atheist Richard Dawkins reveals a Shannon orientation to what information means when he wrote, “Information, in the technical sense, is surprise value, measured as the inverse of expected probability.”41 He adds, “It is a theory which has long held a fascination for me, and I have used it in several of my research papers over the years.” And more specifically,“The technical definition of ‘information’ was introduced by the American engineer Claude Shannon in 1948. An employee of the Bell Telephone Company, Shannon was concerned to measure information as an economic commodity.” 42“DNA carries information in a very computer-like way, and we can measure the genome’s capacity in bits too, if we wish. DNA doesn’t use a binary code, but a quaternary one. Whereas the unit of information in the computer is a 1 or a 0, the unit in DNA can be T, A, C or G. If I tell you that a particular location in a DNA sequence is a T, how much information is conveyed from me to you? Begin by measuring the prior uncertainty. How many possibilities are open before the message ‘T’ arrives? Four. How many possibilities remain after it has arrived? One. So you might think the information transferred is four bits, but actually it is two.” 40In articles and discussions among nonspecialists, questions are raised such as “Where does the information come from to create wings?” There is an intuition among most of us that adding biological novelty requires information, and more features implies more information. I suspect this is what lies behind claims that evolutionary processes cannot create information, meaning complex new biological features. Even Dawkins subscribes to this intuitive notion of information:“Imagine writing a book describing the lobster. Now write another book describing the millipede down to the same level of detail. Divide the word-count in one book by the wordcount in the other, and you have an approximate estimate of the relative information content of lobster and millipede.”40Stephen C. Meyer, director of the Discovery Institute’s Center for Science and Culture and active member of the Intelligent Design movement, relies on Shannon’s theory for his critiques on naturalism. 43,44 He recognizes that some sequences of characters serve a deliberate and useful purpose. Meyer says the messages with this property exhibit specified complexity, or specified information.45 Shannon’s Theory of Communication itself has no need to address the question of usefulness, value, or meaning of transmitted messages. In fact, he later avoided the word information. His concern was how to transmit messages error-free. But Meyer points out that“… molecular biologists beginning with Francis Crick have equated biological information not only with improbability (or complexity), but also with ‘specificity’, where ‘specificity’ or ‘specified’ has meant ‘necessary to function’.”46I believe Meyer’s definition of information corresponds to Durston’s Functional Information. Figure 1. Shannon’s schematic diagram of a general communication system.2 William Dembski, another prominent figure in the Intelligent Design movement, is a major leader in the analysis of the properties and calculations of information, and will be referred to in the next parts to this series. He has not reported any analysis of his own on protein or gene sequences, but also accepts that H0–Hf is the relevant measure from Shannon’s work to quantify information. In part 2 of this series I’ll show that many things are implied in Shannon’s theory that indicate an underlying active intelligence. Thomas Schneider is a Research Biologist at the National Institutes of Health. His Ph.D. thesis in 1984 was on applying Shannon’s Information Theory to DNA and RNA binding sites and he has continued this work ever since and published extensively.17,47

Figure 2. The transmission of genetic message from the DNA tape to the protein tape, according to Yockey.17 Senders and receivers in information theories

There is common agreement that a sender initiates transmission of a coded message which is received and decoded by a receiver. Figure 1 shows how Shannon depicted this and figure 2 shows Yockey’s version.2,17 Figure 3. A comprehensive diagram of the five levels of Universal Information, according to Gitt.32 A fundamental difference in Gitt’s model is the statement that all levels of information, including the Apobetics (intended purpose) are present in the Sender (figure 3). All other models treat the Sender as merely whatever releases the coded message to a receiver. In Shannon’s case, the Sender is the mindless equipment which initiates transmission to a channel. For Yockey the Sender is DNA, although he considers the ultimate origin of the DNA sequences open. Gitt distinguishes between the original and the intermediate Sender.48Humans intuitively develop coded information systemsHumans interact with coded messages with such phenomenal skill, most don’t even notice what is going on. We discuss verbally with ease. Engineers effortlessly devise various designs: sometimes many copies of machines are built and equipped with message-based processing resources (operating systems, drivers, microchips, etc.). Alternatively, the hardware alone could be distributed and all the processing power provided centrally (such as the ‘dumb terminals’ used before personal computers). To illustrate, intellectual tools such as reading, grammar, and language can be taught to many students in advance. Later it is only necessary to distribute text to the multiple human processors.The strategy of distributing autonomous processing copies is common in nature. Seeds and bacterial colonies already contain preloaded messages, ribosomes already possess engineered processing parts, and so on. Conclusion The word information is used in many ways, which complicates the discussion as to its origin. The analysis shows two families of approaches. One is derived from Shannon’s work and the other is Gitt’s. To a large extent the former addresses the how question: how to measure and quantify information. The latter deals more with the why issue: why is information there, what is it good for?The algorithmic definition of information, developed by Solomonoff and Kolmogorov, with contributions from Chaitin, is rarely used in the debate about origins and in general discussions about information currently. For this reason it was not discussed in this part of the series. Information Theory—part 2: weaknesses in current conceptual frameworks by Royal Truman The origin of information is a problem for the theory of evolution. But the wide, and often inconsistent, use of the word information often leads to incompatible statements among Intelligent Design and creation science advocates. This hinders fruitful discussion. Most information theoreticians base their work on Shannon’s Information Theory. One conclusion is that the larger genomes of higher organisms require more information, and raises the question whether this could arise naturalistically. Lee Spetner claims no examples of information-increasing mutations are known, whereas most ID advocates only claim that not enough bits of information could have arisen during evolutionary timescales. It has also been proposed that nature reflects the intention of the designer, and therefore all lifeforms might have the same information content. Gitt claims information can’t be measured. The underlying concepts of these theoreticians were discussed in part 1 of this series. In part 3 a solution will be offered for the difficulties documented here. Background: stock.xchng Origin of life researcher Dr Küppers defines life as matter plus information.1 Having a clear and common understanding of what we mean by information is necessary for a fruitful discussion about its origin. But in part 1 of this series I pointed out that various researchers of evolutionary and creationist persuasion give the word very different definitions.2 Creation Magazine often draws attention to the need for information-adding mutations if evolutionary theory is true, for example:“Slow and gradual evolutionary modification of these crucial organs of movement would require many information-adding mutations to occur in just the right places at just the right times.” 3What does information mean? Williams introduced many useful thoughts in this journal in a three-part series on biological information.4–6 Consistent with the usage of information above, he points out that “Creationists commonly challenge evolutionists to explain how vast amounts of new information could be produced that would be required to turn a microbe into a microbiologist.”7On the same page he adds, “But the extra wings arose from three mutations that switched off existing developmental processes. No new information was added. Nor was any new capability/functionality achieved.”Schneider’s simulations only work because they were designed to do so, and are intelligently guided. I understand and agree with the intuition behind this usage of the word information. Nevertheless, even literature sold by Creation Ministries International, such as MIT Ph.D. Lee Spetner’s classic Not by Chance!,8 are not using information in the same sense. Spetner is an expert on Shannon’s Theory of Communication (information) and is one of the most lucid writers on its application.Sometimes creationists (e.g. Gitt) state that information cannot, in principle, arise naturally whereas others (e.g. Stephen Meyer, Lee Spetner) are saying that not enough could arise for macro-evolutionary purposes.2The view that not enough time was available to add the necessary information found in genomes (based on one definition of information) becomes clouded when Williams argues that “the Darwinian arguments are without force, since it is clear that organisms are designed to vary.”9,10 Behind this reasoning lies a different usage of information. Williams even implies that information cannot be quantified at all:

“… a new, useful enzyme will not contain more information than the original system because the intention remains the same —to produce enzymes with variable amino acid sequences that may help in adapting to new food sources when there is stress due to an energy deficit.”9I believe that approach should be reconsidered, especially if intention is defined in such generic, broad . Suppose the intention is to help one’s daughter get better grades at school. The above suggestion seemingly assigns the same amount of information whether a two-minute verbal explanation is offered, or years of private tutoring over many topics.I believe most of Williams’ intuitions are right, but hope the model given in the third part of this series will bring the pieces together in a more unified manner. Williams suggests that other codes are present in the cell environment in addition to the one used by DNA. He once made the significant statement:“ We could, in theory, quantify this information using an algorithmic approach, but for practical purposes it is enough to note that it is enormous and noncoded.”11I agree that information can also be non-coded, but it is not apparent how an algorithmic measure of information could be used, a topic Bartlett has devoted effort to. 12The precise definition of information has dramatic consequences on the conclusions reached. Gitt believes information cannot be quantified. Others believed it can, and in exact detail. Weber, Claude Shannon’s thesis supervisor, had this to say:“It seems very reasonable to want to say that three relays could handle three times as much information as one. And this indeed is the way it works out if one uses the logarithmic definition of information.”13When asked by creationists if he knew of any biological process that could increase the information content of a genome, Dawkins could not answer the question.6,14 He subscribes to Shannon’s definition of information and understands the issue at stake, writing later:“Therefore the creationist challenge with which we began is tantamount to the standard challenge to explain how biological complexity can evolve from simpler antecedents.”15Several years ago Answers in Genesis sponsored a workshop on the topic of information. Werner Gitt proposed we try to find a single formulation everyone could work with. This challenge remains remarkably difficult, because people routinely use the word in different manners.In 2009, Gitt offered the following definition for information in this journal,16 which at the advice of Bob Crompton he now calls Universal Information (UI).“Information is always present when all the following five hierarchical level are observed in a system: statistics, syntax, semantics, pragmatics and apobetics.”Let us call this Definition 1. Gitt also states that he now uses UI and information interchangeably.17I have collaborated with Werner Gitt during the last 25 years of so on various topics, and the comments which follow are not to be construed as criticism against him or his work. 18 At times it seems there is a discrepancy between what he means and how it is expressed on paper. 19 Considerable refinement has occurred in his thinking, and I hope to contribute by a critical but constructive attempt at further improvement.The variety of usages of the word information continues to trap us. When Gitt wrote:“Theorem 3. Information comprises the nonmaterial foundation for all technological systems and for all works of art”20and“Remark R2: Information is the non-material basis for all technological systems”,21he appears to have switched to another (valid but different) usage of the word information. For example, it is not apparent why valuable technologies like the first axe, shovel, or saw depended on the coded messages (statistics, syntax) portion of his definition of information, a definition which seems to require all five hierarchical levels to be present.As another example of inconsistent, or at least questionable, usage of the word, we read that“… the information in living things resides on the DNA molecule.”22The parts of the definition of information which satisfy apobetics (purpose, result) do not reside on DNA. External factors enhance and interplay with what is encrypted and indirectly implied on DNA, but apobetics is not physically present there. To illustrate, neuron connections are made and rearranged as part of dynamic learning, interacting with external cues and input, but the effects are neither present nor implied on DNA.Another important claim needs to be evaluated carefully. Gitt often states the premise that“The storage and transmission of information requires a material medium.”23It is true that non-material messages can be coded and impregnated on material media. But information can be relayed over various communication channels. Must all of them be material based? If so, then all, or virtually all, theinformation-processing components in intelligent minds could only be material. Let us see why.Suppose one wishes to translate ‘ridiculous’ into German. The intention to translate, and the precise semantic concept itself, are surely encoded and stored somewhere. This intention must be transmitted elsewhere to other reasoning facilities, where a search strategy will also be worked out. All of this occurs before the search request is transmitted into the physical brain, but information is already being stored and transmitted in vast amounts.Furthermore, is the mind/brain interface, part of the transmission path, 100% material?23 We begin to see that Gitt’s statement seems to imply that wilful decision making and the guidance of decisions must be material phenomena.Now, as soon as the German word lächerlich is extracted from the biological memory bank,24 it must be transferred from the brain’s apparatus into the wilful reasoning equipment and compared to the ‘information’ which prompted the search. A huge amount of mental processing (i.e. data storage and transmission) will now occur: are the English and German words semantically synonymous for some purpose, or should more words be searched for?Irrwitzig could be a new candidate, but which translation is better? What are all the associations linked to both German words? Should more alternatives by looked up in a dictionary? Finally, decisions will be performed as to what to do with the preferred translation (stored as the top choice and mentally transmitted to processing components where the intended outcome will be planned).25More to the point, must angels, God, and the soul rely on a material medium to store and transmit information?This objection is serious, because of the frequent statements that all forms of technology and art are illustrations of information. An artist can wordlessly decide to create an abstract painting. Where are the statistics, syntax, and semantics portion of the definition of UI? If in the mentally coded messages (which we read above must be material) then either UI is material based or all aspects of created art and tool-making (technology) need not be UI.In part 3 of this series I’ll offer a simple solution to these issues.Gitt offers a new definition for UI in his 2011 book Without Excuse:“Universal Information (UI) is a symbolically encoded, abstractly represented message conveying the expected actions(s) and the intended purposes(s). In this context, ‘message’ is meant to include instructions for carrying out a specific task or eliciting a specific response [emphasis added].”26Let us call this Definition 2. This resembles one definition of information in Webster’s Dictionary: “The attribute inherent in and communicated by alternative sequences or arrangements of something that produce specific effects.”I don’t believe Definition 2 is adequate yet. Only verbal communication seems to be addressed. It implies that the symbolically encoded message itself must convey the expected actions and intended purposes, but in part 3 I’ll show that this needs not be, and is probably never completely true. Sometimes the coded instructions themselves do convey portions of the expected actions and purpose. This is observed when the message communicates how machines are to be produced which are able to process remaining portions of the message (like DNA encoding the sequence data for the RNA and proteins needed to produce the decoding ribosome machinery). I would agree that the messages often contribute to, but do not necessarily themselves specify the purpose. Communicating all the necessary details would be impractical.Consider the virus as an example. The expected actions(s) and the intended purpose(s) are not communicated by the content of their genomes, nor are the instructions to decode the implied protein (the necessary ribosomes are provided from elsewhere). Some viruses do provide instructions to permit insertion into the host genome and other intermediary outcomes which can contribute to, but not completely specify, the final intended purposes.Another difficulty with Definition 2 is that it does not distinguish between push and pull forms of coded interactions. The code message, ‘What is the density of benzene?’ could be sent to a database. This message, a pull against an existing data source, does not convey the expected actions(s) or the intended purposes.Of the researchers discussed in part 1 of this series, Gitt’s model offers

the broadest framework for a theory of information for the purposes of analyzing the origin of life. He has refined his thoughts continually over the years, but I fear the value will soon plateau out without the change of direction we’ll see in part 3. One reason is that it won’t permit quantitative conclusions.If an evolutionist is convinced that all life on Earth derived from a single ancestor, then ultimately all the countless examples of DNA-based life are only the results of one single original event. Therefore, Gitt’s elevation of his theorems to laws will seem weak compared to the powerful empirical and mathematically testable laws of physics, for which so many independent examples can be found and validated quantitatively.27 I’m sure Gitt’s Scientific Laws of Information (SLI) will never be disproven because my analysis (introduced in part 3 and 4 of this series) of what would be required to create code-based systems makes their existence without intelligent guidance absurdly improbable. Others may find my reasoning in part 3 more persuasive than calling observed code-based principles laws, since they seem to be based on such limited datasets.The contributions of other information theoreticians are quantifiable. Although limited to the lower portions of Gitt’s five hierarchies, I find much merit in them, and their ideas can be included as part of a general-purpose theoretic framework (see part 3). When Gitt wrote:“To date, evolutionary theoreticians have only been able to offer computer simulations that depend upon principles of design and the operation of pre-determined information. These simulations do not correspond to reality because the theoreticians smuggle their own information into the simulations.”It is not clear, based on his own definition, what was meant by ‘pre-determined information’. I will show in part 3 that the path towards pragmatics and apobetics can be aided with resources which do not rely on the lower levels (statistics, syntax, and semantics). The notion of information being smuggled into a simulation is widely discussed in the literature, and very competently by Dembski and Marks,28 who show how the contribution by intelligent intervention can be quantified.Absurdly, Thomas Schneider claims his “simulation begins with zero information” 29 and“The ev model quantitatively addresses the question of how life gains information, a valid issue recently raised by creationists (R. Truman, www.trueorigin.org/dawkinfo.htm) but only qualitatively addressed biologists.”30,31Schneider’s simulations only work because they were designed to do so, and are intelligently guided. 32 This has been quantitatively addressed by William Dembski.32 Furthermore, the framework in part 3 will show that Gitt’s higher levels can also be quantified. Gitt’s four most important Scientific Laws of Information, published in this journal,17,18 are: SLI-1: A material entity cannot generate a non-material entity. SLI-2: Universal information is a non-material fundamental entity. SLI-3: Universal information cannot be created by statistical processes. SLI-4: Universal information can only be produced by an intelligent sender. Can we be satisfied that these are robustly formulated according to Definitions 1 and 2, above? For SLI-1 the question of complete conversion of matter into energy should be addressed. What about SLI-2 through SLI-4? I see no chance they would be falsified if we were to replace ‘Universal information’ by ‘coded messages’, which is integrated into UI. With a slight change in focus, introduced in part 3, I believe a stronger case can be made. SLI-2–SLI-4 using Definition 1 For SLI-2 it is unclear what entity means, since the definition says, “Information is always present when …” and the grammar does not permit the thoughts to be linked. Since apobetics is not provided by the entity making use of DNA, this definition still needs work. Nevertheless, the definition includes the thought ‘in a system’ and this is a major move in the right direction (see part 3). SLI-3 surely can’t be falsified, since the definition requires the presence of apobetics, which seems incompatible with statistical processes. There seems to be a tautology here, since statistical processes describe outcomes with unknown precise causes, whereas apobetics is a deliberate intention. SLI-4 makes a lot of sense, but only if one understands UI to refer to a multi-part system and not an undefined entity. SLI-2–SLI-4 using Definition 2 For SLI-2 it is unclear what entity means, presumably the message. But it is questionable that the message must be responsible to convey the expected actions(s) and the intended purpose(s). Decision-making capabilities could exist a priori on the part of the receiver, who pulls a coded message from a sender, and then performs the appropriate actions and purposes. The actions and purposes need not be conveyed by the message. Cause and effect here can be reversed. Example 1. The receiver wishes to know what time it is. A coded message is sent back. The receiver alone decides what to do with the content of the message. Example 2. A rich man compares prices of various cars, airplanes, and motorboats. The coded information sent back (prices) does not convey the expected actions(s) nor the intended purposes(s). The man provides the additional input, not the message! SLI-3 and SLI-4 make sense. Value of Shannon’s work is underrated Much criticism is voiced in the creation science literature about Shannon’s definition of information, which he preferred to call communication, dealing as it does with only the statistical characteristics of the message symbols. Given Shannon’s goal of determining maximum throughput possible over communication channels under various scenarios, it is true that the meaning and intention of the messages play no role in his work.My concern is that I suspect his critics may have overlooked some deeper implications which Shannon himself did not draw attention to. There are good reasons why all the researchers mentioned8 in part 1 use expressions like, “according to information theory” or, “the information content is” when discussing their analysis of biological sequences like proteins. Implicit in these researcher’s comments are notions of goals, purpose, and intent. These are notions associated with information in generic, layman . Information theory inevitably refers to Shannon’s work, even though the claims made about his work cannot be found directly in his own pioneering publications. Are there reasons why the goal-directing effects of coded messages, like mRNA, remind us of Shannon’s information theory? Is the wish to attain useful goals, intentionally implied in Shannon’s work? The answer is yes. Here are some examples:Corruption of the intended message. The series of symbols (messages) transmitted can be corrupted in route. Shannon devotes considerable effort in analysing the effects of noise and how much of the original, intended message can be retrieved. But why should inanimate nature care what symbols were transmitted? Implicit is that there is a reason for transmitting specific messages.Optimal use of a communication channel. If there are patterns in the strings of symbols to be communicated, then better codes can often be devised. Suppose an alphabet consists of four symbols, used to communicate sequences of DNA nucleotides (abbreviated A, C, G, or T) or perhaps to identify specific quadrants at some location. Statistical analysis can reveal the probabilities, p, which need to be transmitted, e.g. A (p = 0.9), C (p = 0.05), G (p = 0.04), and T (p = 0.01). We decide to devise a binary code. We could assign a two-bit codeword ( 00, 01, 10, 11) to each symbol, so that on average a message requires two bits per symbol.People discuss frequently an immaterial entity called information. Information Theory usually refers to Shannon’s work. The many alternative meanings of the word lead to ambiguity, and detract from the issue of its origin. However, more compact codes could be devised for this example. Let us

invent one and assign the shorter codewords to the symbols which need to be transmitted more often: A = 0; C = 10; G = 111; T = 110. A message is easily decoded without needing any spacers. For example, 0010011000010 can only represent AACATAAAC. On average, messages using this coding convention will have a length of 1 x 0.9 + 2 x 0.05 + 3 x 0.04 + 3 x 0.01 = 1.15 bits/ symbol, a considerable improvement.Implicit in this analysis is that it is desirable for some purpose to be able to transmit useful content and to minimize waste of the available bandwidth. It is also implied that an intelligent engineer will be able to implement the new code, an assumption which makes no sense in inanimate nature. 33Calculation of t entropy and conditional entropy. Various technological applications exist for mathematical relationships such as t and conditional entropies. Calculating these require knowing about the messages sent and those received. Nature has no way or reason to do this. By performing these calculations one senses that intelligent beings are analyzing something and for a purpose.Warren Weaver, Shannon’s mentor professor and co-author of the book edition published in 1949, discerned that meaning and intentionality are implied in their work. In the portion he wrote we read,“But with any reasonably broad definition of conduct, it is clear that communication either affects conduct or is without any discernible and probable effect at all.”34And Gitt’s work is foreshadowed in insights like: “Relative to the broad subject of communication, there seems to be problems at three levels. Thus it seems reasonable to ask, serially, “LEVEL A: How accurately can the symbols of communication be transmitted? (The technical problem.) “LEVEL B. How precisely do the transmitted symbols convey the desired meaning? (The semantic problem.) “LEVEL C. How effectively does the received meaning affect conduct in the desired way? (The effectiveness problem.)”35 Concern about Shannon’s initiative Two reasons are often mentioned for claiming information theory has no relevance to common notions of information: “More entropy supposedly indicates more information.” But how can this be, since a crystal with high regularity surely contains much order and little information? And the chaos-increasing effects of a hurricane surely destroy organization and information. “Longer messages imply more information.” Really? Does the message ‘Today is Monday’ provide less information than ‘Today is Monday and not Tuesday’? Or less than ‘Tdayy/$ *!aau!##$ is Modddndday’? These two objections, commonly encountered, reflect a weak understanding of the topic and prevent extracting a significant amount of value available. For purposes of creation-vs-evolution discussions, a good suggestion is to profit from the mathematics Shannon drew attention to but avoid referring to information theory entirely. Shannon himself only used the phrase theory communication later in his life. For most purposes we are interested in probability issues: how likely are naturalist scenarios, based on specific mechanisms? Generally, we can limit ourselves to three simple equations which are not unique contributions from Shannon. The definition of entropy was already developed for the field of statistical thermodynamics:

H refers here to the entropy per symbol, such as the entropy of each of the four nucleotides on DNA. The Shannon–MacMillan–Breitmann Theorem is useful to calculate the number of high-probability sequences of length N symbols, having an average entropy H per symbol:

An example is shown in table 1. When the distribution of all possible symbols, s, at each site is close to fully random, the number of messages calculated by 2 NH and sN are reasonably similar. The symbols could be amino acids, nucleotides or codons. Eqn (2) is important for low entropy sets, see table 1.Table 1. Example of eqn (2) to calculate the number of high-probability sequences based on the entropy, H*. The first column shows the probability of one amino acid being found at a site and in the second column we assume the remaining 19 amino acids are distributed equally. A protein with N = 200 amino acids (AA) is assumed here.The difference in entropy at each site along two sequences is of paramount interest:where H0 is the entropy at the Source and Hf at the Destination. To analyze proteins, these two entropies refer to amino acid frequencies, calculated at each aligned site. The sequences used to calculate Hf perform the same biological function. Following a suggestion by Kirk Durston, let us call H0 – Hf the Functional Information36 at a site. The sum over all sites is the Functional Information of the sequence. What does eqn. (3) tell us? If the entropy of a Source is unchanged, the lower the entropy which is observed at a receiver, the higher the Functional Information involved (figure 1). Figure 1. (Entropy of the Source) – (Entropy of the Receiver) defines Functional Information (FI) for a specific purpose. In A and B, HSource is the same, so FI for case A is greater than for B. Dark circles represent different messages, or strings of symbols. On the other hand, if the entropy of a receiver is unchanged, the higher the entropy which is observed at a source, the higher the Functional Information involved (figure 2). The ideas expressed in these three equations can be applied in various manners. Suppose the location at which arrows land on a target is to be communicated via coded messages (figure 3). A very general-purpose design would permit all locations in three dimensions over a great distance to be specified at great precision, applicable to target practice with guns, bows, or slingshots. The entropy of the Source would now be very great.

Another design would limit what could be communicated to small square areas on a specific target, with one outcome indicating the target was missed entirely. The demands on this Source would be much smaller, its entropy more limited, and the messages correspondingly simpler.A variant design would treat each circle on the target as functionally equivalent, restricting the range of potential outcomes which need to be communicated by the Source even more.To prepare our thinking for biological applications, suppose the Source can communicate locations anywhere within 100 m to high precision, and that we know very little about the target. We wish to know how much skill is implied to attain a ‘bullseye’. Anywhere within this narrow range is considered equivalent. We are informed of every outcome and whether a bullseye occurred. We can use eqn (1) to calculate H 0 for all locations communicated and the entropy of the bullseye, H f. Eqn. (3) is the measure of interest, and eqn. (2) can be used to determine the proportion of desired–to–non-desired outcomes. Figure 2. (Entropy of the Source) – (Entropy of the Receiver) defines Functional Information (FI) for a specific purpose. In A and B, HReceiver is the same, so FI for case A is greater than for B. Dark circles represent different messages, or strings of symbols. Of much interest for creation research is the proportion of the bullseye region represented by functional proteins. This is calculated as follows. A series of sequences for the same kind of protein from different organisms are aligned, and the probability of finding each of the 20 possible amino acids, p i, is calculated at each site. The entropy at each site is then calculated using (1), the value of which is Hf in eqn (3). The average entropy of all amino acids being coded by DNA for all proteins is the H0 in eqn (3). To these three equations let us add three suggestions: Always be clear whether entropy refers to the collection of messages being generated by the Source; the entropy of the messages received at the Destination; or the resulting entropy of objects resulting from processing the messages received. Take intentionality into when interpreting entropies. Work with bits no matter what code is used. A bit of data can communicate a choice between two possibilities; two bits, a choice from among four alternatives; and n bits, a choice from among 2n possibilities. If the messages are two bits long and each symbol (0 or 1) are equiprobable, it is impossible to specify correctly one of possible eight outcomes. The symbols used by a code are part of its alphabet. The content of messages based on non-binary codes can also be expressed in bits, and the messages could be transformed into a binary code. For example, DNA uses four symbols (A,C,G,T), so each symbol can be specific up to 2 bits per position. Therefore, a message like ACCT represents 2 + 2 + 2 + 2 = 8 bits, so 28 = 256 different messages of length four could be created from the alphabet (A,C,G,T). This can be confirmed by noting that 44 = 256 different alternatives are possible. Figure 3. Coded messages are to communicate the location at which arrows land on a target. Various designs are possible, depending on the intended use. Precise locations could be communicated, or only the relevant circle, or only location within the ‘bullseye’ circle. If the outcomes are far from random, effective and highly compressed codes can be devised to shorten the average length of messages sent with no loss of precision.We are now armed to clarify some confusion and to perform useful calculations. The analysis is offered as the on-line Appendix 1.37 Appendix 237 (also on-line) discusses whether mutations plus natural selection could increase information, using a Shannon-based definition of information. Conclusion People discuss frequently an immaterial entity called information. Information Theory usually refers to Shannon’s work. The many alternative meanings of the word lead to ambiguity, and detract from the issue of its origin. What could be meant when one claims many copies of the same information does not increase its quantity? It cannot refer to Shannon’s theory. Information in this case could mean things like the explanatory details or know-how to perform a task, usable by an intelligent being. Shannon’s model, however, claims that two channels transmitting the same messages convey twice as much information as only one would.What about a question like, ‘Where does the information come from in a cell or to run an automated process?’ Here information could mean the coded instructions or know-how which guide equipment and leads to useful results.The discussion in parts 1 and 2 of this series is not meant to favour nor criticize how others have chosen to interpret the word information. Many valuable insights can be gleaned for this literature. For purposes of gaining a broader view of all the components involved in directing processes to a desired outcome, I felt the need to move in another direction, which will be explained in parts 3 and 4.The evolutionary community is uncomfortable with the topic of information, but the issue is easier to ignore when there is disagreement on very basic issues, such as whether it can be quantified and whether higher life-forms contain more information or not.Covering so many notions with the same word is problematic, and in part 3 a solution will be proposed. Information Theory—part 3: introduction to Coded Information Systems by Royal Truman The literature about information is confusing because so many properties are described for supposedly a singular entity. The discussion can be more fruitful once we realize we are studying systems with many components, one of which is a coded message. We introduce the notion of a Coded Information System (CIS) and can now pose an unambiguous question: “Where do CISs come from?”, which should be more precise than the vague alternative, “Where does information come from?” We can develop a model which is quantifiable by focusing on the effects a CIS has on organizing matter through a sequential set of refining steps. In part 1 of this series1 I demonstrated that there are many usages of the word information, with many specialists working on different notions. Dretske points out that “It is much easier to talk

about information than it is to say what it is you are talking about … . It has come to be an all-purpose word, one with the suggestive power to fulfil a variety of descriptive tasks.”2 In part 2 of this series3 I drew attention to issues in various information theoretic models which seem problematic. There seems to be a common intuition that information leads to a desired outcome. But is information only vaguely (if at all) involved in attaining the intended goal (as implied by Shannon’s theory4) or fully, as Gitt maintains? 5Coded messages play a prominent role in Gitt’s framework, 6,7 and are clearly indispensable for the first three levels of his model (statistics, cosyntics, and semantics) but it is not apparent how symbolic messages appear directly in the last two levels (pragmatics and apobetics). And what exactly is a coded message? The gun fired to start a race consists of only one symbol. Statistics and cosyntics are missing, but meaning (semantics) is present. Was a message sent? Is this information?Schneider claims8 to show with a computer program that information can arise for free, autonomously, but Dembski argues decisively9 that the necessary resources were intelligently embedded into the program in different ways, and shows that information is provided whenever a suitable search algorithm is selected from among other possible ones.10–15 Can these ideas be reconciled to permit a coherent discussion?Surely information is more than mere cause–effect mechanics. Sometimes information is claimed to cause something via mechanical means. For example, the direction and force generated by a billiard cue has been said to provide the information to guide the ball. But all natural causes lead to some effect! So when is information involved? Surely information is more than mere cause–effect mechanics.Now, machines are also used by living beings to achieve a goal. Some, like computers, work with coded messages. What about a watermill which grinds grain into meal? The water provides the energy needed for the machine to work. One could adjust the amount of force delivered upon the rotating wheel by changing the amount of water provided, and the drop height. But there is no coded message in this kind of machine.Although the disagreements about how to define information are rampant, virtually no one would argue the subject matter is vacuous, a meaningless debate of empty words. Pioneering thinker Norbert Wiener stated correctly that “Information is information, neither matter nor energy”, but this left unanswered what it is. And even experts vacillate between different meanings of the word, so readers might not know exactly what is implied in each case. The confusion arises from a multitude (of sometimes only weakly related) ideas applied to a single word, information.To illustrate, Gitt assigns both statistics and apobetics to information in living systems, but how and where? On DNA? Statistics can indeed be discerned from gene sequences, but surely not from intended purpose (apobetics). The goal does not reside on DNA, fully nor implied. As we’ll see later, DNA is only one of multiple contributing factors to produce an intended outcome.As a second example, one of Gitt’s Universal Laws of Information is: “SLI-4c. Every information transmission chain can be traced back to an intelligent sender”. 16 In the same paper he also writes, “Remark R3: The storage and transmission of information requires a material medium.” It seems that transmission chain must be referring to coded messages, a stream of symbols on a physical medium. However, why must the other mandatory elements of his information or Universal Information (semantics, pragmatics, and apobetics) reside on, and be transmitted by, a material medium? Must an intelligent mind and all its parts be 100% material? I am not claiming there is contradiction in what Gitt writes. In fact, I edited and endorsed his last book. 5 Careful consideration of his work reveals that ‘information’ is somehow distributed in separate, organized ensembles of matter, energy, and mind (e.g. the statistics vs the pragmatics portion) with different properties and functions. This makes an answer to “What is information?” almost impossible. And it leads to a struggle to find words with compound meanings to convey the multiplicity of functions assigned to information. His second law states, “SLI-2 Universal information is a non-material fundamental entity”.Entity, in this statement, merely replaces Universal Information, and one does not know what it might mean. It reflects the search for a missing, suitable explanatory construct and therefore provides no additional insight beyond the phrase “Universal information is non-material”. But I believe the simple proposal introduced below will retain almost all his views in a coherent manner.When someone asks, “Where does the information come from which causes a fertilized egg to become an adult?” it seems that a series of linked, guided processes are implied. Processes is plural, whereas a singular word, information, does not capture this intuition very well.What needs to be explained? Analysing the world around us, we note a family of phenomena which are not explained by deterministic law or random behaviour. Examples include: Birds migrate to specific locations during certain time periods. Thousands of proteins are formed each minute in a cell and their concentrations and locations are carefully regulated. A few bacteria can reproduce into a large colony, metabolizing nutrients to survive. A foetus develops into an adult. Caterpillars metamorphose into butterflies. Assembly lines produce hundreds of cars each day. A few years after lava devastates a landscape, a new ecology develops. Text on a computer screen can be transferred to a printed sheet of paper. Deaf people communicate with a sign language. Satellites are sent to a planet and back. Figure 1. Complex equipment sends symbols to a Receiver able to receive and process the coded message. The shapes between Message Sender and Message Receiver represent symbols of a coded message. The above outcomes occur repeatedly, and what we observe does not follow naturalistic (mechanical) principles. Some observations become readily apparent. Observation 1. A series of linked processes are involved. Observation 2. of these processes sequentially refine and contribute towards a goal. Observation 3. A coded message is used somewhere along the chain of processes. Complex equipment generates a series of symbols, usually embedded on a physical medium, 17 which another piece of complex equipment receives, resulting in a measurable change in behaviour of a system attached to the Message Receiver (figure 1). Observation 4. All these kinds of systems are associated with living organisms. Making a fresh start To uniquely specify our area of interest, we exclude all systems and machines which do not use a coded message somewhere in the process. We are left with phenomena which have something to do with ‘information’, and we wonder where such systems come from. But asking, “Where does information come from?” is too vague for our scientific enterprise.

Clearly we are observing systems, with many independent, but linked, components. We need a definition for these message-based systems and then we need to consider how they could arise. Based strictly on observation, we make the following definition:A Coded Information System (CIS) consists of linked tools or machines which refine outcomes to attain a specific goal. A coded message plays a prominent role between at least two of this linked series.CIS theory recognizes Gitt’s five sequential processes: statistics, cosyntics, semantics, pragmatics, and apobetics.5 Messages vs sensors in CIS theory Coded messages are formed by ordered codewords, 18 which themselves consist of symbols from a coding alphabet. Messages must conform to the grammatical rules devised for that coding system.Cues or sensors are often found in a CIS but should not be considered coded messages. For example, a sensor could be composed of two metal parts, the volumes of which respond differently to temperature. When the temperature increases, selective expansion of one of the metals causes the construct to bend, bringing the tip of the sensor into with a critical element to trigger an action (such as by permitting a current to flow).Taste and smell receptors are unique to specific chemical structures, and are also sensors. If interaction at a detector is a simple physical effect, and a signal is transmitted without an alphabet of symbols which are independent of the carrier, then we have a sensor and not a coded message. 19 However, sensors are often valuable components of a CIS, and signals received by sensors could be converted into coded messages, as will be shown later.As one example, barn owls use two methods to localize sounds: the time differential between the arrival of a sound at each ear (the interaural time) and the variance in the sound’s intensity as it arrives at each ear.20 Are these cues, interacting directly with the external physical factors, coded messages? Not at the point of external , which is based on strict physical relationships, with no alphabet, nor grammar.As another example, a photoreceptor on a retina absorbs a photon, causing 11-cis-retinal to isomerize to 11-transretinal, which is followed by a signal cascade. This initially strictly physical behaviour is characteristic of sensors. The location at which the photon lands on the retina determines in most cases where the signal will be transferred to in the primary visual cortex of the occipital lobe. 21 The cue is transmitted over a neural pathway, and eventually coded messages are involved to communicate with the occipital lobe. Why do we make this claim?There are approximately 260 million photoreceptors on human retina. The initial signal gets transmitted a short distance, but these signals are subsequently distributed among only 2 million ganglion cells. “This compression of information suggests that higher-level visual centres should be efficient processors to recover the details of the visual world.” 22The signals originating from the retina are processed by specialized neurons which perform distributed processing to determine object attributes such as colour, location, and movement. Low-level algorithms are available, able to identify edges and corners. 23,24 Somehow the whole needs to be combined into a coherent whole, taking context into . The underlying language is not yet known, but rules are beginning to be identified, such as the use of AND operators. 25Coded messages could also precede and activate a specific sensor. And sometimes activation of a sensor can be supplemented with other contextual inputs which are subsequently coded into a message. To illustrate, a biochemical can dock onto a receptor (a sensor!) of a cell’s outer membrane, leading to a complex cascade of internal processes, culminating in regulation of several genes. The resulting process is part of a cellular language, the details of which are not fully elucidated. 26 In this case, the signal from a sensor contributes input to a coded message.The following example shows how sensors could be integrated into a CIS. Suppose four departments {A,B,C,D} at a university participate in races which occur hourly. During even-numbered hours men race; on odd-numbered hours the women do.A scoreboard is divided into eight portions, representing the four departments and the gender. Each time a sensor on one of the eight squares is activated, the value displayed increases by one. This could be implemented in a mechanical, strictly cause-effect manner. The sensors are identical and so are the cues received. So far there is no alphabet of symbols or syntax. Therefore, a coded message was not received at the scoreboard, although something useful did result. Nevertheless, we’ll show that a coded message could precede or follow the work of the sensor-based equipment. Figure 2. Coded messages can precede or follow the use of sensors. The winners from four departments {A,B,C,D} could be communicated by an initial message, e.g. B C C B D A. The Decoder determines from the time (even or odd hours) whether each symbol received represents a man’s or woman’s race. Both facts permit activating one of eight boxes on a scoreboard. The eight sensors can transmit a signal elsewhere, and at the end of the transmission a new codeword unique to each sensor is generated. The new code, e.g. 0111011001… can then be transmitted or stored.Let us assume the winning department for each hour is communicated by a judge, using a single symbol from the quaternary alphabet {A,B,C,D} which is transmitted towards the scoreboard (figure 2).27 The Decoder is also endowed with an internal clock, thereby permitting the winner’s gender to be identified. Now four departments × two genders, or eight outcomes, can be communicated, to one of the eight portions of the scoreboard, 28 although each symbol alone can only provide two bits of data. The winner can be communicated by transmitting an electric signal through the relevant wire on to the correct one out of eight sensors on the scoreboard (figure 2). 29The codes are independent of the physical infrastructure, as must always be true of informative codes. Suppose the winning department and gender are to be communicated to another location afterward. The back end of each of the eight boxes in the scoreboard first transmit a signal (not a message) along a cable. A coded message, unique to each original sensor, is then produced by encoders (the circles preceding the triangle in figure 2) using a new binary code, with codewords such as (0010), (1100), or (0111), unique to each wire. The new coded message identifies the same facts as the original quaternary one {A,B,C,D}, supplemented by the winner’s gender, and this message can now be transmitted far away or stored somewhere for future retrieval.Note how the specific assignment of A, B, C, or D to either of two out of eight boxes was arbitrary and so was the assignment of specific triplet binary codewords to each sensor. The codes are independent of the physical infrastructure, as must always be true of informative codes.I believe the simple example illustrates a general principle in cellular systems. Methylation at specific location on DNA or phosphorylation of portions of proteins are simple signals which get supplemented with other details and converted into coded messages. Senders and receivers in CIS theory The CIS model focuses on empirical measurements. A series of refining processes are observed, at least one of which results from receiving coded messages. Observations 1–3 above are illustrated in figure 3. Notice that after processing the message, additional refinements can occur, represented by the ever smaller contours in figure 3.

Figure 3. Coded Information Systems sequentially refine behaviour through a series of processes. At least one process is guided by coded instructions. Each goal-directing refinement step could be influenced through coded messages, sensors, physical hardware, or pre-existing resources such as data or logirocessing algorithms. The emphasis of the CIS approach is on observing the modified range of behaviour of the target system, unlike Shannon’s theory which analyzes the statistical features of messages. The effects caused by other sequential refinement components, which can precede or follow receipt of the message, are also evaluated based on resulting consequences. This will be elaborated on in part 4 of this series.Apropos quantifying information, Shannon’s model is unsuitable to evaluate prescriptive instructions. Suppose a robot is to extract trees from a forest. An algorithmic message is sent, indicating how to find the largest tree within 50 metres of the Receiver, step by step. Statistical analysis of the series of 0s and 1s transmitted would be of little value, but the approach of CIS is to measure the resulting outcome empirically. It is the contribution to producing the correct outcome which matters, when compared to the (theoretical) reference state, that defines improvement, measured in bits.The intention thus far is to introduce a more nuanced manner to discuss and measure information. The range of behaviour, weighted by observed probability, is compared for initial and a refined state, for each contour in figure 2. There can be many ways these improvements can be engineered, using software and hardware. Intelligent intervention, what some call smuggling information into a system, can now easily be taken into . For example, any artificial guidance to select a genetic or other algorithm to attain a specific outcome is an input which improves over the preceding, unguided state.The precise, regulated designs used in biology and technology can be understood and quantified with this simple CIS approach. The details themselves, like gene expression or metabolic regulation,30 are often exquisitely sophisticated, but are in a sense ‘only’ details which can be understood by drilling down from the high-level concepts of the CIS model. We will defer a description of the many designs found in nature, the purpose of which is to ensure the right outcomes in a CIS. 31CISs are created to organize matter and energy in precise manner at the correct time and location, a very dynamical challenge which requires sophisticated components. These integrated systems can typically be reused many times. The variety of unsuitable parts, which includes incorrect coded messages, greatly outweighs the functionally acceptable ones.The motivation behind this analysis is to force researchers to consider everything involved to permit a message-processing system, such as cells, to work. One of Truman’s harshest critiques 32 of the Avida setup and claims is that virtually everything necessary for the ‘simulation’ to work, such as physical replication of the electronic organisms, the energy source, physical transfer of data to the appropriate logic processing locations, and so on, were machines already made available. They made decisive contributions to ensure the desired outcomes. In nature all these components are coded for on DNA, and therefore subject to the ravages of random mutations. In Avida, mutations cannot destroy nor disrupt most of the fundamental system components. Virtually everything relevant to information was overlooked in the discussions. Forcing the participants to discuss the complete CIS should have prevented such foolishness.One final notion in the CIS model is to distinguish between two kinds of receivers: mechanical receivers, which respond deterministically to the message’s instructions; and autonomously intelligent receivers, who first evaluate and decide how to respond. Between these extremes lie a range of intermediate possibilities, including programmed artificial intelligence programs designed to incorporate various forms of reasoning, and systems able to query for additional relevant details from environmental sources.Part 4 will introduce the fundamental theorems associated with the CIS model, and show that this framework incorporates the insights from Shannon’s theory, Gitt’s model, Dembski’s contributions and other schemes. But consistent use of the CIS notions does lead to some different conclusions than those proposed by other frameworks. Conclusion The literature attempting to describe information is very broad. It is generally accepted to be non-material, and many attributes are assigned to it. But it seems that people are generally referring to a system which contains physical components, and not to a single entity. Analyzing components of a coded information system, such as coded messages, signals, and physical hardware separately, solves several conceptual difficulties. And as will be further elaborated on in part 4, the effects produced by a CIS as a whole offer a means to quantify what is accomplished by portions, or the complete CIS. Information Theory—part 4: fundamental theorems of Coded Information Systems Theory by Royal Truman In parts 1 and 2 of this series the work of various information theoreticians was outlined, and reasons were identified for needing to ask the same questions in a different manner. In Part 3 we saw that information often refers to many valid ideas but that the statements reflect we are not thinking of a single entity, but a system of discrete parts which produce an intended outcome by using different kinds of resources. We introduced in Part 3 the model for a new approach, i.e. that we are dealing with Coded Information Systems (CIS). Here in Part 4 the fundamental theories for CIS Theory are presented and we show that novel conclusions are reached. freeimages.com/flaivoloka In Part 3 of this series1 we emphasized that the word information, although singular, often refers to separate entities. This led to the notion that we are often describing a system, parts of which involve coded messages.

Definition. A Coded Information System (CIS) consists of linked tools and machines designed to refine outcomes to attain a specific goal. A coded message plays a prominent role between at least two of this linked series. Theorems to explain CISs A series of theorems are presented next, to clarify what a Coded Information System (CIS) is. These are based on observation and analysis of all coded information systems known to us. Theorem 1. A CIS is used to organize matter and energy to satisfy an intended goal. All components of the system which guide towards the final outcome, including timing and location, are part of a CIS. The resulting organization of portions of the material world reflect intended goals. All the components involved in a series of refinements to attain the final state are part of the CIS, and their effect must be quantitatively measurable, at least in principle.2 Theorem 2. A CIS can be used to achieve a mental goal. In the absence of wilful input, the organization of matter can be explained by deterministic laws of nature and statistical principles of randomness. Mental processes, however, are not controlled deterministically or by randomness, and include: making choices; seeking to understand; and developing a strategy.Suppose you are learning German, and are reflecting on what Unsinn might mean. The intention to translate is surely not deterministic, nor explained by randomness. Perhaps the intention is stored temporarily (physically?) in the brain, with which an immaterial you interacts almost instantly. You know what you wish to do and can easily communicate this to others. This intention is converted somehow into a physical search through the data stored in your neurons. This requires very special mental equipment, since a multitude of kinds of searches are possible: for a discrete telephone number; for how a face looks; for a melody. The list is near endless. In this case we’re searching for a concept which we believe reflects the meaning of Unsinn.The concept we seek to translate must be encoded in some manner, and the searches directed efficiently. Suitable data must somehow be extracted from the neurons, requiring further mental machinery, and the results must be encoded and transferred somewhere for the mind to evaluate. Another tool then compares a candidate English word, the associations of which get compared with those of Unsinn. It is absurd to argue neurotransmitter concentrations or electrical signals are being ‘compared’ across billions of neurons. The logical processing must involve some kind of compression and high-performance language. Eventually the mind decides whether a potential translation of Unsinn, like nonsense, is correct or not. All the resources involved in mental processes like these are part of a CIS, and some are not physical. All the resources involved in mental processes like these are part of a CIS, and some are not physical. Various resources narrow the range of possibilities, including when the translation is to occur and where. Theorem 3. Coded messages do not arise from the properties of the physical carrier medium. An implication which results is that the symbols used by the coding alphabet can appear in any order and combination, whether the resulting messages serve a purpose or not. Ideally the carrier must not place any constraints on the potential messages which could be created.3By our definition, a CIS must use a coded message at some point. Otherwise we’ll treat the phenomenon as a tool. Some coded messages provide step-by-step instructions on how to accomplish something. Examples include computer programs and algorithms. These messages must be supplemented with hardware able to carry out the instructions.Another class of coded messages only specify specific outcomes or choices, without any instructions on how to attain them. A communication convention must be established a priori. The message ‘01101’ might mean ‘bring me menu number thirty one’, or ‘pitch a curve ball’. Combinations of these two extremes are possible, such as when a computer program invokes a subroutine (or method or function) using parameter values.Coded messages permit intended outcomes to be communicated between flexible tools and machines, which have been designed to solve a class of problems. This is an efficient manner to use resources to solve problems. The alternative would be to build assembly lines of machines to solve each individual problem and then to communicate which ensemble is required for each problem.Instead, to illustrate, billions of dollars of complex logistics components of an overnight delivery service can be put to use flexibly by only associating a coded delivery address to the object to be transported.The use of coded messages characterizes living organisms, to control their development and response to novel situations; and to interact among each other. Humans devise coding conventions with so little effort that few realize what an extraordinary feature this is. Being so fundamental to a wide class of life-related observations, the presence of a coded message is a requirement for a system to be considered a CIS. Theorem 4. The coded message does not provide the energy which causes the intended changes.The outcomes produced by messages must not be caused only by the carrier medium, to distinguish from mere mechanical effects. The symbols in a coding alphabet could indeed require different amounts of energy to be generated or processed. For example, in alphabet {0, 1} the 0 could be communicated by lifting one arm, and the 1 by lifting both arms. But the energy to produce the symbols must not lead to the resulting changes upon processing the message (e.g. by providing different levels of force, or resulting momentum in a specific direction, caused directly by the symbol). Theorem 4 draws attention to the need for independent components to be engineered for a CIS to work. Energy in the right form, time, and place must work with the intent expressed by the message. Theorem 5. Outcomes improved beyond what coded messages alone convey imply additional refining components are involved. The additional contributions can be expressed quantitatively. Figure 1. A jet interceptor is instructed to fly off in one of four possible directions. This provides log2(4) = 2 bits of information. An example in Part 3 of this series 1 revealed this principle. The coded message communicated only four possible choices (two bits of information), but an internal clock revealed in addition whether a race had been carried out during odd or even hours, thereby indicating the gender of the winner. Therefore, the correct one out of eight choices was able to be determined with the help of the clock.Example 1. Assume the jets on an aircraft carrier are only told whether to fly off in one of four quadrants, figure 1. Suppose careful observation shows that the pilots begin search manoeuvres only once beyond a certain distance from the ship (therefore, the central square in figure 1 was excluded).Although log2(4) = 2 bits of information can only communicate the correct quadrant, we observe that the target is usually identified, although located within a small portion within a quadrant. How is this possible? Clearly additional refining components were available. Repeated observation would allow the scientist to identify at least three sequentially refining components (without knowing anything a priori about the details of the coded message): a) a coded message directs into one of four directions; b) searching begins some distance from the carrier (there is prior knowledge that an alarm will occur when the enemy is still far away); c) there are specific kinds of targets to search for, plus logic and special equipment to perform the searches. Example 2. Proteincoding portions of DNA are the messages which communicate the order in which each of twenty possible amino acids are

linked. But notice that almost always only l-form amino acids appear in the proteins. The choice of isomer was not communicated by the mRNA messages, but optically pure amino acids were independently manufactured as feedstock. We also observe that undesired chemical reactions amino acids normally undergo are prevented when forming the proteins. For example, the side-chains of amino acids don’t react together, nor do short five-to seven-membered chains form.4 This is true because outcome-guiding equipment was deliberately included in the design. Figure 2. Trade-offs between message complexity and engineering design. A) The message communicates only the final destination. Resources receiving the message must interpret it and have the means to act upon the communicated intention. B) The message communicates step-wise what is to be done. U = ‘Up’; L = ‘Left’ one unit. Now the messages are more complex but the equipment can be simplified. Other illustrations (examples A1–A6) are offered online. Figure 2 is explained in example A4 on-line. Theorem 6. Receipt of a message often communicates more than just the coded content. The bits of information provided in a message provide an incomplete picture from the point of view of resulting outcomes. Although choices between alternatives can be communicated, the changes which result occur in narrow time and location ranges. The equipment receiving the message could be used more than once, and the correct Receiver could be targeted, at the correct time and location. Example 3. A zip code can communicate where to deliver a package, but when it is generated and on which object make a difference! The intended goal must be taken into . Theorem 7. Refinement components are integrated into a sequence to produce the intended outcome. Refinement components, designed to refine towards a goal, include: received coded messages engineered constraints or guidance external cues preloaded algorithms or reasoning resources. The state of affairs achieved from one component of the CIS becomes the starting point for additional improvement by other components. Theorem 8. The quantitative contribution of Refining Components can be calculated by comparing ranges of behaviour before and after the goal-directing activity. A fundamental notion in CIS Theory is to identify the contribution provided by each discrete component in the processing chain, by identifying the range of behaviour before the refinement and afterward. The theory applies to any kind of behaviour in time and space. And the improvement can be due to receipt of a coded message and/or of other factors.The range of possible outcomes will be represented by a discrete number n; the entropy H; L or a probability distribution function. We will use some mathematical ideas developed by Shannon, as discussed in Part 3, 1 to define the Refinement Improvement5 as Hbefore – Hafter, which is measured in bits. This permits the improvement by each member of the chain, expressed in bits, to be additive. Theorem 9. Quantifying the contribution from a received message may require analysis of a single final state or of intermediate ones along the way. It is necessary to evaluate what the intention is. Figure 3. Convoluted messages could reveal incompetence or deliberate intention. Upon processing the message, the vehicle here ends at the same place as shown in figure 2, although the message and trajectory is now more complex. If the intention was only to deliver to a specific location, then the message ‘select one out of 64 possibilities’, or 6 bits of information, would suffice. But if the trajectory had a deliberate purpose, the outcome would have to be compared to the relevant reference alternatives, taking each subgoal into .Example 4. In the CIS methodology we focus on behaviour which results from refining factors, and not the statistical details of coded messages (which is Shannon’s methodology). Unlike Example A4 online, suppose the intention of a message was to provide an itinerary, figure 3. Comparing one final destination with all possible outcomes (1/64) would be wrong if the intention was a ‘milk run’,6 like a parcel service delivering packages, or a path to transverse a mine field, or to avoid incoming missiles. Then the result of each successful decision would need to be compared to the relevant reference state and not the one-time final destination.If the intention was a one-time delivery of a package to a final destination, then the space of random possibilities around the starting point would be the ‘message-less’ state and would define the possible outcomes.Alternatively, if the intention was to avoid in-coming missiles again and again, the random behaviour around each decision point would define the reference state. Note that in these kinds of analysis another resource is at play. In the random reference state, the vehicle has no reason to move at all. Independent of the message’s content, its receipt communicates that something is to be done.7Often a message communicates more than necessary. This could be due to incompetence; or to refine or to correct instructions already sent. It is also possible that other resources (logic, stored data) available to the Receiver indicate that messages, or parts of them, are to be discarded. For example, the message to print a page with various colours could be corrected by software which is ‘aware’ that a colour cartridge is missing and only black and white outputs can be generated. Theorem 10. Part of a CIS may permit behaviour to occur which otherwise wouldn’t be observed. To quantify the improvement provided by one of the CIS resources, a realistic hypothetical reference system behaviour needs to be defined. Example 5. DNA encodes the order in which amino acids link to form proteins. For this to occur, the carboxyl group at the end of one amino acid must react with the amino group at the other end of another amino acid, to form peptides bonds. But amino acids in free nature or a laboratory undergo a variety of other chemical reactions. As an example, amino and carboxyl groups that are present on side-chains can also react. In addition, the carboxyl and amino acid ends of a growing

polypeptide will react in an intra-molecular fashion, creating cyclic rings; and other reactions also occur.In cells, clever design prevents the wrong reactions from occurring. Computer simulations could be built to estimate the proportion of protein-like chains which amino acids would form compared to all possible reactions, based on d and l racemic mixtures.8 Example 6. In water, peptides hydrolyze instead of forming long chains. For even a very short protein with 100 peptide bonds (101 amino acids), the equilibrium concentration would be about 3 × 10 –216.9 So how can proteins form at all in cells? It is because water is excluded from the interior of the ribosomes, and energy is provided by ATP to drive the polymerization reaction forward.These examples show it is impractical (and unnecessary) to always perform empirical studies on how nature would react in the absence of a CIS. But a reasonable estimate is still useful, and the probabilities can easily be converted into bits of information.10 It is usually sufficient to determine when a probability is so miniscule that nobody will ever see the event unless something, like intelligence, provides a new pathway for it to occur. Theorem 11. Individual Refinement Components can contain multiple improvement steps. We saw in Examples 5 and 6 that specialized machinery like ribosomes can make multiple contributions. One can combine contributions to simplify the analysis if one wishes. Theorem 12. Accumulated goal refinements, defined by CIS in bits, reveal far more about what is accomplished than Shannon Information Theory implies. Molecular machines are built to solve thousands of kinds of problems such as catalyzing metabolic reactions, transporting bio-chemicals, and replicating chromosomes. The quantitative CIS theory seeks to explain how so much more is accomplished than is implied by the statistical studies of coded messages, such as of gene sequences. Example 7. In the brain there are special kinds of cells called neurons, organized into specialized signal-processing subsystems.11 These come in many sizes and shapes with very different designs and functions. There are about 10 11 neurons in the human brain and about 1014 synapses,12 which must be placed at the right locations, and interconnected correctly. As an example, the Purkinje cells of the cerebellar cortex have about 200,000 synaptic s each. 13 The first question is, where do the instructions come from to physically build such complex brains? And second, where does the input come from which permits brains to make thousands of multimedia decisions each second? These requirements cannot be explained by the bits of Shannon information implied on the chromosomes of the fertilized egg. The coded information is embedded in a context which provides additional refinements, and the neurons are refined by their ability to learn. Theorem 13. There can be trade-offs in how a CIS can be designed. The contributions towards the goal, expressed in bits, can be distributed between the message and the hardware equipment. Examples A4 and A5 online illustrate this principle. Example 8. Suppose 20 copies of five books are to be printed out. One solution would be for the message to transmit the relevant text each time for every book, which flexible printing equipment must then process. Another solution would be to build five machines, each of which mechanically prints out a single book. Now one only needs to send a signal to the appropriate machine, 20 times, communicating to start printing. The final outcome is the same, but the effort, expressed in bits according to resulting outcome, are distributed over different refining components. Example 9. Printers can often handle papers of different standard formats. The content to be printed, plus instructions on how to manipulate all the physical parts to position the paper and ink in the right position, could be part of a huge coded message. A better design would be to engineer the printer to always position the paper for each standard size in the same manner, so that the message only needs to communicate the content and paper size. Example 10. Many business presentations benefit from the use of colour. The background colour and display for PowerPoint presentations are communicated along with the content to be presented. This is a better design than to send content to a large number of differently designed printers, each filled with paper prepared with a specific kind of coloured background. Theorem 14. The hardware components found in an integrated CIS do not arise from the properties of the physical carrier medium. For example, many kinds of media can be used to store the same computer data. These materials could be made into memory sticks, DVDs, hard disks, archival systems, etc. The origin of these engineered parts, as also for biological parts, are not simple extrapolations of atomic properties. They have to be wilfully organized. Theorem 15. The contribution towards a goal provided by a particular refinement component cannot be more than the improvement observed, expressed in bits. This is related to Theorem 5. This simply means that guiding towards a goal cannot come for free. If there are eight equally likely outcomes, communicating the correct one each time cannot be done with less than three bits of coded information.14 These must come from somewhere. This theorem is intuitively obvious but woefully neglected in the evolutionary literature. Bartlett 15 recognized correctly that rapid change can, and does, occur in nature, if the guiding inputs have already been made available and only need to be activated. The notion of preloading of information to ensure future outcomes is also common among Intelligent Design thinkers. Scientists realize intuitively that purposeful behaviour implies that guidance is coming from somewhere. The fact that the same kinds of proteins always ended up in the same place in cells led researchers to look for special signals guiding this process. And the rapid response of whole populations in short time periods to environmental changes led to the search for, and discovery of, epigenetics.16 What is overlooked is the fundamental insight that planning and ensuring desired outcomes are characteristics of intelligent agency, and that the methods used to store intent are not found anywhere in inanimate nature. Theorem 16. There is no direct relationship between goal refinement in bits and importance of the outcome. Thumbs up or down decided life or death of a Roman gladiator. One mere bit of information, two possible outcomes, but with a dramatic impact! Theorem 17. Bits in CIS theory are not a direct indicator of difficulty in achieving the goal. It is true that there is an inverse relationship between many bits in outcome, and likelihood the effect could arise by chance. This is especially clear in CIS theory, where outcomes are compared to what would happen by natural processes. But one must recall (Theorem 13) that there are trade-offs between what the message and the hardware could provide. A simple message to an aircraft carrier flotilla to ‘turn left’ or ‘turn right’ represents only one bit of information because the rest of the details necessary are handled by other parts of the CIS. These one-bit coded messages have a huge lever effect. If the design of two CISs have identical final outcomes, then a comparable number of bits should be calculated. But focusing on the number of bits provided by intermediate CIS ‘services’ can be misleading. Theorem 18. Wilful, intelligent decision-making occurs during the processing of a CIS; or decision-making has been preloaded for it to occur autonomously. In some CISs, parts can respond mechanically, whereas in other CIS designs, intelligent decision-making is involved. In the mechanical version, intelligence is used to ensure intended outcomes. Complex algorithms can be devised to free active

intelligence from having to be present during future execution of a CIS. Examples are techniques used in artificial intelligence. In addition, sensor and queries to the environment can be automated to ensure reliability of the automated portions of a CIS. Theorem 19. The performance of a CIS will not improve over time in the absence of intelligently provided guidance. Refinement in the outcome or adjustment to new circumstances requires preloaded facilities in some part of the CIS. One must not overlook, however, that improvement is possible through an algorithmic, iterative process of selection. This occurs for ß-cell maturation17 and there are many examples in numerical analysis, like Runge-Kutta methods. 18 Natural selection could conceivably be an example, if a small number of organisms, like bacteria, were initially created with the intent of diversifying and specializing. But for this strategy to work, outcomes must be fed back into the causal instructions and an effective method already built in to move in a promising new direction.Natural processes are not capable of creating a CIS. Only sentient, intelligent beings able to identify desired goals can create a CIS. Theorem 20. Natural processes are not capable of creating a CIS. Only sentient, intelligent beings able to identify desired goals can create a CIS. The justification for this is two-fold. First, we notice how easily intelligent beings like humans design a CIS, whereas nothing resembling a CIS occurs in the abiotic universe. Second, by examining in depth how outcomes are guided, we notice that the resulting bits of improvement are huge. These are calculated by comparing to a reference state which lacks the CIS, which ultimately means comparison to random processes, or to those guided by natural law. Every bit represents a factor of two change in probability, where two scenarios are being compared: that the initial state migrated into the new one via the natural processes already operating vs via deliberate intervention. Results from replacing information by CIS Given the many meanings of information, asking where it comes from is too vague and ignores the full picture the Coded Information System approach offers. The issues already introduced in the literature 19,20,1 about information are all subsets of a CIS. For instance, one can always ask what the source of a coding convention is, and coded messages are part of a CIS. Or what guided a particular message to the specific Receiver. CIS goes beyond what Shannon looked into. For example, the decision when to send the message is also unique to the CIS approach. The underlying notions presented in this paper lead to different answers than generally offered about information. Gitt and others say that multiple copies of an identical message do not provide ‘more information’. Once how to accomplish something has been communicated, extra copies are not considered to offer anything additional. This has been a criticism of Shannon’s approach, where if two communication channels transmit the same message, twice as many bits of information are claimed.However, the effect of a CIS is to reorganize matter and energy for some purpose. Therefore, if a coded message is used repeatedly in a CIS at different times and locations, then more matter and energy have been organized. The effect, in bits, is greater from the universe’s point of view. This means that if there are identical copies of a bacteria, the effects of each of these CIS would be additive. Is this not reasonable?We prefer this view than to ask where a gene comes from, and then report the bits from only one copy. Furthermore, reuse of a CIS (including after genetic reproduction) requires the existence of other complex components, which automatically get neglected if one copy and one event only are reported. The total effect of multiple copies and reuse give credit naturally to the additional components which make this possible.Cellular machines can process similar metabolites, using the exact same genes. But in one microenvironment a nutrient might be present but not in the other. Therefore, the measurable effect of two separate but identical CISs at different times and places can vary!The earth contains about 6 x 10 27 gm of matter.21 And 12 gm of the isotope carbon-12 contains 6 × 1023 atoms. The number of entities on Earth is very large, whether we mean atoms or molecules, on the order of roughly 1050.22 Potentially any entity on Earth could be associated with any other: as part of a chemical reaction; as part of a new object; or to modify the properties of other entities. Merely moving an entity during a second changes about 10 (50)2 = 10100 pairwise distance relationships, and sometimes multiple other properties besides only their spatial relationships. The organization of all objects on Earth related to living organisms is a vast number, which places great demands on the organizing effects of the available CISs.Organizing nature on Earth, with its complex ecosystems, means rearranging all this matter and energy in the face of the unimaginably large number of possible distributions. The CIS model credits contribution to this effort to the multiple copies and reuses of the message-containing information systems.Gitt considers his theorems laws of nature. For example, Scientific Law of Information (SLI) 3C states, “It is impossible to generate UI without an intelligent sender.”23 The justification seems to be that the claimed SLIs should be considered laws until disproved. This seems like a weak argument, since there are many statements which reflect all known experience so far and are difficult to disprove. All facts to date a claim such as, “It is impossible to build a manned station on another solar system”, but is this a law of nature? We certainly agree that UI (Universal Information) cannot arise by natural processes. But by UI we mean the whole package, which is a CIS. Based on known science, we are persuaded that bringing together all the components needed by a CIS, at the right time and location, including a coding convention, is never going to happen. But we believe the CIS justification is sounder, since quantitative and measurable criteria underlie this belief. A new view of nature CISs can be embedded hierarchically. A low-level CIS could synthesize an amino acid, which is embedded in a higher CIS to produce proteins. The system analysis would now include all factors involved in reproducing DNA; 24 decoding DNA;25 regulating location;26 timing;27 and number28 of enzymes (mostly proteins); and formation of the tertiary 29 and quaternary30 protein structures, including bonding to other bio-chemicals. An example of a higher-level CIS, with embedded subsystems, would be a multi-cellular organism and include all processes to develop into the final, mature state. An example of a still higher order CIS, with a hierarchy of embedded sub-CISs would be an ecological system, consisting of a variety interacting species.In Part 3 we provided a figure to help visualize how a series of embedded, refining contributors narrow the range of behaviour, using a combination of a) coded messages; b) signals; b) preloaded logic processing and knowledge; and d) engineered components. This is, of course, merely conceptual, and leaves out the exact details used. These four generic classes of refining contributions can be re-invoked to understand the deeper levels of refinement, level by level. This analysis offers a new way of looking at the world we live in. Vast quantities of matter and energy have been organized within hierarchies of dynamic CISs, leading to a cascade of intermediate goals. And our world itself is embedded in higher CISs as part of ultimate goals. Conclusion The CIS model considers the quantitative contribution of all goal-refining components linked by the system. Instead of asking where information comes from in nature, we propose to ask where Coded Information Systems come from, which ensures a more complete coverage of all the issues which need to be addressed. The twenty theorems are based on observation and serve to clarify the key ideas of CIS theory. Additional examples of CIS are discussed in the on-line appendix to illustrate these principles.31

Genetic code optimisation: Part 1 by Royal Truman and Peter Borger The genetic code as we find it in nature—the canonical code—has been shown to be highly optimal according to various criteria. It is commonly believed the genetic code was optimised during the course of an evolutionary process (for various purposes). We evaluate this claim and find it wanting. We identify difficulties related to the three families of explanations found in the literature as to how the current 64 → 21 convention may have arisen through natural processes. 123rf.com/Sergey Sundikov The order of amino acids in proteins is determined by information coded on genes. There are over 1.51 × 1084possible1 genetic codes based on mapping 64 codons to 20 amino acids and a ‘stop’ signal2 (i.e. 64 → 21). The origin of code-based genetics is for evolutionists an utter mystery,3 since this requires a large number of irreducibly complex machines: ribosomes, RNA and DNA polymerases, aminoacyl tRNA synthetases (aaRS), release factors, etc. These machines consist for the most part of proteins, which poses a paradox: dozens of unrelated proteins are needed (plus several special RNA polymers) to process the encoded information. Without them the genetic code won’t work, but generating such proteins requires that the code already be functional.This is one of many examples of ‘chicken-and-egg’ dilemmas faced by materialists. Another is the need for a reliable source of ATP for amino acids to polymerise to proteins: without the necessary proteins and genes already in place such ATP molecules won’t be produced. In addition, any genetic replicator needs a reliable ‘feed stock’ of nucleotides and amino acids, but several of the metabolic processes used by cells are interlinked. For example, until various amino acid biosynthetic networks are functional, the nucleotides can’t be metabolised. These are some of the reasons we believe natural processes did not produce the genetic code step-wise. We hope to present a detailed analysis of the minimal components needed for a genetic code to work in a future paper, but this is not the topic we wish to address here.The literature is full of papers which claim the universal code4 has evolved over time and is in some sense now far better than earlier, perhaps even near optimal. We cannot address all the models and claims here, but we hope to present a few thoughts which we hope will show that these claims are ‘flights of fantasy’. No real workable mechanism has yet been offered 1,3 as to how a simpler genetic system could have increased dramatically in complexity and in robustness towards mutations. If a primitive replicator had gotten started,contra all chemical logic, would it be possible according to various evolutionary scenarios to refine the system to generate the 64 codon → 20 amino acid + ‘stop’ signal convention used by the standard genetic code? Origin of any genetic code Before an evolutionary process could optimise a code, a replicating lifeform must first exist with some kind of information processing capabilities. Trevors and Abel published one of the most honest and illuminating papers 3 on the issues which confront a naturalistic explanation for the origin of life. In particular the origin of an information storing and processing system, able to guide the synthesis of proteins, is recognized as incomprehensible. In their own words, ‘Thus far, no paper has provided a plausible mechanism for natural-process algorithm-writing’.5 Abel is well known for his attempts to find a natural origin for the genetic code and naturalistic explanation of the origin of life. He and The Origin-of-Life Foundation, Inc. ® have a standing offer of $1 million to anyone providing a plausible natural solution. 6 In stark contrast to the straightforward honesty offer in this paper3are a large number of Origin-of-Life papers which appeal to no recognizable chemistry and offer no conceptually feasible path as how to go from their vague notions to extant genetic systems.There are three basic approaches7 used by materialists to explain the 64 → 21 mapping of the genetic code: (I) chemical/stereochemical theories, (II) coevolution of biosynthetically related amino acid pathways and (III) evolution and optimisation by natural selection to prevent errors. There is a logic to the order in which we present these three approaches. (I) is closest to the question of a natural origin for a biological replicator. (II) already requires a large number of complex and integrated biochemical networks to be in place. Attempts to explain the 64 → 21 code mapping at this level would clearly mean ignoring the question as to where all these molecular machines and genes came from. (III) Evolutionary hypotheses to explain the 64 → 21 mapping at this level would require assuming all 20 amino acids are already present in a genetic code and that most genes already code for highly optimised proteins. (I) Chemical/stereochemical theories All the suggestions in this area assume some kind of simple starting system, being guided by natural chemical processes. These primitive systems then accumulated vast amounts of complexity and sophistication.Attempts have been made to find direct chemical interactions between portions of RNA and amino acids.8 These are supposed to have led to the genetic code. Amino acids might bind preferentially to their cognate codons, 9 anticodons,10 reversed codons,11 codon-anticodon double helices12 or other chemical structures.After itting that ‘there is little evidence for selective binding of amino acids to isolated codons or anticodons’, Alberti13 proposed that chains of mRNA would interact with special tRNA chains, and short peptides would attach specifically to these tRNAs. Being now brought close together, the short peptides would polymerise to form proteins. A number of cofactors would stabilize the tRNA-mRNA interactions, eventually becoming ribosomes. Another set of cofactors would decrease the number of amino acids needed to provide a specific interaction with the various tRNA, which today is done by aaRSs. Objections. None of the reports in this area reveal any kind of consistent association between codons and the amino acid expected based on the genetic code.14 The wide variety of chemical systems intelligently conceived in the various scenarios cannot be justified for free nature conditions, and excessive freedom exists in the interpretation of such models, undermining the significance of any particular one. 7 Therefore, it is often alleged15 that the original chemical interactions can no longer be identified through the present coding assignments of the genetic code, but that such putative interactions may have gotten the process started.16

Figure 1. How the genetic code works. Three specific nucleotides (the anticodon) on a tRNA interact with their cognate codon on mRNA, thereby adding the correct amino acid to the growing protein chain. The sequence of nucleotide in each code on the mRNA determines which tRNA will attach, and this communicates the order of amino acids which are to constitute a protein. Each tRNA is charged by aminoacyl tRNA synthetase, using ATP (not shown).Amino acids created under abiotic conditions are assumed to have been introduced first in a primitive code. 17 But, since all but glycine come in d and l mirror-image forms18 such a source of amino acids would lead to chaos. In addition, the 3 chiral C atoms in ribose in RNA would produce even more stereoisomers in free nature. Furthermore, claiming 17,19 that the amino acids found in the Miller experiment would have been the first to be used by a genetic code makes a dope 20 out of the reader who accepts this, since geologists today believe the gases used in such experiments have no relevance to a putative early atmosphere.18,21,22 Subsequent experiments with more reasonable gas mixtures generated very little organic material and virtually no amino acids at all.18,23,24At this time, the order in which amino acids are to polymerise is not communicated by the genetic code through direct amino acid interactions with DNA or RNA polymers. Transfer RNA is used to map codons to their specific amino acids. Three specific nucleotides (the anticodon) are part of the tRNA molecules, and these interact transiently with their cognate codons on mRNA. In figure 1 we show how specific codon-anticodon interactions determine which amino acid is coded for by a mRNA nucleotide triplet. The codon-anticodon interactions must be weak enough to permit separation once no longer needed, but with sufficient specificity to prevent incorrect binding. But in the absence of additional machinery such as ribosomes to help hold everything in place, the interactions between codons and the adaptor’s anticodon would be too weak to be of any value. At a distant and physicochemically unrelated portion of the tRNA adaptor a specific amino acid must therefore be attached (with the consumption of a high energy ATP molecule) (figure 1). How is nature supposed to have gone from an initial system, involving a chemical or a physical interaction of amino acid i (‘AAi’) (where irepresents version 1, 2, 3 …) with RNA tri-nucleotide i (‘codoni’), to the current scheme based on adaptor i (‘adapi’)? Two things must now occur simultaneously (see figure 1). One part of a given adaptor number i, adapi, must replace the original AAi/codoni interaction, and to a second part of adap 1 the same AA; must now be attached (figure 2). These cannot occur sequentially, as both kinds of bonds must occur simultaneously if the primitive ‘code’ based on direct interaction is to be retained. Since the spatial relationship with other amino acids is now very different, any putative chemical reactions with other amino acids can no longer occur. This means all the amino acid to template interactions must be replaced simultaneously! One cannot have a mixed strategy, since then only part of the putative original polypeptide could form.

Figure 2. Evolving from direct amino acid-template interaction to an adaptor molecule. Amino acids are claimed 37 to have originally interacted physically with specific triplet nucleotide sequences, forming the ancient basis of the genetic code. Subsequent insertion of an adaptor molecule, such as tRNA, requires anchoring one end of the adaptor at the original location of amino acid interaction, and that amino acid must now be covalently bonded at another portion of the adaptor. Note that no specific kind of interaction (such as formation of an ester bond between template and amino acid) needs to be claimed, as Figure 3. An adaptor molecule must satisfy various geometric constraints. Amino acids must long as there is a strong be attached to adaptor molecules (e.g. tRNA i) in a manner which permits peptide bonds to preference for interaction form. As shown here the amino acids can’t react together since the two amino acids are too between a specific amino part apart. In the absence of a complex molecular machine, such as a ribosome, it is acid and some unique inconceivable that single adaptor molecules alone could force the reacting amino acids into a suitable geometry to form the correct kind of chemical bond. nucleotide acid sequence. If the ancestral replicator functioned reliably without an adaptor, the new system using many specialized Figure 4. Adaptor molecules must fold reliably to bring the reacting amino acids and cognate adaptor molecules must be codons into the correct geometry. (A) is the approximate shape of folded tRNA molecules. at least as effective Base-pairs at strategic locations hold the various arms together, permitting recognition by the immediately, otherwise the aaRS machinery, and reliable anticodon interaction with the cognate mRNA codons. (B) and former would out-populate (C) represent hypothetical RNA strands which do not fold consistently into reliable structures, the new evolutionary attempt. or into shapes not suitable for the adaptor.

This means that attachment of AAi to adapi must be highly reliable, as is the case with modern aminoacyl tRNA synthetases. Among other implications, this requires a reliable source of the different adaptors i=1,2,3 … (adap 1) during the ‘lifetime’ of this ‘organism’ and during the subsequent ‘generations’. Specifically, all these adaptor sequences must be immediately metabolized consistently and in large amounts for the new coding scheme to function.The adaptor molecules must satisfy several structural requirements. The location where amino acid i is attached to its cognate tRNAi must be at an acceptable distance and geometry to facilitate formation of the peptide bond (figure 3). Each kind of adaptor molecule must fold reliably into a consistent three-dimensional structure which is able to bring the reacting amino acids and cognate codons into the correct geometry with respect to each other (figure 4). In tRNAs this is accomplished by strategically located base pairing and RNA strands of just the right length.Even if two sets of tRNA-amino acid complexes were to be bonded simultaneously somewhere along the template, these won’t form a peptide bond in the absence of the carefully crafted translation machinery. Unless carefully engineered, the adaptors would tangle together with themselves and with the template triplet nucleotides (figure 5). Even if these theoretical adaptors could hold two amino acids close enough to react, the endothermic peptide-forming reaction isn’t going to occur spontaneously. Formation of a peptide bond in living organisms is driven by high-energy ester bonds between amino acids and tRNAs, with the help of aminoacyl tRNA synthetases. Theoretical adaptors which merely hold the reactants physically close together is not sufficient. Should on rare occasions a peptide bond actually form, the resulting molecule would probably remain covalently bonded to one of the adaptors (figure 6) afterwards. One of the design requirements of ribosomes is to move the mRNA along in a ratchet-like manner, detaching the tRNA whose amino acid has already been used. For this purpose energy is provided by GTP, and a complex scheme is used to remove the final polypeptide from the mRNA. This requirement has also been overlooked in the conceptual model presented.

Figure 5. Unless carefully engineered, evolving adaptors would tangle together and with the template triplet nucleotides. RNA, DNA or other sugar template is not explicitly assumed to permit other theoretical chemical proposals. HOOC-XiNH2 represent amino acids, where i = 1 toFigure 6. Without a ribosome, dipeptides will rarely form. If a dipeptide should 20, and Xi = CHRi (Ri are the side chains). form, if would remain covalently bonded to one of the adaptors. RNA, DNA or other sugar template is not explicitly assumed, to permit other theoretical chemical proposals. HOOC-Xi-NH2 represent amino acids, where i = 1 to 20, and Xi = CHRi (Ri are the side chains). If, in spite of the above observations, polypeptides were to start forming; intramolecular reactions, in which the carboxyl end portion of one amino acid bonds to the amino group of the other amino acid in a growing chain would dominate (figure 7). This is simply because they are close to each other and would probably react with themselves before other amino acids show up to extend the chain length. The ribosome machinery is designed to prevent this from occurring. Figure 7. Unless deliberately constrained, amino acids undergo intramolecular reactions. The carboxyl end portion of a growing peptide will almost always react with the amino group at the other end to form an intramolecular amide. n represents two or more amino acids. HOOC-XiNH2 represent amino acids, where i = 1 to 20, and Xi = CHRi (Ri are the side chains). Furthermore, peptide bonds involving the side chains of amino acids can also form, leading to complex and biologically worthless mixtures. For example, amino groups (-NHR) are present on the side chains of amino acids tryptophan, lysine, histidine, arginine, asparagine and glutamine and can react with the carboxylic acid (-COOH) groups of other amino acids. This is especially true if hot conditions are assumed 25 to permit peptide bonds to form. Conversely, some side chains also have carboxylic acids (aspartate and glutamate), which can form amides with any amino group. The highly complex portions of the ribosome machinery were designed to prevent such undesirable side reactions from occurring, by holding the functional groups precisely in place to guide the peptide reactions, and by isolating the functional groups which are not supposed to react together. This very problem is a real issue with automated peptide synthetic chemistries used today, requiring complex side-chain blocking strategies in order to allow the correct peptide extension reactions. Alberti, mentioned above,13 introduced a different scenario: the adaptor is part of the genetic apparatus from very early on. Basically, one must assume that mRNAs, ribosomes, amino acids and tRNAs all came together long ago with a minimum of complexity. Then evolution performed a series of unspecified steps approaching the miraculous, resulting in the genetic code. The initial system somehow added a multitude of molecular tools and was relentlessly fine-tuned. Any other evolutionary model based on similar premises would resemble closely in many details what he proposes. The necessary subsequent stages must occur if these assumptions are used. Therefore, it is worthwhile to devote some thought as to whether the various processes could reasonably occur naturally. Our comments necessarily apply to other possible variants of the basic thesis. Figure 8. Co-evolution of tRNA, mRNA and polypeptides is assumed to have led to the genetic Code. Different peptides are assumed to be able to interact uniquely with a sequence-specific tRNA, which itself base-pairs at a specific portion of an mRNA. ‘α’ are alpha helix polypeptides. (A) Sequence-specific

interactions between ancestral t-RNAs and portions of peptides are assumed to have formed, and between these tRNAs and longer regions of mRNA. (B) Different sequence-specific tRNAs are assumed to attach to portions of mRNA, thereby bringing their attached amino acids close together. (C) A trans-esterification reaction between tRNA-bound peptides is assumed to have occurred in the ancestral genetic code. (D)Release of tRNA which no longer has an amino acid attached is shown, permitting further polymerization. (From Alberti13). The basic notion is shown in figure 8. In practice we will show that virtually none of the necessary claims in such scenarios would work. From start to end, chemical and physical realities are abused. Nature does not produce stereochemically pure polypeptide and polyribonucleotide chains. Therefore, there is no way to initiate a minimally functional proto-code. First, there is the problem of the source of optically pure 26 starting materials. Second, in an aqueous solution, a maximum of 8–10 RNA-mers can polymerise 27 and polypeptide chains would be even shorter, even after optimizing for temperature, pressure, pH, and concentration of amino acid, plus addition of CuCl 2and rapidly trapping the polypeptide in a cooling chamber.28,29 The reactants would be extremely dilute, since the thermodynamic direction would be to hydrolyse back to starting materials. Alternative, non-aqueous environments, such as the side of a dry volcano, would be chemically unpromising. If optically pure nucleotides and amino acids were present, under dry, hot reaction conditions, then larger molecules would form. But the result would be ‘gunk’ or tar, since a complex mixture of three-dimensional non-peptide bonds would form.30 The great majority of random chains of amino acids, even if optically pure, do not conveniently form complex secondary structures such as α helices, as assumed (figure 8). 13 It is certainly true that alpha-helices of specific extant proteins do interact at precise portions of DNA; but this is neither coincidence nor a universal feature, and is caused by a precisely tailored set of spatial and electrostatic relationships, designed to serve a regulatory function. A large collection of mRNAs and tRNAs are needed at the same time and place. And these must provide or transmit the information to specify protein sequences! Sections of mRNAs must have exact sequences, and the complementary tRNAs to base-pair with them must already be available. Not only must the sequences be correct, their order with respect to each other must also be correct. And there must be a large number of such mRNAs, since many different proteins are needed. With a palette of only four nucleotides (nt) even a miniscule chain of 300 nucleotides offers 4 300, or 4 × 10180 alternatives (ignoring all the structural isomers which could also form), the vast majority of which would be worthless. What natural process then, could have organized or programmed the mRNAs, and created the necessary tRNAs? This is a fatal flaw in such models. The proportion of random polypeptides based on the 20 amino acids which are able to fold reliability to offer the chance of producing a useful protein is miniscule, 31,32 to the order of one out of 1050. To provide the necessary information to generate one of the useful variants, something must organize the order of the bases (A,G,C and T) in the mRNAs. But nothing is available in nature which organizes the nucleotides into informationally meaningful sequences. All the various peptides which need to be condensed together must be present. Where did these come from? Alberti writes, ‘Relatively short peptides (down at least to 17mers) recognize short specific sequences of double-stranded RNA or DNA.’33 The environment of the double strand chain offers far more useful physicochemical patterns to recognize than the single strand tRNA in the model, and even then, this would represent about one correct sequence out of 10 22 (= 2017). Where did these peptides come from, and how was generation of the vast majority which are not desired avoided? Note that the necessary peptides would be of different lengths, depending on what needs to be recognized on a specific tRNA.

Figure 9. Peptides will not always associate at the same location of the same tRNA. Many kinds of interaction between tRNA and peptides can occur. For example, ester formation using a free OH group in ribose could occur at many alternative positions. A, B and C illustrate three examples.Whether through ester bonds, weak hydrogen bonds or other interactions, without specific base-pairing as mediated by nucleotide polymers, all the countless varieties of polypeptides would notassociate consistently at the same location on a tRNA-like molecule. For example, any free hydroxyl group of ribose is free to react with the carboxyl group of the peptide, forming an ester. All kinds of van der Waal or hydrogen bond interactions could also occur (figure 9). Therefore, the location of the peptide will not be reliably determined by any particular codon of the mRNA template.The mRNA-tRNA interaction alone is not reliable, requiring a considerable number of suitably located base-pairings between these strands, especially in the absence of any repair machinery, over long regions which is absurd. There will often be internal single-strand loops (figure 10), on the tRNA and mRNA. This will prevent a single codon on the mRNA from specifying uniquely and reliably the location of a putative polypeptide attached to the tRNA. Figure 10. Imperfect base-pairing between the primitive mRNA-tRNA strands would lead to variable placements of the amino acid associated with the ancestral tRNA. Different ancestral tRNA and mRNA strands could base pair by chance at various locations. Nature would not accidentally provide regions of both molecules which just happen to base pair perfectly at the right locations, and simultaneously provide a region on the tRNA at which the right polypeptide would preferential interact. Imperfect base-pairing and coincidences would lead to internal loops on tRNA and on mRNA. Any amino acid or polypeptide attached to the tRNA will then show up at different positions along the templating mRNA. Even if polypeptide chains would form, their sequences would be random, since nothing resembling a code would exist.It is important to understand what the author is calling ‘tRNA’ (see figure 8A).13Key to his reasoning is that ‘Sequence-specific interactions between polypeptides and polynucleotides would result in the accumulation of specific polypeptide-polyribonucleotide pairs.’25 ‘Proximity between a peptide and an RNA molecule is likely to favour the formation of ester bonds between them.’ 25 The author assumes this results in the ancestral ‘tRNA’. Each such ‘tRNA’ consists of a specific polypeptide sequence (and not singleamino acids), which is chemically bonded to a unique single-strand RNA (figure 8B). Multiple tRNAs must then strongly base-pair to a matrix mRNA 25 and be held rigidly25 at specific locations on the template mRNA. But a new peptide bond can only form between adjacent tRNAs if these are able to come into . This implies they must be attached at the ends of tRNAs, as shown in the original literature drawings,13 and that the tRNAs must be located close together on the mRNA. Otherwise the ester bond (between the peptide and RNA to form ‘tRNA’) 25 would be buried and be inaccessible to the amino group of the second peptide it is to

bond with. In figure 11 the carboxyl group of tRNA1 is shown inaccessible to the amino group of tRNA2. To produce the ‘tRNAs’ the author assumes that portions of alpha-helices, each consisting of different series of amino acids to provide specificity, would ensure the unique interactions. 25 However, random peptides can fold in an almost infinite number of ways and will not only form alpha-helices at specific locations (especially if racemic mixtures of amino acids are used). We must assume that polypeptide chains formed under natural conditions would be almost always amorphous polymers.Perhaps there is an alternative to having to place proto-tRNAs very close together along the matrix mRNA. Suppose the locations where the tRNAs:mRNA base-pairings are more flexible, permitting them to eventually come close enough to react. This would happen when portions of tRNA.mRNA cannot base-pair, forming small bulges. Or if the tRNA would dissociate from mRNA and find itself in the vicinity of another tRNA it can react with. In other words, where the reacting ‘tRNAs’ are actually located with respect to the template mRNA would vary. However, this would then destroy the notion of the ancient mRNA strand being a true coding template. It would not specify protein-sequences nor permit eliminating of tRNA-mRNA base-pair interactions (with the help of undefined ‘cofactors’ to hold tRNA and mRNA together) converging to the single codon used in the genetic code.In this grand mixture of tRNAs and mRNAs what is to prevent their cross base-pairing? This would permit all the wrong kinds of peptides to be brought together where they could also polymerise.As peptide chains lengthen, they will start to fold into three-dimensional structures which would surround the esterized point of attachment with the tRNA. This would prevent for steric reasons other tRNAs from attaching in the area on the same mRNA, and the functional groups which are to react from approaching each other.Such a system has no means of self-replicating. Furthermore, postulating multiple covalent ester bonds implies some kind of hot, dryenvironment, which is inconsistent with the favoured evolutionary environments presented as candidates for where life would have arisen. Figure 11. Ester bonds between peptides and templating mRNAs would be buried in polypeptide chains, preventing further polymerization. In ribosomes the protein chains being formed are held in place such that the reactive carboxyl (-COOH) and amine (-NH2) groups can easily react together, no matter how large the growing protein becomes. This fact is overlooked in the simplistic model being discussed. As the protein size grows, the ester bond would become ever more protected by a mass of amorphous polypeptide. After a short polypeptide has formed, further polymerization would be prevented, since the carboxyl and amine function groups won’t come into together.Our greatest objection: nothing which needs to be explained has been seriously addressed. Precisely what are these ‘cofactors’ which are supposed to permit evolution to real ribosomes and aaRSs? These machines (ribosomes, aaRSs, etc.) require dozens of precisely crafted proteins, and it would take multiple miracles to generate precise molecular tools to systematically replace the base-pairings used to link the tRNA and mRNA strands,13 leaving only the codon-anticodon interactions. This is how modern ribosomes supposedly eventually arose. Note that in the earlier evolutionary stages a huge number of unique base-pairings were postulated, which permitted unambiguous association of each ancestral ‘tRNA’ with a precise portion of an mRNA. In the model, these base-pairings are systematically eliminated but the specificity (i.e. which tRNA attaches to which portion of an mRNA) must not be lost. Concurrently, other undefined evolving ‘cofactors’ are responsible to eventually link a single amino acid to the correct tRNA, as modern aaRSs do. Is this feasible? According to the model, 13 initially a multitude of different polypeptides (with 17 or more residues)13 each bonded to a specific RNA, leading to an ancient ‘tRNA’. (By ‘tRNA’ the author actually means an ancient ‘charged tRNA’ which uses a polypeptide and not a single amino acid). Twenty amino acids at seventeen positions leads to 2017 = 1.3 × 1022 possible ‘tRNAs’ plus many others having longer or shorter attached polypeptides. The carboxyl and amino ends of these large polypeptides then bond to form the primitive proteins (figure 11). The author does not explain how a tiny fraction of the more than 10 22 alternatives were selected, nor does he consider whether a miniscule subset used would suffice to provide the minimal biological needs based on such crude proteins. In the modern code, every residue of each protein is coded for, which permits any sequence of residues to be produced. The proposed ancient code, however, would only be able to code for individual large, discrete amino acid ‘blocks’. Alberti believes that shorter and shorter polypeptide chains would eventually be needed to identify the correct RNA they must bond to. This process must culminate in true aaRSs, which charge a single amino acid to a specific RNA strand (i.e. real tRNAs). (Recall that initially longer polypeptides, which form alpha-helices, would be required to permit specific identification of the RNA they are to form an ester bond with). The author has provided no details which justify the claim that unguided nature could produce this effect with ‘cofactors’ or any other natural method. But yet another fundamental point has been overlooked. It is assumed that originally discrete blocks of polypeptide bonded together, providing the necessary proteins. Amino acids are now being eliminated, leading to shorter ‘blocks’. As the polypeptides attached to the RNA strands shorten, different sequences would bond to the same RNA strand as before, producing an evolving code in which each ‘tRNA’ would be charged with different polypeptides. It is not obvious why modification of an individual ‘block’ by eliminating amino acids would still lead to acceptable primitive proteins. And evolving all the ‘blocks’ would lead to utter chaos. The exact same mRNA would now produce vastly different protein versions.As cofactors are introduced between proto-tRNAs and mRNAs, and between peptides and tRNAs, the spatial relationships permitting earlier bonding of peptides together will be destroyed.Instead of continuing with these kinds of vague chemical hypotheses, it seems more sensible for evolutionists to avail themselves of any chemical materials they wish (knowing full well they were of biological origin) and to show in a laboratory something specific and workable. If intelligently organizing all the components in any manner desired (besides simply reproducing an existing genetic system) can’t be made to work, then under natural conditions with > 99.999% contamination, UV light and almost infinite dilution, a code-based replicator is simply not going to arise. (II) Coevolution of biosynthetically related amino acid pathways In this view, the present code reflects a historical development. New, similar amino acids would evolve over time from existing synthesis pathways and be assigned to similar codons. Several researchers claim 34 that biosynthetically related amino acids often have codons which differ by only a single nucleotide. It is also claimed 35 that the class II synthetases are more ancient than class I, and so the ten amino acids served by class II would have arisen earlier in the development of the genetic code. Objections. We cannot provide a thorough analysis of this hypothesis here. The argument is weakened considerably, however, by the fact that many amino acids are interconvertible. Even randomly generated codes show similar associations between amino acids which are biosynthetically related, 34 and it is not at all clear which amino acids are to be considered

biosynthetically related.36Nature would have to experiment with many possible codes and have created many new biochemical networks to provide new amino acids to test. This would require novel genes. Nature cannot look ahead and sacrifice for the future, so each of the multitudes of intermediate exploratory steps cannot require deleterious stages. This poses impossible challenges to what chance plus natural selection could accomplish. We discussed the notion of testing different codes elsewhere.1If only a subset of amino acids were used in an earlier life form, the necessary evidence should be available. The ‘highly conserved’ proteins, presumed to be of very ancient origin, should demonstrate a strong usage of the originally restricted amino acid set. This expectation is especially true if the extant sequences demonstrate little variability at the same residue positions. Furthermore, the first biosynthetic pathway could only have been built with proteins based on the amino acids available at that time. The residue compositions of from both ancient and more modern pathways could be compared to see if a bias exists.Is it unreasonable to demand this kind of ing evidence? Suppose someone reported that the proteins used by the class II synthetases machinery relied on only the amino acids produced thereby. Every evolutionist alive would use this as final and conclusive proof for the theory. Then why should one be reluctant to make such a prediction? Without looking at the data yet, we predict this will not be the case. (III) Evolution and optimisation to prevent errors Some have proposed37–39 that genetic codes evolved either to minimize errors during translation of mRNA into protein, or the severity of the outcome40,41 which results. A similar proposal40,42 is that the effects of amino acid substitution through mutations are to be minimized by decreasing the chances of this occurring and the severity of the outcome should they occur. It would be desirable if random mutations would merely introduce residues with similar physicochemical properties.43,44Amino acids can be characterized by at least 134 different physicochemical properties, 45 begging the question as to which property or cluster of properties are most important. For example, measures of amino acid volumes seem less important than polarity criteria.46 In addition, C ↔ G mutations tend to be more frequent than A ↔ U mutations, 47 for which an optimised genetic coding convention would need to take into . Transition mutations 48 tend to occur more frequently than transversion mutations.48 During translation (and DNA replication), transitional errors are most likely, since mistaking a purine for the other purine or a pyrimidine for the other one is, for stereochemical reasons, more likely.Therefore, the best genetic codes would provide redundancy such that the most likely translation errors or mutations would result in the same amino acid very often. Freeland and Hurst49 took this into when comparing with a computer a million randomly generated codes having the same pattern of codon assignments to different amino acids as the standard code. Using a measure of hydrophobicity as the only key attribute to be protected by a coding convention (and taking nucleotide mutational bias into ) they found only one code out of a million which by the hydrophobicity criterion alone, would be better. We are convinced that taking more factors to be optimised into would reveal this proportion to be much smaller.Hydrophobicity reflects the tendency of amino acids to avoid with water and to be present in the buried inner core of folded proteins. Unfortunately, no best measure of hydrophobicity for amino acids has been agreed upon, and at least 43 different laboratory test methods have been suggested. 50 The different criteria often lead to very different ranking of amino acid hydrophobicity.50Others have thought that mutability played an important role: robustness was important for conservation of some proteins but mutability was required to permit evolution also. 51 Still others have focused on overall effects of mutations on protein surface interactions with solvent52which lead to protein secondary features such as alpha helices and beta sheets.53Having the option of using different codons to code for the same amino acid can be advantageous. For example, if a low concentration of the protein is desired, synonymous codons can be used which lead to slower translation54,55 by taking advantage of the fact that the corresponding aaRSs are often present in very different proportions. If a specific tRNA is only present in a low concentration, the target codon must wait much longer to be translated than if the tRNA is highly available. Sharp et al. reported56 that highly-expressed genes indeed preferentially use those codons which lead to faster translation. This is realized by maintaining different concentrations of the corresponding aaRSs. Translation of an mRNA can be slowed down if a rare codon being translated by a ribosome needs to wait until the appropriate charged tRNA stumbles into that location, for example to give time for a portion already translated to initiate folding.57It is not obvious which property or properties of amino acids should be conserved in the presence of mutations. One suggestion by Freeland and colleagues 16 is to use point accepted mutations (PAM) 74–100 matrix data. Comparing aligned versions of genes which have been mutating (in organisms presumably sharing a common ancestor) after about 100 million years would presumably reveal which amino acid substitutions are more variable or on the other hand, more intolerant to substitution. The authors then examined whether the assignment of synonymous codons protected against such changes, and concluded58 the universal genetic code ‘achieves between 96% and 100% optimisation relative to the best possible code configuration’. Mechanisms for codon swapping. There are various scenarios1 as to how codons could begin to code for a different amino acid. According to the Osawa-Jukes model59 mutations cause some codons to disappear from the genome, and the relevant tRNA genes, being superfluous, disappear. At this point these genomes would not have all 64 of the possible codons present in protein-coding regions. This process is thought to be caused by a mutational bias leading to higher A-T or G-C genome content. When later this mutational bias reverses, the missing codons would begin to show up somewhere in the genome. These could no longer by translated, since the corresponding tRNA is lacking. But duplication of a gene for tRNA followed by mutations at the anticodon position might permit recognition of the new codon on the mRNAs, which would now translate for a different amino acid.The Schultz-Yarus60 model is similar but permits the codon to remain partially present in the genome. Mutations on a duplicated tRNA produces a different anticodon or a new amino acid charging specificity and thereby ambiguous translation of a codon (i.e. the same codon could be identified by different tRNAs). Natural selection would then optimise a particular combination. Incidentally, in some Candida species CUG will encode either serine or leucine,60 depending on the circumstances. Objections. We have discussed various difficulties with the notion of trial-and-error attempts to find better coding conventions elsewhere.1There are over 1.5 × 1084 codes which could map 64 codons to 20 amino acids plus at least one stop signal.1 This is a huge search space, and most of the alternatives would have to be rejected. But when would nature ‘know’ a better or worse coding convention is being explored? Several stages are needed.Many genes would have to be functionally close to optimal so that natural selection could identify when random mutations would produce inferior versions. This means that an unfathomably large number of mutational trials would be needed to produce many optimal genes. Interference with a mutating genetic code would hinder natural selection’s efforts.One or more codons would have to be recoded and the effects throughout the whole genome ascertained. During this process many codons would be ambiguous, such that a myriad of protein variants would be generated by almost all genes, in the same individual. Natural selection would be faced with a continuously changing evaluation as to whether the evolving codon would be advantageous.One evolving coding convention needs to be completed, before another one can be initiated. For example, if during the interval when 70% of the time a codon leads to amino acid ‘a’ and 30% of the time to ‘b’ additional codons were to also become ambiguous, cellular chaos would result. Besides, we see nowhere in nature examples of a multitude of ambiguous codons present simultaneously in an organism.Generating a new code demands removing the means of producing the original

coding option. Depending on the mechanism of code evolution, this could mean removing duplicate tRNA or aaRS variants throughout the whole population. This is going to be near impossible since the selective advantage would be minimal, and at best would consume a huge amount of a key evolutionary resource, time.Nature can’t know in advance which coding convention would eventually be an improvement. An initial 0.1% ambiguity in a single codon, which may be limited to a single gene (such as the case of specific chemical modifications of mRNA), is hardly going to be recognized by natural selection. Note that this 0.1% alternative amino acid would be distributed randomly across all copies of this codon on a gene, and the resulting proteins would be present in multiple copies. The alternative residue would be present in only a small minority of these proteins, and randomly.Once a new code has been fixed, this limits the direction future evolutionary attempts can take. There is no mechanism in place to allow a return to a previous code once it was abandoned other than to re-evolve back to that system. Given the large number of unrelated factors which determine prokaryote survival from the external environment and quality of the genetic system, natural selection would not be provided with any consistent guidance. The rules would change constantly. And a multitude of criteria need to be taken into simultaneously in deciding what to do with each codon. Codons can be used by several codes not related to specifying amino acids, 61 and the relative importance of the tradeoffs will change constantly. Discussion We believe the genetic apparatus was designed, and agree there must be a logical reason for the codon → amino acid mapping chosen. We suspect that protection against the effects of mutations is indeed one of the factors which went into the choice made. This would require foreknowledge of all the kinds of genes needed by all organisms and a weighting of the damage each kind of amino acid substitution could cause. Optimal design may also require variants of the code to be used for some of the intended organisms. But we wish to emphasize that the code to determine amino acid order in proteins is not the whole story. Many other codes61–63 are superimposed on the same genes and noncoding regions, and must also be taken into in the design of the code. Various nucleotide patterns are used for DNA regulatory and structural purposes. DNA must provide information for many other processes besides specifying protein sequences. These requirements affect which code would be universally optimal.Interestingly, a design theoretician may well make a similar suggestion to that of Freeland and colleagues16 mentioned above, but based on other reasoning. To a first approximation, the optimal design of the same proteins in different organisms would be similar. For various reasons, occasionally substituting an amino acid would be better. For example, in hot environments the proteins may have to fold more tightly, whereas this design could prevent enzymatic activity under cooler conditions, by embedding a reactive site too deeply in a rigid hydrophobic code. In general, optimal protein variants must often use residues with similar properties, such as hydrophobicity or size, at a given position. The genes would not be similar due to common descent but by design requirements. Mutations would subsequently generate less than optimal variants which would still be good enough.An intelligently planned genetic code would have taken this into . Therefore, to a first approximation, comparing aligned genes and determining substitutability patterns would indeed provide useful information as to amino acid requirements and use of alternatives. If enough taxa living in many environments are used as a dataset, we should be able to obtain a good idea as to the amount of variability homologous proteins would have. Of course ‘noise’, in the form of random mutations, will also be present. Knowledge of other superimposed codes not responsible for coding for protein sequences, would permit even better quantification as to how optimal the standard code really is. Various alternative codes must satisfy many design requirements, and the optimal one will do best for all demands placed on it.There is however one key difference in the reasoning. We propose that the designer knew what the ideal protein sequences should be, and therefore which needed protection from mutations, and all the other roles nucleotide sequences need to play. The evolutionist here has a problem. Fine-tuning hundreds or thousands of genes concurrently via natural selection to produce a near optimal ensemble is absurd. During the time when the regulation of biochemical networks and enzymes are being optimised, the rules in the form of the code would also be changing. Yet a Last Universal Common Ancestor (LUCA) supposedly already had thousands of genes64 and the full set of tRNA synthetases and tRNAs 7about 2.5 billion years ago.65 Actually, other lines of reasoning66 have led to the belief that the genetic code is almost as old as our planet. In other words, it had virtually no time to evolve and yet is near optimal in the face of over 1.5 × 10 84 alternative 64 → 21 coding conventions.We see evidence everywhere of cellular machinery designed to identify, ameliorate and correct errors. In sexually reproducing we observe that genes are duplicated, which mitigate the effects of many deleterious mutations and thereby help organisms retain morphologic function. Many evolutionists now propose nature has attempted to conserve complex functionality from degradation. All this implies that a highly optimal state has been achieved which nature is trying to retain. More consistent with evolutionary thought would be proposals which encourage ‘evolvability’ or adaptation. Evolution from simple to specified complexity is not achieved by hindering change. Summary A key element in evolutionary theory is that life has gone from simple to complex. But requiring the minimal components of a genetic code to be simultaneously in place without intelligent guidance is indistinguishable from demanding a miracle. No empirical evidence motivated searches for simpler or less optimal primitive genetic codes. Once the possibility of Divine activity has been excluded as the causal factor, an almost unquestioning willingness to accept absurd notions is created among many scientists. After all, it must have happened! We conclude that no one has proposed a workable naturalistic model that shows how a genetic code could evolve from a simpler into a more complex version.

Evidence for the design of life: part 1—Genetic redundancy by Peer Terborg Knockout strategies have demonstrated that the function of many genes cannot be studied by disrupting them in model organisms because the inactivation of these genes does not lead to a phenotypic effect. For living systems, this peculiar phenomenon of genetic redundancy seems to be the rule rather than the exception. Genetic redundancy is now defined as the situation in which the disruption of a gene is selectively neutral. Biology shows us that 1) two or more genes in an organism can often substitute for each other, 2) some genes are just there in a silent state. Inactivation of such redundant genes does not jeopardize the individual’s reproductive success and has no effect on survival of the species. Genetic redundancy is the big surprise of modern biology. Because there is no association between redundant genes and genetic duplications, and because redundant genes do not mutate faster than essential genes, redundancy therefore brings down more than one pillar of contemporary evolutionary thinking.

Figure 1. To create a mouse knockout for a particular gene, a selectable marker is integrated in the gene of interest in an embryonic stem cell. The marker disrupts (knocks out) the gene of interest. The manipulated embryonic stem cell is then injected into a mouse oocyte and transplanted back into the uterus of pseudo-pregnant mouse. Offspring carrying the interrupted gene can be sorted out by screening for the presence of the selection marker. It is now fairly easy to obtain animals in which both copies are interrupted through selective breeding. Mendel’s law of independent segregation assures that crossbreeding littermates will produce individuals that lack both genes.The discovery of the primary rules governing biology in the second half of the 20th century paved the way for a more fundamental understanding of the complexity of life. One of the spin-offs of this knowledge has been the development of sophisticated techniques to elucidate the function of proteins. When molecular biologists want to know the function of a particular human protein they genetically modify a laboratory mouse so that it lacks the corresponding gene (for the laboratory procedure see figure 1). Mice that have both alleles of a gene interrupted cannot produce the corresponding protein—they are called knockouts. Theoretically, the phenotype of a mouse lacking specific genetic information could provide essential information about the function of the gene. Over the years, thousands of knockouts have been generated. The knockoutstrategy has helped elucidate the functions of hundreds of genes and has contributed immensely to our biological knowledge. However, there has been one unexpected surprise—the no-phenotype knockout. This is unexpected, because according to the Darwinian paradigm, all genes should have a selectable advantage. Hence, knockouts should have measurable, detectable phenotypes. The no-phenotype knockouts demonstrate that genes can be disrupted without—or with only minor—detectable effects on the phenotype. Many genes seem to have no measurable function! This is known as genetic redundancy and it is one of the big surprises of modern biology. Molecular switches One of the most intriguing examples of genetic redundancy is found in the SRC gene family. This family comprises a group of eight genes that code for eight distinct proteins all with a function that is technically known as tyrosine kinase. SRC proteins attach phosphate groups to other proteins that contain the amino acid tyrosine in a specific amino acid context. The result of this attachment is that the protein becomes activated; it is switched on, and can hence down information in a signalling cascade. Four closely related of the family are named SRC, YES, FYN and FGR, and the other related are known as BLK, HCK, LCK and LYN. Both families are so-called ‘nuclear receptors’, and transmit signals from the exterior of the cell to the nucleus, the operation centre where the information present in the genes is transcribed into messenger RNA. The proteins of the SRC gene family operate as molecular switches that regulate growth and differentiation of cells. When a cell is triggered to proliferate, tyrosine kinase proteins are transiently switched on, and then immediately switched off.The SRC gene family is among the most notorious genes known to man, since they cause cancer as a consequence of single point mutations. A point mutation is a change in a DNA sequence that alters only one single nucleotide—a DNA letter—of the entire gene. When the point mutation is not on a silent position, it will cause the organism’s protein-making machines to incorporate a wrong amino acid. The consequence of the point mutation is that the organism now produces a protein that cannot be switched off. Mutated SRC genes are of particular danger because they will permanently activate signalling cascades that induce cell proliferation: the signal that tells cells to divide is permanently switched on. The result is uncontrolled proliferation of cells—cancer. The growth-promoting point mutations cannot be overcome by allelic compensation because a normal protein cannot help to switch off the mutated protein.Despite the SRC protein being expressed in many tissues and cell types, mice in which the SRC gene has been knocked out are still viable. The only obvious characteristic of the knockout is the absence of two front teeth due to osteoporosis. In contrast, there are essentially no point mutations allowed in the SRC protein without severe phenotypic consequences. Amino acid changing point mutations in most, presumably all, of the SRC genes can lead to uncontrolled cellular replication. 1 Knockout mice models have been generated to reveal the functions of all the of the SRC gene family. Four out of eight knockouts did not have a detectable phenotype. Despite their cancer-inducing properties, half of the SRCgenes appear to be redundant. Standard evolutionary theory tells us that redundant gene family originated through gene duplications. Duplicated genes are truly redundant and as such they are expected to reduce to a single functional copy over time through the accumulation of mutations that damage the duplicated genes. Such mutations can be frame-shift mutations that introduce premature stop signals, which are recognized by the cellular translation-machines to terminate protein synthesis. The existence of the SRC gene family has been explained as follows: ‘In the redundant gene family of SRC-like proteins, many, perhaps almost all point mutations that damage the protein also cause deleterious phenotypes and kill the organism. The genetic redundancy cannot decay away through the accumulation of point mutations.’1This scenario implies that the SRC genes are destined to reside in the genome forever. Point mutations that immediately kill raise an intriguing origin question. If the SRC genes are really so potently harmful that point mutations induce cancer, how could this extended gene family come into existence through gene duplication and diversify through mutations in the first place? After the first duplication, neither of the genes is allowed to change because it will invoke a lethal phenotype and kill the organism through cancer. Amino acid changing mutations in the SRC genes will permanently be selected against. The same holds true for the third, fourth and additional gene duplication. New gene copies are only allowed to mutate at neutral sites that do not replace amino acid in the protein. Otherwise the organism will die from tumours. Because of this ‘purifying’ selection mechanism, the duplicates should remain as they are. Yet the proteins of the SRC family are distinctly different, only sharing 60–80% of their sequences. Redundancy—the rule not the exception

In 1964, a ‘knockout’ cross-country skier won two gold medals during the Winter Olympics in Innsbruck. In true Olympic tradition, Eero Maentyranta’s 15 and 30 km success was surrounded by controversy. Tests showed that he had 15% more red blood cells than normal subjects and Eero was accused of using doping to increase his level of red blood cells. Yet no trace of blood doping could be found. In 1964 nobody knew, but modern biology showed Maentyranta had a mutated EPO gene, which codes for erythropoietin, a messenger protein that tells the bone marrow to increase the production of red blood cells. To increase red blood levels, EPO binds to the EPO receptor that generates two opposite signals: one to instruct bone marrow cells to become red blood cells (the on-switch) and one to reduce production of red blood cells (the off-switch). This auto-regulatory mechanism assures a balanced production of red blood cells. In 1993, it turned out that the Olympic medallist had a mutation that knocked out the off-switch.2 The EPO receptor of the Finnish athlete generated a normal activation signal, but not the deactivating one. People can do well without the off-switch.In humans, the muscle-fiber-producing ACTN3 gene can also be missed entirely and without consequences for fitness.3 Humans can also do without the GULO gene,4 the gene coding for caspase 12,5 the CCR5gene6 and some of the GST genes that are involved in the detoxification of polycyclic aromatic hydrocarbons present in cigarette smoke. 7 All these genes can be found inactivated in entire human populations (GULO, caspase 12) or subpopulations thereof. The Douc Langur (Pygathrix nemaeus), an Asian leaf-eating Colobine monkey, is the natural no-phenotype knockout for the angiogenin gene that codes a small protein that stimulates the formation of blood vessels. 8 Bacterial genomes can be reduced by over 9% without selective disadvantages on minimal medium, 9 and mice in which 3 megabases of conserved DNA was erased showed no signs of reduced survival and there was no indication of overt pathology. 10 Fewer than 2% of approximately 200 Arabidopsis thaliana (Mouse-Ear Cress) knockouts displayed significant phenotypic alterations. Many of the knockouts did not affect plant morphology even in the presence of severe physiological defects.11 In the nematode worm Caenorhabditis elegans a surprising 89% of single-copy and 96% of duplicate genes show no detectable phenotypic effect when they are knocked out.12 Prion proteins are thought to have a function in learning processes, but when they are misfolded they can cause bovine spongiform encephalitis (BSE) or Kreutzfeld–Jacob disease. In order to make BSE resistant cows, a knockout breed has been created lacking the prion protein. A thorough health assessment of this knockout breed revealed only small differences from wild-type animals. Apparently, cows can thrive very well without the prion protein.13 Research on histone H1 genes, once believed to be indispensable for DNA condensation, suggest that any individual H1 subtype is not necessary for mouse development, and that loss of even two subtypes is tolerated if a normal H1-to-nucleosome stoichiometry is maintained.14 Even complete highly specialized cells can be redundant. A strain of laboratory mouse, named WBB6F1, lacks a specific type of blood cells known as mast cells. The reported no-phenotype knockouts are probably only the tip of the iceberg. As reported in Nature below, few knockout organisms in which no phenotype could be traced ever see the light of day:‘ … a lot of those things [no-phenotype knockouts] you don’t hear about. No-phenotype knockouts are negative results, and as such they are usually not reported in scientific journals; because they do not have news value. To address the problem, the journal Molecular and Cellular Biology has since 1999 a section given over to knockout and other mutant mice that seem perfectly normal.’ 15So how are genes, cells and organisms supposed to have evolved without selective constraints? If organisms can do without complete cells, it would be outlandish to assert that natural selection was the driving force shaping those cells. Two decades of knockout experiments has made it clear that genetic redundancy is a major characteristic of all studied life forms. Paradigm lost Genetic redundancy falsifies several evolutionary hypotheses. Firstly, truly redundant genes are impossible paradoxes because natural selection cannot prevent the accumulation of harmful mutations in these genes. Hence, natural selection cannot prevent redundancies from being lost. Secondly, redundant genes do not evolve (mutate) any faster than essential genes. If protein evolution is due in large part to neutral and slightly deleterious amino acid substitutions, then the incidence of such mutations should be greater in proteins that contribute less to individual reproductive success. The rationale for this prediction is that non-essential proteins should be subject to weaker purifying selection and should accumulate mildly deleterious substitutions more rapidly. This argument, which was presented over twenty years ago, is fundamental to many theoretical applications of evolutionary theory, but despite intense scientific scrutiny the prediction has not been confirmed. In contrast, a systematic analysis of mouse genes has shown that essential genes do not evolve more slowly than nonessential ones.16 Likewise, E. coli proteins that operate in huge redundant networks can tolerate just as many mutations as unique single-copy proteins,17 and scientists comparing the human and chimpanzee genomes found that non-functional pseudogenes, which can be considered as redundancies, have similar percentages of nucleotide substitutions as do essential protein-coding genes.18 Thirdly, as discussed in more detail below, several recent biology studies have provided evidence that genetic redundancy is not associated with gene duplications. What does the evolutionary paradigm say? An important question that needs to be addressed is—can we understand genetic redundancy from Darwin’s natural selection perspective? How can genetic redundancy be maintained in the genome without natural selection acting upon it continually? How did organisms evolve genes that are not subject to natural selection? First, let’s look at how it is thought genetic redundancies arise. Susumo Ohno’s influential 1970 book, Evolution by Gene Duplication, deals with this idea.19 Sometimes, during cell divisions, a gene or longer stretch of biological information is duplicated. If duplication occurs in germ line cells and become inheritable, the exact same gene may be present twofold in the genome of the offspring—a genetic back-up. Ohno argues that gene and genome duplications are the principal forces that drive the increasing complexity of Darwinian evolution, referring to the evolution from microbes to microbiologists. He proposes that duplications of genetic material provide genetic redundancies which are then free to accumulate mutations and adopt novel biological functions. Duplicated DNA elements are not subject to natural selection and are free to transform into novel genes. With time, he argues, a duplicated gene will diverge with respect to expression characteristics or function due to accumulated (point) mutations in the regulatory and coding segments of the duplicate. Duplicates transforming into novel genes with a selective advantage will certainly be favored by natural selection. Meanwhile, the genetic redundancy will protect old functions as new ones arise, hence reducing the lethality of mutations. Ohno estimates that for every novel gene to arise through duplication, about ten redundant copies must the ranks of functionless DNA base sequence.20 Diversification of duplicated genetic material is now the accepted standard evolutionary idea on how genomes gain useful information. Ohno’s idea of evolution through duplication also provides an explanation for the no-phenotype knockouts: if genes duplicate fairly often, it is then reasonable to expect some level of redundancy in most genomes, because duplicates provide an organism with back-up genes. As long as duplicates do not change too much, they may substitute for each other. If one is lost, or inactivated, the other one takes over. Hence, Ohno’s theory predicts an association between genetic redundancy and gene duplication. The evolutionary paradigm is wrong

Figure 2. A very simple scheme of a small robust network comprised of A–E, where several nodes are redundant. Some biologists have looked into this matter specifically using the wealth of genetic data available for Saccharomyces cerevisiae—the common baker’s yeast. A surprising 60% ofSaccharomyces’ genes could be inactivated without producing a phenotype. In 1999, Winzeler and co-workers reported in Science that only 9% of the non-essential genes ofSaccharomyces have sequence similarities with other genes present in the yeast’s genome and could thus be the result of duplication events.21 Most redundant genes ofSaccharomyces are not related to genes in the yeast’s genome, which suggests that genetic duplications cannot explain genetic redundancy. In 2000, Andreas Wagner confirmed Winzeler’s original findings that weak or no-effect (i.e. nonessential and redundant) genes are no more likely to have paralogous—that is, duplicated—genes within the yeast genome than genes that do result in a defined phenotype when they are knocked out. Wagner concluded that the robustness of mutant strains cannot be caused by gene duplication and redundancy, but is more likely due to the interactions between unrelated genes.22 More recent studies have shown that cooperating networks of unrelated genes contribute significantly more to robustness than gene copy number.23 Redundant genes are proposed to have originated in gene duplications, but we do not find a link between genetic redundancy, and duplicated genes in the genomes. Gene duplication is not a major contributor to genetic redundancy, and the robust genetic networks found in organisms cannot be explained. The predicted association between genetic redundancy and gene duplication is non-existent. Ohno’s interesting idea of evolution by gene duplication therefore cannot be right. The non-linearity of biology The no-phenotype knockouts can only be explained by taking into the non-linearity of biochemical systems. It is ironic that standard wall charts of biochemical reactions show hundreds of coupled reactions working together in networks, while graduate students are tacitly encouraged to think in of linear cause and effect. The linear cause-and-effect thinking in ancient Greek philosophy was adopted by nineteenth century European scholars, and is still dominating most fields of science, including biology. We cannot understand that genetic redundancy and biological robustness in linear of single causality, where A causes B causes C causes D causes E. Biological systems do not work like that. Biological systems are designed as redundant scale-free networks. In a scale-free network the distribution of node linkage follows a power law in that it contains many nodes with a low number of links, few nodes with many links and very few nodes with a high number of links. A scale-free network is very much like the Golden Orb’s web: individual nodes are not essential for letting the system function as a whole. The internet is another example of a robust scale-free network: the major part of the websites makes only a few links, a lesser fraction make an intermediate number of links, and a minor part makes the majority of links. Usually hundreds of routers routinely malfunction on the Internet at any moment, but the network rarely suffers major disruptions. As many as 80% of randomly selected Internet routers can fail, but the remaining ones will still form a compact cluster in which there will still be a path between any two nodes. 24 Likewise, we rarely notice the consequences of thousands of errors that routinely occur in our cells. Scale free networks Genes never operate alone but in redundant scale-free networks with an incredible level of buffering capacity. In a simple non-linear biological system—presented in figure 2—with nodes A through E, A may cause B, but A also causes D independent of B and C. This very simple network of only five nodes demonstrates robustness due to redundancy of B and C. If A fails to make the link with D, there are still B and C to make the connection. Extended networks composed of hundreds of interconnected proteins ensure that if one network becomes inactivated by a mutation, essential pathways will then not be shut down immediately. A network of cooperating proteins that can substitute for or by each other’s functions makes a biological system robust. It is hard to imagine how selection acts on individual nodes of a scale-free, redundant system. Complex engineered systems rely on scale-free networks that can incorporate small failures in order to prevent larger failures. In a sense, cooperating scale-free networks provide systems with an anti-chaos module which is required for stability and strength. Scale-free genetic and protein networks are an intrinsic, engineered characteristic of genomes and may explain why genetic redundancy is so widespread among organisms. Genetic networks usually serve to stabilize and fine-tune the complex regulatory mechanisms of living systems. They control homeostasis, regulate the maintenance of genomes and provide regulatory on gene expression. An overlap in the functions of proteins also ensures that a cell does not have to respond with only ‘on’ or ‘off’ in a particular biochemical process, but instead may operate somewhere in between.Most genes in the human genome are involved in regulatory networks that detect and process information in order to keep the cell informed about its environment. The proteins operating in these networks come as large gene families with overlapping functions. In a cascade of activation and deactivation of signalling proteins, external messages are transported to the nucleus with information about what is going on outside so it can respond adequately. If one of the interactions disappears, this will not immediately disturb the balance of life. The buffering capacity present in redundant genetic networks also provides the robustness that allows living systems to propagate in time. In a linear system, one detrimental mutation would immediately disable the system as a whole: the strength of a chain is determined by its weakest link. Interacting biological networks, where parallel and converging links independently convey the same or similar information, almost never fail. The Golden Orb’s web only crumbles when an entire spoke is obliterated in a crash with a Dragonfly, an event that will hardly ever happen. Biological systems operate as a spider’s web: many interacting and interwoven nodes produce robust genetic networks and are responsible for genetic redundancy.23 Conclusion Genetic redundancy is an amazing property of genomes and has only recently become evident as a result of negative knockout experiments. Protein-coding genes and highly conserved regions can be eliminated from the genome of model organisms without a detectable effect on fitness. There is no association between redundant genes and gene duplications, and redundant genes do not mutate faster than essential genes. Genetic redundancy stands as an unequivocal challenge to the standard evolutionary paradigm, as it questions the importance of Darwin’s selection mechanism as a major force in the evolution of genes. It is also important to realize that redundant genes cannot have resided in the genome for millions of years, because natural selection, a conservative force, cannot prevent their destruction due to debilitating mutations. Mainstream biologists who are educated in the Darwinian framework are unable to understand the existence of genes

without natural selection. This is clear from a statement in Nature a few years ago by Mario Cappecchi, a pioneer in the development of knockout technology:‘I don’t believe that there is a single [knockout] mouse that does not have a phenotype. We just aren’t asking the right questions.’15The right question to be asked is: is the evolutionary paradigm wrong? My answer is yes, it is. Current naturalistic theories do not explain what scientists observe in the genomes. Genetic redundancy is the actual key to help us understand the robustness of organisms and also their built-in flexibility to rapidly adapt to different environments. In part 2 of this series of articles, I will explain genetic redundancy in the context of baranomes, the multipurpose genomes baramins were originally designed with in order to rapidly spread to all the corners and crevices of the earth. Evidence for the design of life: part 2—Baranomes by Peer Terborg The major difference between the evolution and creation paradigms is that the evolutionist believes that the natural variation found in populations can explain microbe-to-man evolution via natural selection (Darwinism), while the creationist believes it cannot. This is because the evolutionary, naturalistic framework requires something creationists hold impossible: a continuous addition of novel genetic information unrelated to that already existing. In the creation paradigm neither variation nor selection is denied; what is rejected is that the two add up to explain the origin of species. In part 1, I discussed genetic redundancy and how redundant genes are not associated with genetic duplications and do not mutate faster than essential genes. These observations are sufficient to completely overturn the current evolutionary paradigm and could form the basis for a novel creationist framework to help us understand genomes, variation and speciation. In this second part, I argue and provide biological evidence that life on Earth thrived due to frontloaded baranomes—pluripotent, undifferentiated genomes with an intrinsic ability for rapid adaptation and speciation. Where redundancy leads The canonical view is that most variation in organisms is the result of different versions of genes (alleles) and genetic losses. The variation Mendel studied in peas and that led him to discover several basic inheritance laws, was the result of different alleles. At least, so it is taught. One of the seven traits Mendel described in peas was what he called the I locus—it referred to the colour of the seeds. In Mendel’s jargon, ‘I’ stood for dominance (yellow), whereas ‘i’ meant recessive (green). Plants carrying I had yellow seeds, plants lacking I had green seeds. Mendel shed scientific light on inheritance. Now, 140 years after Mendel’s findings, we know how the yellow-green system works at the molecular level. The colour is determined by the stay-green gene (abbreviated: STG) that codes for a protein involved in the reabsorption of green pigments during senescence.1The recessive trait i is the mutated form of the STG gene; an inactive variant that cannot re-absorb pigments, so the seeds keep their green colour.Is the STG gene essential for survival? Most likely it is not. Molecular biology shows Mendel studied the effects of non-essential and redundant genes. Dominance means at least one redundant or non-essential gene is functional; recessive means both copies of redundant and non-essential genes are defunct. In Bacillus subtilis only 270 of the 4,100 genes are essential,2and in Escherichia coli this is a meagre 303 out of a total of almost 4,300 genes.3 Genetic redundancy is present everywhere,4 and this lead me to believe that biology is quite different from what Darwinians think it is. Namely, organisms are full of genetic tools that are handy but not essential for survival, and selection cannot be involved in shaping these genes. Apparently, genomes are loaded with genetic elements that reside in the genome without selective constraints. This makes sense in the creation paradigm, because the genomes we observe today are remnants of the original genomes in the created kinds. And, apparently, they were created as pluripotent,5 undifferentiated genomes with an intrinsic ability for rapid adaptation and speciation. I have called the undifferentiated, uncommitted, multipurpose genome of a created kind a baranome.6Baranomes explain genetic redundancy: there is no association with gene duplication, and redundant genes do not mutate faster than essential genes.4

The lack of understanding of baranomes recently led to a severe misinterpretation of the origin of genes in the secular literature. Eager to find evidence for the evolution of novel biological information, a novel de novo protein-coding gene in Saccharomyces cerevisiae was reported on the basis of genome comparison among several species ofSaccharomyces. The BSC4 gene had an open reading frame (ORF) encoding a 132-amino-acid-long polypeptide. It was reported that there is no homologous ORF in all the sequenced genomes of other fungal species, including closely related species such as S. paradoxus and S. mikatae. The sequences presented in the figure above demonstrate, however, that the BSC4 gene can be found interrupted and inactivated in S. paradoxus, S. mikatae andS. bayanus. These data confirm the baranome hypothesis, which holds that all Saccharomyces descended from one original undifferentiated genome (Saccharomyces bn) containing all information currently found in the isolated species. This alleged novel gene is in fact ancient frontloaded information that became redundant and inactive in most S. spp but was subject to sufficient constraints to be retained in S. cerevisiae. BSC4 codes for a protein involved in DNA repair; an elaborate and integrated mechanism involving dozens of redundant systems. Therefore, it is predicted that BSC4 knockouts of S. cerevisiae will not show major problems. The top part of the figure shows the alignment of 320 base pairs of the orthologous sequences of BSC4 from Saccharomyces bayanus (S.bay), S. mikatae(S.mik), S. paradoxus (S.par) and S. cerevisiae (S.cer). The conserved nucleotides are shown in bold. (Adapted from Cai and Zhao et al.34). The bottom of the figure shows how only S. cerevisiae retained an active BSC4 gene. The multiple genomes of Arabidopsis In 2007, Science reported on the genome of Arabidopsis thaliana, a flowering plant of the mustard family with a small genome that is suitable for extensive genetic studies.7 This report was of particular interest because it showed the genomes of 19 individual plants collected from 19 different stands, ranging from sub-arctic regions to the tropics. According to a commentary summarizing the results of this painstaking analysis‘ … about four percent of the reference genome either looks very different in the wild varieties, or cannot be found at all. Almost every tenth gene was so defective that it could not fulfill its normal function anymore!‘Results such as these raise fundamental questions. For one, they qualify the value of the model genomes sequenced so far. “There isn’t such a thing as the genome of a species,” says Weigel. He adds “The insight that the DNA sequence of a single individual is by far not sufficient to understand the genetic potential of a species also fuels current efforts in human genetics.”‘Still, it is surprising that Arabidopsis has such a plastic genome. In contrast to the genome of humans or many crop plants such as corn, that of Arabidopsis is very much streamlined, and its size is less than a twentieth of that of humans or corn—even though it has about the same number of genes. In contrast to these other genomes, there are few repeats or seemingly irrelevant filler sequences. “That even in a minimal genome every tenth gene is dispensable has been a great surprise”, its Weigel [emphases added].’8Among the 19 stands of Arabidopsis we find dramatic genetic differences. We observe genetic losses as well as genetic novelties. Although the dispensability of genes is easy to understand with respect to genetic redundancy, the observed novelties are much harder to conceive unless we accept that all observed novelties are not novelties at all but genetic tools that have resided in the genome since the dayArabidopsis was created. The genetic ‘novelties’ may simply reflect environmental constraints that have helped preserve these genetic tools.There is indeed ‘no such thing as the genome of a species’, because what we observe today are rearranged and adapted genomes that were all derived from an original genome that contained all genetic tools we find scattered throughout the population. The ‘great surprise’ is only a great surprise with respect to the Darwinian paradigm. With a pluripotent Arabidopsis genome in mind, the data are not surprising at all. It is in accord with what we might expect from the perspective of a rapid (re)population of the earth.Modern Arabidopsis genomes look as if they were derived from much larger genomes containing an excess of genetic elements—both coding and noncoding (repetitive) sequences—that can easily be lost, shuffled or duplicated. The ‘dispensable genes’ outlined above can be understood as genetic redundancies originally present in the baranome that over time slowly but steadily fell apart in the

19 individuals, because the environment did not select for them. The study strongly suggests that isolated stands of plants originated as a result of loss of genetic redundancies, duplication and rearrangement of genetic elements. The dispensability of 10% of the genes of Arabidopsis could have been predicted because most of the genes still present in individual genomes are redundant.9 In my opinion, these observations strongly favour the baranome hypothesis. The law of natural preservation Genetic redundancy, dispensable genes and disintegrating genomes are scientific novelties revealed to us by modern biology. How can we understand all this? Darwinians hypothesize that life evolved from simple unicellular microbes to multicellular ones via a gradual build-up of biological information, the driving force supposedly being natural selection. According to biology, there is no gradual accumulation of information; biology originated from a ‘big bang’. Sponges, worms, plants and man all have approximately the same genetic content, so the number of genes does not seem to be related to the complexity of organisms.10 In addition, the complex organisms we observe today were not derived from a single or a few simple organisms, but must have derived from a global community of organisms.11 The observations of modern biology pose so many untenable hurdles for naturalistic philosophy that it would be better to simply leave Darwinism for what it is: a set of falsified 19th century hypotheses that do not and cannot explain the origin of species.The way to understand variation and speciation is through disintegration and rearrangement of primordialbaranomes created with an excess of genetic elements. Baranomes initially contained all mechanisms required to quickly respond and adapt to changing environments. They provided organisms with the tools needed to invade many distinct niches, and were ideal for the swift colonization of all corners of the world. Baranomes were multifunctional genomes which can be compared to a Swiss army knife. A Swiss knife contains many functions which are not immediately necessary in a particular environment; but some of them are extremely handy in the mountains, others in the woods, still others are made for opening bottles and cans, or tools for making a fire. Depending on where you are, you may require different sets of functions. Similarly, depending on where the organism lives, it demands different functions (i.e. protein-coding genes and their protein products) from its genome. The environment then determines what part of the non-essential genome is under constraint and it is only this part that will be conserved. In other words, the law of natural preservation—conventionally coined ‘natural selection’—determines the differentiation of the pluripotent genome.12

Figure 1. Phylogeny of modern Flaveria species demonstrates independent losses of the C3 and C4 photosystems from the baranome of Yellowtops species (Flaveria bn). Some have either the C3 or the C4 photosystems, others have both C3 and C4 (or parts there of). Isolated species are in the process of losing redundant parts of theFlaveria baranome. (Adapted from Kutchera and Niklas14). C3 and C4 plants From the creation paradigm, we might expect to find more than one carbon-fixation system. For example a system that functions optimally in warm, tropical regions, also systems that operate at sub-arctic temperatures. We find that plants do indeed have two photosystems for fixing carbon fixation; they are known as C3 and C4. The optimum temperature for carbon fixation in C3 plants is between 15–20ºC, whereas the C4 plants have an optimum around 30–40ºC.13 Today many plants are either C3 plants or C4 plants, but we also find plants that have both C3 and C4. There is clear indication for redundancy of the two photo-systems, because many plants have only one of both systems operable; either C3 or C4, plus remnants of the other system.For instance, in modern Yellow tops (Flaveria spp) we not only see functional C3, C4 or the combination of C3 plus C4 photo-systems, but we also observe C4 remnant in C3 plants. 14 The presence of remnants of one of the systems qualifies as evidence for a baranome containing both photo-systems, and indicates that the C4 system is not stringently preserved when the C3 system is also present (figure 1). The two ‘frontloaded’ photosystems ensure a rapid colonization of both high and low altitudes, and hot and cold environments. In the tropics, the C4 system, which functions optimally at high temperatures, should be active, whereas the C3 system is redundant. Here, the ‘hot’ system would be under permanent environmental constraint and be conserved. Due to accumulation of debilitating mutations in the genetic elements comprising cold systems, these would rapidly disintegrate. A genetic program designed for tropical regions does not make sense in arctic regions, and vice versa. It is the organism’s environment or habitat that determines whether genetic elements are useful or not. Conforming to the baranome hypothesis, the habitat determines genetic redundancy. There is no biological reason to assume why unused, habitat-induced redundancies should be preserved. The law of natural preservation tells us that unused genes will rapidly degrade.

What baranomes contain Baranomes are information carriers. They were frontloaded with three classes of DNA elements: essential, non-essential and redundant. When essential elements mutate to change the amino acid sequences, the information carrier as a whole is immediately subject to a severe reproductive disadvantage. In the worst case the mutation is incompatible with life and mutated essential DNA elements will not be present in the gene pool of the next generation. Essential DNA elements can be defined as biological information that is unable to evolve. Non-essential genes are genes that are allowed to mutate and may thus contribute to allelic variations. As they produce non-lethal phenotypes, they contribute to the variation observed in populations. Classic Mendelian genetics is largely due to variation in non-essential genes. Variation in non-essential genes is what geneticists call alleles. Recessive Mendelian traits can usually be attributed to dysfunctional non-essential genetic elements; in particular elements that determine expression of morphogenesis programs, including those that determine length and shape—‘the morphometry’—of the organism. To induce the recessive trait the disrupted (or inactivated) alleles must be inherited from both parents, because an active wild-type gene usually compensates for an inactivated gene. In Mendel’s jargon, this compensation is known asdominance.The third class of frontloaded genetic elements are correct genes that underlie genetic redundancy. They make up a special class of non-essential genes and have only recently been discovered. That is because their existence cannot be deduced from genetic experiments: they do not contribute to a detectable phenotype. Their peculiarity is that redundant genes may be completely lost from the genome without any effect on reproductive success. That redundant genetic elements make up a major part of the genome of all organisms became evident when biologists interested in gene function developed gene-knockout strategies; with the remarkable observation that many knockouts do not have a phenotype. 4 Genetic redundancy is an intrinsic property of pluripotent baranomes. It should be noted, however, that the environment also plays a crucial role in determining whether a genetic algorithm is redundant, non-essential or essential. The pathway for vitamin C synthesis, for instance, is a diet-induced genetic redundancy which is inactive in humans, four primates, guinea pigs and fruit-eating bats as a result of two debilitating mutations.15The law of natural preservation often dictates the course for the development of baranomes. In addition, baranomes initially contained variation-inducing genetic elements (VIGEs) that helped to induce rapid duplications and rearrangements of genetic information. Modern genomes of all organisms are virtually littered with VIGEs (which are usually referred to as remnants of retroviruses; LINEs, SINEs, Alus, transposons, insertion sequences, etc.) and due to their ability to duplicate and more genetic material they facilitate and induce variation in genomes.16 Speciation from baranomes Variation in reproducing populations is mostly due to position effects of VIGEs. That is because the presence of VIGEs in or near genes determines the activity of those genes and hence their expression. 17 Variation is a result of a change in gene expression. In addition, VIGEs that function as chromosome swappers may also help us understand reproductive barriers. A reproductive barrier between organisms is in fact another term for ‘speciation’, the formation of novel species. ‘Species’ is meant here in the sense of Ernst Mayr’s species concept, which includes intrinsic reproductive isolation.18 Indeed, the gene swapping mechanism present in primordial pluripotent genomes also allowed for intrinsic reproductive isolation. If we want to understand how chromosome-swapping VIGEs are involved in speciation, we first have to look into some details of sexual reproduction.In all cells of sexually reproducing organisms the chromosomes are present as homologous pairs. One is inherited from the father and the other from the mother. The arrangement of homologous chromosomes allows them to easily pair up. Each parental chromosomes recognizes the other and they easily align. The alignment is necessary for the formation of gametes during meiosis, where the two sets of parent chromosomes are reduced to one set. Differences in chromosome pattern impede the pairing of chromosomes at meiosis, resulting in hybrid sterility. Chromosomal rearrangements may be one of the most common forms of reproductive isolation, allowing rapid adaptive radiation of multipurpose genomes without the need for geographic isolation or natural selection. The activity of chromosome-swapping VIGEs may thus have produced reproductive barriers and hence facilitating speciation.If it is true that chromosomal order determines whether organisms are able to reproduce, speciation can theoretically be reversed by chromosomal adjustments. In other words, we must be able to produce viable offspring from two reproductively isolated species just by rearranging their chromosomes. This may sound like an untestable hypothesis, but experimental evidence demonstrates that it is indeed possible to ‘unspeciate’ distinct, reproductively isolated, species by chromosomal adjustments. Using Mayr’s species definition, yeasts of the genus Saccharomyces comprise six well-defined species, including the well known baker’s yeast.19 The Saccharomyces species will readily mate with one another, indicating that they stem from one single baranome (figure 2), but pairings between distinct species produce sterile hybrids. Three of the six species are characterized by a specific genome rearrangement, known as reciprocal chromosomal translocations. Reciprocal chromosome translocation occurs when the arms of two distinct chromosomes are exchanged. Analysis of the six species revealed that translocations between the chromosomes do not correlate with the group’s sequence-based phylogeny, a finding that has been interpreted as ‘translocations do not drive the process of speciation’. However, a study carried out by the Institute of Food Research in Norwich, United Kingdom, showed that the chromosomal rearrangements in Saccharomyces do indeed induce reproductive isolation between these organisms.19 The reported experiments were designed to engineer the genome of Saccharomyces cerevisiae (baker’s yeast) so as to make it collinear with that of Saccharomyces mikatae, which normally differs from baker’s yeast by one or two translocations. The results showed that the constructed strains with imposed genomic collinearity allow the generation of hybrids that produced a large proportion of spores that were viable. Viable spores were also obtained in crosses between wild-type

baker’s yeast and the naturally collinear speciesSaccharomyces paradoxus, but not in crosses between species with noncollinear chromosomes. Figure 2. Left : Adaptive radiation from one single pluripotent baranome. The figure shows a hypothetical model for the radiation of the Saccharomyces bn into the six Saccharomyces species we observe today. Initially, the uncommitted pluripotent baranome radiated in all possible directions. Due to intrinsic mechanisms, variation is constantly generated but slowed down over time because of the redundant character of the variation-inducing genetic elements (and were easily lost). Speciation may occur when a reproductive barrier is thrown up, for instance as the result of chromosomal rearrangements. Genetic elements that facilitate variation are specified in the genome and there is no need for the millions of years that are required for Darwinian evolution. This is clear from the long-running (20 years) evolutionary experiments which show that the major adaptive changes occurred during the first 2 years. 35 Right : Hypothetical time courses for the total amount of information in a baranome (black line) and the number of species derived from that baranome (red line). Over time there is a tendency to lose biological information with an increase of the number of species.This is empirical proof that a reproductive barrier between species can be reversed just by reconfiguration of their chromosomes. In addition to reciprocal chromosomal translocations, many small-scale genomic rearrangements, involving the amplification and transposition of VIGEs may cause reproductive isolation. VIGEs are thus basic to understanding variation and speciation of baranomes. Modern biology demonstrates that although the six species of Saccharomyces yeasts are all derived from one single baranome, their individual karyotypes20 determine whether they can interbreed and leave offspring.That the karyotype is an important determinant of reproductive isolation is also observed in deer. Eight species of Asian deer of the genusMuntiacus inhabit an area speading from the high mountains in the Himalay to the low land forests of Laos and Cambodia. Their karyotypes differ dramatically; chromosome number varies from a low of only three pairs to a high of 23.21 The muntjack species demonstrate that individuals that differ substantially by chromosomal reorganizations of otherwise identical genetic material will invariably be sterile. The sterility of muntjack hybrids is exclusively due to the inability of the chromosomes to pair. The chromosomes of distinct species simply cannot form pairs, and formation of viable reproductive cells is impossible. The karyotype s for reproductive isolation, and the baranome hypothesis leaves room for speciation events through adaptive radiation. Identification of baranomes How do we identify whether organisms descended from one primordial multipurpose genome? Darwinians claim a continuum between genomes of distinct species and view all modern species as transition stages, so this question is not of particular interest. For micro-organisms this may well be true. Between bacteria, the exchange of biological information is common and for this purpose they possess elaborate mechanisms to facilitate the uptake of foreign DNA from the environment. Still, over 5,000 distinct bacteria have been scientifically described, indicating distinctive borders between bacterial ‘species’.22Likewise, the biological facts in higher organisms these are distinctive borders between genomes; borders determined by reproductive barriers. For instance, humans and chimps both have comparable genomic content, but very distinctive karyotypes, so the species cannot reproduce with each other. Therefore, the question raised above is not easy to answer. Because genomes tend to continuously lose unused genetic information over time, genomic content may not be suitable to identify common descent from the same primordial baranome.A first indication that two distinct species have descended from the same baranome is this ability to mate. The offspring does not have to be fertile; neither does it have to be viable at birth. Zygote formation is a significant indication that the organisms were derived from the same baranome.The best tool for baranome identification currently available, however, may be indicator genes. Indicator genes are essential genes with a highly specific marker. In the human baranome (Homo bn) we indeed observe indicator genes, such as FOXP223 and HAR1F.24 Both genes are also present in primates, but in humans they have highly specific characteristics not found in primates, indicating that human genomes stem from a distinct baranome. Specific characteristics typify humans. A comparative analysis of indicator genes in primates is sufficient to discriminate between man and chimpanzee (Pan bn) baranomes, or whether ancient bones belong to the human baranome. Recent research shows that indicator genes may indeed be a promising tool for baranome detection. Analyses of ancient Neandertal DNA, revealed typical human FOXP2 characteristics.25 This observation is compelling evidence that both modern humans and Neandertals originate from one and the same baranome. Further research is required to develope a full range of baranome indicator genes for other organisms. Darwin revisited From the baranome hypothesis we can begin to understand how Africa’s Rift Valley lakes became populated with hundreds of species ofCichlids within a mere few thousand years. We can also understand the origin of dozens of (sub) species of woodpeckers, crows, finches, ducks and deer. And we begin to see how wings could develop many times over in stick insects.26 We also understand why two distinct sex systems operate in Japanese wrinkled frogs (Rana rugosa),27 and why Dictyostelium has genetic programs for both sexual and asexual reproduction. 28 And we begin to see why ancient trilobites radiated so rapidly.29 The required genetic programs (Dictyostelium’s sexual reproduction program make up over 2,000 genes!) did not have to evolve step-by-step under the guidance of natural selection. Rather, these programs were a ‘dormant’ frontloaded part of the baranome and only required a ‘wake-up call’. If Darwin had the knowledge of 21 st century biology, I believe his primary conclusion would be similar to what I propose: limited common descent through adaptive radiation from pluripotent and undifferentiated baranomes. The limits to common descent are determined by the elements that have been frontloaded intothat baranome. Natural varieties of sexually reproducing organisms can be established by means of differential reproductive success, but reversal to wild types follows as soon as selective constraints are relieved and hybridization between previously isolated populations occurs. Hybridization is, in fact, nothing but reversal to a more original multipurpose genome; the wild type is the more stable (‘robust’) form of the baranome because it contains more redundancies. Reversal to the wild-type was a known principle in Darwin’s day, but Darwin dismissed the obvious and invented his own naturalistic biology:‘To it this view [of unstable created species] is, as it seems to me, to reject a real for an unreal, or at least for an unknown, cause. Darwin rejected the baranome for theological, or at best for philosophical, reasons. Why would a flexible, highly adaptable, pluripotent genome present in primordial creatures make the the work of the designer ‘mere mockery and deception’? A pluripotent genome with an intrinsic propensity to rapidly respond to changing situations elegantly explains ‘the co-adaptations of organic beings to each other and to their physical conditions.’ Organisms that cannot adapt or, in other words, organisms that lose their ‘evolvability’ are bound to become extinct. The baranome hypothesis with frontloaded VIGEs is sufficient to explain what Darwin observed and there is no need to invoke a gradual and selection-mediated evolution from microbe-to-man, which is non-existing and not in accord with scientific observations anyway. In every generation, VIGE activity generates novel genetic contexts for pre-existing information and hence gives rise to novel variation. VIGEs were an intrinsic property of baranomes, and they are the source of variation and adaptive radiation. It must be emphasized that, because all elements that induce variation are already in the genome, there is no need for the millions of years required for Darwinian evolution. Conclusion and perspective

The findings of modern biology show that life is quite different from that predicted by the evolutionary paradigm. Although the evolutionaryparadigm assumes an increase of genetic information over time, the scientific data show that an excess of biological information is present even in the simplest life forms, and that we instead observe genetic losses. A straightforward conclusion therefore should be that life on Earth thrived due to frontloaded baranomes—pluripotent, undifferentiated genomes with an intrinsic ability for rapid adaptation and speciation. Baranomes are genomes that contained an excess of genes and variation-inducing genetic elements, and the law of natural preservation shaped individual populations of genomes according to what part of the baranome was used in a particular environment.With so many genomes sequenced and an ever increasing knowledge of molecular biology, we will find more and more evidence to thebaranome hypothesis. We will increasingly recognize traces and hints of frontloaded information still present in the genomes of modern species. We may expect that the genomes of the descendants of the same multipurpose genome independently lost redundant genetic elements. We may expect to find impoverished genomes and also reproductively isolated populations at different latitudes to be highly distinct with respect to their genomic content. We may even be able to piece together the genomic content of the original multipurpose genome of these species simply by adding up all unique genetic elements present in the entire population.Finally, it will be possible to detect indicator genes, such as the FOXP2, which may become genetic tools for establishing the borders between distinct baranomes. Frontloaded baranomes are an important tool to help us understand biology. I believe there is grandeur in this view of life, where the Great Omnipotent Designer chose to breathe life into a limited number of undifferentiated, uncommitted, pluripotent baranomes; and from these baranomes all of the earth was covered with an almost endless variety of the most beautiful and wonderful creatures.31 Karyotype rearrangements In 1970, Neil Todd developed the karyotypic fission hypothesis (KFH)32 to correlate the physical appearance of chromosomes with the evolutionary history of mammals. Todd postulated wholesale fission of all medio-centric chromosomes. Todd’s fasttrack, single event, genome rearrangement still is the most parsimonious theory to for mammalian karyotypes and potentially explains rapid speciation events. Todd’s was rejected mainly because it postulated something opposing the dominant Darwinian paradigm.In 1999, Robin Kolnicki revived Todd’s KFH. Although her kinetochore reproduction hypothesis33 was largely theoretical, each step had a known cellular or molecular mechanism. During DNA replication, just before meiotic synapsis and sister chromatid segregation, the formation of an extra kinetochore on all chromosomes is facilitated. The kinetochore is the organizing centre that holds the sister chromatids together during meioses and is composed mainly of repetitive DNA sequences. The freshly added kinetochores do not disrupt the distribution of chromosomes to daughter cells during meiosis because tension-sensitive checkpoints operate to prevent errors in chromosome segregation. The result is a new cell with twice the number of telocentric chromosomes. 10The duplication of the kinetochores on many chromosomes at the same time is highly unlikely in a naturalistic model, but the telocentric chromosomes of rhinoceros, rock wallaby and many other species are physical evidence that their genomes were formed instantly.I postulate that the genomes, as we observe them today, are the result of thousands of years of rearrangements (fission, fusion and duplications) brought about by specific variation-inducing genetic elements (VIGEs). Initially, well controlled rearrangements may have been facilitated by these elements, but over time the control over regulated genome rearrangement deteriorated. VIGEs may be the genetic basis to help us understand wholesale genomic rearrangements from pluripotent baranomes.In order to rapidly occupy novel niches, a mechanism or ability to create reproductive barriers may have been intrinsic to baranomes. The ability to adapt, including speciation-events, is merely due to neutral rearrangements of chromosomes, and the VIGEs involved may easily become inactive because of the permanent accumulation of debilitating mutations. The remnants of VIGEs can still be found in contemporary genomes; they are known as (retro)(trans)posons, LINEs, SINEs, Alu insertion sequences, etc. Some VIGEs may have started a life of their own and now jump around more or less uncontrolled.

The design of life: part 3—an introduction to variation-inducing genetic elements by Peer Terborg The inheritance of traits is determined by genes: long stretches of DNA that are ed down from generation to generation. Usually, genes consist of a coding part and a non-coding regulatory part. The coding part of the gene determines the functional output, whereas the non-coding portion contains switches and units that determine when, where and how much of the functional output should be generated. Point-mutations in the coding part are predominantly neutral or slightly detrimental genetic noise that accumulates in the genome, whereas point-mutations in the regulatory part of DNA units can induce variation with respect to the amount of output. Previously, in part 2, I argued that created kinds were frontloaded with baranomes: that is, pluripotent genomes with an ability to induce variation from within. The output of (morpho)genetic algorithms present in the baranome can readily be modulated by variation-inducing genetic elements (VIGEs). VIGEs are frontloaded genetic elements normally referred to as endogenous retroviruses, insertion sequences, LINEs, SINEs, microsatellites, transposons, insertion sequences, and the like. In the present report, these transposable and repetitive DNA sequences are redefined as VIGEs, which solves the RNA virus paradox. The (morpho)genetic algorithms were designed in such way that VIGEs easily integrated into it and became a part of it, hence making the program explicit. The variation that Darwin saw in pigeons can be explained with the activation or deactivation of existing genetic sequences for feather production in different parts of the body. This gives no basis for asserting that pigeons could change into something which is not a pigeon.In order to fight off invading bugs and parasites, higher organisms have an elaborate mechanism that induces variation in immunological defence systems. One particular type of immune cells (B cells) produces defence proteins known as immunoglobulins. Immunoglobulins are very sticky; they bind to intruders as biological tags and mark them as ‘alien’. Other cells of the immune system then recognize the intruder, and a destruction cascade is activated. To have a tag available for every possible alien intruder, millions of B cells have their own highly specific gene for immunoglobulin production. In the genome there is only limited storage space for biological information, so how can there be millions of genes? Well, there aren’t.

Immunoglobulin genes are assembled from several pre-existing DNA sequences that can be independently put together. The part of the immunoglobulin that does the ‘alien’ recognition contains several domains which are each highly variable. Every single B cell forms a unique immunoglobulin gene by picking from several short pre-existing DNA sequences. We also observe that later generations of immunoglobulins are more specific than the earlier generations, in the sense that they bind more tightly to invading microorganisms. Binding affinity to an invader is equivalent to recognition of that invader. And the better the immune system is able to recognize an intruder, the better it is able to clear it. The increased specificity is due to somatic mutations deliberately introduced in the genes of the immunoglobulins. A mechanism to rapidly induce mutations in immunoglobulin genes is present in the B cell genome. This mechanism ensures that the recognition pattern specified by the genes becomes increasingly specific for the intruder. This ability to recognize and defeat all potential microorganisms is characteristic of the immune systems of higher organisms, including humans. The genomes contain all the necessary biological information required to induce variation from within. A flexible genome is required to effectively ward off diseases and parasitic infections. B cells don’t wait for mutations to happen; they generate the necessary mutations themselves. Darwin revisited Previously, in part 2,1 I argued that organisms are equipped with flexible, highly adaptable, pluripotent, multipurpose genomes. Organisms are able to conquer the world through adaptive radiation of baranomes. But how do baranomes unleash information? Do organisms have to wait for selectable mutations to occur in order to rapidly invade and occupy novel ecological niches? Or were the baranomes of created kinds equipped with mechanisms to rapidly induce mutations, similar to the variation generated by B cells? Let’s turn to Darwin’s The Origin of Species, where we will find some clues. Darwin wrote quite extensively on variation, and in particular on the variation of feather patterns in pigeons: Box 1. Common names of some well-known variation-inducing genetic elements (VIGEs) in prokaryotes (bacteria) and eukaryotes (yeast, plants, insects and mammals). ‘Some facts in regard to the colouring of pigeons well deserve consideration. The rockpigeon is of a slaty-blue, and has a white rump (the Indian sub-species, C. intermedia of Strickland, having it bluish); the tail has a terminal dark bar, with the bases of the outer feathers externally edged with white; the wings have two black bars; some semidomestic breeds and some apparently truly wild breeds have, besides the two black bars, the wings chequered with black. These several marks do not occur together in any other species of the whole family. Now, in every one of the domestic breeds, taking thoroughly well-bred birds, all the above marks, even to the white edging of the outer tail-feathers, sometimes concur perfectly developed. Moreover, when two birds belonging to two distinct breeds are crossed, neither of which is blue or has any of the above specified marks, the mongrel offspring are very apt suddenly to acquire these characters; for instance, I crossed some uniformly white fantails with some uniformly black barbs, and they produced mottled brown and black birds; these I again crossed together, and one grandchild of the pure white fantail and pure black barb was of as beautiful a blue colour, with the white rump, double black wing-bar, and barred and white-edged tail-feathers, as any wild rock pigeon! We can understand these facts, on the well-known principle of reversion to the ancestral characters, if all the domestic breeds have descended from the rock-pigeon.’ 2Darwin argues—and correctly so— that all domestic pigeon breeds have descended from the rock-pigeon. He even knew, as demonstrated above, how to breed the rock-pigeon from several distinct pigeon races following a breeding pattern. Darwin describes a breeding algorithmfor pigeons, to obtain the ancestor to all pigeons! But does he also describe an algorithm for breeding turkeys from pigeons? No. Darwin doesn’t know such an algorithm. If he had found an algorithm for breeding ducks or magpies from pigeon genomes, he would have had solid evidence in favour of his proposal On The Origin of Species Through the Preservation of Favoured Races. His breeding experiments led him to discover ‘the principle of reversion to ancestral characters’, but contrary to common Darwinian wisdom, it is also the falsifying observation to his proposal for the origin of species. The observation that pigeons bring forth pigeons, and nothing else but pigeons, is not exactly the evidence needed to argue for the common descent of all birds. On the contrary! Darwin’s breeding experiments demonstrated that a pigeon is a pigeon is a pigeon. Characteristics and traits within single species of pigeons may vary tremendously, but he always started and ended with pigeons. Breeding experiments have always shown, without exception, that novel and distinct bird species do not arrive through artificial selection. Even Darwin argues that there is no doubt that all varieties of ducks and rabbits have descended from the common wild duck and rabbit. 3 From the variation Darwin observed in wild and domesticated populations, it does not follow that rabbits and ducks have some hypothetical common ancestor in a fuzzy distant past. Darwin observed inborn, innate variation that already existed in the genomes of the pigeons and it only had to be activated or expressed.From the excerpt above, we may even get an impression of how it works. A genetic algorithm for making feathers (a feather program) is part of the pigeon’s genome and is present in every single cell. The feather program is present in billions of pigeon cells, but it is NOT active in all those cells. Feathers are only formed when the program is activated. The feather program is silent in cells where it should normally not operate. Activation of the feather program in the wrong cells may often be incompatible with life, but sometimes it may produce pigeons with (reversed) feathers on the feet. The program may be derepressed or activated through a mechanism that operates in the pigeon’s genome. Whether feathers appear on the feet or on the head, and whether they appear normal or reversed is merely a matter of activation and regulation of the feather program. But Darwin didn’t know about silent genomic programs or how they could become active. He didn’t know about gene regulation and molecular switches. Darwin did not know anything about genes and genomes. Analogous variation The idea that Darwin had been working on for over two decades prior to the publication of Origin, his idée fixe, was how organic change (i.e. variation) present in populations might explain how novel species came into being. Unchanging, stable species is not what Darwin had in mind. He pondered the riddles of variation; he thought about laws and principles associated with the process of variation and believed he could disclose them by the study of the formation of new breeds. Drawing from what he knew about pigeon breeding and equine varieties, Darwin describes some of his ideas about the ‘laws of variation’ in chapter five of Origin:‘Distinct species present analogous variations; and a variety of one species often assumes some of the characters of an allied species, or reverts to some of the characters of an early progenitor. These propositions will be most readily understood by looking to our domestic races. The most distinct breeds of pigeons, in countries most widely apart, present sub-varieties with reversed feathers on the head and feathers on the feet, characters not possessed by the aboriginal rock-pigeon; these then are analogous variations in two or more distinct races.’ 4Darwin

describes that the exact same traits can appear in distinct breeds of pigeons and—importantly—these traits appeared independently in ‘countries most widely apart’. If several breeds arrive with the same characteristics independently, it is unlikely they do so because of chance. Rather, the pigeon genomes may activate or derepress the same feather program independently. The effect is that distinct breeds ‘in countries most widely apart’ acquire the same characteristics. Over and over the same traits appear in separated populations of organisms as the result of mutations ‘from within’. Animal breeders like exuberant patterns and rarities; that is exactly what they are looking for to select. Aberrant traits that are normally under stringent negative selection, as might be the case for the pigeon’s reversed feathers, may readily become visible as soon as the selective pressure is relieved; that is, when organisms are reared and fed in the protective environment of captivity. Darwin called the phenomenon of independent acquisition of the same traits analogous variation. It is a common phenomenon well known to breeders, and Darwin easily found more examples of analogous variation:‘The frequent presence of fourteen or even sixteen tail-feathers in the pouter, may be considered as a variation representing the normal structure of another race, the fantail. I presume that no one will doubt that all such analogous variations are due to the several races of the pigeon having inherited from a common parent the same constitution and tendency to variation, when acted on by similar unknown influences. In the vegetable kingdom we have a case of analogous variation, in the enlarged stems, or roots as commonly called, of the Swedish turnip and Ruta baga [sic] plants which several botanists rank as varieties produced by cultivation from a common parent: if this be not so, the case will then be one of analogous variation in two so-called distinct species; and to these a third may be added, namely, the common turnip. According to the ordinary view of each species having been independently created, we should have to attribute this similarity in the enlarged stems of these three plants, not to the vera causa of community of descent, and a consequent tendency to vary in a like manner, but to three separate yet closely related acts of creation.’ 5Analogous variation originates in the genome. Through rearrangement and/or transposition of DNA elements, previously silent (cryptic) traits can be activated. The underlying molecular mechanism can’t be merely random; if it were, then Darwin, and other breeders, would not have observed the expression of the same traits independently of each other. A more contemporary translation of analogous variation would benonrandom (or: non-stochastic) variation, and it implies some sort of mechanism. Reversions In the excerpt above, Darwin also describes what he calls reversions. By this term he meant traits that are present in ancestors, then disappear in first generation offspring, and then reappear in subsequent generations. Darwin acknowledged that unknown laws of inheritance must exist, but still he talks about ‘the proportion of blood’. Reversions are easily explained as traits present on separate chromosomes, and the inheritance of such traits is best understood from Gregor Mendel’s inheritance laws. Through Mendel’s discovery of the genetic laws that underlie the inheritance of traits associated with chromosome segregation (a hallmark of sexual reproduction), Mendel gave us a quantum theory of inheritance. He found that traits are always inherited in well-defined and predictable proportions, and do not just come and go. Darwin’s ‘reversions’ are traits that reappear in later generations due to the inheritance of the same genes (alleles) from both parents.5 Darwin didn’t know about Mendel’s laws of inheritance, neither did he know about how variation is generated in genomes. What Darwin described inOrigin, however, is that variation in offspring is a rule of biology. What Darwin described in isolated species (whether domesticated breeds or island-bound birds) was the result of a burst of abundant speciation resulting from multipurpose genomes. Variant breeds of pigeons are the phenotypes of a rearranged multipurpose pigeon genome. The Galápagos finches (with their distinct beaks and body sizes) are the phenotypes of a rearranged multipurpose finch genome. Where does the variation stem from in populations of Galápagos finches?Darwin was well aware of the profound lack of knowledge on the origin of variation, and did not exclude mechanisms or laws to drive biological variation:‘I have hitherto sometimes spoken as if the variations so common and multiform in organic beings under domestication, and in a lesser degree in those in a state of nature had been due to chance. This, of course, is a wholly incorrect expression, but it serves to acknowledge plainly our ignorance of the cause of each particular variation.’ 6Since Darwin’s days, almost all corners of the living cell have been explored and our biological knowledge has expanded greatly. Through a vast library of data generated by new research in biology, we now have the answers to many questions of a biological nature that had puzzled Darwin. We may also have the answer to ‘the cause of each particular variation’, although we may not be aware of it (yet). That is not because it is hidden between billions of other books and hard to find. No, it is because of the Darwinian paradigm. The mechanism(s) that drive biological variations have been elucidated but are not yet recognized as such.One of the findings of the new biology was that the DNA of most (if not all) organisms contains jumping genetic elements. The mainstream opinion is that these elements are the remnants of ancient invasions of RNA viruses. RNA viruses are a class of viruses that use RNA molecule(s) for information storage. Some of them, such as influenza and HIV, pose an increasing threat to human health. Are virus invasions responsible for all the beautiful intricate complexity of organic beings? Is a virus a creator? Most likely it is not. Otherwise why would we pump billions of research dollars into research to fight off viruses? Could it be that mainstream science is mistaken? The RNA virus paradox Here is one good reason for believing that mainstream science is indeed mistaken: the RNA virus paradox. It has been proposed that these RNA viruses have a long evolutionary history, appearing with, or perhaps before, the first cellular life forms.7 Molecular genetic analyses have demonstrated that genomes, including those of humans and primates, are riddled with ‘endogenous retroviruses’ (ERVs), which are currently explained as the remnants of ancient RNA virus-invasions. RNA virus origin can be estimated using homologous genes found in both ERVs and modern RNA virus families. By using the best estimates for rates of evolutionary change (i.e. nucleotide substitution) and assuming an approximate molecular clock,8,9 the families of RNA viruses found today ‘could only have appeared very recently, probably not more than about 50,000 years ago’.10 These data imply that present-day RNA viruses may have originated much more recently than our own species. The implication of a recent origin of RNA viruses and the presence of genomic ERVs poses an apparent paradox that has to be resolved. I will argue, in order to resolve the paradox, we should abstain from the mainstream idea that ERVs are remnants of ancient RNA virus invasions.Solving the RNA paradox can only be accomplished by asking questions. First, we have to ask ourselves, What do scientists mean when they refer to genetic elements as endogenous retroviruses (ERVs)? In addition, we have to ask, How do ERVs behave, and what—if any—are their functions? ERVs have been extensively studied in microorganisms, such as baker’s yeast (Saccharomices cerivisiae) and the common gut bacterium Escherichia coli. Most of our knowledge on the mechanisms of transposition of ERVs comes from those two organisms. In yeast, the ERV known as Ty is flanked by long terminal repeats and specifies two genes, gag and pol, which are similar to genes found in free operating RNA viruses. This is the main argument why scientists believe RNA viruses and ERVs are evolutionarily closely related. The long terminal repeats enable the ERV to insert into the host’s DNA. The transposition and integration is a stringently regulated process and seems to be target or site-specific. 11,12 During the transpositions of an ERV, the host’s RNA polymerase II makes an RNA template, which is polyadenylated to become messenger RNA. Thegag and pol mRNAs are translated and cleaved into several individual proteins. The gag gene specifies a polyprotein that is cleaved into three proteins, which form a capsid-like structure surrounding the ERV’s RNA. We

may ask here: why is a capsid involved? It should be noted that single stranded RNA molecules are very sticky nucleotide polymers and the capsid may prevent the ERV from sticking at wrong places. The capsid may also be required to direct the ERV to the right spots in the genome. The pol polyprotein is cleaved into four enzymes: protease, reverse transcriptase, RNase and integrase. Protease cleaves the polyproteins into the individual proteins and then the RNA and proteins are packed into a retrovirus-like particle. Reverse transcriptase forms a single-stranded DNA molecule from the ERV RNA template, whereas RNase removes the RNA. The DNA is then circularized and the complementary DNA strand is synthesized to create a double-stranded, circular copy of the ERV, which is then integrated into a new site in the host’s genomic DNA by integrase’s activity. This intricate mechanism for transposition of ERVs seems to be irreducibly complex (and thus a sign of intelligent design) since all ERVs and RNA viruses use the same or similar genetic components. Variation-inducing genetic elements (VIGEs). What can the function, if any, of ERVs be? If we follow the mainstream opinion, ERVs integrated into the genomes a very long time ago as viral infections. Currently, ERVs are not particularly helpful. They merely hop around in the genome as selfish genetic elements that serve no function in particular. They are mainly upsetting the genome. Long ago, however, RNA viruses are alleged to have significantly contributed to evolution by helping to shape the genome.It’s hard to imagine this story to be true, and not only because of the RNA virus paradox. Modern viruses usually do not integrate into the DNA of the germ line-cells; that is, the genes of an RNA virus don’t usually become a part of the heritable material of the infected host. If we obey the uniformitarian principle, we are allowed to argue: ‘What currently doesn’t happen didn’t happen a long time ago, either’. To answer the question raised above, we must start finding out more about some biological characteristics of a less complicated jumping genetic element, the so-called insertion-sequence (IS) element. IS elements are DNA transposons abundantly present in the genomes of bacteria. IS elements share an important characteristic with ERVs: transposition. Genome shuffling takes place in bacteria so frequently that we can hardly speak of a specific gene order. The shuffling of pre-existing genetic elements may unleash cryptic information instantly as the result of position effects. Shuffling seems to be an important mechanism to generate variation. But what is the mechanism for genome shuffling? The answer to this question comes unexpectedly from evolutionary experiments, in which genetic diversity (‘evolutionary change’) was determined between reproducing populations of E. coli. During the breeding experiment, which ran for two decades, it was observed that the number and location of IS (‘insertion sequence’) elements dramatically changed in evolving populations, whereas point mutations were not abundant.13After 10,000 generations of bacteria, the genomic changes were mostly due to duplication and transposition of IS elements. A straightforward conclusion would thus be that jumping genetic elements, such as the IS elements, were designed to deliberately generate variation—variation that might be useful to the organism. In 2004, Lenski, one of the co-authors of the studies, demonstrated that the IS elements indeed generate fitness-increasing mutations.14 In E. coli bacteria IS elements activate cryptic—or silent—catabolic operons: a set of genetic programs for food digestion. It has been reported that IS element transposition overcomes reproductive stress situations by activating cryptic operons, so that the organism can switch to another source of food. IS elements do so in a regulated manner, transposing at a higher rate in starving cells than in growing cells. In at least one case, IS elements activated a cryptic operon during starvation only if the substrate for that operon was present in the environment. 15It is clear that in Lenski’s experiments, IS elements did not evolve over night. Rather, the IS elements reside in the genome of the original strain. During the two decades of breeding, the IS elements duplicated and jumped from location to location. There was ample opportunity to shuffle genes and regulatory sequences, and plenty of time for the IS elements to integrate into genes or to simply redirect regulatory patterns of gene expression. Microorganisms may thus induce variation simply through shuffling the order of genes and put old genes in new contexts: variation through position effects that can be inherited and propagated in time. It’s hardly an exaggeration to state that jumping genetic elements specified by the bacterium’s genome generated the new phenotypes.Transposition of IS elements is mostly characterized by local hopping, meaning that novel insertions are usually in the proximity of the previous insertion and may be a more-or-less random phenomenon; the site of integration isn’t sequence dependent. Bacteria have a restricted set of genes and they divide almost indefinitely. Therefore, sequencedependent insertion and stringent regulation of transposition may not be required for IS-induced reshuffling of bacterial genomes; in a population of billions of microorganisms all possible chromosomal rearrangements may occur due to stochastic processes. In ‘higher’ organisms the order of genes in the chromosomes is more important, but there is no reason to exclude jumping genetic elements as a factor affecting the expression of genetic programs through position effects. Transposable elements may therefore be a class of variation-inducing genetic elements (VIGEs) in ‘higher’ organisms. Indeed, ERVs, LINEs and SINEs resemble IS elements in bacteria in that they are able to transpose. In fact, these elements may be responsible for a large part of the variability observed in higher organisms and may even be responsible for adaptive phenotypes. The genomic transposition of VIGEs is not just a random process. As observed for Ty elements in yeast, integration of all VIGEs may originally have been designed as site or sequence specific. It should be noted that VIGEs might qualify as redundant genetic elements, of which the control over translocation may have deteriorated over time. VIGEs in humans Mobile genetic elements make up a considerable part of the eukaryotic genome and have the ability to integrate into the genome at a new site within their cell of origin. Mobile genetic elements of several classes make up more than one third of the human genome.Human endogenous retroviruses (ERVs) are, as with yeast ERVs, first transcribed into RNA molecules as if they were genuine coding genes. Each RNA is then transformed into a double stranded RNA-DNA hybrid through the action of reverse transcriptase, an enzyme specified by the retrotransposon itself. The hybrid molecule is then inserted back into the genome at an entirely different location. The result of this copy-paste mechanism is two identical copies at different locations in the genome. More than 300,000 sequences that classify as ERVs have been found in the human genome, which is about 8% of the entire human DNA.16 Figure 1. Variation-inducing genetic elements (VIGEs) are found throughout all biological

domains, ranging from bacteria to mammals. In yeast, insects and mammals we observe similar designs. (Homologous sequences are indicated by the same colour).Long terminal repeats retrotransposons (LTR retrotransposons) are transcribed into RNA and then reverse transcribed into a RNA-DNA hybrid and reinserted into the genome. LTRs and retroviruses are very similar in structure. Both contain gag and pol genes (figure 1), which encode a viral particle coat (GAG), reverse transcriptase (RT), ribonuclease H (RH) and integrase (IN). These genes provide proteins for the conversion of RNA into complementary DNA and facilitate insertion into the genome. Examples of LTR retrotransposons are human endogenous retroviruses (HERVs). Unlike RNA retroviruses, LTR retrotransposons lack envelope proteins that facilitate movements between cells.Non-LTR retrotransposons, such as long interspersed elements (LINEs), are long stretches (4,000–6,000 nucleotides) of reverse transcribed RNA molecules. LINEs have two open reading frames: one encoding an endonuclease and reverse transcriptase, the other a nucleic acid binding protein (figure 1). There are approximately 900,000 LINEs in the human genome, i.e. about 21% of the entire human DNA. LINEs are found in the human genome in very high copy numbers (up to 250,000).17Short interspersed elements (SINEs) constitute another class of VIGEs that may use an RNA intermediate for transposition. SINEs do not specify their own reverse transcriptase and therefore they are retroposons by definition. They may be mobilized for transposition by using the enzymatic activity of LINEs. About one million SINEs make up another 11% of the human genome. They are found in all higher organisms, including plants, insects and mammals. The most common SINEs in humans are Alu elements. Alu elements are usually around 300 nucleotides long, and are made up of repeating units of only three nucleotides. Some Alu elements secondarily acquired the genes necessary to hop around in the genome, probably though recombination with LINEs. Others simply duplicate or delete by means of unequal crossovers during cell divisions. More than one million copies of Alu elements, often interspersed with each other, are found in the human genome, mostly in the non-coding sections. Many Alu-like elements, however, have been found in the introns of genes; others have been observed between genes in the part responsible for gene regulation and still others are located within the coding part of genes. In this way SINEs affect the expression of genes and induce variation. Alu elements are often mediators of unequal homologous recombinations and duplications.18 Figure 2. Schematic view of the central role VIGEs may play to generate variation, adaptations and speciation events. Lower part: VIGEs may directly modulate the output of (morpho)genetic algorithms due to position effects. Upper part: VIGEs that are located on different chromosomes may be the result of speciation events, because their homologous sequences facilitate chromosomal translocations and other major karyotype rearrangements.Repetitive triplet sequences (RTSs) present in the coding regions of proteins are a class of VIGEs that cannot actively transpose. RTSs are usually found as an intrinsic part of the coding region of proteins. For instance, RTSs can be formed by a tract of glycine (GGC), proline (CCG), or alanine (GCC). Usually RTSs form a loop in the messenger (m)RNA that provides a docking site for chaperone molecules or proteins involved in the mRNA translation. RTSs may increase or decrease in length through slippery DNA polymerases during DNA replication. Conclusions and outlook Now that we have redefined ERVs as a specific class of VIGEs, which were present in the genomes from the day they were created, it is not difficult to see how RNA viruses came into being. RNA viruses have emerged from VIGEs. ERVs, LINEs and SINEs are the genetic ancestors of RNA viruses. Darwinists are wrong in promoting ERVs as remnants of invasions of RNA viruses; it is the other way around. In my opinion, this view is ed by several recent observations. RNA viruses contain functional genetic elements that help them to reproduce like a molecular parasite. Usually, an RNA virus contains only a handful of genes. Human Immunodeficiency virus (HIV), the agent that causes AIDS, contains only eight or nine genes. Where did these genes come from? An RNA world? From space? The most parsimonious answer is: the RNA viruses got their genes from their hosts.The Rous arcoma virus (RSV), which has the ability to cause tumours, has only 4 genes: gag, pol, envand src. In addition, the virus is flanked by a set of repeat sequences that facilitate integration and promote replication. Gag, pol and env are genes commonly present in ERVs. The src gene of RSV is a modified hostderived src gene that normally functions as a tyrosine kinase—a molecular regulator that can be switched on and off in order to control cell proliferation. In the virus, the regulator has been reduced to an on-switch only that induces uncontrolled cell proliferation. The src gene is not necessary for the survival of RSV, and RSV particles can be isolated that have only the gag, pol and env genes. These have perfectly normal life cycles, but do not cause tumours in their host. It is clear the virus picked up the src gene from the host. Why wouldn’t the whole vector be derived from the host? VIGEs may easily pick up genes or parts thereof as the result of an accidental polymerase II read-through. This will increase the genetic content of the VIGE because the gene located next to the VIGE will also be incorporated. An improper excision of VIGEs may also include extra genetic information. Imagine for instance HERV-K, a well-known human-specific endogenous retrovirus, transposing itself to a location in the genome where it sits next to thesrc gene. If in the next round of transposition a part of the src gene was accidentally added to the genes of HERV-K, it has already transformed into a fully formed RSV (see figure 3). It can be demonstrated that most RNA viruses are built of genetic information directly related to that of their hosts. Figure 3. RNA viruses originate from VIGEs through the uptake of host genes. In the controlled and regulated context of the host DNA, genes and VIGEs are harmless. A combination of a few genes integrated in VIGEs may start an uncontrolled replication of VIGEs. In this way, VIGEs may take up genes that serve to form the virus envelope (to wrap up the RNA molecule derived from the VIGE) and genes that enable them to leave and re-enter host cells. Once VIGEs become full-blown shuttle vectors between hosts, they act as virulent, devastating and uncontrolled replicators. Hence, harmless VIGEs may degenerated into molecular parasites in a similar way normally harmless cells turn into tumors once they lose the power to control cell replication. VIGEs are on the basis of RNA viruses, not the other way around. The scheme outlined here shows

how the Rous sarcoma virus (RSV) may have formed from a VIGE that integrated the env gene and part of the src gene (a proto-oncogene: for details see text).The outer membranes of influenza viruses, for instance, are built of hemagglutinin and neuraminidase molecules. Neuraminidase is a protein that can also be found in the genomes of higher ‘host’ organisms, where it serves the function to modify glycopeptides and oligosaccharides. In humans, neuraminidase deficiency leads to neurodegenerative lysosomal storage disorders: sialidosis and galactosialidosis. 19 Even so-called orphan genes, genes that are only found in viruses, can usually be found in the host genomes. Where? In VIGEs!To become a shuttle-vector between organisms, all that is required is to have the right tools to penetrate and evade the defenses of the host cell. HIV, for instance, acquired part of the gene of the host’s defence system (the gp120 core) that binds to the human beta-chemokine receptor CCR5.20These observations make it plausible that all RNA viruses have their origin in the genomes of living cells through recombination of host’s DNA elements (genes, promoters, enhancers). Every now and then such an ‘unfortunate’ recombination produces a molecular replicator: it is the birth of a new virus. Once the virus escapes the genome and acquires a way to re-enter cells, it has become a fully formed infectious agent. It has long been known that bacteria use genes acquired from bacteriophages—i.e. bacterial viruses that insert their DNA temporarily or even permanently into the genome of their host—to gain reproductive advantage in a particular environment. Indeed, work reaching back decades has shown that prophage (the integrated virus) genes are responsible for producing the primary toxins associated with diseases such as diphtheria, scarlet fever, food poisoning, botulism and cholera. Diseases are secondary entropy-facilitated phenomena. Virologists usually explain the evolution of viruses as recombination: that is, a mixing of pre-existing viruses, a reshuffling and recombination of genes.21 In bacteria, viruses may therefore be recombined from plasmids carrying survival genes and/or transposable genetic elements, such as IS elements. Discussion Where did all the big, small and intermediate noses come from? Why are people tall, short, fat or slim? What makes morphogenetic programs explicit? The answer may be VIGEs. It may turn out that the created kinds were designed with baranomes that had an ability to induce variation from within. This radical view implies that the baranome of man may have been designed to contain only one morphogenetic algorithm for making a nose. But the program was implicit. The program was designed in such way that a VIGE easily integrated into it, becoming a part of it, hence making the program explicit. Most inheritable variation we observe within the human population may be due to VIGEs—Elements that affect morphogenetic and other programs of baranomes. It should be noted that a huge part of the genomic sequences are ‘redundant’ adaptors, spacers, duplicators, etc., which can be removed from the genome without major affects on reproductive success (fitness). In bacteria, VIGEs have been coined IS elements; in plants they are known as transposons; and in animals, they are called ERVs, LINEs, SINEs, and microsatellites. What these elements are particularly good at is inducing genomic variation. It is the copy number of VIGEs and their position in the genome that determine gene expression and the phenotype of the organism. Therefore, these transposable and repetitive elements should be renamed after their function: variation-inducing genetic elements. VIGEs explain the variations Darwin referred to as ‘due to chance’.I will address the details of a few specific classes of VIGEs and argue why modern genomes are literally riddled with VIGEs in a future article. With the realization that RNA viruses have emerged from VIGEs the RNA paradox is solved. For many mainstream scientists this solution will be bothersome because VIGEs were frontloaded elements of the baranomes of created kinds and that implies a young age for their common ancestor and that all life is of recent origin. The design of life: part 4—variation-inducing genetic elements and their function by Peer Terborg Endogenous retroviruses (ERVs) are claimed to be the selfish remnants of ancient RNA viruses that invaded the cells of organisms millions of years ago and now merely free-ride the genome in order to be replicated. This selfish gene thinking still dominates the public scene, but well-informed biologists know that the view among researchers is rapidly changing. Increasingly, ancient RNA viruses and their remnants are being thought of as having played (and still do) a significant role in protein evolution, gene structure, and transcriptional regulation. As argued in part 3 of this series of articles, ERVs may be the executors of genetic variation, and qualify as specifically designed variation-inducing genetic elements (VIGEs) responsible for variation in higher organisms. VIGEs induce variation by duplication, transposition, and may even rearrange chromosomes. This extraordinary claim requires extraordinary scientific , which is present throughout this paper. In addition, the VIGE hypothesis may be a framework to understand the origin of diseases and explain rapid speciation events through facilitated chromosome swapping. The idea that mobile genetic elements are involved in creating variation is not new. Barbara McClintock, who discovered the first mobile genetic elements in maize, was also the first to recognize the true nature of such jumping genetic elements. In 1956, she suggested that transposons (as she coined them) function as molecular switches that could help determine when nearby genes turn on and off. Her key insight was that all living systems have mechanisms available to restructure and repair the chromosomes. When it was discovered that more than half of the human genome consists of (remnants of) mobile elements, McClintock’s ideas were revived and further developed by Roy Britten and Eric Davidson. 1 It is only recently that we have begun to understand the power of VIGEs (variation-inducing genetic elements) as genetic regulators and switches. A team of investigators lead by Haussler recently provided direct evidence that even when a short interspersed nucleotide element (SINE) lands at some distance from a gene, it can take on a regulatory role with powerful regulatory functions.2‘Haussler and his colleagues then looked at a particular example—a copy of the ultra-conserved element that is near a gene called Islet 1 (ISL1). ISL1 produces a protein that helps control the growth and differentiation of motor neurons. In the laboratory of Edward Rubin at the University of California, Berkeley, postdoctoral fellow Nadav Ahituv combined the human version of the LF-SINE sequence with a “reporter” gene that would produce an easily recognizable protein if the LF-SINE were serving as its on-off switch. He then injected the resulting DNA into the nuclei of fertilized mouse eggs. Eleven days later, he examined the mouse embryos to see whether and where the reporter gene was switched on. Sure enough, the gene was active in the embryos’ developing nervous systems, as would be expected if the LF-SINE copy were regulating the activity of ISL1.’3This excerpt shows that some functions of SINEs are easily uncovered because they are directly affecting the expression of a particular gene. However, most functions of SINEs may not be as easily detected as described of above, because they can integrate in gene deserts—regions of the genome where the chromosomes are devoid of any recognizable protein-coding genes—or they may only subtly affect expression of morphogenetic programs. Gene expression patterns largely determine how cells behave and determine the morphology of organisms. VIGEs integrated in such genetic programs will change expression patterns of genes that will result in different cellular behaviour and morphology. Whether the ultimate effect on the phenotype of the organism can be predicted, however, remains to be established. This is largely due to the fact that we still do not know what morphogenetic algorithms look like. Of course, biologists have argued that evolution and development are determined by homeobox (HOX) genes, but HOX genes are merely executors of developmental (or morphogenetic) programs; they are not the programs themselves.In another study by

the same group, thousands of short identical DNA sequences that are scattered throughout the human genome were analyzed. Many of those sequences were located in gene deserts, which are in fact so clogged with regulatory DNA elements that they have recently been renamed regulatory jungles. But what do they regulate? The answer could be morphogenesis. Most of the short DNA elements cluster near genes that play a decisive role during an organism’s first weeks after conception. The elements help to orchestrate an intricate choreography of ‘when-and-where’ developmental genes are switched on and off as the organism lays out its body plan. These elements may provide a sort of blueprint for how to build the animal. The exact mechanism as to how such sequences may function as a plan to build an animal is not entirely clear, but the DNA elements are particularly abundant near genes that help cells to stick together. That ‘stickiness’ is important in an organism’s early life phase because these genes help cells to migrate to the right location and to form into organs and tissues of the correct shape. The 10,402 short DNA sequences studied by Bejerano are derived from transposable genetic elements—retrotransposons that duplicate themselves and hop around the genome. Apparently, transposable genetic elements are not what they have been mistakenly thought to be: mess makers. Indeed, the view that transposable elements are just bad stuff is rapidly changing. In an interview with Science Daily, Bejerano says:‘We used to think they were mostly messing things up. Here is a case where they are actually useful.’4The genome is literally littered with thousands of transposable elements. The word is that ‘when ancient retroviruses slipped bits of their DNA into the primate genome millions of years ago, they successfully preserved their own genetic legacy.’ 5 It is hard to imagine that they all have functions, but their presence could certainly determine or fine-tune the output of nearby genes. In this way they may create subtle, but novel, variation. Bejerano and Haussler’s research has already identified a handful of transposons that serve as regulatory elements, but it is not clear how common the phenomenon might be. The 2007 study showed that the phenomenon may be a general one:‘Now we’ve shown that transposons may be a major vehicle for evolutionary novelty.’4The new findings indeed show that, in many cases, transposable elements function as regulators of gene output, but major vehicles for evolution from microbe to man they are not. The transposition of jumping genetic elements may certainly affect gene expression patterns, but it does not follow that they produce new genetic information. Considering the biological data, it seems reasonable that transposable elements are present in the genome to deliberately induce biological variation. Transposable elements thus qualify as variation-inducing genetic elements (VIGEs), and by leaving copies, they make sure the new variation is heritable. The transposable elements present in regulatory jungles do not produce new biological information, but they induce variation in the genetic algorithms and may underlie rapid adaptive radiation from uncommitted pluripotent genomes. The regulatory jungles may provide an active reservoir of VIGEs that put existing genes in new regulatory environments. Regulated activity of VIGEs The chromosome of the E. coli strain K12 includes three cryptic operons (linear genetic programs that encode programs to metabolize three alternative sugars): one for cellobiose, one for arbutin and one for salicin. The organization of those operons is like a normal substrate-induced bacterial operon; but the operons themselves are abnormal in that they are cryptic (silent) in wild-type strains. Even in the presence of alternative sugars the operons are not activated, which indicates that these bacteria don’t readily use alternative sugars. Unused cryptic operons are redundant genetic programs that are not observed by natural selection:‘As cryptic genes are not expressed to make any positive contribution to the fitness of the organism, it is expected that they would eventually be lost due to the accumulation of inactivating mutations. … Cryptic genes would thus be expected to be rare in natural populations. This, however, is not the case. Over 90% of natural isolates of E. coli carry cryptic genes for the utilization of beta-glucoside sugars. … These cryptic operons can all be activated by IS [insertion-sequence] elements, and when so activated allow E. colito utilize beta-glucoside sugars as sole carbon and energy sources.’6The excerpt shows that operons are kept inactive by repressors; that is, proteins that sit on the DNA of the operon to ward off the nanomachines responsible for gene expression. Operons will only be active in bacteria that don’t have a functional gene coding for the repressors. Disrupting the repressor gene releases the cryptic programs. That’s where the VIGEs come in. The transposition and integration of an IS element into the silencer elements is the mutational event that activates the cryptic operon. Usually, the lack of an appropriate carbon and energy source triggers transposition of IS elements. The transposition of IS elements appears to be regulated by starvation, and the integration in the repressor gene is not utterly random. For instance, position 472 in the ebgR gene in the ebg operon of E. coli is a hotspot for integration of IS elements, but only under starvation conditions. VIGEs may thus accumulate and integrate at well-defined positions in the genome; this indicates a site-specific mechanism.In the fruit fly, some non-LTR (long terminal repeats retrotransposons) integrate at very specific sites, but some others have been shown to integrate more or less at random. The specificity is determined by endonucleases, enzymes that cut the DNA.7 Assuming VIGEs are part of a designed genome, we must expect that their transposition and activity can be controlled and regulated. To avoid deleterious effects on the host and retrotransposon, we may expect that the activity of VIGEs is regulated both by retrotransposon-and host-encoded factors. Indeed, the mechanism of transposition seems to be dictated by the species in which the VIGEs operate. Recent research has shown that in zebra fish the transposable element known as NLR integrant usually carries a few extra nucleotides at the far end of the sequence, but it is not expressed in human cells.8 This observation would argue for the involvement of host specific protein machinery in transposition—one more argument for the design origin of VIGEs.From the design perspective, we may expect that the activity of VIGEs used to be a tightly controlled process. This is because the genomes in which they operate also specify control factors: retroviral restriction factors. The restriction factors are proteins with the ability to bind to retroviral capsid proteins and target them for degradation. Several restriction factors have been identified, including Fv1, Trim5-alpha and Trim5-CypA.9 These factors share the common property of containing sequences that promote selfassociation: that is, they can assemble themselves. This fact, together with the observation that the restriction factors are encoded by unrelated genes, is clear evidence of purposeful design. Retroviral restriction factors play an important role in innate immunity against invading RNA viruses. For instance, Trim5-alpha binds directly to the incoming retroviral capsid core and targets its premature disassembly or destruction. 10 In addition, some integrated VIGEs show evolutionary-tree deviations, indicating a sequence-specific integration/excision mechanism. For instance, Alu HS6 is present in human, gorilla and orangutan, but not in chimpanzee (see figure 1). This highly peculiar observation prompted the investigators to consider the possibility of the specific excision of this Alu element from the chimpanzee’s genome.11 Precise excision implies

precise integration.

Figure 1. The Alu HS6 insertion sites in human, chimpanzee, gorilla, orangutan and owl monkey. Note the complete absence in chimpanzee and owl monkey of any evidence for an extraction site. This suggests a highly specific mechanism for integration and/or extraction. Alternatively, the sequences are a molecular falsification of the common descent of primates. Biologists specializing in synthetics at the Johns Hopkins University have built, from scratch, a LINE1-based retrotransposon —a genetic element capable of jumping around in the mouse genome. The man-made retrotransposon was designed to be a far more effective ‘jumper’ than natural retrotransposons; indeed, it inserts itself into many more places in the genome.12,13 Why do not all LINEs jump so effectively? The scientists that constructed the synthetic LINE changed the regulator sites used in transposition. Native LINE1 elements are relatively inactive in mice when they are introduced into the mouse genome as transgenes. The synthetic LINE1-based element, ORFeus, contains two synonymously recoded ORFs relative to mouse L1 and is far more active. This indicates that the integration and excision of native LINE1 elements are controlled and regulated by an as yet unknown mechanism.VIGEs qualify as redundant genetic elements that can simply be erased from the genome without fitness effects. As long as VIGEs do not upset critical genomic functions and do affect reproductive success of the carrier, they are selectively neutral. Therefore, not only VIGEs, but also the mechanisms by which they integrate, may readily wither and degrade due to accumulation of debilitating mutations. The control over integration and activity we observe today may be less stringent compared to how it was originally designed. The originally fine-tuned control for excision and transposition may have deteriorated over time and what is left today are more or less free moving elements that may predominantly cause havoc when they integrate in the wrong location. It is easy to understand how, for instance, endonucleases became less specific through mutations. This view may also explain why VIGEs are often found associated with heritable diseases. As long as VIGE activity and integration do not significantly affect the fitness of the organisms in which they operate, they are free to copy and paste themselves along the genome. Indeed, inactivating VIGEs have been observed in genes not immediately required for reproduction. The GULO gene, which qualifies as a redundant gene in populations with high vitamin C intake, has been hit several times by VIGEs and this may have contributed to pseudogenization of GULO in humans.14Over time, VIGEs may have become increasingly detrimental to the host’s genome. That is because information that regulates the integration and activity of VIGEs is subject to mutation. Some VIGEs have been associated with susceptibility or resistance to diseases. In asthma, increased susceptibility appears to be associated with microsatellite DNA instability (a term used for copy-number differences in repetitive DNA sequences). 15 Psoriasis is also associated with HERV expression.16 It should be clear that deregulated and uncontrolled VIGEs cause havoc when they integrate with and disrupt functional parts of genes.From the vantage of design, VIGE transpositions would make sense during meiosis, which is the process leading to the formation of gametes. Controlled activity of VIGEs during meiosis may be responsible for variation that can be ed on to the offspring. Although information is scant, it has been shown in fungi17 and plants18 that VIGEs become active during meiosis and even have mechanisms to silence deleterious bystandereffects, such as deleterious point mutations.17 This shows transposable elements function to induce genetic variation, providing the flexibility for populations to adapt successfully to environmental challenges. In chimpanzees, for instance, it has been documented that large blocks of compound repetitive DNA, which have demonstrated retrotransposon function, induce and prolong the bouquet stage in meiotic prophase and affect chiasm formations. 19 This may seem like a mouthful, but it merely means that these repetitive genetic elements facilitate sister-chromosome exchanges when reproductive cells (sperm and eggs) are being generated. Mammalian VIGEs, in particular Alu sequences, have the ability to induce genetic recombination and duplications and contribute to chromosomal rearrangements, and they may for the major part of variation observed in humans. The methylation pattern of Alu sequences possibly determine activity and/or serve as markers for genomic imprinting or in maintaining differences in male and female meiosis. 21 VIGEs and the human family When short triplet repeat units are present in the coding part of a gene, they may even have functional consequences. There is evidence that repeat units in the Runx2 gene formed the bent snout of the Bullterrier in a few generations.22 Likewise, in mice and dogs, having five or six toes is determined by a repeat unit in the Alx4 gene.23 These novel phenotypes can form almost over night, i.e. within one generation. Repetitive coding triplets that can be gained or lost provide another mechanism to generate (instant) variation. It should be noted that this mechanism leads to reversible genetic change, because a lost repetitive unit can readily be added back through duplication of a preexisting one, and vice versa. Therefore, the RTS mechanism may explain seasonal changes in beak size observed for Galapagos finches, adaptive phenotypes in Australian snakes and the ‘evolution’ of the Cichlid varieties in African lakes.If we accept the idea of deliberately designed VIGEs, we may also expect these elements to have played an important role in determining the variety of human phenotypes. In other words, human races are the result of the activity of VIGEs! Biologists used to think that our genomes all had the same basic structure—the same number of genes, in roughly the same order, with a few minor differences in the sequence of DNA bases. Now, technologies that compare whole human genomes are revealing that this picture is far from complete. Michael Wigler at Cold Spring Harbor Laboratory provided the first evidence that human genomes are strikingly variable: his group showed marked differences in the copy number of protein-coding genes.24 Apparently, some people have more copies of certain genes and, large-scale copy number polymorphisms (CNPs) (about 100 kilobases and greater) contribute substantially to genomic variation between individuals. 25 In addition, people not only carry different copy numbers of parts of our DNA they also have varying numbers of deletions, insertions and other major rearrangements in their genomes.In 2005, Evan Eichler of the University of Washington reported 297 locations in the genome where different individuals have different forms of major structural variations. At these spots some carry a major deletion, for example, or an extra hundred bases of DNA. Differences between individuals were found in the protein-coding genes; structural differences were also observed between individual genomes.26 From these and other studies we now know that every one of us shares only about 99% of our DNA with all the other people on Earth. 27 The difference is due to repetitive sequences that easily amplify or delete parts from the genome. With this, we have discovered another class of VIGEs. The highly variable repetitive sequences also explain why genetic screening methods are so reliable nowadays: they detect copy-number differences and hence are capable of discriminating between the DNA of a father and his son. Yes, fathers and sons apparently differ at the level of VIGEs!A comparison of Asian and Caucasian people showed that 25% of more than 4,000 protein-coding genes had significantly different expression patterns. Some gene expression levels differed as much as twofold.28 The researchers commented that these findings ‘ … the idea that there are genetically determined characteristics that tend to be clustered in different ethnic groups.’ Some genes are simply not expressed at all, or are simply not present in the genomes. For instance, the gene UGT2B17 is deleted more often in Asians than in Caucasians, and has a mean expression level that was more than 20 times greater in Caucasians relative to Asians. How can such big differences be explained? Of course, single nucleotide polymorphisms (SNP; i.e. point mutations) in regulatory sequences could affect gene regulation patterns. It is not clear, however, ‘whether the SNPs themselves might be regulating gene expression or whether they travel together with other DNA that’s the regulator.’ We may also expect VIGEs to be responsible for differences observed between human races.

VIGEs and chromosome 2 Human chromosome 2 looks as if it is the product of the fusion of two chromosomes that we find in chimpanzees as chromosome 12 and 13. Therefore, some Darwinists take human chromosome 2 as the ultimate evidence for common descent with chimpanzees. We know that a fusion of two ancestral chromosomes would have produced human chromosome 2 with two centromeres. Currently, human chromosome 2 has only one centromere, so there must be molecular evidence for remnants of the other. In 1982, Yunis and Prakash studied the putative fusion site of chromosome 2 with a technique known as fluorescence in situ hybridization (FISH) and reported signs of the expected centromere.29In 1991, another study also reported signs of the centromere.30 In 2005, after the complete sequencing of human chromosome 2, we would have expected full proof of the ancestor’s centromere. However, even after intense scrutiny there are still only signs of the centromere. If signs of the centromere were already observed in 1982, why can it not be proved in the 2005 sequence analysis? Apparently, the site mutated at such high speed it is no longer recognizable as a centromere:‘During the formation of human chromosome 2, one of the two centromeres became inactivated (2q21, which corresponds to the centromere of chromosome 13) and the centromeric structure quickly deteriorated’. 31Why would it quickly deteriorate? Why would this region deteriorate faster than neutral? A close up scrutiny in 2005 showed the region that has been interpreted as the ancestor’s centromere to be built from sequences present in 10 additional human chromosomes (1, 7, 9, 10, 13, 14, 15, 18, 21 and 22) as well as a variety of other genetic repeat elements that were already in place before the fusion occurred.31 The sequences interpreted as ‘ancient centromere’ are merely repetitive sequences and may actually qualify as (deregulated) VIGEs.The chimpanzee and human genome projects demonstrated that the fusion did not result in loss of protein coding genes. Instead, the human locus contains approximately 150,000 additional base pairs not found in chimpanzee chromosome 12 and 13 (now also known as 2A and 2B). This is remarkable: why would a fusion result in more DNA? We would rather have expected the opposite: the fusion would have left the fused product with less DNA, since loss of DNA sequences is easily explained. The fact that humans have a unique 150 kb intervening sequence indicates it may have been deliberately planned (or designed) into the human genome. It could also be proposed that the 150 kb DNA sequence demarcating the fusion site may have served as a particular kind of VIGE, an adaptor sequence for bringing the chromosomes together and facilitating the fusion in humans.Another remarkable observation is that in the fusion region we find an inactivated cobalamin synthetase (CBWD) gene. 32 Cobalamin synthetase is a protein that, in its active form, has the ability to synthesize vitamin B12 (a crucial cofactor in the biosynthesis of nucleotides, the building blocks of DNA and RNA molecules). Deficiency during pregnancy and/or early childhood results in severe neurological defects because of impaired development of the brain. The Darwinian assumption is that the cobalamin synthetase gene was donated by bacteria a long time ago and afterwards it was inactivated. Nowadays, humans must rely on microorganisms in the colon as well as dietary intake (a substantial part coming from meat and milk products) for their vitamin B12 supply. It is also noteworthy that humans have several copies of inactivated cobalamin-synthetase-like genes on a number of locations in the genome, whereas chimpanzees only have one inactivated cobalamin synthetase gene. That the fusion must have occurred after man and chimp ‘split’ is evident from the fact that the fusion is unique to humans:‘Because the fused chromosome is unique to humans and is fixed, the fusion must have occurred after the humanchimpanzee split, but before modern humans spread around the world, that is, between 6 and 1 million years ago.’ 32The molecular analyses show we are more unique than we ever thought we were, and this is in complete accordance with creation. Apparently the fusion of two human chromosomes that took place may have been the result of an intricate rearrangement or activation of repetitive genetic elements after the Fall (as part of, or executors of, the curse following the Fall) and inactivated the cobalamin synthetase gene. The inactivation of the gene may have reduced people’s longevity in a similar way as the inactivation of the GULO gene, which is crucial to vitamin C synthesis. 14 Understanding the molecular properties of human chromosome 2 is no longer problematic if we simply accept that humans, like the great apes, were originally created with 48 chromosomes. Two of them fused to form chromosome 2 when mankind went through a severe bottleneck.33 And, as argued above, the fusion was mediated by VIGEs (see figure 2). Figure 2. Putative mechanism for how the human chromosome 2 formed through the fusion of two ancestral chromosomes p2 and q2, which are similar to chimpanzee chromosome 12 and 13). Like the great apes, originally the human baranome may have contained 48 chromosomes. A) Independent transposition events may have led to the integration of a relative small variation-inducing genetic element (VIGE). B) Extended duplication events of the VIGE may have resulted in rapid expansion of the region in both p2 and q2, preparing it to become an ‘adapter sequence’ required for fusion. C) The expanded homologous regions align and facilitate the fusion of the chromosomes. The fusion region (2q21) and other parts of the modern human genome still shows the remnants of this catastrophic event that only occurred in humans: the cobalamin synthetase gene was inactivated and several inactive copies, which are not found in the chimpanzee, scattered throughout the genome. Speculative note: Before the great flood, and probably shortly after, a balancing dynamics of both 48 and 46 chromosomes may have been present in the human family. This may explain the two extreme cranial morphologies present in the human fossil record. The Homo erectus/Neandertal humans may have had a karyotype comprised of 48 chromosomes (non-fused p2 and q2), whereas the other humans had 46 (fused p2 and q2). The upside-down world The p53 protein is a mammalian transcription factor that functions as the main switch controlling whether cells divide or go into apoptosis (programmed cell death, which is sometimes required for severely damaged cells that may become tumours).

Scientists have long wondered how p53 gained the ability to turn on and off more than 1200 genes related to cell division, DNA repair and programmed cell death. Without the p53 control system organisms would not function: all life would have died as bulky tumors.Biologists at the University of California now claim that ancient retroviruses helped p53 to become an important master gene regulator in primates.34 An RNA virus invaded the genome of our common ancestor, jumped into hundreds of new positions throughout the human genome and spread numerous copies of repetitive DNA sequences that allowed p53 to regulate many other genes, the team contends. Studies such as these prompted Darwinians to change their minds about jumping genetic elements. In other words, a randomly hopping ERV provided the human genome with carefully regulated decision-making machinery. The idea is beyond reasonable belief. Darwinists tend to mix things up. What really happened in the human genome is a read-through of polymerase II in a VIGE that was next to a gene that already contained a binding site for p53. Or maybe the VIGE was excised improperly, taking a bit of a flanking gene containing the p53 binding site. Next, the modified VIGE amplified, transposed, amplified and so on. That explains this family of transposons. A similar story can be told for the syncytin gene, which encodes a protein of the mammalian placenta that helps the fertilized egg to become embedded in the uterus wall. Since syncytin has also been found on a transposable element, 35 mammals are alleged to have obtained the gene from an RNA virus that infected a mammalian ancestor millions of years ago. It is more likely, however, that syncytin was captured by a VIGE.In bacteria it is often observed that genes that convey a specific advantageous character are transmitted via plasmids. Plasmids often contain genes for alternative metabolic routes or genes that provide resistance to antibiotics, and they replicate independently from the host’s genome. Plasmids easily shuttle between microorganisms via a DNA uptake-process known as transformation (or horizontal gene transfer). The uptake of plasmids is regulated and controlled, and is DNA sequence dependent. The result of DNA transformations is rapid adaptation to, for instance, antibiotics. Likewise, viruses replicate independently from the genomic DNA, leaving many copies and easily transferring from one organism to another. Viruses are not plasmids, although some viruses may have a similar function in higher organisms as do plasmids in bacteria: they may be able to aid in rapid adaptations to changing environments. It has been observed that a virus can indeed transfer an adaptive phenotype. The virus that is present in the fungus (Curvularia protuberata), can induce heat resistance in tropical panic grass (Dichanthelium lanuginosum), allowing both organisms to grow at high soil temperatures in Yellowstone National Park. This shows that ‘viruses’ still provide strategies for rapid adaptation.‘Fungal isolates cured of the virus are unable to confer heat tolerance, but heat tolerance is restored after the virus is reintroduced. The virus-infected fungus confers heat tolerance not only to its native monocot host but also to a eudicot host, which suggests that the underlying mechanism involves pathways conserved between these two groups of plants.’36In fruit flies, wing pigmentation depends on a gene known as yellow. The gene exists in the genome of all individual fruit flies, but in some it is not active. By analysing the genetic origin of the spots on fruit fly wings, researchers have discovered a molecular mechanism that explains how new patterns of pigmentation can emerge. The secret appears to be specific genetic elements that orchestrate where proteins are used in the construction of an insect’s body. The segments do not code for proteins, but rather regulate the nearby gene that specifies the pigmentation. As such, these regulatory DNA segments qualify as VIGEs. The researchers transferred the regulatory DNA segment from a spotted species (Drosophila biarmipes) into another species not expressing the spot (D. melanogaster), and attached the regulatory region to a gene for a fluorescent protein. They found that the fluorescent gene was expressed in the spot-free species in exactly the same patterns as the yellow gene is expressed in the spotted species. By comparing several spotted and spotfree species, the scientists established that mutation of a regulatory DNA segment led to the expression of the spotted trait. They discovered that in the species with spotted wings this regulatory segment has multiple binding sites for a protein that then activates the yellow gene. Spotless species do not have multiple binding sites. 37 The multiplicity of regulatory DNA segments may argue for an amplification mechanism or targeted integration of the regulatory sequence. That explains why the same pattern of pigmentation can emerge independently in distantly related species (Darwin’s analogous variation). The observed shuttle function of viruses leads me to pose an intriguing question: Were endogenous retroviruses originally designed to serve as shuttle-vectors to deliver messages from the soma to the germ-line? If yes, then it would put Lamarckian evolution in an entirely new perspective. Discussion The findings of the new biology demonstrate that mainstream scientists are wrong regarding the idea that transposable elements are the selfish remnants of ancient invasions by RNA viruses. Instead, RNA viruses originate from transposable elements that were designed as variation-inducing genetic elements (VIGEs). Created kinds were deliberately frontloaded with several types of controlled and regulated transposable elements to allow them to rapidly invade and adapt to all corners and crevices of the earth. Due to the redundant character of VIGEs, their controlled regulation may have readily deteriorated and some of them may now merely cause havoc. The VIGE hypothesis provides elegant explanations for several biological observations that may otherwise be difficult to interpret within the creationist framework, including the origin of diseases (RNA viruses) and chromosome rearrangements. The VIGE hypothesis may be a framework for extended creationist research programs. Some intriguing question can already be raised. Were VIGEs intentionally designed to cause diseases? No, they were not. It is conceivable that the transposition and integration of VIGEs is not entirely random. The transposition of VIGEs may have been originally present in the baranome as controlled and regulated elements and activated upon intrinsic or external triggers. To induce variation in offspring, triggers for the transposition of VIGEs could be released during meiosis, when the reproductive cells are being produced. The emergence of RNA viruses from VIGEs may be a result of the Fall, when we were cut of from the regenerating healing power of the designer. Why are some VIGEs located on the exact same position in primates and humans? Each original baranome must have had a limited number of VIGEs, some of which we still find on the same location in distinct species. In distinct baranomes, VIGEs may have been located on the exact same positions (the T-zero location), which then explains why some VIGEs such as ERVs, can be found in the same location in, for instance, primates and humans. In addition, sequencedependent integration of VIGEs may also contribute to this observation. How could Bdelloid rotifers, a group of strictly asexually reproducing aquatic invertebrates, rapidly form novel species?Asexual production of progeny, as observed in Bdelloids, is found in over one half of all eukaryotic phyla and is likely to contribute to adaptive changes, as suggested by recent evidence from both animals and plants. 38 The Bdelloids may have been derived from pluripotent baranomes containing numerous DNA transposons and retro elements, including active LTR retrotransposons containing gag,pol, and env-like open reading frames.39 These elements are able to reshuffle the genomes and facilitate instant variation and speciation. Do we also observe remnants of DNA viruses in the mammalian genomes? If not, this s my idea that RNA viruses emerged from VIGEs, and implies DNA viruses have a different origin; probably, as with the Mimi-virus 40, they originated from degenerated bacteria. Why was a class of VIGEs designed with information for protein capsids? The capsid may have been acquired from the host’s genome or it may have been designed to prevent the RNA molecules from attaching themselves to, or finding,

integrations sites. A very speculative idea may be that these VIGEs were designed to shuttle information from the soma to the germ-line. One thing is clear, however: creation researchers have loads of work to do. And then there was life by Gordon Howard What is the difference between figure 1 and figure 2? Both are patterns of light and dark. Both are arrangements of the same 12 particular shapes in the same groupings. Both exhibit a complexity of arrangement. The probability of either arrangement arising by chance is similar. Neither arrangement has been produced by any action of the properties of the material they appear on.But there is a world of difference between the two, and that difference is equivalent to the difference between the imagined ‘primordial soup’1 of non-living chemicals, and a living cell. This is because a living cell is not a random collection of chemicals, but an incredibly complex machine controlled by information stored in a computer-like program.The essential difference between the figures is simply that figure 2 carries information while figure 1 does not. This difference has nothing to do with the material the figures are made of. That is, the difference cannot be detected by physical means. It is immaterial, existing only in the reader’s mind, and then only if the reader speaks English. That is, only if the reader understands the inherent code.Could the arrangement of figure 2 arise by chance? Yes, but then it would not necessarily carry information. Consider a set of letters randomly selected that made the pattern “I LOVE YOU”. It would not actually be carrying the information we might like, because the letter “I” (for example) would be just a letter like any other. It would not represent anything, such as the concept of a particular person. There would be no ‘sender’ (because it is random), no intended recipient, no code, and therefore no meaning—it would just be a pattern of shapes no more significant than any other.Figure 2 carries information only if the pattern of shapes conforms to an agreed code; that is, if it is specified by a set of rules, such as the rules of the English language, and represents the concept of something not physically present. Furthermore, it only carries information if that code can be interpreted by another party or process, through some decoding ‘machinery’ in a recipient. In other words, the pattern needs to be filtered through a set of rules which can then be used to put the information into action. Only then does it become meaningful, because meaning does not arise from the arrangement, but from the interpretation, or decoding, of the arrangement. That is what happened when you decoded the pattern in figure 2.While a required arrangement (such as figure 2) might arise by chance, 2 its rules of interpretation cannot, since the rules for coding and decoding are likewise non-material, an abstraction, and therefore can only be formulated and understood by an intelligence. 3 Neither can the specification for arriving at the particular arrangement in the first place arise by chance, again because therules for the specificity (the ‘language’ that determines the arrangement of the letters) cannot arise from any property of matter. Thus these rules are also the work of intelligence, or mind.Information, therefore, cannot arise from inanimate matter by chance.However, a living organism requires information to function. This is because a living organism requires carefully specified materials and processes, not only for itself, but for its replication. In fact, reproduction is part of the definition of a living thing. Replication assumes instructions for the process of building the replicant from scratch, all the while maintaining a functioning organism, and thus needs still more information than that needed simply to live.It is obvious that the specifications, or information, for all the processes needed for an organism to grow, live and reproduce must have beenpreviously conceived and stored before the organism could begin its life. It is now stored in and interpreted by its DNA, but none of it could have occurred by chance ‘in the beginning’, since no ‘primordial soup’ or primitive organism can generate information, or a code system for storing it. Further, a random arrangement of DNA nucleotides would not carry any information. Since the source of all information is a mind, this situation is an absolute indicator that the source of life was in a mind rather than in non-thinking materials or chemical or physical processes. This implies an intelligent, volitional Designer.Trying to put a living thing together using only materials, without information, is like soldering wires together to try to produce a computer program. Just as a robot without a program is no better than a statue, so a cell containing its biotic chemicals without its instructions—its DNA—would be no better than disorganized ‘primordial soup’. It’s no wonder that Craig Venter produced his ‘synthetic life’ using the information and reading machinery of previously living cells. 4A living cell lives, not because it contains bio-chemicals, but because it can carry out its encoded instructions for life processes—processes for making and deploying those bio-chemicals. Thus, a living cell lives on information; information necessarily conceived in the mind of its designer, before life began. First there is information, and then there is life. Cell systems—what’s really under the hood continues to drop jaws By Brian Thomas Two 2009 papers summarized recent discoveries of utterly unforeseen intricacy, adaptability, robustness and precision in regulating gene expression, even in “simple” cells. Gene expression in eukaryotic cells I conservatively counted 24 recently discovered mechanisms that help regulate gene expression in eukaryotic cells, as reviewed by Moore and Proudfoot.1 Here are just a few of them. Figure 1. Widely regarded as the simplest genome, Mycoplasma gene expression is instead far more complicated than expected. It performs functions that had been considered the sole domain of higher eukaryotes. For example, DNA is transcribed in both the sense and antisense directions, indicating that valuable genetic information is double-stacked. RNA transcripts undergo post-translational modifications, single

enzymes have more than one application, and when certain metabolic breakdowns occur, the cell is able to formulate a workaround solution. Illustration after. sciencemag.orgChromatin is not loosely wadded DNA inside cellular nuclei. Instead, it is very precisely organized, with specific portions dynamically looped outward. Each loop is associated with a separate nuclear pore, and can retract to a storage position when appropriate. Robust and efficient machinery ensures that the correct portions of chromatin are unspooled from nearer the center of the nucleus to an appropriate nuclear pore. Each pore is extremely active, with a host of interacting regulatory RNA’s, proteins, and ribonucleoproteins. 2 These send and receive communications from and toward the farthest ends of the RNA and protein manufacturing processes.RNA Polymerase does not typically transcribe DNA in fluid space, but is attached to a cadre of proteins associated with each nuclear pore. This way, the rapidly emerging RNA transcript is already proximal to the pore, through which much of it will exit to the cytoplasm. Further, cell biologists have determined that the first copy of a transcript is like a practice run. This first, rough draft RNA transcript either serves as a quality control run, so that its integrity is ensured prior to full manufacture and export from the nucleus, as a primer for the total set of transcript processing machinery to be properly set, as a chemical communicator providing information to downstream processes, or all three. Warming up for transcription In addition, extracellular messages are transferred from the cell membrane to the nuclear pore sites via biochemical cascades, and these influence whether or not a gene region will switch from being transcribed into these rough ‘abortive transcripts’, or into full-length, properly marked and exported transcripts. It appears that transcription machinery is constantly transcribing in an ‘idle’ mode, but when the correct switches are tripped, the machinery fully engages. In full production mode, RNA transcripts often become marked for translation to proteins. Some of the switching messengers are proteins that are temporarily restrained by other proteins, which in turn can release them upon detection of certain cell signals carried by yet more precisely interacting biochemicals. For example, even sugar moieties riding on proteins have been found to act as a “safety switch that regulates the microswitches” which fine tune protein expression during cell division.3 Full-on eukaryotic transcription runs super-fast When all systems are ‘go’, transcription proceeds with “fully processive elongation of the full body of the gene.” 1 Inside the nucleus, the relevant DNA is pulled, like a loop of magnetic tape, across a nuclear pore. Some of the proteins involved in this action are named Set1PAF, Spt6, FACT, Chd1, along with other histone proteins. This way, the emerging transcript is under the constant watchful attention of a wide array of sensory, quality control, marking, and transporting machinery, all kept near the pore by precise chemical interactions specified by exactly arranged biomolecular sizes, shapes, charges, and polarities.It was known that transcripts in eukaryotic cells undergo cut-and-pasting as well as splicing. It is now known that this occurs simultaneously with manufacture, and requires a separate host of proteins. However, those pre-mRNA splicing proteins directly interact with the RNA polymerase assemblage, which all works together to react to ‘pause-sites’ in the gene it is transcribing. RNA polymerase acts like a ‘molecular juggernaut’,1 streaming RNA’s out as though through a jet engine. It must be slowed down in order for cutting and splicing machinery to have opportunity to insert. Since not all DNA pause sites become RNA cut sites, and since the alternative combinations of cut and spliced mRNA transcripts can specify a wide variety of regulatory or catalytic RNA’s and proteins from just one ‘gene’, 4 it is apparent that somehow precise communication occurs to discern which pause sites will result in cuts. In yeast, a model eukaryote, the THO/TREX protein complex serves three roles: one in transcription, one in “transcriptdependent recombination”, and one in mRNA export.1 And it does these while in constant communication with machine parts that are involved in transcript initiation as well as parts involved in slowing and stopping transcription. It is therefore one of many proteins and protein complexes that are being discovered with multiple functions—a clear sign of elegant engineering. Process flow management in translation The emerging RNA transcript then gets labeled with specific protein markers. The markers had already been gathered to the nuclear pore site, and are presented to the nascent transcript just inside the nucleus. The immediacy of labeling thus is vital. It guards against the dangers of having naked RNAs in the nucleus, as described below. The markers, too, serve multiple purposes. The more splices in the transcript, the more markers are attached, and this eventually causes more efficient translation because a transcript thus bedecked is more likely to have some surface exposed to cytoplasmic proteins vital to translation. The markers also signal watchdog nuclear pore proteins to expedite the transcript’s export.These same watchdog proteins also serve to prevent naked transcripts from re-entering the nucleus. This is vital, for bits of RNA naturally anneal to unzipped DNA. If this happened, it would quickly create havoc in the nucleus by both generating mutations and gumming up the many nuclear processes that depend on accurate DNA recognition, clamping, spooling, unwinding, and other processes.After export, the cytoplasmic machinery links each transcript to other machines. Some of these shepherd the transcript toward a ribosome. Each time a transcript has been thus shepherded, some of its markers are removed, with most being lost after its first round of translation. Eventually the transcript becomes naked and difficult for translational machinery to detect, and subject to degradation. In this way, the freshest and highest quality transcripts are by far most translated by the ribosome. Eukaryotic gene expression is astonishing Effective quality control mechanisms constantly cull corrupt transcripts. For example, if a transcript did not have the correct signal sequence attached when it was first formed, due to gene mutation or an error in processing, the compromised molecule would have been recognized immediately at the nuclear pore, and degraded by RNase enzymes. This ensures that downstream processes are not gummed up with useless transcripts. Quality control is critical to forming the correct products in the needed amounts, and at appropriate paces.Other systems produce a stockpile of quality transcripts in strategic pockets within the cytoplasm. This way, there can be “a tightly controlled burst of the desired [protein] product.”1There is no indication that the discovery pace of more mind-bogglingly brilliant cell processes will slow down anytime soon. If none of the above made sense, then let the reader be edified by the glowing research summary:“At every point along the way, multifunctional proteins and [ribonucleoprotein] complexes facilitate communication between upstream and downstream steps, providing both feedforward and information essential for proper coordination of what can only be described as an intricate and astonishing web of regulation.”1 The ‘simple’ Mycoplasma Mycoplasma pneumoniae bacteria, long considered the simplest prokaryote, can no longer be described thus. It is a parasitic bacterium that (M. pneumonia causes walking pneumonia) has a reduced genome size. It relies on its host for certain nutrients that its ancestors apparently were able to manufacture. Thus, it has undergone significant genomic decay. How Mycoplasma bacteria really work The authors of a paper in Science endeavored to investigate “how a cell actually accomplishes” necessary processes using the most basic subject of study.5 But they ran into a juggernaut of layered information-rich complexity that inspired their assessment: “Together, these findings suggest the presence of a highly structured, multifaceted regulatory machinery, which is unexpected because bacteria with small genomes contain relatively few transcription factors … revealing that there is no

such a thing as a ‘simple’ bacterium.”5Specifically, evolutionists Ochman and Raghavan cited research that found in many cases the ‘sense’ strand of protein-coding genes is transcribed, the complementary or ‘anti-sense’ strand is also transcribed. The resulting ‘sense mRNA’ is eventually translated to protein, and the resulting ‘antisense mRNA’ binds to the sense mRNA to make a double stranded RNA. This slows its path toward translation, and is thus an important speed regulator. This was previously only known to occur in eukaryotes. Mycoplasma cells have eukaryotic complexity In other experiments, different environmental growth conditions caused different lengths and segments of genomic DNA to become transcribed. This implies a suite of chemical communication cascades from the cell wall inward, as well as the ability to make alternate products from one gene. This, too, was a surprise, only known in eukaryotes.Like eukaryotic cells, these ‘simplest’ among prokaryotes have multifunctional proteins which can be used in different metabolic pathways as backup machines. Other data strongly suggests that newly manufactured proteins can be altered by other cellular machinery. Termed ‘post-translational modification’, this was taught dogmatically in my 1998 graduate biochemistry courses as exclusive to eukaryotes.Also shocking was the discovery that over 90% of Mycoplasma proteins are involved in protein complexes, again like eukaryotes. Another genome-wide survey found indirect evidence of tight gene expression regulation, but nobody yet knows the mechanism for it.They finally argue that because Mycoplasma is still alive even after such reduction in quality and quantity of its genome, it must have “an underlying eukaryote-like cellular organization replete with intricate regulatory networks and innovative pathways.”5 Where did Mycoplasma get all this in the first place? These authors then bravely ask, “How did these remarkable layers of gene regulation and the highly promiscuous [multifunctional] behavior of proteins in M. pneumoniae arise?”4 But they instead explain that:“ … the reduced efficacy of selection that operates on the genomes of host-dependent bacteria … reductions in long-term effective population size [from the bottleneck that occurred when the bacteria first became host-dependent, and] the accumulation and fixation of deleterious mutations in seemingly beneficial genes due to genetic drift, [together cause a] reducing genome size.” 5If selection, bottlenecks, and mutations only reduced the genome, then these processes are no help at all. What in nature expanded the genome with ingeniously useful data that the remarkably robust yet genomically truncated Mycoplasma retains plenty of? Conclusion At every level, scientists have uncovered more information. That information takes the form of three-dimensional shapes, electronic and charge configurations, as well as raw coding sequence information. Communication pathways, routines and subroutines, prioritizing, quality control, and process regulation plans are all stunningly effective and strikingly small.More indepth knowledge of these fantastically complicated cell features demands greater faith from naturalists in the belief that laws of chemistry built cells. The more informational structures that are found, the greater the gap between the organization in living system parts and the disorganization found in nonliving chemicals.A reminder of some inferences about information would seem appropriate here. First, wherever precise regulation of processes due to expertly engineered machines and codes are seen coming into existence, they always comes from persons. Stated negatively, these machines and codes are never observed to originate from natural laws. Therefore, it is most parsimonious to infer that wherever similar machines, processes, and codes are found, they, too, were not derived by nature, but instead by a person or persons.Second,“ … like spoken languages, biological language is irreducibly complex and yet without physical substance. It comes complete with symbols, meanings for those symbols, and a grammatical structure for their interpretation. Remove any one of these three fundamental features, and the informational system is lost. Physics has nothing to do with symbols or grammar, and therefore nothing to do with the origin of life, which cannot exist without its coded information.” 6If run-of-the-mill information always comes from a mind, then this cellular information, being extraordinary, came from a mastermind. Transposon amplification in rapid intrabaraminic diversification by Evan Loo Shan Transposons are wide-spread mobile genetic elements that make up a huge part of the genomes of species. They are so named because of their ability to jump from one place in the genome to another. Often, they are given whimsical names, such as gypsy, Mariner, Tourist, or Pack-MULEs, which reflect their mobility. Barbara McClintock discovered the existence of these elements after witnessing the phenotypical change they brought about after jumping around in the maize genome. Due to evolutionary bias, transposons have generally been regarded as parasitic “junk DNA”, using the host’s genetic machinery to propagate. However, the actual functionality, diversity, and high abundance of transposons justify a revision of this viewpoint. Such rapid transposon accumulation puts the mechanisms for rapid speciation (given a recent creation and subsequent Flood-induced genetic bottleneck) into a new perspective, and may lead to a further development of a scientific basis for baraminological research. This paper deals with the distribution and dispersal of transposons in the light of evolutionary models as well as a creationist reinterpretion. Some calculations of transposition rates are given which recent creation and rapid intrabaraminic variation. The importance of transposons is discussed in regard to mapping baramin life-histories. Transposons in general Table 1. Basic types of human transposons In the higher species (eukaryotes), two basic types of transposons can be distinguished: Class I and Class II. Class I transposons replicate through an RNA intermediate, and are therefore called retrotransposons, and end in sequences called long terminal repeats (LTRs). Class I transposons are located in areas where recombination between genes takes place. of Class I are short and long interspersed nuclear elements (called SINEs and LINEs, respectively); these make up a major part of the repetitive elements present in eukaryotic genomes. Class I transposons are usually located further away from the coding region of genes than the Class II transposons. LINEs can contain ORFs (open reading frames) from a few genes, such as reverse transcriptase or integrase, and are capable of transposing autonomously. They end up in LTRs. SINEs are much shorter elements which do not contain any coding sequences. Alu elements are examples of SINEs.Class II, or DNA transposons replicate autonomously, using

their own genes and proteins to copy their own sequences, and insert themselves into other parts of the genome. In this way they are capable of moving parts of the host’s genome along within themselves. They are located closer to genes (for example MITE sequences in cereal genomes) as opposed to Class I type transposons. Class II transposons can be divided into many different families and subfamilies, and bear names such as Activator, Mutator, or Helitron. Class II transposons are present in a few hundred or thousand copies per genome at most, and are sparser than Class I type transposons. 15 Basic types of transposon elements are depicted in table 1. Why transposons are a problem for evolutionary theory Introductory thoughts on the effects of transposons on the genome The naturalistic view of life assumes that the first “simple” genome of a living organism emerged from a chemical soup. Through selectable mutations accumulated over several billion years, this original genome evolved into all the intricate genomes we observe today. However, genome research in the past 10 years presents a picture of a far more dynamic genome that has been shaped and sculpted to a significant degree by transposable elements. 6 We can see in table 2 that transposons make up a large percent of the genomes of different organisms. Table 2. Genome sizes and content of repetitive elements in some well-known organisms. For example, evolutionists claim the maize genome acquired virtually all retrotransposons (which make up about 80% of the maize genome: see table 1) in the last 6 million years.3 This statement is quite profound. First, it raises a question related to species stability. If it really took 6 million years for the maize genome to quadruplicate in size, then how could acquiring such a great quantity of genetic material keep maize the same species for such a long time? Maize was derived from teosinte, a plant hardly recognizable as modern maize.Teosinte was domesticated by the Amerindians over the past few thousand years, making rapid diversification by intelligent selection a more plausible explanation as to how the maize genome changed in such a way.Evolutionists contend that, as in the case of transcription factor binding sites, random base substitutions can cause the appearance and disappearance of regulatory sequence elements. With transposons inflating the genome in such a manner, large chunks of raw genetic material would appear out of which new kinds of genes or other genetic elements could be formed. This is similar to howArabidopsis is supposed to have acquired a major part of its genes. 60% of BAC sequences covering 80% of the Arabidopsis genome were found to contain duplicated segments, but yet it remained the same species. 7Since it is commonly accepted that transposons rapidly spread within the genome after colonizing the germ line (when the delicate developmental program is active), this is strongly discouraging to the idea that transposons are only harmful in their phenotypic effect. Actually, some functions of transposons can be assigned to repetitive elements; for example, certain structural functions and recombination sites, as well as genome rearrangement through transpositioning of genetic elements. Transposons can also react to abiotic stresses by regulating expression patterns of genes through cis-regulatory elements inserted by moving transposons. 8 Other functional examples include induction of alternative splicing, or changing the expression patterns in certain tissues or even the subcellular location of proteins.9 It looks as though researchers will have to rethink the “junk DNA” theory 10).The concept that transposon-induced gene inflation is not only not producing junk DNA, but that it is also beneficial and strategic could be taken a step further. An interesting technique for studying the phenotypic effect of multiple genes has been developed in recent years by a Canadian research team involving the synthesis of a mammalian artificial chromosome (MAC) construct. It has been shown that MAC constructs persisted stably throughout several mouse generations. The interesting thing here is that even with the MAC carrying a whole array of novel genes (each with a potential to severely affect the phenotype) the mice are expected to remain mice. The researchers do not predict that they will evolve into a new species! 11,12Lacking observational evidence, evolutionists can always fall back on the argument that such acquisitions of raw genetic material may indeed give rise to new species and claim that “ … the rice genome would be, in effect, ‘the wheat genome without the repetitive sequences’.”3This implies that changes in the transposon content are sufficient to give rise to new species. However, this would still not answer how the coding regions of the wheat/rice genome came about; it only deals with regulatory or contextual changes.13-15 A study done by Kalendar et al. dealing with the copia-type BARE-1 retrotransposon in barley shows that transposable elements can spread rapidly in response to microclimatic divergence. 16 In this study, the copy numbers of BARE-1 ranged from 8,300 to 22,100 per haploid barley genome within a 400 m long gorge at Evolution Canyon in Mount Carmel, Israel. Such changes surely could not have taken millions of years because the wild barley that was studied exhibited retrotransposon replicative spread variability assumed to be correlated to sudden stress due to microclimate variations within the gorge and other climatic factors. Figure 1. Model of transposon accumulation. The equation used for calculating the number of transposons as a function of time is . Evolutionary models dealing with the rate of transposition state that the distribution of transposons within host genomes can take place in short “bursts”, the accumulative effect of which could eventually lead to “genomic obesity”. Afterward, genetic

material could be slowly lost (although the mechanism remains unclear). It is reasonable to propose that unequal cross-over recombinations or deletions of different sizes may be the underlying mechanism. If so, larger genomes could be expected to contain transposons younger than those in smaller genomes, because the latter could already be diminished in size due to deletions.A study by SanMiguel in 1998 dealing with a number of plant species (such as Arabidopsis, rice, lotus, sorghum, maize, barley and diploid wheat) showed that even by evolutionary standards the studied retrotransposons are all thought to be about the same age. 17 It should be noted, however, that the age of the LTR sequences is calculated by the gammacorrected Kimura 2 method and depends on the substitution rate of nucleotides in the LTR sequences. In this model, the age of an LTR sequence is calculated from the substitution rate, but the substitution rate is based on the estimated time to the divergence between the species. It is an obvious case of circular reasoning. 17,18-23The number of LTR sequences in barley was also shown to correlate with altitude and temperature. 24Parallel to this, the differences in the repetitive content of the wheat/rice genome could shed light on how intrabaraminic variation could occur, as these two species belong to a single holobaramin.25Considering these observations, it is clear that a mechanism to induce rapid variation makes more sense in a creationist framework (where new species arise almost instantly) than in the evolutionary model (where it supposedly takes hundreds of thousands of years for novel species to arise).Consequently, it would be a stretch of the imagination that different species persisted for millions of years without having their genomes affected. For example, genome size variation has been observed within the progeny of Helianthus annuus, where the difference in genome size was 14.7%. This would mean 441 Mb (which is larger than the genome of rice itself!) of the 3,000 Mb genome of sunflower. 26 With many thousands of copies of transposons within the genome, genomes should have grown quite quickly during a very short period relative to the evolutionary timescale. Contrary to this, evolutionists estimate that according to gene loss models, it would take around 1.5 billion years for maize to get rid of the same amount of this excess genetic material. 27 Model of transposon accumulation in genomes Transposons are capable of adding large tracts of DNA to the genome, and it would be of great importance to formulate a mathematical model describing the rate of transposon amplification within a genome. The model presented below is completely hypothetical in nature. Research is required to elucidate the exact way in which transposons accumulate and may validate or reject the proposed model.Since the numbers of new transposons which arise within the genome are proportional to the number of transposons capable of replicating themselves, we may say that That is, the rate of spread of transposons n’(t) within the genome is proportional to the function f(t) of the number of transposons n(t)capable of replicating after t transposition events. From this we can deduce that

where n(t) is the number of transposons after t transposition events, C’ is a constant, and F(t) is the primitive function of the function f(t)which is characteristic of the rate of transposon accumulation within the genome. From this we may deduce one of two possible things. If the primitive function F(t) of f(t) is constant, that is meaning that the number of transposons in a genome after t transpositions grows exponentially. If so, it would lead to an exponential explosion relatively quickly. This would lend to the creationist model, which predicts large numbers of transposons accumulating in genomes only recently (that is, with a short period of time allowed for accumulation to occur). It would also be in line with evidence from other fields of science that the recent creation/worldwide Flood model (for example: high mutation rates are observed, yet the number of mutations that have occurred since mitochondrial Eve is too small if we assume long ages; also extremely high rates of radioactive decay are suggested by the creationist RATE team).28,29In the evolutionary framework, the model implies a runaway / out of control accumulation of transposons in the genome a long time ago. Since we see genomes still intact, this means that runaway transposon accumulation has not yet occurred in the relatively short time since creation.However, if the function f(t) is not constant, then the rate of transposon accumulation may change during time. A further investigation of the function f(t) reveals important characteristics about the dynamics of transposon accumulation. We know that the lower and upper bounds of the function f(t) are 0 and ln 2, respectively: The lower bound 0 would mean a complete stasis in the accumulation of transposons within the genome, resulting in no increase; i.e. no transposition and/or amplification. Therefore, f(t) is always greater than zero. Since after any t number of transposition events the maximum number of transposons within the genome is n(t) = 2t , then

If we take the function f(t) to decay exponentially, we get However, when the variable t (= transposition events) increases, e-gt/g decreases and tends to decline to 0. The remaining function n(t) = eht, however, still describes an exponential growth of transposon copy acquisition. However, if in equation 6 h is equal to 0, we arrive at an equation for a sigmoidal curve. According to this model, transposon accumulation lags off after an exponential burst in a later phase. This means that after an initial burst phase of transposon accumulation, a lag phase follows, characterized by a shutdown of transposon activity. This is noteworthy, because it fits with certain aspects of the AGEing hypothesis of Todd Wood, 30,31 who contends that genetic rearrangement occurred during a certain period of time after the Flood in the genomes of organisms to allow the rapid phenotypic change necessary for

adaptive dispersal via genetic variation.In figure 1 we can see a hypothetical situation where the number of transposons is calculated as a function of transposition events. The equation n(t) = 100000 •e–e–1 (if we assume that g = 1) gives a sigmoidal curve of the form n(t) = a •e–e–1, where e–e–1 ranges from 0 to 1. Therefore, a would denote the maximum number of transposons in the genome.The obvious question is that if the number of transposons has already reached a plateau, then how long has this plateau condition persisted? Evolutionists could argue that it has continued for an indefinitely long time. This would mean that all transposon activity has had ample time to shut down completely. Contrary to this, some transposons have been shown to be active in a number of organisms, such as humans. 27,32However, very few plant retrotransposons have been shown to be transcriptionally active (one is BARE-1 in barley). 1,8,33 MITE sequences in plants have not been shown to excise, except for the rice mPing element, also indicative of their low transposase activity.1,9This would mean that we are presently at the top shoulder of the sigmoidal curve, where transposon activity is slowly dying out. This is marked by the presence of many defective transposon sequences within genomes. The importance of transposons in baraminology studies Many repetitive sequences are either species or genera specific in bacteria, plants and animals, and are thought to promote speciation.34 This is good news for baraminologists, since transposons can therefore be used as a sort of signature to identify of a baramin. This would mean that transposons could be used as a diagnostic tool to determine whether or not a species is a member of a given baramin. Figure 2. Average number of LTR sequences in thousands per barley genome. The average number of LTR sequences is shown in the H, Y and I genomes of barley for species listed in table 3. The number of LTR sequences for tetraploid genomes was divided by two. The data was taken from Vicient et al., ref. 33. Data for genome X was not used because it was only from a single species. By counting the number of the various transposons in the genomes of different species that belong to the same baramin, we can get a picture of the life history of a given baramin. In other words, by following the change in the number of a given transposable element, we can estimate which species originated from a particular baranome (see refs. 14 and 15). For example, particular MITE sequences can be found at the same position in the genomes of different plant genomes because of their relative stability.1 Therefore MITEs can be used as landmark or reference sequences to mark the inflation or change of a certain baranome. Also, the BARE-1 transposon element is widespread and specifically found in a number of grass species (such as wheat, rye and oats), each with slightly diverged sequence, whereas it is absent in other species. This may indicate that BARE-1 is a baramin-specific transpoable element.24 A similar diagnostic transposon element is the RIRE-1 element in rice.1The number of BARE-1 elements in a genome can be approximated by the number of LTR, in and rt sequences within the genome. According to Vicient et al.,33 the number of copies of these element decreases in the Y, H and X genomes of different barley species (Hordeum spp.) as compared to the I genome of barley, and may reflect the spreading of the transposon during the life history of the Hordeum monobaramin (see figure 2). In the genus Hordeum, the I genome is the most representative of barley, and contains the most sequences. The Y, H and X genomes are characteristic of other barley species, and contain a decreasing number of these elements, Y having the highest. Furthermore, Vicient et al. also found that genome size was negatively correlated (r = –0.593) to genetic distance from barley, meaning that the genomes of the Hordeum species may have inflated parallel to their acquisition of transposable elements. Table 3. Number of LTR sequences in different species of barley. Table 3 is a list of barley species with different types of genomes (H, Y and I) and the 1,000s of LTR sequences they contain, which are supposedly equal to the number of BARE-1 transposons in the genome. In addition, table 3 shows that barley genomes roughly fall into three groups: group I contains the highest number of LTR sequences; group Y has an intermediate number of LTR sequences; and group H has the lowest number.

According to mainstream evolutionists, the wheat genome equals the rice genome but without the repetitive elements. Since transposon activity adds large tracts of DNA to the genomes of organisms, and because they do not easily back-mutate, transposons may be a tool to track back the “life-history” of baramins. For the rice and wheat genomes, which belong to the same baramin,30 it would be an interesting endeavour to map species relationship as a function of transposon content. Figure 3. Model of the life history of baramins following transposon amplification. According to this model, genome size expands in time after Creation/Flood along with transposon content. The archebaramin is at the base of the baraminic tree, and represents the original genome with little or no transposon content. At different intervals, transposon invasion and amplification can occur, causing large-scale intrabaraminic diversification (represented by the large branches). At different branch points, monobaraminic variation can occur, as seen in the genus Hordeum.33In this respect it is interesting to determine whether species with the same gene content and colinearity all classify as of the same holobaramin. For example, microcolinearity has been shown to exist between certain parts of the genome in rice and of the tribeTriticeae, even though the distance between genes may be up to at least sevenfold.35Similarly, species with about the same transposon content may be of the same monobaramin, such as species in the genus Hordeum, which show intrabaraminic (and evenintraspecies) variation. The nature and degree of variation would obviously be helpful in determining ancestry. In contrast, species with the same gene colinearity but with different transposon content could be of different monobaramins. This is because different numbers of transposon would have accumulated after speciation occurred.Because of the widespread dispersion and conserved LTR termini, molecular studies such as REMAP (Retrotransposon-Microsatellite Amplification Polymorphism) and IRAP (InterRetrotransposon Amplified Polymorphism) may be useful tools in tracking the spread of transposons within baramins.36 Given their large difference in genome size, rice and wheat could be of different monobaramins. Moreover, species in a given baramin with small genome size could be of the archebaramin, representing the original state of the baranome before the amplification process started. This model is presented in figure 3.The life history of a baramin undergoing transposon amplification is analogous to an uninflated balloon on which a number of dots/bars are drawn and connected to each other by lines (see figure 4). The dots represent different genes, whereas the lines represent the intergenic spaces. Inflating the balloon is analogous to an increase in transposon content: The further the dots move from each other on the surface of the balloon, the greater the length of the intergenic regions become.This is in accord with a study in rice, sorghum, and maize, which showed significant differences in a certain segment of the Adh1-F locus between the three species, although the genes in this region were mainly colinear. In this case, homologs of the Adh1 and u22 genes were 50 kbp apart in sorghum, but 120 kbp apart in the larger maize genome. The gene density in this region was approximately one gene per 9–12 kbp in rice and sorghum, whereas the density was one per 30–80 kbp in maize, which shows intrabaraminic variation due to transposon amplification. 37 This shows that determination of gene colinearity in related species such as cereals could be of great help in exploring the boundaries of baraminology.38,39 Furthermore, microcolinearity of genes is proof of a young age for plant species since, if they really are millions of years old according to evolution, then the order of their genes should have become scrambled past recognition. Figure 4. Genome model of gene colinearity and retrotransposon markering. In this model, six species are represented by six concentric circles of different line thicknesses. The six circles represent chromosomes with genes at specific intervals. The first five chromosomes starting from the centre of the circles, represent species belonging to a specific baramin (e.g. the grasses), while the outer circle represents a genome belonging to another baramin (e.g.Arabidopsis). Here we can see that genes (black dots/bars) are colinear in the case of the first five circles/chromosomes/species, since they belong to the same holobaramin. The concentricity of the circles also illustrates baramin-specific transposon amplification. We can see that the 2nd and 3rd circles contain three elements (grey bars) denoting specific transposon elements that are monobaraminspecific. The 4thand 5th circles contain light grey elements that are also monobaraminspecific.When gene colinearity was studied between Arabidopsis (Brassicaceae) and rice, it was found that ESTs (expressed sequence tags) from rice had very low homology with genes on the chromosomes of Arabidopsis, even at the protein level. This was interpreted by our evolutionary friends to indicate that the genomes of the both plants had “eroded” too much for a successful comparison. In other words, gene colinearity and order were unrecognizable.40In a separate study of rice, wheat and Arabidopsis, researchers found that out of 46 types of rice copia elements, only two (Adena and Osr8) were present inArabidopsis, and even the Osr8 element was thought to be in silicocontamination.41 Similarly, a computer analysis of Tourist and Stowaway rice short inverted-repeat elements in the non-coding regions of 413 Arabidopsisgenes failed to identify a single repeat longer than 30 bp. 9 It is most interesting to note that Moore et al. have found that the genomes of a number of grass species can even be circularized (formed into a circle) around one another and divided into 19 colinear rice

linkage segments that are all representative of the ancestral grass genome (in our case the genome of thearchebaramin).42 This mode of representation of the genomes of a single monobaramin may even be adapted to all baraminology.Furthermore, when comparing mammalian and plant transposons, we find that SINEs and LINEs are more common to mammalian genomes, whereas MITEs and LTR retrotransposons are more common to plant genomes. We can take these transposons as marker elements common to the mammalian and plant apobaramins, respectively. These would be examples of baramin-specific transposable element markers.Creationists could interpret this observation to the notion that colinearity of genes is evidence of interbaraminic relationships; for example, lack of colinearity of genes between Arabidopsis and rice demonstrates the discontinuity between the monocot grasses and dicot Brassicaceae, thereby asg these two plant groups to separate baramins. Conclusion The process of genome expansion by means of transposable elements as observed in several plant species shows that genomes can be moulded quite dynamically without crossing evolutionary boundaries. Contrary to mainstream assumptions, the expansion of genomes via transposon amplification is much faster than anticipated by the evolutionary model. Neither is the type of speciation of the kind that is required to evolve from microbe to man. In addition, the rapid spread of transposable elements within these genomes shows that genomes are recent. Variation induced by accumulation of transposable elements and fast-track speciation events are very rapid phenomena and fit nicely with the young age timescale. A large number of transposable elements also give to the Wood model of rapid baraminic diversification after the Flood followed by subsequent widespread deactivation. Furthermore, the distribution of certain transposable elements shows that they can be used as marker elements in baraminology studies. Considering the increasing body of evidence that transposable elements induce variation in baranomes, and may even be involved in post-Flood speciation events, they should be renamed variation-inducing genetic elements (VIGEs; as proposed by Terborg, ref. 14). Glossary BAC sequence: bacterial artificial clone. Copia element: a common type of retrotransposon with retrovirus-like sequence organization. EST: expressed sequence tags used to determine gene transcripts. Usually short in length, covering only part of a gene. gag/prt/pol/env a number of proteins coded for by Class II type transposons and which are necessary for proteins: transposition. Gamma-corrected a substitution model for calculating genetic distances between DNA sequences. Kimura two method: in sequence: a domain within the BARE-1 element encoding the integrase protein and needed for replication. LTR: long terminal repeat—a type of sequence belonging to LINEs and involved in the insertion of the transposon. MITE: miniature inverted-repeat transposable element: short transposon of several hundred bps which are restricted in transposition. May contain genetic regulator elements. ORF: open reading frame—that part of a gene which can be potentially translated into peptides/proteins. rt sequence: a domain within the BARE-1 element encoding the reverse transcriptase protein and needed for replication. Myriad mechanisms of Gene regulation by Alex Williams The 2007 ENCODE pilot study report on the human genome showed astonishing complexity in the structure of the information stored on, in and around the DNA molecule. 1 Now come two new studies that show astonishing complexity in the function of the information copying and usage systems in cells.

Transcription (copying) of information from a DNA molecule onto a messenger RNA molecule is carried out by a molecular machine called RNA polymerase (RNAP). Initiation of the transcription process (schematic A) is followed by the engagement of the transcription machinery resulting in the elongation of the RNA strand (schematic B). A pause during this process helps to regulate the rate of copying. A molecular model of the real system is shown (C). The DNA is shown as the twin coils of rounded blue bead-like nucleotides protruding at top and bottom, the RNAP is shown as the long purple spaghetti-like molecular machinery, and the RNA transcript is shown in green emerging from the centre of the RNAP. (Images from www.wikipedia.org) Ingenious transcripts The first step in using the complex information stored on the DNA molecule is to transcribe (copy) it onto a messenger RNA molecule (mRNA). Transcription is carried out by a molecular machine called RNA polymerase (RNAP) which attaches to the DNA strand at the START end of a gene and works its way, nucleotide by nucleotide, to the STOP end, producing an exact complimentary copy of each nucleotide at each step in the chain. More than one RNAP can work on a particular gene at any one time, and a recent study by an international team working on the mechanics of transcription found that in a

culture of human cells there were, on average, two RNAPs per gene. 2The rate of transcription often needs to vary—for example, in response to environmental stress or a fight-or-flight threat situation—and one might think that the best way to increase the rate would be to increase either the number of copying machines working on the gene, or to increase the speed at which the machines progress along the DNA. Surprisingly, cells use neither of these options.In a normal metabolic state, RNAP copying seems stunningly inefficient. Only about 1 in 90 transcripts produce mature messenger RNA; the majority are aborted. Furthermore, the measured step-by-step transcription rate goes about twice as fast as previously measured for whole transcript production because along the way there are quite long pauses.There are three main phases in the transcription process. First, a region upstream of the transcription site called the promoter is activated. Second, the promoter acts upon an adjacent region to initiate the formation of the transcription machinery. Third, when the transcription machinery goes into action, it is said to be engaged in the copying process.About a third of the transcripts can be found in each of these three stages at any one time. 3 The average residence time in each stage was 6 seconds for the promoter, 54 seconds for initiation, 517 seconds for engagement, and pause times ranged from 204 to 307 seconds. At any one time, about a quarter of all transcripts were paused. A single gene produced a mature RNA transcript every 31 to 63 seconds.Because of the long pauses in the transcription process, there is a ‘traffic pile-up’ in the transcription queue. The authors likened it to a Sunday driver going slowly along a country road, with cars lined up for miles behind. This may seem to be an awkward and inefficient way to proceed, but the authors suggest that there may be method in this apparent madness.The speed at which the RNAP can copy is limited by its inherent enzymatic properties, so that leaves only the rate of initiation and the length of the pause time as control points for controlling the rate of mRNA production. By having a very high rate of initiating that is mostly abortive, that then leaves the pause control as the single determinant of copying rate. By having just one control parameter—length of the pause time—the rate of transcript production can be varied almost instantaneously if needed. The authors end the report by saying:‘We therefore expect that future results with endogenous genes [i.e. in living organisms rather than in cell culture], as more sensitive microscopy methods are introduced, will reveal the myriad of controls by which genes are expressed [emphasis added].’2It is not hard to imagine what at least some of these myriad controls might involve. For example, cells normally function at only a fraction of their potential rate and range of operation. This is often referred to as redundancy—having more structure and functional capacity than strictly needed. The so-called ‘inefficiency’ of RNA transcription (only 1 transcript in 90 reaching maturity) may actually be a method of both repression and ready activation. Since the excess capacity in a redundant system is not normally used, it spends most of its time in a repressed state.One of many methods of gene regulation involves small fragments of RNA that bind to the RNA transcript and thus interfere with and prevent its translation into protein. There are many different ways in which this can occur,4 and it is quite possible that the large proportion of aborted RNA strands may act as repressors. On the other hand, when accelerated transcription is required, the rapid rate of transcription initiation can quickly be turned to full use in being carried through to mature RNA production. There is more than enough capacity for acceleration in such a mechanism when compared with the pause-time control rate. The average production rate of mature RNA was 1 every 31 to 63 seconds per gene, while the pause time ranged from 204 to 307 seconds. By turning the pause time down to zero, RNA production could thus be accelerated by 3 to 10 times over the normal rate, well within the 90 to 1 value for aborted initiations.So not only does DNA contain a myriad of information structures, it is also consulted by the cell for that information in a myriad ways. It makes reading a book, or an article like this, pale into insignificance by comparison. Smart thinking Once the information on the DNA molecule has been transcribed onto an RNA molecule, a number of posttranscription processes occur, and then the transcript is translated into protein. Sounds easy? Read on!The human brain is the most complex organ in our body. It is made up of about 100 billion nerve cells (neurons), that each has numerous treelike branches (dendrites). When we learn or something new, a new pathway for thinking is created by a unique pattern of dendrites ing up into a memory circuit. Problem—how to prevent a highly branched dendritic network from ing up with itself and short-circuiting the memory or thought pattern?Researchers approached this problem by studying a simpler system—the development of dendrites in the fruit fly Drosophila melanogaster, which has only about 200,000 neurons in its brain!5 What they discovered was beautifully elegant, surprisingly simple yet mind-bogglingly complex in the execution.6 A particular cell surface protein on the dendrites (called Dscam) is made subtly different in each dendrite so that each one can sense whether the nearby branch it is about to up with is ‘self’ or ‘non-self’. It is similar in concept to the complexes of proteins in flakes of human skin that allow a dog to track the scent of a particular individual human sometimes a day or more after the person has ed by. Except in the dendrite case, it is thought that variations in just the one protein, Dscam, solve the problem.How do you make one protein in a large number of different varieties? The answer is alternative splicing—the RNA transcript is cut and pasted together in slightly different ways to produce proteins that are almost exactly the same, but not quite—just a few amino acid differences. TheDscam gene can potentially generate more than 38,000 closely related trans-membrane proteins that are different enough to be reliably identifiable, but similar enough to function in exactly the same way.Trans-membrane proteins are folded up and down through the membrane, ing up both the outside and the inside of the cell several times.Dscam is thus able to be sensed by other dendrites from the outside, but can be also be used as a signalling molecule to tell the internal workings of the cell whether to go ahead with the connection if it is ‘non-self’, or to stop the connection if the other is part of itself. It doesn’t matter which one of the 38,000 versions a particular dendrite has, as long as it is different from its near neighbours. Easy, once you know how!But just how do you cut and paste a single RNA transcript into 38,000 different but functionally identical proteins? Well, the mechanics are complex and dynamically multi-functional,7 but not yet fully known. We do know, however, that the spliceosome—the machine that does the alternate splicing—is the largest machine in the cell. It consists of about 300 different proteins and several nucleic acids.8 It clearly takes a big machine to do a big job! Vary or perish According to a new theory of how life works at the molecular level, called facilitated variation,9 all the mechanisms of variability—both within an individual organism and between parent and offspring—must be in place before life can function and persist in the face of environmental challenge and change. A purely mechanical kind of life—such as William Paley’s watch found upon a heath—would become extinct the first time a malfunction occurred. But life as we now see it in its vast molecular detail is astonishingly variable. If the new theory is correct, and life without such ingenious built-in mechanisms of variation is not possible, then life itself becomes the greatest testament to creation that the world has ever seen. More marvellous machinery: ‘DNA scrunching’ by Jonathan Sarfati Some of the most startling discoveries in the last few decades have improved our understanding of the amazing complexity of the cell. This includes the world’s tiniest machines. 1 But not only are there machines, but also theirblueprint—the message molecule DNA.2 DNA’s function is to store and transmit genetic information, but it can’t work without many molecular machines. However, as the noted philosopher of science, Sir Karl Popper (1902–1994), commented:‘What makes

the origin of life and of the genetic code a disturbing riddle is this: the genetic code is without any biological function unless it is translated; that is, unless it leads to the synthesis of the proteins whose structure is laid down by the code. But … the machinery by which the cell (at least the non-primitive cell, which is the only one we know) translates the code consists of at least fifty macromolecular components which are themselves coded in the DNA. Thus the code can not be translated except by using certain products of its translation. This constitutes a baffling circle; a really vicious circle, it seems, for any attempt to form a model or theory of the genesis of the genetic code. Figure 1. The ‘scrunching’ model for RNAP–activecentre translocation during abortive initial transcription.5,6 ‘Thus we may be faced with the possibility that the origin of life (like the origin of physics) becomes an impenetrable barrier to science, and a residue to all attempts to reduce biology to chemistry and physics.’3 Transcription tricks Now Richard H. Ebright and his team from Rutgers University have discovered more intricacies in the process of transcription,4 where information from the right part of the DNA is copied onto a strand of messenger RNA (mRNA).5,6 Indeed, it is this mRNA that is translated into proteins in the complex machines known as ribosomes. 7–9DNA is double stranded, so must first be unwound, so that the right strand can be copied onto mRNA, in a sense like a photographic negative. So the machine, called RNA polymerase (RNAP), first locks on to the start of the gene. Ebright and colleagues demonstrated what happens next with two complementary techniques, single-molecule fluorescence resonance energy transfer (FRET)6 and single-molecule DNA nanomanipulation,5 and were able to rule out other ideas of how it works. The next stage is that the anchored RNAP then reels in the DNA—scrunching (figure 1).10 This unwinds the double strand so the messenger RNA copy can be formed off one of them. Also, the unwinding stores energy, just like winding the rubber band of a rubber-band-powered airplane. And just like the toy plane, this energy is eventually released, with the machine then breaking free of its starting point and shooting forward. This also rewinds the unwound DNA (‘unscrunching’) which escapes from the back of the machine.Ebright states that this research should also enable them to develop antibacterial agents that target the bacterial version of this machine.4 Evolutionary conundrum This discovery provides yet more for Popper’s bafflement. The instructions to build RNAP are themselves encoded in the DNA. But the DNA could not be transcribed into the mRNA without the elaborate machinery of RNAP. And this is also an example of irreducible complexity because it would not be able to perform its function unless every feature was working fully. There would be no use being able to dock onto the right spot of the gene and getting stuck there, or unwinding the DNA without being able to wind it back.Furthermore, RNAP uses ATP as an energy source to achieve its feats. And ATP is made by another nano-machine, the ATPase complex, which is a rotary motor.1 This is also coded on the cell’s DNA.Natural selection is no answer, because this means differential reproduction, i.e. fully formed self-reproducing entities that can on the information that codes for their features. But until RNAP is fully formed, the coding would not work at all, being unable to get past first base (pun intended). Thus Darwinian evolution could not even have got off the starting block. The genetic puppeteer by David White Back in 2005 a group of researchers published a landmark study on a question that has long puzzled geneticists: why aren’t identical twins … identical?1 Considering that they have the same DNA sequence in each of their cells, it seems a bit strange that they often possess a number of physical differences, such as different fingerprints, and different susceptibilities to disease. This raises the question: if two people can have identical DNA sequences and yet be so different, is there more to our genetic blueprint than just DNA? The answer is an emphatic ‘yes’! Everyone, it seems, has heard of DNA. But many people are unaware that the DNA code itself is governed by another code, known as the epigenetic code. In fact, so significant is this code that one Science writer said that genes (stretches of DNA) are ‘little more than puppets’, whereas the enzymes controlling this other code are the ‘master puppeteers’.2 (See ‘Another layer of complexity’.)So what did the researchers find? Put simply, identical twins possess the same DNA code, but different epigenetic codes.3 They found that the epigenetic codes of identical twins, though indistinguishable during the early years of life, can diverge markedly as they age. Also, epigenetic differences were greater in identical twins that lived apart and had different lifestyles. Solving medical mysteries Mutations in DNA are often regarded as the chief culprits of disease, but epigenetic errors can have equally devastating effects. Biologists have known since the 1970s that DNA in cancer cells has an unusually high level of methylation, suggesting that crucial genes may be ‘switched off’. 4 ‘Tumour suppressor genes’, as their name suggests, are required for normal development, and several instances have been found where these are ‘switched off’ by methylation—and directly linked to cancer. Alternatively, researchers have noted that cancer genes (oncogenes) can be activated through de-methylation.5However, adding or removing chemical groups can reverse epigenetic changes. So the race is now on to develop drugs that control key epigenetic enzymes. One such drug has already been approved in the US to treat preleukemia.6 And even common dietary components, such as green tea, can prevent or reverse the effects of cancer by inhibiting certain enzymes and reactivating ‘switched off’ genes. 7Cancer research, however, is just the tip of the iceberg. What causes schizophrenia and autism?8 Why are children born through IVF more likely to have epigenetic disorders? 9 These are key questions epigenetic researchers hope to answer. Epigenetics and early development Scientists at Duke University recently managed to radically alter a group of mice without altering one ‘letter’ of their DNA.10 Agouti mice (so-called because they have the agouti gene) are typically yellow, obese and highly susceptible to cancer and type II diabetes. However, this experiment produced mice that were brown, slender and didn’t share their parents’ vulnerability for disease, despite carrying the dominant agouti gene. 11But what makes this transformation so

remarkable is the way it was achieved—simply by feeding the pregnant mothers a methyl-rich diet, which managed to ‘switch off’ the harmful agouti gene! And not only can a mother’s diet profoundly affect gene expression in her children but also her grandchildren and possibly succeeding generations after that.12 As one writer quipped, ‘you are what your grandmother ate’.13The fact that a mother’s diet during pregnancy can impact the epigenome of her grandchildren may explain why human populations that suffer famine can continue to see health problems in well-nourished future generations.14 Moreover, some have suggested that the obesity epidemic in some western countries may partly be due to the lifestyles and nutrition of past generations.15 Cloning conundrums When Dolly the Sheep was cloned over a decade ago, many believed that cloning animals would soon be easy and routine. However, progress has been frustratingly slow, as scientists have realized that the epigenetic code is far less amenable to cloning than the DNA code. Since the epigenetic profile of the DNA changes over time, the epigenome of a 6-year-old sheep is very different from that required just after fertilisation. Consequently, the egg has to erase the DNA’s epigenetic profile, and ‘reprogram’ it, appropriately. Dolly’s creator commented, ‘When you think about what we’re asking the egg to do for us, in a way, I think we should still be surprised that cloning works at all’.16 Did epigenetics evolve? The core histone proteins that package DNA are possessed by anything ‘higher’ than bacteria on the evolutionary ‘tree of life’. Therefore, many believe that the histone code has been regulating gene expression for ‘at least’ 2.7 billion years, when the first cells with an organized nucleus supposedly evolved.17 But just because ‘higher life forms’ package their DNA in much the same way, does not necessarily mean they all descended from a common ancestor. Even though an architect may design totally different structures, on closer inspection, many of the concepts and materials used to build them would be similar. So why can’t the ‘architect of life’ do the same? 18The famous evolutionary biologist, Theodosius Dobzhansky, once claimed that ‘Nothing in biology makes sense except in the light of evolution’. If this statement were true, you’d expect that unravelling the complexities of epigenetic control would rely strongly on the ‘light of evolution’. But the opposite seems to be the case. As one researcher candidly itted:‘While the role of epigenetic inheritance in development is becoming a major subject of biological research, the study of its implications for evolution is lagging far behind’ 19 [emphasis mine].So here we have yet another example where biological research has flourished, without any need for evolutionary belief or speculation. The big picture Referring to the DNA code, Australian physicist Paul Davies has stated that ‘The key question … is how this ingenious system of coding emerged?’20 But even though he regards it as ‘ingenious’—and openly confesses that a naturalistic origin remains a mystery—the idea that this code and the complex messages it communicates originated with an intelligent source isn’t even considered.But now that we know DNA has another layer of coded instructions, and thus another layer of complexity, will more scientists attribute this to an intelligent designer? I seriously doubt it. DNA already has impressive credentials, such as holding the title of the world’s most compact information storage system and possessing a remarkable ability to conduct electricity to identify strand breaks. 21 So another layer of complexity isn’t likely to ‘budge’ someone already committed to explaining the universe purely in naturalistic . As world-renowned geneticist, Richard Lewontin declared, ‘we cannot allow a Divine Foot in the door’. 22So don’t be surprised that as future research sheds more light on epigenetics23 many intelligent scientists overlook a conclusion that others consider obvious: the epigenetic code is the handiwork of a supremely intelligent programmer. Another layer of complexity The epigenetic code controls gene expression in two known major ways. The first of these is related to the way DNA is packaged. Inside the cell nucleus, DNA is wrapped around proteins called histones. These proteins can be bunched together tightly or loosely, depending on the chemical environment. This is significant because to utilize the information in DNA, certain proteins need access so they can bind to it. If the histones are packaged too tightly, the DNA can’t be accessed. It’s a bit like arriving at the library after closing time—the information is still there, but inaccessible. So when histones are bunched together tightly, gene expression is prevented. But when they are loosely bunched, gene expression is allowed. This form of control is referred to as The Histone Code. The second major way the epigenetic code controls gene expression is by attaching or detaching chemical groups to the DNA itself. Methyl groups are small chemical clusters (– CH3 ) that attach to DNA and ‘switch off’ or prevent genes being expressed. This form of regulation is known as DNA methylation. The Histone Code and DNA methylation provide an ‘epigenetic code’, which is a heritable physical and chemical code that controls gene expression. It’s a bit like the stage manager at a concert—it choreographs when certain acts (genes) play their part in the ‘concert of life’. What’s more, the epigenetic code is a dynamic code that changes throughout development and in response to the environment.

MUTATIONS Can mutations create new information? by Dr Robert W. Carter In the same way that species are not static, neither are genomes. They change over time; sometimes

randomly, sometimes in preplanned pathways, and sometimes according to instruction from pre-existing algorithms. Irrespective of the source, we tend to call these changes ‘mutations’. Many evolutionists use the existence of mutation as evidence for long-term evolution, but the examples they cite fall far short of the requirements of their theory. Many creationists claim that mutations are not able to produce new information. Confusion about definitions abounds, including arguments about what constitutes a mutation and the definition of ‘biological information’. Evolution requires the existence of a process for the invention of new information from scratch. Yet, in a genome operating in at least four dimensions and packed with meta-information, potential changes are strongly proscribed. Can mutations produce new information? Yes, depending on what you mean by ‘new’ and ‘information’. Can they for the evolution of all life on Earth? No! Mutations are known by the harm they cause, such as the one in the ‘feather duster budgie’ (left), which results in deformed feathers in the budgerigar. However, some genetic changes seem to be programmed to happen, creating variety and assisting in organisms adapting. Is this ‘new information’?The phrase, “Mutations cannot create new information” is almost a mantra among some creationists, yet I do not agree. Evolutionists have a number of responses to the idea, although most of them display faulty reasoning. Most evolutionary responses display a lack of understanding of the complexity of the genome. I will explain below why I believe the genome was designed to operate in at least four dimensions and why this causes difficulty for the evolutionary belief in the rise of new information.Another issue, especially displayed among evolutionists (but creationists, including myself, are not immune), is a lack of understanding of the location of biological information. Most people tend to think DNA (the ‘genome’) is the storage place of information. While it is certainly the location of a tremendous amount of it, this gene-centered view ignores the information originally engineered into the first created organisms. The architecture of the cell, including the cell wall, nucleus, sub-cellular compartments and a myriad of molecular machines, did not originate from DNA, but was created separately and alongside DNA. Neither can exist without the other. Thus, a large, yet immeasurable, part of biological information resides in living organisms outside DNA. Taking an organism-centric view changes the debate dramatically.1 Yet, because the organism-centric view ultimately involves the creative genius of a designer, which we cannot begin to fathom, we immediately run into a ‘wall of incalculability’. For this reason, I will focus on one subset of biological information, genetic information, for the remainder of this article.A third issue involves the fact that Darwin actually wrote about two different ideas, what I like to call his specialand general theories of evolution (described below). Creationist reactions against evolution in general have led to some misunderstanding of the amounts of change we might expect in living organisms over time. There are three basic ideas I would like to introduce in this discussion: 1) In the same way that the designer was not limited to creating static species, he was not limited to creating static genomes; 2) The designer may have placed intelligently designed genetic algorithms into the genomes of His created kinds that cause changes in genetic information or even create information de novo; and 3) The designer could have engineered information in compressed form into the genome that would be later decompressed and seen as ‘new’ information. What is a mutation? A ‘mutation’ is a change in the sequence of DNA. Mutations can be bad or (theoretically) good, but they all involve some change in the sequence of letters (base pairs) in the genome. A single mutation can be as simple as a single letter swap (e.g. C changed to T) or the insertion or deletion of a few letters. These simple mutations are in the majority. Mutations can also be complex, like the deletion or duplication of an entire gene, or even a massive inversion of a millions-of-base-pairs section of a chromosome arm. We have to make a distinction between mutation and ‘designed variation’. I do not believe all current human genetic differences are due to mutation. We have to make a distinction between mutation and ‘designed variation’. There are a huge number of single letter differences between people, and these are mostly shared among all people groups.2 This indicates that much of the diversity found among people was designed: The first people carried a significant amount of diversity; and in the Babel population immediately after the Flood, and the post-Babel people groups were large enough to carry away most of the variation present at Babel. Most deletions (~90%), however, are not shared among the various human subpopulations.3 This indicates that a significant number of deletions have occurred in the human genome, but after Babel. Deletions are apparently not designed variation and are an example of rapid genomic decay. The same can be said of DNA insertions, but they are about 1/3 as common as the same-size deletion. The ubiquity of large, unique deletions in the various human subpopulations worldwide is evidence for rapid erosion or corruption of genetic information, through mutation. What is a gene? Technically, a ‘gene’ is a piece of DNA that codes for a protein, but modern genetics has revealed that different parts of different genes are used in different combinations to produce proteins,4,5 so the definition is a bit up in the air at the moment.6 Most people, including scientists, use ‘gene’ to mean two different things: either 1) a piece of DNA that codes for a protein, or 2) a trait. This is an important distinction to keep in mind. What is information? This question, ‘What is information’, is the real crux of the argument, yet the term ‘information’ is difficult to define. When dealing with this subject, in most cases evolutionists use a statistical measure called Shannon Information. This was a concept invented by the brilliant electronic engineer C.E. Shannon in the middle of the 20 th century, who was trying to answer questions about how much data one could stuff into a radio wave or push through a wire. Despite common usage, Shannon’s ideas of information have little to do with biological information.Case in point: A beautiful cut-glass vase can be described quite easily. All one needs is a description of the material and the location of each edge and/or vertex in 3-D space. Yet, a milliondollar vase can be smashed into a worthless pile of sand quite easily. If one wanted to recreate that pile of sand exactly, a tremendous amount of Shannon information would be required to describe the shape of each grain as well as the orientation and placement of grains within the pile. Which has more ‘information’, the pile of sand or the original vase into which a tremendous amount of purposeful design was placed? It depends on which definition of information one uses! Figure 1. A biological system is defined as containing information when all the following five hierarchical levels of information are observed: statistics (here left off for simplicity), syntax, semantics, pragmatics and apobetics (from Gitt, ref. 9).In other definitions of ‘information’, the pile of sand could be described quite easily with just a few statistical measures (e.g. average

grain size mass of sand angle of repose). In this sense, any number of independent piles of sand can be, for all practical purposes, identical. This is the essence of Zemansky’s use of information,7 yet this also has little to do with biological information, for biology is not easy to summarize, and any such attempts would produce meaningless results (e.g. a statistical measure of the average rate of a chemical reaction mediated by a certain enzyme says nothing about the origin of the information required to produce that enzyme).A definition of ‘biological information’ is not easy to come by, and this complicates the discussion of the power of mutation to create information. However, pioneers in this field, including Gitt 8and others, have discussed this issue at great length so it is not necessary to reproduce all the arguments here. I will follow Gitt and define information as, “ … an encoded, symbolically represented message conveying expected action and intended purpose”, and state that, “Information is always present when all the following five hierarchical levels are observed in a system: statistics, syntax, semantics, pragmatics and apobetics” (figure 1). 9 While perhaps not appropriate for all types of biological information, I believe Gitt’s definition can be used in a discussion of the main focus of this article: potential changes in genetic information. Can mutations create information? Now we can address the main question, “Can mutations create new genetic information?” Figure 2. Schematic view of the central role that ‘intelligentlydesigned’ VIGEs may play in generating variation, adaptations and speciation events in the genomes of living things to induce DNA changes. Lower part: VIGEs may directly modulate the output of (morpho)genetic algorithms due to position effects. Upper part: VIGEs that are located on different chromosomes may be the result of speciation events, because their homologous sequences facilitate chromosomal translocations and other major karyotype rearrangements. (From Borger, ref 22.) 1) The designer was not limited to creating static genomes, in the same way that He was not limited to creating fixed species. 10 In the 1800s, Darwin pushed back against the popular idea that The designer created all species in their present form. Today, most creationists do not have trouble with non-fixity of species. Evolutionists constantly attempt to bring up the straw man argument that we believe in species stasis, even comparing us to people who believed in a flat earth, but both of these are historical myths.12 Most people throughout history believed the earth was round, and there were creationists, like Linnaeus 13 and Blyth,14 prior to Darwin who believed species could change (though not beyond a certain limit). CMI, in particular, have published articles and one DVD15 on the subject of how species change over time and have an entire section on the topic on our Q&A page.16 Here is an important question: if species can change, what about their genomes?Not only are species not fixed, but more than several articles have been published in this journal alone on the topic of non-static genomes, including recent articles by Alex Williams,17 Peter Borger,18 Jean Lightner,19 Evan Loo Shan,20 and others. It looks like the designer engineered into life the ability to change DNA. This occurs through homologous crossover, jumping genes (retrotransposons,21 ALUs, etc.), and other means (including the random DNA spelling errors generally called ‘mutations’). Borger has coined a phrase, ‘variation inducing genetic elements’ (VIGEs) 22 to describe the intelligently-designed genetic modules the designer may have put into the genomes of living things to induce DNA sequence changes (figure 2). 2) Creationists are making a strong case that genomes are not static and that the DNA sequence can change over time, but they are also stating that some of these changes are controlled by genetic algorithms built into the genomes themselves. In other words, not all changes are accidental, and a large proportion of genetic ‘information’ is algorithmal. If a change occurs in DNA through an intelligently-designed algorithm, even an algorithm designed to make random, but limited, changes, what do we call it? Mutation originally simply meant ‘change’ but today it carries a lot of extra semantic baggage. Can we say that a mechanism designed to create diversity over time within a species can be a cause of ‘mutation’, with its connotation of unthinking randomness? In fact, there is considerable evidence that some mutations are repeatable 23,24 (that is, not wholly

random) (figure 3). This suggests the presence of some genomic factor designed to control mutation placement in at least some cases. If that something causes an intentional change in the DNA, do we call that a ‘mutation’ or an ‘intelligently engineered change in the DNA sequence’? Of course, random mutations still occur, and these are mostly due to the error rate of the DNA replication and repair machinery. Figure 3. There is considerable evidence that some mutations are not random. E.g. mutations in nucleotide sequences of exon X (ten) from GULO genes and pseudogenes from a number of species. In this illustration, positions with identical nucleotides in all organisms are not shown. The deletion mutation in position 97 (indicated by *) in this pseudogene is usually hailed as the ultimate evidence for the common descent shared between humans and the great apes. At first glance, this may appear to be a very strong case for common descent. However, after examining a large number of organisms, enabling the excluding non-random mutations, it becomes obvious that position 97 is in fact a hot spot for non-random mutations. (From Borger, ref. 24.)

3) There could be a considerable amount of information stored in the genome in compressed, hidden form. When this information is decompressed, deciphered, revealed, or unscrambled (call it what you will), this cannot be used as evidence for evolution, since the information was already stored in the genome.Take the information the desiner put into the first people. An evolutionist looks at any DNA difference as a result of mutation, but the designer could have put a significant amount of designed variation directly into the first people. There are millions of places in the human genome that vary from person to person, the majority of this variation is shared among all populations, 25 and most of these variable positions have two common versions (Aor G, T or C, etc.).26 The bulk of these should be places where the designer used perfectly acceptable alternate readings during the creation of man. These are not mutations!The in-built alternatives he put into the first people are scrambled over time, and new traits (even many good ones not previously in existence) might arise during this process. How? One way is through a process called ‘homologous recombination’. People have two sets of chromosomes. Let’s say a certain portion of one of Adam’s chromosome #1 reads ‘GGGGGGGGGG’ and codes for a greencolored something-or-other. The other copy of chromosome 1 reads ‘bbbbbbbbbb’ and codes for a blue something-or-other, but blue is recessive. Someone with one or two copies of the all-G chromosome will have a green something-or-other. Someone with two copies of the all-b chromosome will have a blue something-or-other. In the early population, about three quarters of the people will have the green version and about one quarter will have the blue version.How, then, does this process produce new traits? Homologous chromosomes are recombined from one generation to the next through a process called ‘crossing over’. If a crossing over event occurred in the middle of this sequence, we might get one that reads ‘GGGGGbbbbb’ that causes the production of a purple something-or-other. This is a brand new thing, a new trait never seen before. This is the result of a change in the DNA sequence and we will not be able to tell the difference between this crossing over event and a ‘mutation’ until we can sequence the piece of DNA in question. Thus, new traits (sometimes incorrectly or colloquially referred to as ‘genes’) can arise through homologous recombination. 27 But this is not mutation. Recombination is part of the intelligently-designed genome and usually only reveals information that was previously packed into the genome by the Master Designer (it can also reveal new combinations of mutations and designed diversity). Also, recombination is not random,28,29 so there is a limit to the amount of new traits that can come about in this way. Bad examples used by evolutionists Adaptive immunity I have a hard time calling something like adaptive immunity, which involves changes in the order of a certain set of genes to create novel antibodies, ‘mutation’. Adaptive immunity is often brought up by the evolutionist as an example of ‘new’ genes (traits) being produced by mutation. Here we have an example of a mechanism that takes DNA modules and scrambles those modules in complex ways in order to generate antibodies for antigens to which the organism has never been exposed. This is a quintessential example of intelligent design. The DNA changes in adaptive immunity occur only in a controlled manner among only a limited number of genes in a limited subset of cells that are only part of the immune system, and these changes are not heritable. Thus, the argument for evolution falls flat on its face.30 Gene duplication Gene duplication is often cited as a mechanism for evolutionary progress and as a means of generating ‘new’ information. Here, a gene is duplicated (through several possible means), turned off via mutation, mutated over time, turned on again through a different mutation, and,voilà!, a new function has arisen.Invariably, the people who use this as an argument never tell us the rate of duplication necessary, nor how many duplicated but silenced genes we would expect to see in a given genome, nor the needed rate of turning on and off, nor the likelihood of a new function arising in the silenced gene, nor how this new function will be integrated into the already complex genome of the organism, nor the rate at which the silenced ‘junk’ DNA would be expected to be lost at random (genetic drift) or through natural selection. These numbers are not friendly to evolutionary theory, and mathematical studies that have attempted to study the issue have run into a wall of improbability, even when attempting to model simple changes. 31-33 This is akin to the mathematical difficulties Michael Behe discusses in his book, The Edge of Evolution.34 In fact, gene deletions35 and loss-of-function mutations for useful genes are surprisingly common.36 Why would anyone expect a deactivated gene to stick around for a million years or more while an unlikely new function develops?But the situation with gene duplication is even more complicated than this. The effect of a gene often depends on gene copy number. If an organism appears with extra copies of a certain gene, it may not be able to control the expression of that gene and an imbalance will occur in its physiology, decreasing its fitness (e.g. trisomy causes abnormalities such as Down syndrome because of such gene dosage effects). Since copy number is a type of information, and since copy number variations are known to occur (even among people37), this is an example of a mutation that changes information. Notice I did not say ‘adds’ information, but ‘changes’. Word duplication is usually frowned upon as being unnecessary (ask any English teacher). Likewise, gene duplication is usually, though not always, bad. In the cases where it can occur without damaging the organism, one needs to ask if this is really an addition of information. Even better than that, is this the type of addition required by evolution? No, it is not.Several creationists have written on this subject, including Lightner,38 Liu and Moran.39 Even if an example of a new function arising through gene duplication is discovered, the function of the new must necessarily be related to the function of the old, such as a new but similar catalysis end product of an enzyme. There is no reason to expect otherwise. New functions arising through duplication are not impossible, but they are vanishingly unlikely, and they become more unlikely with each degree of change required for the development of each new function. Degraded information There are abundant examples in the evolutionary literature where genetic degradation has been used in an attempt to show an increase in information over time. Examples include sickle cell anemia (which confers a resistance to the malaria parasite by producing deformed hemoglobin molecules), 40 aerobic citrate digestion by bacteria (which involves the loss of control of the normal anaerobic citrate digestion),41and nylon digestion by bacteria (which involves a loss of substrate specificity in one enzyme contained on an extra-chromosomal plasmid).42Since they all involve decay of prior information, none of these examples are satisfactory evidence for an increase in biological complexity over time. Antibiotic resistance in bacteria This has been dealt with so many times that I hesitate to even mention it. However, for some reason evolutionists keep bringing it up, almostad nauseam. The interested reader can easily find many articles on the subject, with detailed creationist rebuttals.43 General gain-of-function mutations Evolution requires gain-of-function (GOF) mutations, but evolutionists have had a difficult time coming up with good examples.44 Adaptive immunity, homologous recombination, antibiotic resistance in bacteria, and sickle-cell anemia in humans have all been used as examples, but, as detailed above, each of these examples fails to meet the requirements of a true GOF. The general lack of examples, even theoretical examples, of something absolutely required by evolution is strong testimony against the validity of evolutionary theory. The real issue

The development of new functions is the only thing important for evolution. We are not talking about small functional changes, but radical ones. Some organism had to learn how to convert sugars to energy. Another had to learn how to take sunlight and turn it into sugars. Another had to learn how to take light and turn it into an interpretable image in the brain. These are not simple things, but amazing processes that involve multiple steps, and functions that involve circular and/or ultra-complex pathways will be selected away before they have a chance to develop into a working system. For example, DNA with no function is ripe for deletion, and making proteins/enzymes that have no use until a complete pathway or nanomachine is available is a waste of precious cellular resources. Chicken-and-egg problems abound. What came first, the molecular machine called ATP synthase or the protein and RNA manufacturing machines that rely on ATP to produce the ATP synthase machine? The most basic processes upon which all life depends cannot be co-opted from pre-existing systems. For evolution to work, they have to come up from scratch, they have to be carefully balanced and regulated with respect to other processes, and they have to work before they will be kept.Saying a gene can be copied and then used to prototype a new function is not what evolution requires, for this cannot for radically new functionality. Thus, gene duplication cannot answer the most fundamental questions about evolutionary history. Likewise, none of the common modes of mutation (random letter changes, inversions, deletions, etc.) have the ability to do what evolution requires. Darwin pulled a bait and switch in his On the Origin of Species. He actually produced two separate theories: what I call his special and general theories of evolution, following Kerkut45. Darwin went on at length to show how species change. This was the Special Theory of Evolution and he was preceded by numerous others, including several creationists, with the same idea. It took him a long time to get to the point, but he finally said, “ … I can see no limit to the amount of change … which may be effected in the long course of time by nature’s power of selection.”46 The ‘can mutations create new information’ argument is really about the bridge between the special and general modes of evolution.This was his General Theory of Evolution, and this is where he failed, for he provided no real mechanism for the changes and was ignorant of the underlying mechanisms that would later be revealed. To use a modern analogy, this would be akin to saying that small, random changes in a complex computer program can create radical new software modules, without crashing the system.47 Thus, the ‘can mutations create new information’ argument is really about the bridge between the special and general modes of evolution. Yes, mutations can occur within living species (kinds), but, no, those mutations cannot be used to explain how those species (kinds) came into existence in the first place. We are talking about two completely separate processes. The meta-information challenge We need to get past the naïve idea that we understand the genome because we know the sequence of a linear string of DNA. In fact, all we know is the first dimension out of at least four in which the genome operates (1: the one-dimensional, linear string of letters; 2: the two-dimensional interactions of one part of the string with another, directly or through RNA and protein proxies; 3: the three-dimensional spatial structure of the DNA within the nucleus; and 4: changes to the 1 st, 2nd and 3rd dimensions over time). There is a tremendous amount of information packed into that genome that we have not figured out, including multiple simultaneously-overlapping codes.48 When discussing whether or not mutations can create new information, evolutionists routinely bring up an overly-simplistic view of mutation and then claim to have solved the problem while waving their hand over the real issue: the antagonism between ultra-complexity and random mutation.If a fourdimensional genome is hard enough to grasp, there is also a huge amount of ‘meta-information’ in the genome. This is information about the information! This is the information that tells the cell how to maintain the information, how to fix it if it breaks, how to copy it, how to interpret what is there, how to use it, when to use it, and how to it on to the next generation. This is all coded in that linear string of letters and life could not exist without it. In fact, life was designed from a top-down perspective, apparently with the meta-information coming first. According to a brilliant paper by Alex Williams, 49 for life to exist, organisms require a hierarchy of Perfectly pure, single-molecule-specific biochemistry, specially structured molecules, functionally integrated molecular machines, comprehensively regulated, information-driven metabolic functions, and inversely-causal meta-information. None of these levels can be obtained through natural processes, none can be predicted from the level below, and each is dependent on the level above. Meta-information is the top level of biological complexity and cannot be explained by naturalistic mechanisms, yet life cannot exist without it. 50 Putting all other arguments for and against the rise of biological information aside, where did the meta-information, upon which all life depends, come from? Conclusions Can mutation create new information? Yes, depending on what you mean by ‘information’. Also, ‘new’ does not necessarily imply ‘better’ or even ‘good’. When evolutionists cite examples of ‘new’ information, they are almost invariably citing evidence of new traits, but these traits are caused by the corruption of existing information. Mutations can create new varieties of old genes, as can be seen in white-coated lab mice, tailless cats, and blue-eyed people. But damaging mutations cannot be used to vindicate molecules-to-people evolution. Breaking things does not lead to higher function (and presupposes a pre-existing function that can be broken). Also, not all new traits are caused by mutation! Some come about by unscrambling pre-existing information, some from decompressing packed information, some from turning on and off certain genes.In all the examples I have seen used to argue against creation, evolution is not helped. There are no known examples of the types of information-gaining mutations necessary for large-scale evolutionary processes. In fact, it looks like all examples of gain-of-function mutations, put in light of the long-term needs of upward evolutionary progress, are exceptions to what is needed, because every example I have seen involves something breaking.We as creationists have the upper hand here. If we treat this properly, we can score a great victory in our long war for truth. The genome is not what evolution expected. The examples of mutations we have are not of the types required for evolution to advance. Evolution has to explain how the four-dimensional genome, with multiple overlapping codes and chock full of meta-information, came about. Can a mutation create new information? Perhaps, but only in the most limited sense. Can it create the kind of information needed to produce a genome? Absolutely not! Acknowledgments I must thank Don Batten, Jonathan Sarfati, and three anonymous reviewers for critical comments on this manuscript. This was very much a team effort as the ideas were distilled through years of interaction among my creationist colleagues, many of whose contributions were not mentioned due to lack of space, not due to lack of merit. I am afraid I did not do justice to those who have gone before me. Refuting Evolution 2

A sequel to Refuting Evolution that refutes the latest arguments to evolution (as presented by PBS and Scientific American). by Jonathan Sarfati, Ph.D. with Michael Matthews Argument: Some mutations are beneficial Evolutionists say, ‘Mutations and other biological mechanisms have been observed to produce new features in organisms.’ First published in Refuting Evolution 2, Chapter 5 When they begin to talk about mutations, evolutionists tacitly acknowledge that natural selection, by itself, cannot explain the rise of new genetic information. Somehow they have to explain the introduction of completely new genetic instructions for feathers and other wonders that never existed in ‘simpler’ life forms. So they place their faith in mutations.In the process of defending mutations as a mechanism for creating new genetic code, they attack a straw-man version of the creationist model, and they have no answer for the creationists’ real scientific objections. Scientific American states this common strawman position and their answer to it.10. Mutations are essential to evolution theory, but mutations can only eliminate traits. They cannot produce new features.On the contrary, biology has catalogued many traits produced by point mutations (changes at precise positions in an organism’s DNA)—bacterial resistance to antibiotics, for example. [SA 82]This is a serious misstatement of the creationist argument. The issue is not new traits, but new genetic information. In no known case is antibiotic resistance the result of new information. There are several ways that an information loss can confer resistance, as already discussed. We have also pointed out in various ways how new traits, even helpful, adaptive traits, can arise through loss of genetic information (which is to be expected from mutations).Mutations that arise in the homeobox ( Hox) family of development-regulating genes in animals can also have complex effects. Hox genes direct where legs, wings, antennae, and body segments should grow. In fruit flies, for instance, the mutation called Antennapedia causes legs to sprout where antennae should grow. [SA 82]Once again, there is no new information! Rather, a mutation in the hox gene (see next section) results in already-existing information being switched on in the wrong place. 1 The hox gene merely moved legs to the wrong place; it did not produce any of the information that actually constructs the legs, which in ants and bees include a wondrously complex mechanical and hydraulic mechanism that enables these insects to stick to surfaces. 2These abnormal limbs are not functional, but their existence demonstrates that genetic mistakes can produce complex structures, which natural selection can then test for possible uses. [SA 82]Amazing—natural selection can ‘test for possible uses’ of ‘non-functional’ (i.e., useless!) limbs in the wrong place. Such deformities would be active hindrances to survival. Gene switches: means of evolution? William Bateson (1861–1926), who added the word ‘genetics’ to our vocabulary in 1909, found that embryos sometimes grew body parts in the wrong place. From this he theorized that there are underlying controls of certain body parts, and other controls governing where they go.Ed Lewis investigated and won a Nobel Prize in 1995 for discovering a small set of genes that affect different body parts (Hox or Homeobox). They act like ‘architects of the body.’ Mutations in these can cause ‘dramatic’ changes. Many experiments have been performed on fruit flies (Drosophila), where poisons and radiation induced mutations.The problem is that they are always harmful. PBS 2 showed an extra pair of wings on a fly, but failed to mention that they were a hindrance to flying because there are no accompanying muscles. Both these flies would be eliminated by natural selection.Walter Gehring of the University of Basel (Switzerland) replaced a gene needed for eye development in a fruit fly with the corresponding gene from a mouse. The fly still developed normal fly eyes, i.e., compound eyes rather than lens/camera. This gene in both insects and mammals is called eyelessbecause absence of this gene means no eyes will form.However, there is obviously more to the differences between different animals. Eyeless is a switch—it turns on the genetic information needed for eyes. But evolution requires some way of generating the new information that’s to be switched on. The information needed to build a compound eye is vastly different from that needed to build a lens/camera type of eye. By analogy, the same switch on an electric outlet/power socket can turn on a light or a laptop, but this hardly proves that a light evolved into a laptop!All the same, the program says that eyeless is one of a small number of common genes used in the embryonic development of many animals. The program illustrated this with diagrams. Supposedly, all evolution needed to do was reshuffle packets of information into different combinations.But as shown, known mutations in these genes cause monstrosities, and different switches are very distinct from what is switched on or off. Also, the embryo develops into its basic body plan before these genes start switching—obviously they can’t be the cause of the plan before they are activated! But the common genes make perfect sense given the existence of a single designer. Increased amounts of DNA don’t mean increased function Biologists have discovered a whole range of mechanisms that can cause radical changes in the amount of DNA possessed by an organism. Gene duplication, polyploidy, insertions, etc., do not help explain evolution, however. They represent an increase in amount of DNA, but not an increase in the amount of functional genetic information—these mechanisms create nothing new. Macroevolution needs new genes (for making feathers on reptiles, for example), yet Scientific American completely misses this simple distinction:Moreover, molecular biology has discovered mechanisms for genetic change that go beyond point mutations, and these expand the ways in which new traits can appear. Functional modules within genes can be spliced together in novel ways. Whole genes can be accidentally duplicated in an organism’s DNA, and the duplicates are free to mutate into genes for new, complex features. [SA 82]In plants, but not in animals (possibly with rare exceptions), the doubling of all the chromosomes may result in an individual which can no longer interbreed with the parent type—this is called polyploidy. Although this may technically be called a new species, because of the reproductive isolation, no new information has been produced, just repetitious doubling of existing information. If a malfunction in a printing press caused a book to be printed with every page doubled, it would not be more informative than the proper book. (Brave students of evolutionary professors might like to ask whether they would get extra marks for handing in two copies of the same assignment.)Duplication of a single chromosome is normally harmful, as in Down’s syndrome. Insertions are a very efficient way of completely destroying the functionality of existing genes. Biophysicist Dr Lee Spetner in his book Not By Chance analyzes examples of mutational changes that evolutionists have claimed to have been increases in information, and shows that they are actually examples of loss of specificity, which means they involved loss of information (which is to be expected from information theory).The evolutionist’s ‘gene duplication idea’ is that an existing gene may be doubled, and one copy does its normal work while the other copy is redundant and non-expressed. Therefore, it is free to mutate free of selection pressure (to get rid of it). However, such ‘neutral’ mutations are powerless to produce new genuine information. Dawkins and others point out that natural selection is the only possible naturalistic explanation for the immense design in nature (not a good one, as Spetner and others have shown). Dawkins and others propose that random changes produce a new function, then this redundant gene becomes expressed somehow and is fine-tuned under the natural selective process.This ‘idea’ is just a lot of hand-waving. It relies on a chance copying event, genes somehow being switched off, randomly mutating to something approximating a new function, then being switched on again so natural selection can tune it.Furthermore, mutations do not occur in just the duplicated gene; they occur throughout the genome. Consequently, all the deleterious mutations in the rest of the genome have to be eliminated by the death of the unfit. Selective mutations in the

target duplicate gene are extremely rare—it might represent only 1 part in 30,000 of the genome of an animal. The larger the genome, the bigger the problem, because the larger the genome, the lower the mutation rate that the creature can sustain without error catastrophe; as a result, it takes even longer for any mutation to occur, let alone a desirable one, in the duplicated gene. There just has not been enough time for such a naturalistic process to for the amount of genetic information that we see in living things.Dawkins and others have recognized that the ‘information space’ possible within just one gene is so huge that random changes without some guiding force could never come up with a new function. There could never be enough ‘experiments’ (mutating generations of organisms) to find anything useful by such a process. Note that an average gene of 1,000 base pairs represents 4 1000 possibilities—that is 10602 (compare this with the number of atoms in the universe estimated at ‘only’ 10 80). If every atom in the universe represented an ‘experiment’ every millisecond for the supposed 15 billion years of the universe, this could only try a maximum 10100 of the possibilities for the gene. So such a ‘neutral’ process cannot possibly find any sequence with specificity (usefulness), even allowing for the fact that more than just one sequence may be functional to some extent.So Dawkins and company have the same problem as the advocates of neutral selection theory. Increasing knowledge of the molecular basis of biological functions has exploded the known ‘information space’ so that mutations and natural selection—with or without gene duplication, or any other known natural process—cannot for the irreducibly complex nature of living systems. Yet Scientific American has the impertinence to claim: Comparisons of the DNA from a wide variety of organisms indicate that this [duplication of genes] is how the globin family of blood proteins evolved over millions of years. [SA 82]This is about the vital red blood pigment hemoglobin that carries the oxygen. It has four polypeptide chains and iron. Evolutionists believe that this evolved from an oxygen-carrying ironcontaining protein called myoglobin found in muscles, which has only one polypeptide chain. However, there is no demonstration that gene duplication plus natural selection turned the one-chained myoglobin into the four-chained hemoglobin. Nor is there any adequate explanation of how the hypothetical intermediates would have had selective advantages.In fact, the proposed evolution of hemoglobin is far more complicated than Scientific American implies, though it requires a little advanced biology to understand. The α- and β-globin chains are encoded on genes on different chromosomes, so they are expressed independently. This expression must be controlled precisely, otherwise various types of anemia called thalassemia result. Also, there is an essential protein called AHSP (alpha hemoglobin stabilizing protein) which, as the name implies, stabilizes the α-chain, and also brings it to the β-chain. Otherwise the α-chain would precipitate and damage the red blood cells.AHSP is one of many examples of a class of protein called chaperones which govern the folding of other proteins.3 This is yet another problem for chemical evolutionary theories—how did the first proteins fold correctly without chaperones? And since chaperones themselves are complex proteins, how did they fold?4Identifying information-increasing mutations may be a small part of the whole evolutionary discussion, but it is a critical ‘weak link’ in the logical chain. PBS, Scientific American, and every other pro-evolution propaganda machine have failed to identify any evidence that might strengthen this straw link. Beetle bloopers Flightless insects on windswept islands Even a defect can be an advantage sometimes by Carl Wieland A big obstacle for evolutionary belief is this: what mechanism could possibly have added all the extra information required to transform a one-celled creature progressively into pelicans, palm trees, and people? Natural selection alone can’t do it— selection involves getting rid of information. A group of creatures might become more adapted to the cold, for example, by the elimination of those which don’t carry enough of the genetic information to make thick fur. But that doesn’t explain the origin of the information to make thick fur.For evolutionists there is only ‘one game in town’ to explain the new information which their theory requires—mutations. These are accidental mistakes as the genetic information (the coded set of instructions on the DNA which is the ‘recipe’ or ‘blue-print’ specifying the construction and operation of any creature) is copied from one generation to the next. Naturally, such scrambling of information will tend to either be harmful, 1 or at best neutral.2However, evolutionists believe that occasionally, a ‘good’ mutation will occur which will be favored by selection and will allow that creature to progress along its evolutionary pathway to something completely different. The wrong type of change Are there ‘good’ mutations? Evolutionists can point to a small handful of cases in which a mutation has helped a creature to survive better than those without it. Actually, they need to take a closer look. Such ‘good’ mistakes are still the wrong types of changes to turn a fish into a philosopher—they are headed in precisely the wrong direction. Rather than adding information, they destroy information, or corrupt the way it can be expressed (not surprising, since they are random mistakes).For example, beetles losing their wings. A particular winged beetle type lives on large continental areas; the same beetle type on a small windy island has no wings.What happened is easy to imagine. Every now and then in beetle populations, there might be a mutational defect which prevents wings from forming. That is, the ‘wing-making’ information is lost or scrambled in some way.The damaged gene (a gene is like a long ‘sentence’ carrying one part of the total instructions recorded on the DNA) will then be ed to all that beetle’s offspring, and to theirs, as it is copied over and over. All these descendant beetles will be wingless.If a beetle with such a wingless defect is living on the Australian mainland, for example, it will have less chance to fly away from beetle-eaters, so it will be more likely to be eliminated by ‘survival of the fittest’ before it can leave offspring. Such so-called ‘natural selection’ can help to eliminate (or at least reduce the buildup of) such genetic mistakes. Blown away However, on the windy island, the beetles which can fly tend to get blown into the sea, so not having wings is an advantage. In time, the elimination of all the winged ones will ensure that only those of this new ‘wingless’ variety survive, which have therefore been ‘naturally selected.’ ‘There!’ says the evolutionist. ‘A favorable mutation—evolution in action!’ However, it fails to make his case, because though beneficial to survival, it is still a defect—a loss or corruption of information. This is the very opposite of what evolutionists need to demonstrate real evolution.To belief in a process which has allegedly turned molecules into man would require mutations to add information. Showing that information-losing defects can give a survival advantage is irrelevant, as far as evidence for real evolution is concerned. In short, Evolutionary theory requires some mutations to go ‘uphill’—to add information. The mutations which we observe are generally neutral (they don’t change the information, or the ‘meaning’ in the code) or else they are informationally downhill—defects which lose/corrupt information.The rare ‘beneficial’ mutations to which evolutionists cling, all appear to be like this wingless beetle—downhill changes, losses of information which, though they may give a survival advantage, are headed in precisely the wrong direction for evolution.All of our real-world experience,

especially in the ‘information age,’ would indicate that to rely on accidental copying mistakes to generate real information is the stuff of wishful thinking by ‘true believers,’ not science. The evolution train’s a-comin’ (Sorry, a-goin’—in the wrong direction) by Carl Wieland The atmosphere in the crowded lecture theatre foyer was alive with curious anticipation. It was the late 1970s, the heady early days of the creation movement in South Australia. The creation/evolution debate I was about to take part in, before some 40 science teachers and involving a prominent academic evolutionist, was a first for the region.As the words of an animated conversation drifted across to me, I realized that my opponent-to-be was only a few metres to my left. A senior lecturer (associate professor in US ) in population biology, he was holding forth to a small group of ers, clearly unaware that his creationist protagonist was within earshot.‘This is really frustrating’, I heard him say. ‘I feel like an astronaut who’s come back from the moon, seen the spherical Earth, and now he’s supposed to debate with someone who tries to tell people it’s flat. In my job we seeevolution happening in front of our eyes.’Back then, before creationist arguments had had a good airing, it was understandable for him to think like that. Biology teachers could perhaps be excused for perpetuating such a naïve belief. They simply assumed that the easily observable genetic changes in many types of living populations were an obvious demonstration that evolution from microbes to man was fact. Just give it enough time, and voilá , such ‘micro’ changes would accumulate, continually filtered and guided by natural selection. It seemed obvious and logical to expect these ‘little steps’ to keep adding up so as to lead to the ‘macro’ changes—the really big jumps, frog-to-prince, fish-to-philosopher, that type of thing. (As we will show later in this article, though, the very opposite is true.) In that light, this biology lecturer’s perplexed frustration can be readily understood, because he thought that he was often seeing a small bit of what would in time become a large chunk of change. We need to understand that most evolutionists, even today, still think this way. Which is, frankly, why the usual answers given by most creationists, when challenged on the subject of biological change, are inadequate.For instance, a challenger might say, ‘Mosquitoes have evolved resistance to DDT in just 40 years. If that’s not evolution happening before our eyes, what is?’ Most people responses focus on the amount of change. For instance, they will say, ‘Well, that’s just variation within a kind.’ Or they reply, ‘But the mosquito’s still a mosquito, isn’t it? It hasn’t turned into anything else.’Both of these replies are true. But they are inadequate and seldom impress the challenger, who thinks, ‘Well, that’s just a copout for the people. Evolution takes millions of years, and here we have all this change in only 40 years. So, give it a million years and imagine what sort of change we’ll have then!’The analogy I have for many years used in explaining this in public lectures is that of a railway train. Imagine you see a train pulling out of a station in, say, Miami, Florida, headed north to Chicago. 1 The distance you see it travel is only a few hundred metres. But you can reasonably presume that, given enough time, it will end up in Chicago. You have seen sound evidence to indicate that it is in principle capable of making the whole journey, you don’t need to see it make the whole trip. This is just how evolutionists see the little changes (often called ‘microevolution’, but seeaside below) happening all around us. If a mosquito has changed a little in 40 years, you don’t need to see it turning into an elephant—it has shown that it is in principle capable of making a similarly radical journey.What we need to be aware of, and focus on in our answers, I tell audiences, is not the amount of change, but thetype or direction of change. It is not just that the train has not gone far enough, but that it is headed in the wrong direction. The types of changes observed today, though they can be accommodated within an evolutionary framework, are, we will see, precisely and demonstrably the opposite of the ones which evolutionists really need in order to give some semblance of credibility to their belief system.So while you may be seeing the train pulling out of the station at Miami, if the reality is that it is not heading north, up to Chicago, but is headed in the opposite direction, downwards to where the line (if there was one) would end in the deep blue ocean, then it will never get to Chicago. Time will not solve the problem, since it is in principle an impossibility to reach Chicago by train in that downward direction. Just so, once we can point out to people that the ‘evolution train’ (really the train of biological change) is headed downwards, not upwards, then the more time there is, the less likely the whole evolution scenario becomes.Before explaining what I mean by biological changes having a ‘direction’, I will share what triggered this article. It was a book review2 by well-known evolutionary biologist Dr Jerry Coyne, of the University of Chicago, who could not resist an opportunity to lash out at the creationists. 3 Amazingly, Coyne uses the train journey analogy himself, reinforcing my point of how evolutionists see the issue. Though his intention is to mock creationists, he unwittingly provides a great opportunity to show how misplaced this common reasoning is.The book he was reviewing 4 uses familiar examples of rapid human-induced biological changes (antibiotic resistance in bacteria, pesticide resistance in insects, changes in growth rate of fish from overfishing) to get people to ‘consent’ to the bigger idea of microbes-to-man evolution.Coyne deplores the fact that the book’s examples will probably not change the minds of creationist advocates, who have already accepted such changes as ‘adaptation within a species’ (‘variation within a kind’ would have been more precise). He says that creationists argue that ‘such small changes cannot explain the evolution of new groups of plants and animals’, and goes on to say: ‘This argument defies common sense. When, after a Christmas visit, we [presumably his family in Chicago—CW] watch grandma leave on the train to Miami, we assume that the rest of her journey will be an extrapolation of that quarter-mile.’ Thus, says Coyne, a ‘creationist unwilling to extrapolate from micro- to macroevolution’ is being ‘irrational’. Reason vs rhetoric Why can one say with confidence, concerning the biological changes observable today (man-induced or otherwise) that the train is headed in the wrong direction? Why is it that when evolutionists use this ‘grandma’s train’ extrapolation argument, it can be turned around to make the opposite point? Because the real issue in biological change is all about what happens at the DNA level, which concerns information.5 The information carried on the DNA, the molecule of heredity, is like a recipe, a set of instructions for the manufacture of certain items.Evolutionists teach that one-celled organisms 6 (e.g. protozoa) have given rise to pelicans, pomegranates, people and ponies. In each case, the DNA ‘recipe’ has had to undergo a massive net increase of information during the alleged millions of years. A one-celled organism does not have the instructions for how to manufacture eyes, ears, blood, skin, hooves, brains, etc. which ponies need. So for protozoa to have given rise to ponies, there would have to be some mechanism that gives rise to new information.Evolutionists hail natural selection as if it were a creative goddess, but the reality (which they invariably concede when pressed) is that selection on its own always gets rid of

information, never the opposite.7 To have a way to add information, the ‘only game in town’ for evolution’s true believers is genetic copying mistakes or accidents, i.e. random mutations (which can then be ‘filtered’ by selection). 8However, the problem is that if mutations were capable of adding the information required, we should see hundreds of examples all around us, considering that there are many thousands of mutations happening continually. But whenever we study mutations, they invariably turn out to have lost or degraded the information. This is so even in those rare instances when the mutational defect gives a survival advantage—e.g. the loss of wings on beetles on windy islands.9 What’s in a word? Micro vs macro Many creationists will say, ‘We accept microevolution, but not macroevolution.’ As our main article points out, the ‘micro’ changes (i.e. observed genetic variation) are not capable of accumulating into macro ones, anyway.We suggest, however, that it would be wiser to avoid the use of the term ‘microevolution’. To most people, it sounds as if you are conceding that there is a ‘little bit of evolution’ going on. I.e. a little bit of the same process that, given enough time, will turn microbes into millipedes, magnolias and microbiologists. Thus, you will be seen as churlish or, as in Dr Coyne’s inverted ‘train’ example, as irrational for putting what they see as an arbitrarydistinction between the ‘micro’ and ‘macro’.If the use of such potentially misleading terminology is unavoidable, always take the opportunity to point out that the changes often labelled ‘microevolution’ cannot be the same process as the hypothetical ‘goo-to-you’ belief. They are all information-losing processes, which thus depend on there being a store of information to begin with.As creatures diversify, gene pools become increasingly thinned out. The more organisms adapt to their surroundings by selection, i.e. the more specialized they become, the smaller the fraction they carry of the original storehouse of created information for their kind. Thus, there is less information available on which natural selection can act in the future to ‘readapt’ the population should circumstances change. Less flexible, less adaptable populations are obviously heading closer to extinction, not evolving.We see that, just like with the train pulling out from Miami and headed south, if the sorts of changes we see today are extrapolated over time, they lead to extinction, not onwards evolution., evolutionary belief teaches that once upon a time, there were living things, but no lungs—lungs had not evolved yet, so there was no DNA information coding for lung manufacture. Somehow this program had to be written. New information had to arise that did not previously exist, anywhere.Later, there were lungs, but no feathers anywhere in the world, thus no genetic information for feathers. Real-world observation has overwhelmingly shown mutation to be totally unable to feed the required new information into the system. 10 In fact, mutations overall hasten the downward trend by adding genetic load in the form of harmful mutations, of which we have all accumulated hundreds over the generations of our ancestry.11In other words, populations can change and adapt because they have a lot of information (variety) in their DNA ‘recipe’. But unless mutations can feed in new information, each time there is variation/adaptation, the total information decreases (as selection gets rid of the unadapted portions of the population, some information is lost in that population). Thus, given a fixed amount of information, the more adaptation we see, the less the potential for future adaptation. The train is definitely headed downhill, destined to fall off the jetty of extinction.The supreme irony is that, of all the examples lauded by Dr Coyne as ‘evolution’, whether antibiotic resistance 12 or changes in fish growth rates, not one single one s his ‘train’ analogy, but rather the reverse. Not one involves a gain of information; all show the opposite, a net loss. Pondering all this, I feel a sense of the same sort of frustration (only in reverse) that my evolutionist opponent was airing all those years ago, which he could have paraphrased as: ‘Why can’t they see it? It’s obvious, isn’t it?’ Who knows, perhaps somehow this article will get into Dr Coyne’s hands. Maybe it will give him, and some other evolutionist apologists, food for thought the next time they put one of their grandmothers on a train. Can any genetic information be gained from mutations Ancon sheep: just another loss mutation by Jerry Bergman Many examples of mutations that produce phenotypic changes are ‘loss mutations’ in which the mutation causes the loss of a structure. Loss mutations that result in a non-functional protein or structure can be beneficial if the functional protein loss or malformation somehow benefits the organism (or, far more often, humans—as in the case of the loss of seeds in a fruit, producing a convenient seedless fruit). One of the first and most common examples of the latter was an alleged new breed —Huxley called it a race, others labeled it a species—that resulted when Massachusetts farmer Seth Wright noticed in 1791 that he had a very short-legged sheep in his flock.1,2 The story is usually claimed that, realizing the advantages of this trait to sheepherders, Wright bred a ‘flock’ of the short-legged ‘species’ of sheep, all of whom were unable to jump over ordinary stone walls or fences.3,4 Called the Ancon or Otter ‘breed,’ it was believed to reduce the need for tall fences, as well as reducing the number of lost sheep. 1 In addition, the short legs limited the sheep’s ability to run so that, as a result, they were less active, more gentle, and gained weight far more readily then other sheep breeds.5 Charles Darwin and Ancon sheep Charles Darwin was evidently the first person to use the Ancon breed as evidence for evolution. He discussed them at least three times in his published books. In the Origin of Species, first published in 1859, Darwin speculated that some animal variations ‘have probably arisen suddenly,’ or by one step ‘in one generation.’ One example that Darwin used was ‘the turnspit dog.’ He then added that such ‘one step’ rapid evolution also is known ‘to have been the case with the Ancon sheep.’6 In another work, Darwin claimed that in a‘… few instances new breeds have suddenly originated; thus, in 1791, a ram-lamb was born in Massachusetts, having short crooked legs and a long back, like a turnspit-dog. From this one lamb the otter or ancon semi-monstrous breed was raised; as these sheep could not leap over the fences, it was thought that they would be valuable … . The sheep are remarkable from transmitting their character so truly that Colonel Humphreys never heard of “but one questionable case” of an ancon ram and ewe not producing ancon offspring. When they are crossed with other breeds the offspring, with rare exceptions, instead of being intermediate in character, perfectly resemble either parent; even one of the twins has resembled one parent and the second the other. Lastly, “the ancons have been observed to keep together, separating themselves from the rest of the flock when put into enclosures with other sheep”.’7 Is the Ancon mutation beneficial? Other evolutionists such as Kenneth Miller have also touted Ancon sheep as an example of evolutionary jumps. But this is deceptive because the condition actually is ‘pathological,’ known as achondroplasia (where cartilage fails to develop, from Greek a–, not; chondros, cartilage; plassein, to mould or form—a form of dwarfism) or a related pathology, 8 and‘… would bring about the extinction of these creatures in a natural environment, rather than an advance through natural selection. The suggestion, by Miller, that the four-winged fly and the Ancon sheep present evolutionary advances was simply a deceptive ploy.’9Actually, the mutation has proved lethal in a protected environment as well. Gish concludes that Ancon sheep are deformed animals, specifically, the‘… product of a pathological condition, called achondroplasia. In his presentation, Miller pointed out that these sheep have been bred by sheep breeders because they are short-legged and thus cannot jump fences—an advantage for those who raise sheep. What he did notsay was that their condition is caused by a mutation which results in the failure of the cartilage between the ts to develop. There is thus little or no cartilage

between the ts of their legs, causing them to be short. This abnormal condition would, of course, result in their rapid extinction in a natural environment and could never be considered an evolutionary advance.’ 9The Ancon mutation, in harmony with our general experience with mutations, was harmful to the sheep for many reasons. Achondroplasia is a type of genetic dwarfism characterized by slow limb growth relative to the rest of the skeleton. 10Many other abnormalities aside from short legs have been discovered as a result of Ancon sheep postmortems. These included looser leg t articulations, abnormal spines and skulls, flabby subscapular muscles, and crooked bent inward forelegs that caused the legs to appear like elbows while the sheep were walking. 11,12 This prominent trait is the reason for the term Ancon (ancon is the Latin transliteration of the Greek word for elbow, αγκων). The Ancon legs resemble the clubfeet condition, and, in fact, as adults were clumsy cripples that could neither run nor jump like other sheep.13 Conclusion A major problem for Darwinists is that the Ancon mutation (a Mendelian recessive), as is true with most other mutations, is a loss mutation. This type of mutation does not result in an information gain, as Darwinism requires, but an information loss (often of a complete structure or protein). A chief difficulty in arguing for macroevolution by mutations is the fact that most expressed mutations are either lethal or semi-lethal. Either they kill the organism outright, or they prove harmful, so that in the ordinary course of life they are eliminated. This includes both mutations in which the fertility rate is reduced as well as mutations that result in the loss of certain structures.And as shown, even the rare ‘beneficial’ mutation, as some might consider the Ancon to be, are the result of information loss. Therefore they are going in the opposite direction from what goo-to-you evolution requires.14 Bacteria ‘evolving in the lab’? ‘A poke in the eye for anti-evolutionists’? Some bacteria cultured in a laboratory have gained the ability to use citrate as an energy source. We have had lots of queries about this matter, so this is our weekend to all those who have asked. A New Scientist article proclaims: ‘Lenski’s experiment is also yet another poke in the eye for anti-evolutionists, notes Jerry Coyne, an evolutionary biologist at the University of Chicago. “The thing I like most is it says you can get these complex traits evolving by a combination of unlikely events," he says. “That’s just what creationists say can’t happen."’1The many comments posted on the New Scientistwebsite shows just how excited the atheists are about this report. They are positively gloating. The context In 1988, Richard Lenski, Michigan State University, East Lansing, founded 12 cultures of E. coli and grew them in a laboratory, generation after generation, for twenty years (he deserves some marks for persistence!). The culture medium had a little glucose but lots more citrate, so once the microbes consumed the glucose, they would continue to grow only if they could evolve some way of using citrate. Lenski expected to see evolution in action. This was an appropriate expectation for one who believes in evolution, because bacteria reproduce quickly and can have huge populations, as in this case. They can also sustain higher mutation rates than organisms with much larger genomes, like vertebrates such as us. 2 All of this adds up, according to neo-Darwinism, to the almost certainty of seeing lots of evolution happen in real time (instead of imagining it all happening in the unobservable past). With the short generation times, in 20 years this has amounted to some 44,000 generations, equivalent to some million years of generations of a human population (but the evolutionary opportunities for humans would be far, far less, due to the small population numbers limiting the number of mutational possibilities; and the much larger genome, which cannot sustain a similar mutation rate without error catastrophe; i.e. extinction; and sexual reproduction means that there is 50% chance of failing to on a beneficial mutation ).As noted elsewhere (see ‘Giving up on reality’), Lenski seemed to have given up on ‘evolution in the lab’ and resorted to computer modelling of ‘evolution’ with a program called Avida (see evaluation by Dr Royal Truman, Part 1 and Part 2, which are technical papers). Indeed, Lenski had good reason to abandon hope. He had calculated1 that all possible simple mutations must have occurred several times over but without any addition of even a simple adaptive trait. Lenski and co-workers now claim that they have finally observed his hoped for evolution in the lab. The science: what did they find? In a paper published in the Proceedings of the National Academy of Science, Lenski and co-workers describe how one of 12 culture lines of their bacteria has developed the capacity for metabolizing citrate as an energy source under aerobic conditions.3This happened by the 31,500th generation. Using frozen samples of bacteria from previous generations they showed that something happened at about the 20,000th generation that paved the way for only this culture line to be able to change to citrate metabolism. They surmised, quite reasonably, that this could have been a mutation that paved the way for a further mutation that enabled citrate utilization.This is close to what Michael Behe calls ‘The Edge of Evolution’—the limit of what ‘evolution’ (non-intelligent natural processes) can do. For example, an adaptive change needing one mutation might occur every so often just by chance. This is why the malaria parasite can adapt to most antimalarial drugs; but chloroquine resistance took much longer to develop because two specific mutations needed to occur together in the one gene. Even this tiny change is beyond the reach of organisms like humans with much longer generation times. 4 With bacteria, there might be a chance for even three coordinated mutations, but it’s doubtful that Lenski’s E. coli have achieved any more than two mutations, so have not even reached Behe’s edge, let alone progressed on the path to elephants or crocodiles.Now the popularist treatments of this research (e.g. in New Scientist) give the impression that the E. coli developed the ability to metabolizecitrate, whereas it supposedly could not do so before. However, this is clearly not the case, because the citric acid, tricarboxcylic acid (TCA), or Krebs, cycle (all names for the same thing) generates and utilizes citrate in its normal oxidative metabolism of glucose and other carbohydrates.5Furthermore, E. coli is normally capable of utilizing citrate as an energy source under anaerobic conditions, with a whole suite of genes involved in its fermentation. This includes a citrate transporter gene that codes for a transporter protein embedded in the cell wall that takes citrate into the cell. 6 This suite of genes (operon) is normally only activated under anaerobic conditions. this would be the sort of thing that mutations are good at: destroying things So what happened? It is not yet clear from the published information, but a likely scenario is that mutations jammed the regulation of this operon so that the bacteria produce citrate transporter regardless of the oxidative state of the bacterium’s environment (that is, it is permanently switched on). This can be likened to having a light that switches on when the sun goes down—a sensor detects the lack of light and turns the light on. A fault in the sensor could result in the light being on all

the time. That is the sort of change we are talking about.Another possibility is that an existing transporter gene, such as the one that normally takes up tartrate,3which does not normally transport citrate, mutated such that it lost specificity and could then transport citrate into the cell. Such a loss of specificity is also an expected outcome of random mutations. A loss of specificity equals a loss of information, but evolution is supposed to for the creation of new information; information that specifies the enzymes and cofactors in new biochemical pathways, how to make feathers and bone, nerves, or the components and assembly of complex motors such as ATP synthase, for example.However, mutations are good at destroying things, not creating them. Sometimes destroying things can be helpful (adaptive), 7 but that does not for the creation of the staggering amount of information in the DNA of all living things. Behe (in The Edge of Evolution) likened the role of mutations in antibiotic resistance and pathogen resistance, for example, to trench warfare, whereby mutations destroy some of the functionality of the target or host to overcome susceptibility. It’s like putting chewing gum in a mechanical watch; it’s not the way the watch could have been created. Much ado about nothing (again) it has no relevance to the origin of enzymes and catalytic pathways that evolution is supposed to explain Behe is quite right; there is nothing here that is beyond ‘the edge of evolution’, which means it has no relevance to the origin of enzymes and catalytic pathways that evolution is supposed to explain.8 A cat with four ears (not nine lives) by Don Batten A kitten born on a farm in has an extra pair of ears! 1 ‘Lilly’ is perfectly healthy. The extra ears do not hear; only her usual ears, and they hear quite normally.Animals, and even humans, can be born with extra toes/fingers/ears, and so on. Evolutionists sometimes use these extra bits, such as an extra pair of wings on a fruit fly, to claim that genetic information has increased spontaneously; that is, without an intelligent designer.2 As a propaganda tool, this does confuse some people.However, no new genetic information is involved with making these extras. The cat already has the information for making ears, and the fruit fly already has information for making wings. An error during development has merely caused the information to activate twice instead of once!If you used a photocopier to make a copy of a document and it malfunctioned and printed two copies, you would not conclude that you had created new information by this accident. It is like this with the extra organs that sometimes appear on animals (and plants). There is no new information created, so it has nothing to do with evolution!Lilly’s extra ears most likely came about because of a defect during development, rather than inheriting a defective gene from a parent. Chemicals in the environment can cause such defects. Everyone knows about how thalidomide caused many abnormalities in human babies—usually loss of limbs due to suppression of the information for making limbs, for example. Radiation can also cause defects, or they can be spontaneous.In Lilly, the defect resulted in the expression of the ear-design information twice, resulting in two pairs of ears. However, not all the information activated twice, because apparently only the external parts of the extra ears are present, since the ears do not hear. New plant colours—is this new information? One skeptic believes that he has found an example of ‘new information’ arising by mutations and natural selection. Could he be correct? Question/statements from skeptic Since I have some background in genetics and plant breeding, I can tell you that the entire field of plant breeding is based on ‘new information’ arising from random mutations. New traits do appear, at the molecular and morphological level new proteins, new pigments, etc. These are novelties.Two parents with blue eyes will generally produce children with blue eyes, and likewise two plants with white flowers will generally produce new plants with white flowers, but sometimes that seedlings with red or purple flower turns up, not because a recessive allele has been revealed, but because a mutation has altered an existing pigment or biochemical pathway to produce something entirely new, that has never existed before. This is NEW INFORMATION.As an example, there is nothing like an ear of corn in any other species of grass. It seems to be entirely unique in the plant kingdom. And yet there are three or four species of grass, very similar to corn in their overall growth, but with typical grass-like reproductive organs. The funny thing is, they will breed with corn to produce fully fertile offspring. It is clear that a combination of mutation and selection has produced in corn an unusual and entirely novel structure from a very typical grass— in other words, NEW INFORMATION. Response by Don Batten, Ph.D. The question comes from someone who does not understand the concept of information. The appearance of a ‘new trait’ does not have to involve the addition of information via the DNA coding. In fact, as bioinformatics expert Dr Lee Spetner has demonstrated (in his book, Not by Chance, Judaica Press), such is so unlikely that it could never be the basis for the increased information needed for molecules-to-man evolution. Information content is measured not by the number of traits, but by what is called the specified complexity of a base sequence or protein amino acid sequence. A mutation, being a random change in highly specified information contained in the nucleic acid base sequence, could almost never do anything but scramble the information; that is, reduce the information.Now sometimes such a loss of information results in a new trait —for example, purple or red flowers where there were only blue ones before. This would have to be studied at the DNA base sequence level (or amino acid sequence in the enzyme producing the pigment, or the pigment itself) to show this. For example, a blue pigment could be changed into a red or purple pigment by loss of a side-chain from the basic pigment molecule. Such a change would involve a loss of specified complexity and therefore a loss of information. Even an informationally neutral change could be responsible—this is not to be confused with Kimura’s neutral mutation, which has nothing to do with the concept of information, only the effect on survival. Even a change of one amino acid in a protein, not altering information content, can alter energy levels in such a way as to change the visible absorption spectrum, e.g. by reducing the number of consecutive conjugated bonds. And a small change in pH can have a large effect on color (this effect was overlooked by a group of molecular biologists who managed to get the gene for the blue pigment in hydrangeas into a rose—the rose was not blue, although the pigment was manufactured, because the cell pH was not the same as a hydrangea’s!).Of the many hundreds of antibiotic, herbicide and insecticide resistance mechanisms studied at a biochemical level, none involve addition of specified complexity in the DNA. Although some are ‘new traits’ due to mutations, all involve loss of information. An example is the loss of control over the production of an enzyme that happens to break down penicillin in Staphylococcus aureus, resulting in the production of greatly increased amounts of the enzyme and thus conferring resistance to penicillin. Another mode of antibiotic resistance due to mutation is decreased effectiveness of a membrane transport protein so that the antibiotic is no longer taken up by the cell (but the normal function of the transporter is also impaired and the bacterium is less fit to survive in the wild). However, much antibiotic resistance seems to be acquired by the transfer of plasmids from other species of bacteria via conjugation, which of course does not explain the ultimate origin of the information.What about the corn story? The questioner is probably correct about the species of grass and the origin of corn. I have no problem with that. Creationists would say that the species that interbreed with corn (maize) are of the same created kind (see Ligers and wholphins? What next?, Q&A: Speciation). However, until the biochemical/genetic basis of the

difference between maize and its wild relatives is determined, it cannot be said that the maize inflorescence is due to new information. Loss of information in some base sequences responsible for early steps in inflorescence development could easily for such seemingly large differences.It must be noted (again) that creationists do not say that mutations are always harmful, just that they are almost invariably a loss of information (i.e. specified complexity). Sometimes a loss of information can be beneficial, but it is a loss of information. For example, loss of function of wings in the flightless cormorant in the Galápagos Islands, which can now dive better than its flying cousins, or flightless beetles on a windswept island that are better off because they are less likely to be blown into the sea—see Beetle bloopers.Evolution needs swags of new information, if a microbe really did change into a man over several billion years. The additional new information would take nearly a thousand books of 500 pages each to print the sequence. Random changes cannot for a page, or even a sentence, of this, let alone ing for all of it. The evolutionist has an incredible faith! Sickle-cell anemia does not prove evolution! by Felix Konotey-Ahulu Sixth-graders I have lectured on genetic counselling invariably pop Dr Felix Konoteysome questions such as: Ahulu, M.D. (Lond.), ‘Is it true that the sickle-cell phenomenon has established Darwinian FR, DTMH, is a evolution as fact?’ world authority on Behind the question, of course, lies the assumption that observing sickle-cell disease, selection/adaptation involving a mutation (an inherited random change with 25 years’ or defect) somehow implies that the more complicated forms seen experience as a today arose from simpler forms traced back ultimately to one-cell physician, clinical organisms.The answer is of course ‘no’. In the early 1950s I did a geneticist and course on evolution and metaphysics at the feet of Professor J.Z. consultant physician Young, perhaps the greatest evolutionist of recent years. Nothing has in Ghana and happened during the past 30 years in molecular biology in general, subsequently in and the sickling phenomenon vis-à-vis malaria in particular, to have London. He is a raised evolution from theory to established fact. visiting professor at Howard University College A scientific theory that tackles ‘origins’ must of necessity find that it is of Medicine in Washington, and honorary out of its depth. In his 1985 book, The Limits of Science, Nobel consultant to its Center for Sickle Cell Disease. laureate Sir Peter Medawar stated clearly that ultimate questions like He is the author of a major 643-page ‘origins’ go ‘beyond the explanatory competence of science’. For text,The Sickle Cell Disease Patient(Macmillan, people to state that because sickle-cell trait children are resistant to 1991, ISBN 0333-39239-6; Tetteh-A’Domeno cerebral malaria, therefore the whole neo-Darwinian scenario is fact, is Co., Watford, UK, ISBN 0-9515442-2-5, 1996). like saying that my black skin’s ability to withstand the tropical sun This article is abstracted with Dr Konoteyestablishes an evolutionary process, starting perhaps with a ‘big Ahulu's permission from pages 106–108 of his bang’, leading to single-celled organisms, multicelled organisms, book. invertebrates, vertebrates, and on up to man. In any case, although malaria would certainly seem to be a major factor in maintaining a high frequency of such inherited red cell defects, the real situation concerning their distribution also involves a complex interaction of viral infections, dietary habits and social factors. There is not the random mating which Western population geneticists often assume, and African anthropogenetics cannot ignore the effect of marriage customs, and social and religious habits that lead to in-breeding, for example. Stuttering facts The hypotheses of some anthropologists and theoretical geneticists detract from more serious work. While natural selection is a fact, attention to selection hypotheses is frequently overdone and other factors ignored. In one case it was found that out of 10 West African individuals carrying the sickle-cell trait and living in the UK, there were five who had the genetic predisposition to stuttering (which is known to be high in West Africa). The temptation to use natural selection explanations to link the stuttering gene frequency to child-hood malaria and sickling overlooks some important sociological facts.First, most who have the stuttering tendency in Ghana in particular are left-handed, which is a major social disadvantage. Relatives heckle and bully the left-hander for doing household jobs with the ‘wrong hand’. The already nervous left-hander is then forced in the schools to write with the right hand, evoking a constant state of agitation.The desire to excel against all odds is great, so left-handers are generally better at their studies. You will thus find a higher number of left-handers, and thus more stutterers, in any academic institution. If that institution is in northern Nigeria, for instance, 30 per cent of these stutterers will also be sicklers, simply because 30 per cent of the rest of the population are sicklers. This has nothing to do with malaria and selection, nor does the fact that of the five consultants in the haematology department of a famous African teaching hospital, 80 per cent had the sickle-cell trait.I have indicated more than once that African anthropogenetics would be much better served by thinking along factual lines rather than theoretical evolutionary concepts. The same could certainly be said for science and medicine in general. Sickle-cell disease Sickle-cell anaemia is caused by an inherited defect in the instructions which code for the production of haemoglobin, the oxygen-carrying pigment in red blood cells. You will only develop the full-blown, serious disease if both of your parents have the defective gene. If you inherit the defect from only one parent, the healthy gene from the other one will largely enable you to escape the effects of this serious condition.However, this means you are capable of transmitting the defective gene to your offspring, and it also happens that such carriers are less likely to develop malaria, which is often fatal. Being a carrier of sicklecell disease without suffering it (heterozygosity is the technical term) is far more common in those areas of the world which are high-risk malaria areas, especially Africa.This is good evidence that natural selection plays a part in maintaining a higher frequency of this carrier state. If you are resistant to malaria, you are more likely to survive to on your genes. Nevertheless, it is a defect, not an increase in complexity or an improvement in function which is being selected for, and having more carriers in the population means that there will be more people suffering from this terrible disease. Demonstrating natural selection does not demonstrate that ‘upward evolution’ is a fact, yet many schoolchildren are taught this as a ‘proof’ of evolution.

Evolution of a new master race? by Jonathan Sarfati

News reports are talking about a German baby ‘superman’.1 He is only 4, but his thigh already has twice the muscle mass of most kids his age, and half the fat He is strong enough to hold 3 kg (7 lb) weights outstretched, hard for many adults His strength is the result of a genetic mutation (an inherited copying mistake in the DNA ‘instructions’) that gives him the extra amount of muscle.The child’s mother was a muscular 24-year-old former sprinter who had one copy of this mutation, but paired with the normal gene Her brother and three other close male relatives also seem to have this mutation, because they are very strong. One of them was a construction worker who can unload heavy curbstones by hand.The boy has two copies of the mutated gene, the other one almost certainly from his father. Evolution proved? Is this not an example of ‘evolution in action’, a way in which organisms can become ‘bigger and better’? Not at all. It pays to look closely at the nature of the mutation in this case. Normally, muscle growth is well controlled, and one controller is a protein calledmyostatin or growth/differentiation factor 8 (GDF-8). This new mutation actually damages the gene that produces myostatin.2 As a result, the myostatin protein is not properly formed and the muscles grow in an uncontrolled fashion.Evolution from goo to you via the zoo requires a huge number of mutations to increase information content. This is to build newstructures and enzymes that didn’t previously exist. If this were occurring, we would expect to find lots of information-increasingmutations. But instead we have yet to find even one heritable random mutation of this type. 3 Rather, observed mutations are either neutral or information-losing.Notice that we don’t deny there are beneficial mutations, i.e. mutations that benefit their possessors. But even these are going in the wrong direction to help turn bacteria into babies. The ‘superbaby’ mutation is just one in a long line of information-losing mutations that might count as beneficial. It obviously can’t explain how muscles and myostatin evolved in the first place.Indeed, readers of Creation magazine and our website might that we have written on exactly the same thing in animals. 4 The Piedmontese and Belgian Blue cattle are extremely muscular precisely because a mutation results in the production of a defective myostatin protein. 5 A similar mutation has produced muscular mice.It is debatable whether the mutation is really beneficial in the long run. The Belgian Blue mutation has side effects, for example, reduced fertility. And doctors worry that this superboy might later suffer from health problems including heart trouble. It should not be surprising that a protein like myostatin is there for a reason, so destroying its effectiveness would cause problems.But the main point is still that the mutation is losing information, not gaining it. So it is just like the wingless beetles on windswept islands. They can’t fly up so the wind doesn’t sweep them into the sea, which is a good thing for their survival. But they have still lost the power of flight. This doesn’t explain how wings or flight could have evolved in the first place.6 The 'werewolf' gene by Thomas Awtry The general public is bombarded with evolutionary propaganda through television, radio, magazines, and newspapers. A good example of such was found in a recent newspaper article by Associated Press science writer Malcolm Ritter, 'Scientists move closer to finding "werewolf" gene'.1The article describes a very rare condition of excessive hairiness which is not known to afflict anybody outside a large family in rural Mexico. Some newborn males are born with hair all over their face, including the eyelids, with only the lips remaining hairless. Men with the condition have inch-long hair all over their face, and on some parts of their upper body. Women with the condition, while not being affected to the same degree as the men, have random patches of hair on the face and on the body.According to the article, scientists have moved closer to finding the gene, which someday may help treat baldness and excessive hairiness. Readers are then informed that the werewolf condition 'comes from an aberrant gene that runs through their large family, perhaps after reawakening from a long sleep during human evolution'. The last phrase speaks volumes: this hairiness condition is said to be a leftover trait from our alleged ape-type ancestry.As is true of several evolution-creation topics of discussion, the difference lies not in the data under consideration, but rather in the interpretation of the data. While it is true that an aberrant gene now runs in the one family, it does not therefore mean that it is a 'reawakening' effect of 'human evolution'. Another interpretation which is just as viable is that it is simply a mutated gene. The mutation changed the amount of a physical feature (hairiness) of humans which has existed in humans from their initial creation. This may be from damage to a gene controlling hair growth or its distribution.And as creationists have been saying for years about all mutations, this random mutation is harmful, if anything. The article reveals how much the individuals with the trait suffer, and how most become outcasts of society, often becoming of sideshows for a travelling circus. It is possible then that this condition might become even more rare as selection works against these individuals. Of course, this s the creationists' explanation, but not the evolutionary explanation. , Darwinian evolution requires mutations to be favourable and cumulative, increasing viability.Another physical phenomenon which some evolutionists have claimed in the past as evidence of evolutionary ancestry is when a child is born with a 'tail'. The 'tail', however, is really not a tail or part of the coccyx, but is rather a fatty tumour.2 The lesson to be learned, though, is that no one now claims it to be due to a 'reawakening' of human evolution. We can learn several lessons from the article: Sometimes there is more than one interpretation of data. Evidence suggests mutations to be random and detrimental. And because Evolution must have favourable, 'uphill' mutations, and many of them, therefore Evolution, like werewolves, is a myth.

‘Evolution in a Petri dish’? Have scientists demonstrated evolution in action? by Don Batten So trumpeted Scientific American, December 2007, p.17. What are they talking about? Some Spanish researchers managed to get some nematodes (tiny roundworms) commonly used in lab experiments to grow in the presence of bacteria that normally kill them. Apparently a mutant form of the nematode was adapted to living with the bacteria. This is supposed to demonstrate ‘evolution’.Have they demonstrated that mutations can create new, complex features—the sorts of changes needed to change worms into fish, for example? The biochemical basis of this nematode

adaptation has not yet been elucidated, but the article reveals that,‘The difference in the worms’ movements shows that the ability to survive bacteria does not come without cost. The mutated individuals breathe poorly—they consume 30 percent less oxygen—and they are not as fast as their wild cousins in competing for food. … From a Darwinian perspective, Martinez says, the phenomenon represents a “second-class selection” that resembles the utility of the sickle cell mutation against malaria.’So we are looking at ‘broken’, defective worms, not ones that are on an upward path to greater complexity. These worms are not going to become humans!Sometimes it is helpful to be broken—as in the beetles with defective wings that could not fly on a windy island (and thus avoided being blown into the sea)—seeBeetle bloopers. Note the comparison with sickle cell trait. This is another example of a broken gene that happens to be adaptive under certain circumstances, according to one of the world’s leading experts on the disease,Dr Felix Konotey-Ahulu. That’s what mutations do: they break existing genes, not create brand new ones.Mutations do not create the complex, integrated DNA code needed to explain how some worms changed into fish or ultimately how microbes changed into mankind. Nor do natural processes explain the origin of incredibly complex, essential cellular components such as the ATP synthase complex that all living things need to have to live (see Fantastic voyage), or the DNA code that is common to all living things for that matter (see DNA: marvellous messages or mostly mess?).In a side bar note, the editors claim that this observation ‘provides evolution with experimental evidence—evidence that creationism does not have.’ Now creationists accept that mutations occur, that natural selection occurs and that adaptation occurs (see the many articles on this web site under Mutations Q&Aand Natural Selection Q&A), so whoever wrote this either has no idea of what he/she is arguing against, or is being deceptive.They also claim that this nematode is ‘on the verge of speciation’. But creationists don’t deny that ‘speciation’ occurs either—yet another straw man argument, as speciation can happen without natural processes having to invent new complex features. For example, different species of cattle (Bos spp.) all have the same suite of organs; they only vary in size, colour, etc. See: Speciation Q&AThis article is yet another example of the deceptive bait-and-switch trick, or equivocation, that is so favoured by evolutionary propagandists like the editor of SA, John Rennie. My colleague, Jonathan Sarfati, countered Mr Rennie on a previous occasion when Rennie launched into an incredibly ill-informed scathing attack on creationists. See 15 ways to refute materialistic bigotry.If by ‘evolution’ Mr Rennie and Co. mean that organisms can adapt by mutations and natural selection, then we creationist biologists readily accept this, so they have not provided evidence for anything that contradicts ‘creationism’. But if they mean that they have demonstrated that worms can change into fish (which is the grand claim of Evolution / Darwinism), then what they have shown has nothing to do with proving this.Interestingly, the editorial sidebar quotes a Spanish scientist as saying, ‘“To my knowledge, it is the first time that an evolutionary law has been demonstrated” in a complex creature’. That’s an interesting ission, considering that evolutionists have been telling us for decades that evolution is a fact. But the article itself refutes this claim, pointing out that the adaptation in the nematode resembles sickle cell in humans. In their endeavour to hype up the findings to try to score a point against ‘creationism’, they contradict themselves. Warfarin resistance in rats is another example of a mutation breaking an existing gene in a complex creature where it is adaptive (see Rats! Another case of sickle cell anemia). The CCR5 delta32 mutation in humans is another example of an adaptive mutation in humans (conferring resistance to HIV), but again, it is a broken gene. There are many more examples of mutations breaking, wrecking existing genes where they simply cause disease, with no benefits whatsoever. Indeed, over a thousand human diseases are known to be caused by mutations. The mutation-natural-selection train is going in the wrong direction.So, Mr Rennie and Co., of Scientific American, you have not demonstrated Evolution at all, only ‘Devolution’ that happens to be adaptive, which is no threat to creationists. When you find a mutation or a series of mutations that occurred naturally that creates one of the hundreds of enzyme complexes upon which life depends, you might perhaps have a valid point to make. But I won’t hold my breath while I wait for an example, I might end up breathless like the nematodes! Breathtaking new frog surprise by Carl Wieland The discovery that this rare frog, living in Borneo, has no lungs, is being used to promote evolution. But as the article shows, this is off the mark.Making headlines is an amazing discovery about a unique species of frog. The amphibian is described as ‘bizarre’, a fitting epithet given that it is missing lungs altogether (the wordplay in the title is intentional).1 The 5 cm (2 inch) long Barbourula kalimantanensislives in the jungles of Borneo, and apparently gets all the oxygen it needs through its skin. It was first known about some 30 years ago, but being very rare, only one other specimen has been discovered to date, and neither was dissected.Some of the media descriptions associate the frog with the word ‘primitive’, a term loaded with evolutionary connotations. But is it somehow an intermediate, a form closer to some ancestor that had not evolved lungs yet? Not at all; even most informed evolutionists would agree with the conclusion that it is almost certainly descended from a frog that once had lungs.We can ‘connect the dots’ to lead to a very likely scenario of how this species arose.Frogs with lungs already get a significant amount of their oxygen through the skin—this is absorbed directly from the water.Even though its habitat is close to the equator, the streams that B. kalimantanensis lives in are very fast-flowing and extremely cold. Such waters contain large amounts of dissolved oxygen.There is a very similar species of frog in the Philippines that does have lungs, and the two may well be descendants of the same created kind.If one such frog with lungs happened to have a (information-losing, hence not evolutionary in the ‘microbes to man’ sense) mutation causing lungs to disappear or dramatically reduce, then the descendants of such a frog exhibiting this loss/defect wouldBe well able to survive in their oxygen-rich home waters, using the existing mechanism of skin-breathing. But in addition:They would actually be at a selective advantage compared to their lung-equipped co of the population. In such fast-moving streams, those with lungs (which make the creature float) would be more likely to be carried away from the breeding population. Also:Without lungs, the body would flatten more readily, increasing the available surface area for skin-breathing still more.Thus, just as in the case of the blind cave fish that have ‘devolved’ from fish with eyes (see this article), natural selection would soon ensure that the entire population was lungless. Such a downhill change would only need a few generations, especially in a small isolated population. No vast time spans are required.Although such fascinating features of the natural world are always trumpeted in evolution-ing , they actually make far more sense in a framework of history. Vast amounts of information were created in separate biological populations at the beginning, and the direction of biological change since creation has been overwhelmingly downhill—the very opposite of the grand-scale claims of evolution. CAN MUTATION BE THE MECHANISM FOR EVOLUTION?

Hox (homeobox) Genes—Evolution’s Saviour? by Don Batten Some evolutionists hailed homeobox or hox genes as the saviour of evolution soon after they were discovered. They seemed to fit into the Gouldian mode of evolution (punctuated equilibrium) because a small mutation in a hox gene could have profound effects on an organism. However, further research has not born out the evolutionists’ hopes. Dr Christian Schwabe, the non-creationist sceptic of Darwinian evolution from the Medical University of South Carolina (Dept. of Biochemistry and Molecular Biology), wrote: ‘Control genes like homeotic genes may be the target of mutations that would conceivably change phenotypes, but one must that, the more central one makes changes in a complex system, the more severe the peripheral consequences become. … Homeotic What is the REAL message of the patterns changes induced in Drosophilagenes have led only to monstrosities, and of life? most experimenters do not expect to see a bee arise from The Biotic Message their Drosophila constructs.’ (Mini Review: Schwabe, C., 1994. Theoretical Walter ReMine limitations of molecular phylogenetics and the evolution of relaxins. Comp. Biochem. Physiol.107B:167–177).Research in the six years since Schwabe This book scientifically fights wrote this has only born out his statement. Changes to homeotic genes cause evolutionists on their , monstrosities (two heads, a leg where an eye should be, etc.); they do not on their issues, using their change an amphibian into a reptile, for example. And the mutations do not testimony, and their ground add any information, they just cause existing information to be mis-directed to rules. It dismantles many produce a fruit-fly leg on the fruit-fly head instead of on the correct body evolutionary illusions, and offers a new segment, for example.Evolutionists, of course, use the ubiquity of hox genes creation theory of biology: Life was in their argument for common ancestry (‘Look, all these creatures share these designed to shout that it had only ONE genes, so all creatures must have had a common ancestor’). However, designer, and to resist all other commonality of such features is to be expected with their origin from the explanations. 538 pages, hardbound. same (supremely) intelligent designer. All such homology arguments are only arguments for evolution when one excludes, a priori, origins by design. Indeed many of the patterns we see do not fit common ancestry. For example, the discontinuity of distribution of hemoglobin-like proteins, which are found in a few bacteria, molluscs, insects, and vertebrates. One could also note features such as vivipary, thermoregulation (some fish and mammals), eye designs, etc. For more detail, see The Biotic Message. Gain-of-function mutations: at a loss to explain molecules-to-man evolution by Dr Jean Lightner Evolutionists point to mutations as providing the raw material necessary for the onward, upward change they believe has occurred since life began. Mutations which affect an organism are often categorized into two basic types: loss-of-function mutations and gain-of-function mutations.1A loss-of-function mutation is ‘a mutation that results in reduced or abolished protein function’.2 A gain-of-function mutation has been defined as ‘a mutation that confers new or enhanced activity on a protein’. 3 A good understanding of these two types of mutations can be gained by examining mutations in the gene coding for a receptor located on thyroid cells and how these changes affect the control of thyroid hormone levels in the body. A well designed pathway The thyroid hormones, triiodothyronine (T3) and thyroxine (T4), affect essentially every tissue in the body. These hormones are necessary for maintaining an appropriate basal metabolic rate and are produced by the thyroid gland located in the front of the neck (figure 1, right). Thyroid stimulating hormone (TSH), a glycoprotein secreted by the pituitary gland in the brain, binds with the TSH receptor on the surface of the thyroid follicular cells. This initiates a series of biochemical events that result in an increase in circulating thyroid hormone. The rise in blood thyroid hormone concentration is detected by the pituitary which responds by decreasing the release of TSH. With this negative loop the body is able to carefully control circulating levels of the thyroid hormones. 4 Several diseases exist where the body is unable to properly regulate thyroid hormone levels in the blood. Hypothyroidism occurs when there are insufficient levels of thyroid hormone and is often associated with signs of intolerance to cold, lethargy, weight gain and cool, dry skin. Hyperthyroidism is caused by excessive thyroid hormone and signs may include rapid heart rate, intolerance of heat, weight loss and fatigue.5 Loss-of-function mutations One important part of this regulatory pathway is the TSH receptor found on the surface of cells in the thyroid gland. Not surprisingly, mutations within the gene coding for the TSH receptor can create problems for the body in controlling thyroid hormone levels. A number of loss-of-function mutations have been identified which impair the receptor to different degrees and thus result in varying degrees of hypothyroidism.6Like most loss-of-function mutations, these mutations are generally recessive. This means that clinical signs are typically observed only when both genes (one being inherited from each parent) for the receptor carry such a mutation. There are around 20 different loss-of-function mutations in this gene that have been described in the literature.7 A gain of … what?

Figure 1. A highly simplified schematic showing the negative loop used by the body to maintain appropriate thyroid hormone (T3 + T4) levels. Thyroid stimulating hormone (TSH) is secreted by the pituitary and binds to its receptor on the follicular cells of the thyroid gland. This initiates a series of biochemical events that result in the release of more T3 + T4. Elevated T3 + T4 levels are detected by the pituitary, resulting in a decrease of TSH secretion. This is an important part of controlling hormone levels and maintaining homeostasis. Many other factors (not shown) also play a role in the regulation of T3 + T4. (Click on picture to see a higher resolution version)

Other mutations within the gene for this receptor result in a ‘gain-of-function’.8 In this case the receptor is constitutively active, or ‘switched on’ even when TSH is not present. Many of these mutations have been identified, yet most of these are not heritable (germ-line) but somatic mutations.9 Most commonly, activating mutations are found in thyroid nodules (over 2 dozen different mutations, some identified in more than one individual) which develop from long term iodine deficiency or exposure to goitrogens.10 Activating mutations have also been described in cases of sporadic hyperthyroidism and thyroid cancer (carcinoma—see figure 2, right).7 At this point it should be apparent that the ‘enhanced activity’ mentioned in the definition has an unwarranted positive connotation. Activating mutations may result in more product, but they don’t result in something more Figure 2. In addition to controlling the output of thyroid valuable.11 Instead, there is a loss of control of a pre-existing hormone, the TSH receptor is part of a second biochemical biochemical pathway. Living things depend on being able to pathway that regulates the growth and development of maintain homeostasis, or a balance. Although the pituitary 5 cells in the thyroid gland. Mutations in the genes coding responds to the high thyroid hormone levels by decreasing for such proteins can often lead to the development of TSH release, it has no effect on the constitutively active cancer. (Click on picture to see a higher resolution version). receptor. The excess thyroid hormone doesn’t ‘enhance’ After: National Cancer Institute (US). anything, it causes disease. A new, but not improved, function One gain-of-function mutation is different and results in a protein with a ‘new function’. In this case the mutation alters the receptor so it responds to human chorionic godadotropin (HCG). HCG is a hormone that increases early during pregnancy to help maintain the pregnancy. While HCG naturally stimulates the TSH receptor to some degree in early pregnancy, the mutation causes the receptor to be so sensitive that overt gestational hyperthyroidism develops.12 Again, the pituitary responds to increased thyroid hormone by decreasing TSH, but since the receptor is responding to HCG this doesn’t solve the problem. When a protein loses its specificity and becomes involved in reactions it wouldn’t normally be involved in, it has a ‘new function’. This is often referred to as promiscuous activity. Even though very rarely a protein with promiscuous activity may prove beneficial under special circumstances, still the loss of specificity represents a downward change in the genome.13 It is impossible to build complex pathways with appropriate mechanisms by randomly introducing errors. Conclusion It is worth noting that mutations produce new alleles (variant forms of a gene) and certainly add variety. However, molecules-to-man evolution requires the generation of new information to build new, complex, interdependent biochemical pathways. Despite the deceptive wording found in the gain-of-function definition, there is no increase of information or improvement of biochemical pathways. Without a mechanism for developing such pathways, evolution is nothing more than a myth. Instead, what we observe fits exactly with what we would expect if the young age model is true. Living things are very well designed. Errors introduced by mutations do not build new, well integrated biochemical pathways; instead they often cause disease.

Are ‘gain of function’ mutations really downhill and so not ing of evolution? A biologist questions Mutations are good at getting rid of genetic information; in this case information for making horns.Daniel H. of the United Kingdom, who gave permission for the publication of his name, wrote: Dear CMI, I’m a scientific researcher and I came across your site by accident in a google search, in the form of the article ‘Gain-of-function mutations: at a loss to explain molecules-to-man evolution’, by Dr Jean Lightner. I feel the urge to provide you with some on this article. It appears to me, as written, to demonstrate nothing and to be either misled or misleading. While the example of TSH receptor gain-of-function mutations producing disease could certainly be used as part of a wider discussion of gain-of-function mutations in general (which are also associated with cancer), fundamentally you cannot take one example and ‘prove’ an argument completely based upon it. The author completely fails to demonstrate how the example of this particular TSH mutation proves some universal rule about the effects of gain of function mutations.For instance I work with G protein coupled receptors, a large family of membrane receptor proteins. The adrenoceptor (for adrenaline) and the nicotinic acid receptor (for ketone bodies produced in starvation) appear to both result as divergent descendents of an ‘ancestral’ G protein coupled receptor, through gain/loss of function mutations over genomic history. Now they both respond to different chemicals; however, both now also play useful roles, even having grown into vital roles. Would you like to discuss this possibility as well?Evolution sometimes means that bad variants of a gene don’t persist—eg the TSH receptor example—but as any biologist would tell you it also has the capacity to promote ‘good’ ones.For the record, I am a Catholic and standing up for Christianity in the field of biology is a challenging and vitally important thing. I don’t feel this kind of bad ‘science’ helps at all. It has no credibility. Thanks for the chance to provide you with this . Yours sincerely, Daniel

Here is Daniel’s email repeated with a response from Dr Jean Lightner, author of the questioned article, interspersed in common email fashion: Dear CMI, I’m a scientific researcher and I came across your site by accident in a google search, in the form of the article ‘Gain-offunction mutations: at a loss to explain molecules-to-man evolution’, by Dr Jean Lightner. I feel the urge to provide you with some on this article. It appears to me, as written, to demonstrate nothing and to be either misled or misleading. While the example of TSH receptor gain-of-function mutations producing disease could certainly be used as part of a wider discussion of gain-of-function mutations in general (which are also associated with cancer), fundamentally you cannot take one example and ‘prove’ an argument completely based upon it. The author completely fails to demonstrate how the example of this particular TSH mutation proves some universal rule about the effects of gain of function mutations. Dear Daniel, Thank you for taking the time to write. I wrote the article you mentioned a number of years ago because the term ‘gain of function’ implies to the lay person that something like ‘onward, upward evolution’ is occurring. In the article I was able to give an example of a loss of function mutation and two types of gain of function mutations. So the intent of the article was to inform readers about what these mean (which is best done, in my opinion, by including specific examples) and show that they do not inherently molecules-to-man evolution. For instance I work with G protein coupled receptors, a large family of membrane receptor proteins. The adrenoceptor (for adrenaline) and the nicotinic acid receptor (for ketone bodies produced in starvation) appear to both result as divergent descendents of an ‘ancestral’ G protein coupled receptor, through gain/loss of function mutations over genomic history. Now they both respond to different chemicals; however, both now also play useful roles, even having grown into vital roles. Would you like to discuss this possibility as well? I have been doing some research on seven-transmembrane G-protein coupled receptors (MCRs and Olfactory receptors). They are fascinating and I have argued that some were designed to change. In fact, I argue that our worldview gives us reason to look for directed changes in genes. One of these articles appears on the web and the other is scheduled to appear in the next issue of Journal of Creation.I would love to discuss with you the possibility that the two receptors you mention may have developed from an ‘ancestral’ G-protein. It would have been nice to have had a reference which explores this suggestion in more detail, but we certainly can begin a discussion on the information you provided. First, I would like to mention a few things that may help you better understand what I am saying.The word evolution is sometimes defined as ‘change in the genetic makeup of a population over time.’ I wholeheartedly agree that this occurs (as do the many other creationists I know) and I discuss it in much of my writing. However, evolution also refers to the idea that all life on earth has developed from a single common ancestor by random, chance processes. In college when I asked for evidence of evolution, I was always given examples of the former and expected to accept that this implied the latter had occurred.When doing science we will always have some assumptions and we should be aware of what these are. One I expect we share is that science is a useful tool for learning about the world around us. There are a number of assumptions involved in molecules-toman evolution that I am unwilling to accept on faithI am constantly astounded at the layer upon layer of complexity we find in living things; there are numerous biological features that ‘wow’ human engineers (hence the rapidly growing field of biomimetics). While you may believe that somehow ‘God did it,’ by accepting common ancestry you are still looking at things through an ‘atheistic’ lens which basically assumes that natural processes can for this. See: Design features Q&A. It assumes that random errors (which are what evolutionists consider all mutations to be) can increase the level of complexity of biological systems. Random errors naturally destroy complexity orders of magnitude faster than they build it. Natural selection is not effective at eliminating these errors, so there is no plausible naturalistic way to increase specified complexity. See, for example, From ape to man via genetic meltdown: a theory in crisis.It uses equivocation or bait-andswitch to imply that it is scientifically plausible. the two definitions of evolution mentioned above? One is expected to assume they are essentially synonymous. However, observed genetic changes over time have not been shown to effectively increase biological complexity, so those who operate in the evolutionary paradigm do so by blind faith and not because of the evidence. See: Separating the sheep from the goats.Back to the issue of an ‘ancestral’ G protein: I am certain that you could show that a series of changes from a putative ancestral protein could for the two receptors you mention. This is rather weak circumstantial evidence that something like this may have happened. Would the animal carrying the ‘ancestral’ protein have been viable? Would the intermediates be viable? The ‘circuitry’ these receptors are part of is incredibly complex. How does one propose a series of possible changes in one protein and have an explanation of how the two actual proteins are each well integrated into complex circuits where they effectively regulate important functions?I’d like to point out that one can always make a ‘phylogenetic tree’ whether things are actually related or not. I can take the silverware and cutlery in my kitchen, lay them out on the table, and give you a very nice story of how they all evolved from the spoon over a period of time. Someone else may disagree and feel they all descended from a butter knife. Either way, a good story does not necessarily correlate with reality. Evolution sometimes means that bad variants of a gene don’t persist—eg the TSH receptor example—but as any biologist would tell you it also has the capacity to promote ‘good’ ones. As a veterinarian I know that persistence of bad variants is a widespread problem. Recessive disorders are common and natural selection is not effective at eliminating them. In humans, many diseases strike after the childbearing years, and so defective genes get ed on whether they are recessive or not. As I pointed out in #3 above, naturalistic processes cannot really for an increase in complexity even though we are often told that they can. ARE MUTATIONS EVER BENEFICIAL? CCR5-delta32: a very beneficial mutation by Andrew Lamb Cysteine-cysteine chemokine receptor 5 (CCR5) is found in the cell membranes of many types of mammalian cells, including nerve cells and white blood cells. 1,2 The role of CCR5 is to allow entry of chemokines into the cell 3—chemokines are involved in signaling the body’s inflammation response to injuries. 4The gene that codes for CCR5 is situated on human chromosome 3. Various mutations of the CCR5 gene are known that result in damage to the expressed receptor. One of the mutant forms of the gene is CCR5-delta32, which results from deletion of a particular sequence of 32 base-pairs. This mutant form of the gene results in a

receptor so damaged that it no longer functions. But surprisingly, this does not appear to be harmful:Yersinia pestis seen at 2000x magnification. This bacterium, carried and spread by fleas, is generally thought to have been the cause of millions of deaths.‘It’s highly unusual,’ says Dr. Stephen J. O’Brien of the National Institutes of Health in Washington D.C. ‘Most genes, if you knock them out, cause serious diseases like cystic fibrosis or sickle cell anemia or diabetes. But CCR5-delta32 is rather innocuous to its carriers. The reason seems to be that the normal function of CCR5 is redundant in our genes; that several other genes can perform the same function.’4Moreover, this mutation can be advantageous to those individuals who carry it. The virus HIV normally enters a cell via its CCR5 receptors, especially in the initial stage of a person becoming infected.5 But in people with receptors crippled by the CCR5-delta32mutation, entry of HIV by this means is blocked, providing immunity to AIDS for homozygous carriers and greatly slowing progress of the disease in heterozygous carriers. 6– 8 Up to 20%8 of ethnic western Europeans carry this mutation, which is rare or absent in other ethnic groups. 9–11 This suggests that theCCR5-delta32 mutation was strongly selected for sometime during European history. Some researchers have proposed that the plague epidemics that repeatedly swept Europe during the Middle Ages were responsible.12 However, recent experiments in mice suggest that Yersinia pestis, the cause of plague, can infect mammalian cells by other means13–15 and so some scientists have proposed that smallpox, which is caused by the variola virus, was the selection agent that historically caused CCR5-delta32 carriers to proliferate in Europe.15There has also been research suggesting that CCR5-delta32 hampers development of cerebral malaria from Plasmodium infection,16 and that it may slow progression of Multiple Sclerosis.17,18With the advantage of providing full or partial immunity to certain diseases, and with no apparent disadvantages [But see Addendum March 2009. Ed.], CCR5-delta32 can be considered a prime example of a beneficial mutation—a mutation that decreases the information content of the genome and degrades the functionality of the organism, yet provides a tangible benefit.19To date over 10,000 specific disease-causing mutations of the human genome have been identified.20 In contrast, only a handful of beneficial mutations have been discovered, none of which involve an increase in genetic information as required by evolution. All this is highly consistent with the young age of a very good creation21 followed by the Fall,22 and a subsequent six millennia23 of cumulative physical degeneration.24 However, it clashes irreconcilably with the evolutionary view that the accumulation of mutations over time brings about upward evolution (increasing functional complexity).In original creation, the CCR5 receptor would not have constituted an entryway for pathogens. It may be that infectious agents like HIV only became pathogenic after degeneration from their original ‘very good’ created state. Or it may be that humans did not live in the same environment as such pathogens and so were just not exposed to them. Perhaps both these scenarios apply (see The origin of bubonic plague on p. 7). Addendum August 2007 ‘A new generation of sophisticated therapies designed to HIV-proof the immune system promises to enter the clinic soon. For example, [Carl] June, working with Sangamo Bio-Sciences in Richmond, California, later this year plans to start trials in 12 HIV-infected people of a gene therapy designed to endow immune cells with a genetic mutation that protects them from HIV.To infect immune cells, HIV must first bind to chemokine receptors. Researchers discovered in 1996 that people who had a naturally occurring mutation in their genes for one of these, CCR5, were strongly protected from developing AIDS—or even becoming infected in the first place—and suffered no ill effects from lacking the receptor.Sangamo specializes in developing enzymes called zinc finger nucleases that can bind to genes, clip their DNA, and repair mutations (Science, 23 December 2005, p. 1894). But for the HIV gene therapy, they’ve created a nuclease to specifically disrupt the CCR5 gene in the same manner as the natural mutation. In the new trial, researchers will put the gene for this zinc finger nuclease into an adenovirus vector, transduce harvested CD4+ T cells of HIV-infected people, and infuse those cells back. June says this is the first gene-therapy experiment that aims to create a phenotype that’s known to confer disease resistance.’26 Addendum March 2009 A reader alerted us to the fact that at least one drawback associated with this mutation has been found. The CCR5-delta32 mutation is strongly associated with a chronic and potentially life-threatening liver disease: Eri, R, et al., CCR5-Delta 32 mutation is strongly associated with primary sclerosing cholangitis, Genes And Immunity 5(6):444–450, September 2004, .

The mutant ‘feather-duster’ budgie by Andrew Lamb When a clutch of four budgerigar chicks hatched out one sunny September day in 1999, it was a happy occasion for their breeder, Damien Harris of New Zealand. It wasn’t until they began to grow feathers a few weeks later that Damien noticed something odd about one of the chicks. Her feathers were curly instead of straight, and they just kept growing—and growing —and growing!Because this odd chick (pictured below) needed special care, Damien didn’t sell her, but instead gave her to bird-lover Warren Scholes, who named her Nora, after a local political character. Nora Nora’s long, curly feathers seemed to lack some component of the normal barb, barbule and hook structures of standard feathers, and they greatly hampered her mobility. Although able to eat normal budgie fodder and shuffle around, Nora couldn’t climb, preen or fly like other budgies, and she could hardly chatter or squawk either. However, with Warren’s help she did eventually learn to perch on the low rung in her cage.Nora’s parents were both descendants of English show budgies, the only birds known to produce ‘feather duster’ mutants, the first such case being reported in England in 1966. 1,2 Breeders think a mutation (genetic copying mistake) in a recessive gene causes the problem.Since Nora’s three siblings were healthy, they must have each inherited a good copy of the gene from at least one of the two parents. (If the gene from their other parent was defective, the good copy would override it.) If they inherited one good copy and one mutant copy they would be carriers of the disease, while remaining healthy themselves.When the copies from both parents have this mutation, as with Nora, the ‘feather duster’ syndrome results. To avoid the possibility of more chicks like Nora, Damien separated Nora’s parents, and did not breed them together again.These ‘feather duster’ mutants also carry some strains of Budgerigar Herpesvirus that aren’t found in normal budgies, but experts don’t know whether the virus plays a role in this genetic problem.3 As their bodies divert precious nutrients and energy into

continual feather growth, these mutant birds suffer severe muscle wasting. Most die after four to eight months. Warren gave Nora special care, but even with this attention she managed to live only 12 months before succumbing, whereas a typical budgie lifespan is anywhere from six to 14 years. 4Mutations, disease, death—how did our world come to be such a tragic place? The ‘feather duster’ mutation probably damages the control gene responsible for turning off feather growth. Though rarely observed in birds, many similar mutations are known in mammals. For example, just as Nora had feathers that wouldn’t stop growing, so too poodles have hairthat won’t stop growing. Most dogs moult each spring, but poodle hair just keeps on growing non-stop all year round! Some scientists think this is caused by a mutation in the control gene that regulates moulting. It makes poodles a favourite for fashion-minded dog groomers, but if owners don’t regularly trim their poodle’s ear hair, it can quickly obstruct their ears, causing debilitating life-threatening infections.5,6 Normal budgie Besides poodles, a number of other domestic mammal breeds are the result of selecting for abnormal hair growth, e.g. Australian Merino sheep, Scottish Highland cattle, Hungarian Mangalica pigs, and Angora goats. 7 And people have observed mutant hairy specimens in numerous other mammal species, including minks, guinea pigs and horses. King William IV of Britain owned a mutant horse with a mane 4 m (13.5 ft) long and a tail 8 m (27 ft) long! 7 Even humans have on occasion been afflicted with such mutations,8 which have often been misinterpreted as evolutionary ‘throwbacks’ to mythical furry ancestors.Control gene mutations are not restricted to hair and feathers. Some bacteria have a mutation disabling the control gene that regulates manufacture of a chemical that destroys penicillin, resulting in unrestrained production, which thus renders them immune to penicillin. 9 Belgian Blue cattle have a mutation that deactivates the myostatin gene, resulting in uncontrolled muscle growth, and thus abnormally big cattle. 10 In all these examples information is lost—the control genes are damaged and no longer able to fully perform their original function.Evolutionists are compelled to believe that mutations lead to new information, and new types of organisms, but this has never been observed. What we do observe is, however, entirely consistent with the young age model of degeneration from a ‘very good’ original state. Many mutations lead to innocuous neutral changes that do not impede the health of the organism, but this is not upward evolution. In rare cases, a mutation can confer an advantage in a particular environment, but this is always due to a loss of information resulting in a loss of some particular functionality. For example, a mutation resulting in the loss of wings is an advantage to beetles on a windy island.11More commonly, such loss of functionality results in disease. Researchers have now tracked down the exact nature and chromosomal locations of a staggering 9,500 specific DNA defects that cause, or predispose towards, over 900 different human diseases, with a further 3,400 mutations identified but not yet confirmed, and new mutations being uncovered almost daily.12 ‘Lost World of Mutants’ discovered by Carl Wieland In 1986, construction workers unexpectedly drilled into the Movile Cave, close to the western (Romanian) coast of the Black Sea. A ‘secret kingdom of strange creatures’ was revealed—a group of living things that have clearly been cut off from the outside world for many generations. They are found in air-pockets which can only be reached by diving. Forty-seven species altogether have been studied by a Romanian scientist, Serban Sarbu, who escaped the communist dictatorship and has only recently been able to resume his work. They include such things as spiders, leeches, millipedes, pill bugs, flatworms, mites, beetles, and water dwellers such as water scorpions and nematode worms.The unique thing about the ecosystem within which these creatures function is that they do not depend, even indirectly, on the energy of sunlight. The entire community appears to be fueled by energy from the metabolism of hydrogen sulfide (the foul-smelling ‘rotten egg gas,’ H 2S), carried out by dense mats of bacteria which live on the cave walls. These bacteria produce sulphuric acid, which incidentally carves out increasing volumes of space in the limestone.The bacteria are eaten by creatures higher on the ‘food chain’ which are then eaten by others, and so on. There is no photosynthetic vegetation at all.Air can seep in through tiny fissures, but the atmosphere is very different from outside, with 100 times as much CO 2, one tenth the level of oxygen, and a lot of H2S, produced by natural sulfur springs. The animals scuttle for cover when they detect a change in oxygen levels.All of them have the condition known as troglomorphy—a loss of coloring pigment, giving them a pale-yellow appearance. All are born blind, with the exception of one spider that is born with the usual eight eyes. However, these degenerate as it matures, so that it is blind as an adult.Many have large antennae which assist them to find their way around in the dark. A creationist understanding The obvious explanation would be similar to the standard evolutionary interpretation, except for the time-scale. Genetic loss through mutation is an integral part of the creation model, whereas molecules-to-man evolution requires huge volumes of new, functionally more complex information to arise.It is important to understand that the loss of characters such as eyes and pigment does not arise from disuse as such, although most of the public will surely see it in such Lamarckian . (Modern biologists, whether creationist or evolutionist, overwhelmingly disown such beliefs. The giraffe’s neck cannot get progressively longer from stretching over generations, nor shorter from lack of stretching.) Use and disuse do not cause changes which can be inherited—that is, there is no change in the DNA code as a result of use and disuse of bodily parts. Let’s look at the likely course of events. Loss of pigment Many cave dwellers have long been known to show this. If a creature living in the normal, outside world were to have a mutation causing a loss of its pigment, it would normally be less able to survive, losing some protection against sunlight. However, in a cave without the sun, such a mutation can readily spread through the population.These recently-discovered Romanian creatures are thus almost certainly the descendants of previously pigmented ancestors cut off from the outside perhaps thousands of years ago (not 5 million, as evolutionists speculate in this instance). Loss of eyes Blind fish, with scars where eyes normally appear, have long been known to exist in certain caves. A mutant gene damaging the genetic information for eye manufacture would have no selection pressure opposing its spread in a lightless environment. In addition, there may well be a selective advantage to such a loss/defect, as follows.Eyes are complex structures, prone to disease and injury. If a fish with eyes bumped into a cave wall in the dark, it could damage the eye surface, introducing infection leading to death. The acidic environment would also be detrimental to eye health. After many hundreds of generations, the eyeless gene would confer a slight but significant selective advantage. In the thousands of years since the Flood, the Romanian cave-dwelling creatures have had time to go through a huge number of their short generational life cycles, allowing them plenty of time for maximum adaptation to their new environment. This adaptation is based, however, on: the original created information, and adaptive losses/defects from mutation since creation. Large antennae

What about the huge, sensitive feelers some of these creatures apparently have? These are clearly adaptive to their dark environment. In addition, there are probably a host of other specialized features which have not yet been described, as so far only newspaper reports (ittedly quite detailed) of conferences have been available to us.Creationists would generally claim that it is vanishingly improbable that completely new biological apparati involving teleonomy (project-oriented functional complexity) will ever arise de novo from natural law—that is, chance copying mistakes/mutations in the first instance, to be subject to the filter of natural selection.A population may respond to environmental selection pressure based on information already present in its total gene pool. For instance, if a population of plants in a moist environment is exposed to ever-increasing dryness, only those plants carrying genes for deeper roots and waxier cuticles will survive. The population will have ‘responded’ and become ‘adapted,’ but only because the genetic information coding for waxier cuticles and deeper roots was already present.Therefore, a reasonable postulate regarding any of the adaptive features of these cave creatures is that: they are indeed the descendants of similar creatures from the ‘outside’ which became trapped (perhaps progressively) and cut off from the parent population; and they already had the genetic information for feelers/antennae. Individuals which (rarely) inherited the combination of genes for oversize feelers would be at a disadvantage ‘outside,’ but would be selectedfor in this world of darkness. Perhaps a mutational defect involving a loss of control (or loss of ‘switch-off’ of growth) of feeler size during development might have been involved in at least some, leading to gigantism in an existing structure, which is inherited.There is clearly no way in which, and no need to postulate that, these feelers themselves, with all their complex associated sensory and control mechanisms, arose by mutation in creatures which previously had no such information in their genes. The ecosystem Creationists sometimes point to complex predator-prey relationships, food chains, etc., as examples of creative design. While this is certainly feasible in many cases, even likely, it appears unlikely that the particular food chain in this case was the direct result of original creative design; at least, not created for that purpose. Rather, it probably arose as a result of each member being forced to survive on what it could, an adaptation (of an earlier ecosystem) based on necessity. Summary Complex information is never seen to arise from natural law, although that is the very core claim of evolution. These Romanian cave creatures show no evidence of having ‘evolved’ such information. However, they can indeed be described as ‘strange mutants’—the offspring of non-cave-dwellers which demonstrate the results of selection and degenerative change, not upward evolution. New eyes for blind cave fish? A remarkable experiment leads to much evolutionary misinterpretation by Carl Wieland, CMI–Australia Fish living in caves, in permanent darkness, are blind, with apparent ‘scars’ where their eyes should be. In the quarter of a century in which I have written and spoken on creation issues, I have often raised the matter of eyeless fish to argue against evolution, despite the fact that I believe that these fish arose from ones that originally had eyes. I also agree with evolutionists about the fairly obvious mechanism by which they think this happened. Nevertheless, I hope it will be clear from what follows that I find it exceedingly strange that some evolutionists would gloat about this as a ‘classic proof’ of evolution.1Note that such fish often are, in all other respects, identical to the same species of fish living at the surface and having eyes.Imagine a situation in which a group of such ‘normal’ fish swim into a stream which enters an underground cave, and become trapped in this pitch-dark environment. Their eyes are completely useless here.But eyes do not ‘disappear’ just because they are no longer needed. The fish’s DNA would have programmed into it the instructions on constructing eyes, and the code on the DNA does not ‘know’ that the eye is no longer needed, so it will keep on manufacturing eyes, generation after generation. In fact, in a moderate-sized population, many of these errors occur in each generation. It is not hard to see how one of these could result in a gene that usually ‘switches on’ eye development being corrupted, or somehow ‘switched off’, via mutation.In a normal above-ground situation, such eyeless fish would probably never survive much past early infancy, because they would be so handicapped both in locating food and escaping predators. So for all practical purposes, we never see eyeless fish in the wild where there is sunlight.However, in the cave, it is a different matter. The eyeless type no longer suffers this disadvantage compared to its compatriots. Not only that, the eyeless ones even have an advantage over the others. This is because, as fish bumped into rocks and cave walls in the darkness, the eyed ones would be likely to injure their eyes. The delicate tissue of eyes is prone to injury, which would allow harmful bacteria to enter, leading to infection and often death.The eyed fish would thus have a lesser chance of surviving to produce offspring. Those fish carrying the ‘eyeless’ genetic defect would have a greater chance of ing it on to the next generation, so it would not take many generations under such circumstances for all the fish to be of the ‘eyeless’ type.But this classic example of mutation/selection causing adaptation to a new environment is also a classic example of a mutation causing adownhill change. It is not showing us how the first stages of a new, complex adaptation could arise, it is merely showing us how complex information coding for great engineering design is being corrupted or lost. The grand-scale theory of evolution—that microbes have become millipedes, magnolias, and microbiologists—demands that huge amounts of new information, of true genetic novelty, have arisen over millions of years. To show such information arising from natural processes is the real challenge for evolution. It is a challenge which the renowned Darwinist Richard Dawkins was unable to answer, as shown in the video From a Frog to a Prince (as well as refutation of Skeptic’s attack andrefutation of Dawkins’ later response).Even if one tiny example could be found where information had arisen by chance mutation, Dr Lee Spetner’s classic book Not By Chance (see right; as well as this review) shows that neo-Darwinian theory requires literally hundreds to be observable today. So far, all the examples studied (including the handful of ‘helpful defects’, like the loss of eyes in cave fish, or wingless beetles on windy islands [see Beetle bloopers]) show a loss of information.The fascinating experiment (by researchers from the University of Maryland, USA) that has brought blind cave fish back into the news was one in which young eyeless fish had lenses implanted in them from the same species of fish (Astyanax mexicanus) living at the surface. Eight days later, the blind fish seemed to be regrowing eyes. After two months, they had a ‘large restored eye with a distinct pupil, cornea and iris. In addition, the retina of the restored eye showed rod photoreceptor cells …’. 2The researchers are not saying that the fish developed sight, which would require regrowth of nerve connections to the brain and more. This experiment is of great interest in helping us understand more about the pathways by which genes express the development of certain structures in the embryo. The following may be helpful in understanding what has taken place:It has long been known that during the development of certain frog embryos, for instance, the lens not only appears first, it acts as an ‘inducer’ of the development of most of the rest of the eye. Thus, if the lens from one embryo is surgically embedded into another embryo at a spot different from where the eye normally develops, an eye will start to form at that location.Both in the above example, and that of the cave fish, the development of the eye structures can only take place if the organism into which the lens is transplanted has the genetic instructions present in its DNA to manufacture such structures.This indicates

that the mutation by which the fish initially became ‘eyeless’ did not somehow ‘delete’ all of the ‘eye information’, but just interfered with the process leading to the eye’s development. An analogy with computers would be deleting files on a computer—the information is not deleted, just the record of its location on the hard disk. If the data as such were not still there, ‘undelete’ programs would not be possible.In the example here, the mutation most probably just blocked the proper formation of the lens. Without the lens to induce the rest of the eye to form, it won’t. This is ed by the fact that in the embryos of eyeless cave fish, eyes start to form, but the lens that has started to form deteriorates, and the other structures remain undeveloped.This is the first time, to my knowledge, that such optic induction experiments have been successful on any organism in a post-embryonic stage. As such it is important in future embryological research into the immensely ingenious, complex, and still very poorly understood, processes by which an adult organism develops from a tiny fertilized egg.Sadly, though not surprisingly, this has been described in such a way as to promote the ‘evolution is fact’ idea—even though it has nothing to do with demonstrating that microbes could turn into man (and as shown, the change is in the opposite direction required). It has been described as ‘Eye parts lost during millions of years of evolution were restored in just a matter of days’. 3 We have already seen that it is misleading to describe the loss of the ability to produce eyes as ‘evolution’, because it gives rise to the impression that it has something to do with how there came to be such things as fish with eyes in the first place. In addition, there is not the slightest bit of evidence that the process of losing them took millions of years. In fact, it would be surprising if it took more than a few dozen generations, or just a few short years, given the scenario described earlier.Indeed, considering the supposed creative power of ‘evolution’, it is remarkable that these fish, allegedly separated for millions of years, are so near-identical to those living at the surface that even evolution’s most hardened ‘true believers’ concede that they should be given the same species name. The notion that they have not been cut off from each other for anywhere near as long, directly fits the facts. Christopher Hitchens—blind to salamander reality Photo by ensceptico, flickr.com A well-known atheist’s ‘eureka moment’ shows the desperation of evolutionists In a recent article in the leftist online magazine Slate, prominent atheistic journalist Christopher Hitchens (b. 1949) thinks he has found the knock-down argument against creationists and intelligent design ers. Fellow misotheist Richard Dawkins (b. 1941) and another anti-theist Sir David Attenborough (b. 1926) agree. Not surprisingly, there have been questions to us about this, so Dr Jonathan Sarfatiresponds. As will be seen, their whole argument displays ‘breathtaking inanity’ and ignorance of what creationists really teach, and desperation if this is one of their best proofs of evolution.Christopher Hitchens is a British-born American journalist and author, recently best known for his antitheistic bookGod Is Not Great. He is also an avid debater, although he seemed to come off second best against Dinesh D Souza(b. 1961), author of What’s So Great About Christianity? 1 In a bizarre recent article, Losing Sight of Progress: How blind salamanders make nonsense of creationists claims, 2 Hitchens thinks he has clinched the case for his antitheistic faith. He begins: It is extremely seldom that one has the opportunity to think a new thought about a familiar subject, let alone an original thought on a contested subject, so when I had a moment of eureka a few nights ago, my very first instinct was to distrust my very first instinct. To phrase it briefly, I was watching the astonishing TV seriesPlanet Earth (which, by the way, contains photography of the natural world of a sort that redefines the art) and had come to the segment that deals with life underground. The subterranean caverns and rivers of our world are one of the last unexplored frontiers, and the sheer extent of the discoveries, in Mexico and Indonesia particularly, is quite enough to stagger the mind. Various creatures were found doing their thing far away from the light, and as they were caught by the camera, I noticed—in particular of the salamanders—that they had typical faces. In other words, they had mouths and muzzles and eyes arranged in the same way as most animals. Except that the eyes were denoted only by little concavities or indentations. Photo by Yolaine Conti, sxc.hu So Hitchens thinks that eyeless salamanders are a ‘moment of eureka’. He later explains why: If you follow the continuing argument between the advocates of Darwin’s natural selectiontheory and the partisans of creationism or “intelligent design”, you will instantly see what I am driving at. The creationists (to give them their proper name and to deny them their annoying annexation of the word intelligent) invariably speak of the eye in hushed tones. How, they demand to know, can such a sophisticated organ have gone through clumsy evolutionary stages in order to reach its current magnificence and versatility? That is indeed a problem, and Hitchens continues: The problem was best phrased by Darwin himself, in his essay “Organs of Extreme Perfection and Complication”: To suppose that the eye, with all its inimitable contrivances for adjusting the focus to different distances, for itting different amounts of light, and for the correction of spherical and chromatic aberration, could have been formed by natural selection, seems, I freely confess, absurd in the highest possible degree. As we have advised in our Don’t Use page, care must be taken with this quote. Darwin went on to say that although it seems absurd, he nevertheless believes it could have happened via small changes worked on by natural selection. Hitchens goes on to say: His defenders, such as Michael Shermer in his excellent book Why Darwin Matters, draw upon post-Darwinian scientific advances. They do not rely on what might be loosely called “blind chance”: Evolution also posits that modern organisms should show a variety of structures from simple to complex, reflecting an evolutionary history rather than an instantaneous creation. The human eye, for example, is the result of a long and complex pathway that goes back hundreds of millions of years. Initially a simple eyespot with a handful of light-sensitive cells that provided information to the organism about an important source of the light … This is indeed a continuation of Darwinian ideas. Yet there are a number of problems with this as well as the next point. For example, the usual simulations start with the nerve behind the light-sensitive spot. The vertebrate eye has the nerves in front of the photoreceptors, while the evolutionary just-so story provides no transitions from behind to in front, with all the other complex coordinated changes that would have to occur as well. See also Fibre optics in eye demolish atheistic bad design argument.

Hold it right there, says Ann Coulter in her ridiculous book Godless: The Church of Liberalism. “The interesting question is not: How did a primitive eye become a complex eye? The interesting question is: How did the ‘light-sensitive cells’ come to exist in the first place?” Coulter’s book actually nails the ‘Darwiniacs’, as she calls them, on this and in many other places. Indeed, the photochemistry involved in even the simplest light-detecting cells is enormously complex. So although evolutionists claim to be climbing a gentle slope up ‘Mt Improbable’, they are really starting from a sheer ledge near the top. See At the bottom of Mount Improbable? Eye evolution, a case study. The salamanders of Planet Earth appear to this layman to furnish a possibly devastating answer to that question. Humans are almost programmed to think in of progress and of gradual yet upward curves, even when confronted with evidence that the past includes as many great dyings out of species as it does examples of the burgeoning of them. Thus even Shermer subconsciously talks of a ‘pathway’ that implicitly stretches ahead. But what of the creatures who turned around and headed back in the opposite direction, from complex to primitive in point of eyesight, and ended up losing even the eyes they did have? Well, what about them? This is the crux of Hitchens’ argument. Yet this is his own blind spot. Proving that someone can fall down the mountain (Improbable or otherwise) is hardly proof that he could have climbed up there in the first place . That’s the general problem with many alleged proofs of evolution: it’s not that the changes are too small, but that they are going in the wrong direction —see The evolution train’s a-comin (Sorry, a-goin in the wrong direction).This is easily explainable: there are many ways to break something, but not many ways to makesomething in the first place. So it’s not surprising that it would be relatively easy for a mutation, or copying mistake in the genes, to ruin the eyes. In the light, natural selection would eliminate such mutations, since blind creatures could see neither prey nor predators.But in a pitch-black cave, there would be no natural selection against blind creatures, so they could proliferate. They might even have an advantage, because a shrivelled eye is less likely to be damaged. Creationists have explained this long ago—see New eyes for blind cave fish? A remarkable experiment leads to much evolutionary misinterpretation.In one of the best known blind cave fish, Astyanax mexicanus, there is another reason why the blind fish can have an advantage in caves. This is pleiotropy, where a single gene has more than one effect on an organism. It turns out that a control gene, hedgehog, which affects a number of processes including development of the jaws and tastebuds, also inhibits another control gene, pax6, which controls development of the eyes. A fish with bigger jaws and more sensitive tastebuds would have an advantage in finding food, but this must be traded off with the loss of eye development. In the light, loss of eyes is a big disadvantage, so natural selection would eliminate a fish that over-expresses hedgehog, despite its better jaws and taste. But in the dark caves, a fish with highly expressed hedgehog would have a big advantage, since the loss of eyes would be irrelevant. 3Also, to underscore the point that there are many ways to break things, there are actually a number of ways to produce blindness, even in Astyanax. This is shown by breeding different populations of blind fish, and resulting in a number of sighted progeny. This is explained because the sight loss in the different populations is caused by different mutations, so ‘when you cross them, the genetic deficiencies in one lineage are compensated for by strengths in the other, and vice-versa.’ 4 We have also pointed this out in Let the blind see: Breeding blind fish with blind fish restores sight, so Hitchens has even less excuse—exactly the same principles apply to blind salamanders and other blind troglobionts (cave-dwelling living organisms).When it comes to breaking something, it need not take very long either. Breaking is often quicker than making, just as it’s often much quicker to fall off a mountain than to climb it. We can see this in humans, when sighted parents have blind children due to a genetic defect—this can happen in only one generation. Yet Hitchens gushed: Even as I was grasping the implications of this, the fine voice of Sir David Attenborough was telling me how many millions of years it had taken for these denizens of the underworld to lose the eyes they had once possessed. He of course provides no proof. Indeed, the fact that sight can be regained in one generation shows that there has been little time for mutations to further degenerate the genes—note that natural selection would not preserve genes connected to eyes and the visual parts of the brain if there were no selection for eyesight. Indeed, Dr John Sanford, inventor of the gene gun, in his book Genetic Entropy and the Mystery of the Genome, shows that the known rate of harmful mutations accumulation would have resulted in error catastrophe if we had really been around for millions of years. Whereas the likelihood that the post-ocular blindness of underground salamanders is another aspect of evolution by natural selection seems, when you think about it at all, so overwhelmingly probable as to constitute a near certainty. Which is why creationists agree that mutations and selection is the right explanation. But we have also pointed out that natural selection is the opposite of evolution, since it removes information. Indeed, creationists proposed natural selection as a conservative force well before Darwin, which hinders the downward slide of a population by eliminating the less fit. The blind fish are one of the best proofs of this: natural selection conserves sight in most populations by eliminating sightless mutants; when this selective pressure is removed, blind mutants proliferate, so the population goes informationally downhill. I wrote to professor Richard Dawkins to ask if I had stumbled on the outlines of a point, and he replied as follows: Vestigial eyes, for example, are clear evidence that these cave salamanders must have had ancestors who were different from them—had eyes, in this case. That is evolution. Why on earth would the designer create a salamander with vestiges of eyes? If he wanted to create blind salamanders, why not just create blind salamanders? Why give them dummy eyes that don’t work and that look as though they were inherited from sighted ancestors? Maybe your point is a little different from this, in which case I don’t think I have seen it written down before. Of course, creationists deny the designer created blind salamanders, and agree that this is one genuine example of a vestigial organ. But even genuine vestigial organs prove merely devolution, not evolution. What would be impressive would be a nascent organ, one growing where none existed before in the creature’s ancestry. Dawkins must be willingly ignorant of what creationists teach, or is deceitfully knocking down a straw man. After all, why should his ethics be trusted under his own belief system when Dawkins hasagreed that ultimately evolution ‘leads to a moral vacuum … in which [people’s] best impulses have no basis in nature’, and scoffed at the idea of righteous indignation and retribution against child murderers and other vile criminals? I recommend for further reading the chapter on eyes and the many different ways in which they are formed that is contained in Dawkins’ Climbing Mount Improbable; I’ve already read that—see my review. also “The Blind Cave Fish’s Tale” in his Chaucerian collection The Ancestor’s Tale. Also reviewed in the Journal of Creation.5 I am not myself able to add anything about the formation of light cells, eyespots, and lenses, but I do think that there is a dialectical usefulness to considering the conventional arguments in reverse, as it were. As shown, there is a big difference in the forward and reverse directions: as one of Australia’s leading molecular biologists, Dr Ian Macreadie, pointed out:‘Evolution would argue for things improving, whereas I see everything falling to

pieces. Genes being corrupted, mutations [mistakes as DNA is copied each generation] causing an increasing community burden of inherited diseases. All things were well designed initially.’ For example, to the old theistic question, “Why is there something rather than nothing?” Which we note Hitchens has not actually answered. Atheists must believe by faith that nothing exploded and became everything. Can’t drink milk? You’re “normal”! How mutations cause lactose tolerance in adults by David Catchpoole Lactose intolerance was really only recognized in the 1960s, and ranges from about 5% in northern Europe, around 70% for southern Europe, to more than 90% in some African and Asian countries. The aversion to milk among Asians was once mostly regarded in the West as cultural in basis (rather than biological/genetic), with powdered milk often being sent as part of food aid.18For many, the mere mention of milk will be enough to invoke memories of nausea, bloating, cramps, diarrhea, and perhaps in some cases, jibes and taunts about “wind” and bad breath. Some will have undergone medical tests that diagnosed the cause as “ Lactose intolerance ”.Lacking the enzyme lactase, which breaks down the milk sugar lactose (see box), they are unable to digest milk, whereas lactose-tolerant people can. Others, though, might still be unaware that they are “deficient” in lactase, not realizing that drinking milk causes their feelings of nausea, etc. 1For many years, lactose intolerance was regarded as abnormal, and was used by many as evidence of human evolution. As a measure of evolutionary “advancement”, milk-drinking seemed to fit the stereotype perfectly. Pale-skinnned northern Europeans usually retained full intestinal lactase activity into adulthood, in stark contrast to the world’s darker-skinned peoples who are only able to digest milk as infants or young children. Well, that’s the way the story went.However, “lactose deficiency” in adults is not in fact abnormal, but the norm! Research has shown that the gene for lactase normallyswitches off as children are weaned. And a genetic mutation that results in lactase production not being switched off s for the ability of certain people to drink milk into adulthood.So there has now been a dramatic change in terminology, with those who cannot digest milk no longer being called “lactase deficient”. Instead, they are now regarded as normal, while those adults who retain the enzymes allowing them to digest milk are called “lactase persistent”.2,3Furthermore, different mutations can stop lactase production from being switched off after weaning. The mutation that confers lactase persistence in northern Europeans 4 is different from the mutation in East Africans who are lactase persistent.5 Researchers have identified three different mutations (in the same stretch of DNA as the European variant) in various African populations in Tanzania, Kenya and the Sudan.6 Evolutionary notions overturned The findings have overturned previously-held evolutionary notions in dramatic manner. Anyone enamoured with the blackpeople-are-less-evolved-than-white-people idea must confront the fact that dark-skinned Africans have been shown to have genetic mutations conferring lactase persistence—some of them even had all three of the mutations so far discovered in that region.7In that light it’s interesting to make comparative reference to a notable pale-skinned person, namely, Charles Darwin. Some of the symptoms of his “mystery illness”, 8 viz. continual “diarrhea, bloating and gas”,9 match those resulting from lactose intolerance!Another shake-up for evolutionists was the researchers’ assessment that the most common variant arose “as recently as 3,000 to 7,000 years ago”. University of California anthropologist Diane Gifford-Gonzalez says the finding of recent multiple mutations arising independently is changing the way they think about human history: “Until the geneticists contributed to the data, the rest of us always thought about evolution happening very slowly and gradually.” 10This is not the first time, however, that evolutionists have been surprised by the speed of genetic changes. 11However, they still claim it as evolution. “This is the best example of convergent evolution in humans that I’ve ever seen,” said geneticist Joel Hirschhorn, of the Children’s Hospital Boston, Massachusetts.10 But note that these genetic changes are not “evolution” in the uphill molecules-to-milkman sense, as the changes are downhill, i.e., information has been lost (viz., the normal switching-off mechanism of lactase production following weaning). 12 Rather, at best this is an example of selection, as Hirschhorn himself went on to acknowledge: “Lactase persistence has always been a textbook example of selection, and now it’ll be a textbook example in a totally different way.” 10Hirschhorn’s comments also highlight two key factors underscoring the creation-evolution issue. First, the extreme flexibility of evolutionary theory. It seemingly doesn’t matter what the evidence is—evolutionary theory can be made to do an “about-face” when desired. Second, the classic “bait-andswitch” tactic of interchanging “evolution” with “selection”. But natural selection is not evolution.13Another unexpected result of the milk-drinking mutation survey in east Africa was the finding that the Hadza people of Tanzania “show a surprisingly high level of lactase persistence despite having very little to do with cattle”. That led to this evolutionarily-radical suggestion: “One possibility is that, though they are now mainly hunter-gatherers, their ancestors might have been pastoralists.” While that idea goes against the traditional evolutionary order, it is right in line with a young age perspective. Furthermore, this is not the first time that evolutionists have had to face up to evidence that today’s hunter-gatherer peoples previously practised farming or animal husbandry—contrary to their cherished ideas.14 Being a “mutant” can be advantageous Although the loss of the ability to turn off lactase production following weaning is a loss of information (i.e. a downhill change), the mutation confers some obvious advantages in areas where milk is available. The “cost” of the mutation, i.e., the extra energy needed to continue to produce lactase beyond infancy, would be more than compensated for by being able to safely extract the energy and nutrients in milk. 15So in what time frame could the milk-drinking mutation have arisen? Even the evolutionists acknowledge that man’s original status was indeed “lactose intolerance”. University of California geneticist Leena Peltonen quipped, “I find it ironic that a so-called disease [i.e. ‘lactase deficiency’] actually represents the original condition.”18So, those of you who are unable to drink milk as adults today without feeling nauseous (or worse) can take heart from being closer in that respect to the originally “physically-perfect” first man and woman than are those of us who are milkdrinking “mutants”! Lactase and lactose Most human infants produce ample quantities of lactase for milk digestion. The cells that line the small intestine produce the enzyme lactase, which breaks down lactose, the characteristic disaccharide sugar of milk, into the monosaccharides glucose and galactose. These sugars are easily digested (absorbed) by humans.However, when lactase is lacking, as it is in most adult humans19 and animals, the lactose cannot be broken down and absorbed in the small intestine. The lactose therefore

es to the large intestine where the resident bacteria ferment it, generating gas—hence the discomfort of nausea/bloating/flatulence experienced by “lactase-deficient” people after drinking milk.Many “lactose intolerant” people are able to consume some dairy products, such as cheese, without experiencing the debilitating symptoms they get following consumption of milk. That is because there is little lactose in such fermented products, as the bacteria (e.g. lactobacilli) have already fermented most of the lactose in the original milk into lactic acid, with the by-product gas released harmlessly into the atmosphere.

Don’t confuse “lactose intolerance” for milk protein allergy Some children who are said to be “lactose intolerant” are later found to be able to tolerate milk. However, almost certainly those children were not lactase deficient but rather were allergic to a milk protein (lactoglobulin). This is fairly common in young children—they usually grow out of milk allergies as their gastro-intestinal tract matures. Such children can usually tolerate goat’s milk, which also has lactose, of course, but lacks the cow’s milk proteins that cause the problems. There is even a difference between breeds of cows, it turns out. A person might not tolerate Friesian milk (most commercial pasteurized milk is largely Friesian) but tolerate Guernsey or Jersey milk, for example. Lactose-intolerant persons can often well tolerate natural yoghurt, which has about 2/3 the lactose of milk. Researchers think that this is due to the presence of lots of live fermenting bacteria, which quickly digest the lactose at body temperature, and also contribute lactase.

At last, a good mutation? by Carl Wieland There are children who are so prone to infection that, if they survive at all, they have to spend their lives in an artificial ‘bubble’. This is the usual fate of those who have inherited two defective copies (one from each parent) of a gene which produces an enzyme called ADA (adenosine deaminase).Because they are unable to make ADA, toxic substances accumulate in their blood which slowly damage the body’s immune cells.However, in an unprecedented finding, a U.S. boy called Jordan Houghton has spontaneously recovered from his condition.1 All the evidence indicates that in one line of his immune cells, one of the faulty genes has apparently repaired itself.Geneticist Hagop Youssoufian at Brigham and Women’s Hospital, Boston, says about this 'fascinating' occurrence: ‘We finally have a clear example of a mutation doing something good’. ‘Back mutations’, replacing a letter in the DNA sequence which was faulty back to what it originally should have been, are not unknown. They certainly do not show us how significant information can arise de novo, as they merely (accidentally) ‘restore’ what should have been there.An occurrence like this (encouraging, but exquisitely rare) may actually not be mutational as such, as there are abundant error-checking, proof-reading and repair mechanisms in our genetic machinery.Youssoufian’s ‘at last’ statement highlights the fact that mutations, random accidental changes in copying hereditary information, are overwhelmingly a downhill process. Geneticists in hospitals are all too familiar with the harm they cause in people who inherit their effects. A-I Milano mutation—evidence for evolution? 21 February 2003 This week’s selected from J.R. is about another claimed beneficial mutation, since many people have an idea that this would disprove creation. Despite the rule against URLs in s, in this case it was unavoidable, and we thought that Dr Don Batten’s scientific perspective would be helpful. Once again, the key is that evolution requires informationincreasing mutations, while even the rare beneficial ones do not help evolution because they are losses of information. J.R. responded to the original answer with appreciation, showing that Dr Batten’s explanation was helpful in clearing up this common misunderstanding. I really hope [your ministry] does an article or report on this. So far, I haven’t found a creationist group that will report anything on this complex. Seeing as how [CMI] reported on the fruit fly issue, with the evolutionists claiming this A-I Milano complex as vastly more important evidence than the fruit fly stuff, I hope to see a [CMI] report soon. Here are two URLs: Site #1)The Milano Mutation: A Rare Protein Mutation Offers New Hope for Heart Disease Patients 1 Site #2)‘Defective’ but beneficial gene may bring about novel ways to clear arterial plaque buildup2 It would appear that the questioner is under the mistaken impression that beneficial mutations are a problem for creationists. Some creationists make this unfortunate error. The mutations Q&A section of our Web site clearly teaches that the issue is not whether the mutation is beneficial but if it adds new genetic information (specified complexity). So it would have been clear that the A-I Milano mutation is not evidence for microbe-to-man evolution.What has happened? One amino acid has been replaced with a cysteine residue in a protein that normally assembles high density lipoproteins (HDLs), which are involved in removing ‘bad’ cholesterol from arteries. The mutant form of the protein is less effective at what it is supposed to do, but it does act as an antioxidant, which seems to prevent atherosclerosis (hardening of arteries). In fact, because of the added -SH on the cysteine, 70% of the proteins manufactured bind together in pairs (called dimers), restricting their usefulness. The 30% remaining do the job as an antioxidant. Because the protein is cleverly designed to target ‘hot spots’ in arteries and this targeting is preserved in the mutant form, the antioxidant activity is delivered to the same sites as the cholesterol-transporting HDLs. In other words, specificity of the antioxidant activity (for lipids) does not lie with the mutation itself, but with the protein structure, which already existed, in which the mutation occurred. The specificity already existed in the wild-type A-I protein before the mutation occurred.Now in gaining an anti-oxidant activity, the protein has lost a lot of activity for making HDLs. So the mutant protein has sacrificed specificity. Since antioxidant activity is not a very specific activity (a great variety of simple chemicals will act as antioxidants), it would seem that the result of this mutation has been a net loss of specificity, or, in other words, information. This is exactly as we would expect with a random change.Note that quantifying the amount of information is not as easy as just counting the number of functions or even the number of base pairs (‘letters’) in a gene. This is simplistic reasoning. It is firstly, but not only, a question of specificity. For example, if I said, ‘Fix the Porsche,’ this conveys more information than ‘Fix the automobile,’ although the latter has more letters. If I said, ‘Fix the car and the truck,’ we now have two ‘functions’ in this sentence, but does it contain more information than ‘Fix the Porsche’? We are now comparing a command with two ‘functions,’ but both of low specificity, with a command with one

function and high specificity. In this case deciding which has the most information is not simple. This illustrates the importance of context and purpose (teleology). For example, if there were only one car to fix, a Porsche, ‘Fix the automobile’ would carry as much information as ‘Fix the Porsche.’ But if there were dozens of possible cars or trucks to fix, ‘Fix the Porsche’ would contain much more useful information than ‘Fix the car and truck.’ Dr Werner Gitt explores these issues in detail in his incisive In the Beginning Was Information.For more information on defining information mathematically, see How is information content measured? (somewhat technical). However, mathematical definitions of information only work in certain contexts (e.g. substrate specificity of enzymes).It would also be useful to study the article Is antibiotic resistance really due to increase in information? and the explanations about information content accompanied by Dr Lee Spetner's graphs of the activity of the enzyme ribitol dehydrogenase. The Milano mutation seems to parallel the mutant enzyme, with a lower peak and broader spectrum, i.e. towards lower specificity hence lower information.Of course it remains to be seen if this mutation is completely beneficial. The fact that the persons with it are unable to produce normal levels of HDLs, which are known to perform a valuable role in moving ‘bad’ cholesterol, suggests that there could be a health down side to this mutation (as there is with sickle-cell anemia).Apparently this mutation has only been seen in heterozygotes. That is, all those who have the mutation have a normal gene pairing the mutant gene. The homozygous state (both genes the same) could be lethal. This would then parallel sickle-cell anemia, which evolutionists often put up as an example of evolution in action. Here the heterozygote has an advantage, but the homozygote is lethal. This cannot be an example of upward evolutionary progression since the mutant form can never take over the population; it will always be limited to a small percentage of individuals in the population.However, with the A-I Milano mutation, there are not yet many people with the mutation, so the chances of two people with the mutation marrying and having children so that a homozygote could be produced (1 in 4 of the children) would be very low—it probably has not happened yet. The ‘jury remains out’ on whether a homozygote would be viable.3Needless to say, if someone follows a healthy lifestyle, eats the right things (something like the food pyramid as recently revised by Harvard Medical School, although this could be improved further), exercises, maintains a healthy weight and does not abuse their body by smoking, the A-I Milano mutation will likely be of no use. Epidemiological studies show that heart disease can probably be avoided. Dr Don BattenFor the original paper, see: Bielicki, J.K., Oda, M.N., Apolipoprotein A-I (Milano) and apolipoprotein A-I(Paris) exhibit an antioxidant activity distinct from that of wild-type apolipoprotein A-I, Biochemistry 41(6):2089-96, 2002. Note: the original posting of this response was modified following interaction with a Dr Steven Pirie-Shepherd, an evolutionist. We started out publishing Dr Pirie-Shepherd’s objections with Dr Batten’s responses, but he was clearly not happy with our publishing his letters after we had demonstrated the flaws in them; he kept coming back for more, continually changing his point of contention. If we had persisted with publishing this interaction as the back-and-forth continued it would have become quite tedious to follow. Also, it became clear that Dr Pirie-Shepherd was willing to concede nothing and was using the opportunity merely to develop a propaganda piece to be published on a web site given to opposing the young age model. Consequently, our answer was modified in response to Pirie-Shepherd’s claims, but his words were not included.Dr Pirie-Shepherd has contributed his name to ‘Project Steve’ of the National Center for Science Education, an organization founded and still run by secular humanists (atheists)—NOT to promote real science such as physics, chemistry and experimental biology, but solely to oppose the young agemodel and promote evolution from goo-to-you-via-the-zoo (see How Religiously Neutral are the Anti-Creationist Organizations?). Special tools of life by Dr Jean Lightner Have you ever tried to do a job, but not had the right tools? Many tools (like screw drivers, saws and wrenches) come in a variety of sizes and shapes so that different jobs can be done quickly and easily. Specialty tools are designed with unique shapes and bends so a person can do a special job very well. Trying to use a tool poorly suited for the job (like a slotted screw driver on a Phillips screw) often leads to poor results and frustration.Did you know that living things make their own tools? For example, they use enzymes to break down large molecules for parts (building blocks) and some for energy. Other enzymes construct things, such as cell walls. These enzymes are like awesomely designed specialty tools with a very specific size and shape. Many do only one job and do it very well. There are several thousand known enzymes that are used to do all the different jobs necessary to keep living things alive and well. 1How do living things make these tools? They use the information from their DNA (the molecule in the nucleus that contains all the ‘programs’ a cell needs to function) and materials from the world around them. Since it would be wasteful for a creature to constantly be producing an enzyme even when it wasn’t needed, the DNA also contains an ON/OFF switch (repressor gene). This is normally switched OFF until the enzyme is needed.2 There are two competing worldviews as to how this information got on the DNA. Creationists believe that the designer put the information there when he created life.Evolutionists believe that it got there by mistake; actually by a lot of mistakes. That’s right! Before a cell divides, it copies the DNA so each new cell has a copy. Sometimes there is a copying error, called a mutation, that takes place. These mutations, according to the theory of evolution, are the source of new information. Natural selection then supposedly selects the useful mutations and eliminates the useless ones. This is how evolutionists for new enzymes, hormones, organs, etc. as living things have (supposedly) developed upward from a single-celled beginning.Most mutations that make a noticeable difference are harmful. A few might be considered beneficial—at least sometimes.3 But do these mutations add information to the DNA? A number of scientists thought so when they saw mutations in a bacterium that normally grows in the soil. 4 This bacterium can grow well when it has one of several unusual sugars as an energy source: ribitol or Darabitol.5 The scientists growing it in the lab tried giving it a very similar sugar, xylitol, as its only energy source. Xylitol is not normally found in the bacteria’s environment. The bacteria have no enzymes specifically designed for the first step in breaking it down.The The unsuspecting soil dwelling wild-type of the bacteria couldn’t grow. However, a mutant strain (X1) arose that could bacteria were suddently whisked grow on xylitol, although very slowly. Later, a second mutant strain (X2) arose from X1 off to the lab and fed nothing but that grew faster on xylitol. From this, a third mutant strain (X3) developed that grew xylitol. faster still. Evidence for evolution? A new enzyme evolving? Hardly.Ribitol is broken down for energy by a series of steps, and each step is done by a different enzyme. The enzyme for the first step has a really cool name, ribitol dehydrogenase (RDH). If you’re ever stuck trying to come up with a name for a pet, this might be just the name. RDH, the enzyme, is like a specialty tool that is designed to take apart ribitol. Although xylitol is very similar to ribitol, RDH doesn’t take it apart very easily. When it does finally get it apart, the bacteria has all the right enzymes to break it down the rest of the way. The X1 was able to grow because the mutation destroyed the ON/OFF switch for RDH.

Therefore, RDH was constantly produced and the large amounts of this enzyme broke down the xylitol that was able to get into the cell. The second mutation affected the RDH enzyme and changed its shape slightly. A new enzyme, or a defective one?6 This new shape caused RDH to be less effective on ribitol, but more effective on xylitol and L-arabitol (the mirror image of Darabitol) as shown in the accompanying graph. This means RDH in X2 was less specific in its action. Is it beneficial for a mechanic to have bolts randomly loosened throughout the car when he wants to remove the starter? There are plenty of acids and bases that can take lots of molecules apart very well. However, living things use tools that are more specific so that important parts of the cell aren’t dismantled. A loss of specificity is a loss of information and usually not beneficial. Nevertheless, since the scientists insisted on growing the bacteria on only xylitol, the mutation was beneficial in this case. It allowed X2 to grow about 2½ times faster than X1, which was still slow, but it did grow faster.The third mutation allowed more Living things use enzymes that are usually very specific. Ribitol xylitol into the bacteria cell. Normally cells dehydrogenase (RDH) is very specific in the wild-type bacteria (red) as seen are very picky about what they let in. Some by the tall spike in the graph. The mutant (X2, shown in green) has an things that are important to the cells are enzyme that has lostsome of its specificity as seen by a less pronounced pulled in. This bacteria has an enzyme that peak and higher base. If the theory of evolution were true, there should brings D-arabitol into the cell. When xylitol be many examples of new enzymes developing with increasing specificity. is present, it is brought in as well because it So far we know of none. is so similar. This enzyme also has an ON/OFF switch in the DNA which is kept switched OFF unless D-arabitol is available. The third mutation destroyed this ON/OFF switch and xylitol ended up with a free ride into the cell. This enabled the X3 mutant to grow about twice as fast as X2.If the theory of evolution were true, each step, on average, would add new information. This would explain the tremendous amount of information in bass, bison and birds compared to bacteria. In the length of time mankind has been studying genetics and mutations, many examples of information increase should have been documented. Yet, none have been found. In the example discussed here, the X3 mutant still only grew about half as well on xylitol as the wild-type did on ribitol. If the mutants were put back into a soil environment, they would quickly die out because they are less fit. Many otherwise intelligent people, in their quest for knowledge, have missed the obvious. Anyone who looks at a well designed tool should know that someone made it. Mutations: A losing change Although it is extremely rare for a mutation to be beneficial, the following mutations were, as long as the bacteria were restricted to xylitol. Bacterium Loss Benefit Wild-type None Grows well in soil Mutant X1 On/off switch for RDH destroyed; RDH constantlyRDH available in large amounts; produced even when ribitol is absent (waste of xylitol broken down slowly; X1 grows resources; inefficient) slowly on xylitol Mutant X2 RDH shape changed; loses specificity for ribitolRDH works better on xylitol; X2 (grows slower than wild type on ribitol) grows faster on xylitol than X1 Mutant X3 On/off switch for ‘enzyme’ that brings in D-arabitol Xylitol gets a free ride into the cell; destroyed; enzyme constantly produced, evenmore xylitol available in cell; X3 when D-arabitol absent (waste of resources) grows faster on xylitol than X2 DAILY Mutations: evolution’s engine becomes evolution’s end! by Alex Williams In neo-Darwinian theory, mutations are uniquely biological events that provide the engine of natural variation for all the diversity of life. However, recent discoveries show that mutation is the purely physical result of the universal mechanical damage that interferes with all molecular machinery. Life’s error correction, avoidance and repair mechanisms themselves suffer the same damage and decay. The consequence is that all multicellular life on earth is undergoing inexorable genome decay. Mutation rates are so high that they are clearly evident within a single human lifetime, and all individuals suffer, so natural selection is powerless to weed them out. The effects are mostly so small that natural selection cannot ‘see’ them anyway, even if it could remove their carriers. Our reproductive cells are not immune, as previously thought, but are just as prone to damage as our body cells. Irrespective of whether creationists or evolutionists do the calculations, somewhere between a few thousand and a few million mutations are enough to drive a human lineage to extinction, and this is likely to occur over a time scale of only tens to hundreds of thousands of years. This is far short of the supposed evolutionary time scales. Mutations destroy

Ever since Hugo de Vries discovered mutations in the 1890s they have been given a central role in evolutionary theory. De Vries was so enamoured with mutations that he developed an anti-Darwinian saltationist theory of evolution via mutation alone.1 But as more became known, mutations of large effect were found to be universally lethal, so only mutations of small effect could be credibly considered as of value to evolution, and de Vries’ saltationist theory waned. When the Neo-Darwinian Synthesis emerged in the 1930s and 1940s, mutations were said to provide the natural variations that natural selection worked on to produce all new forms of life.However, directly contradicting mutation’s central role in life’s diversity, we have seen growing experimental evidence that mutations destroy life. In medical circles, mutations are universally regarded as deleterious. They are a fundamental cause of ageing,2,3cancer4,5 and infectious diseases.6Even among evolutionary apologists who search for examples of mutations that are beneficial, the best they can do is to cite damaging mutations that have beneficial side effects(e.g. sickle-cell trait,7 a 32-base-pair deletion in a human chromosome that confers HIV resistance to homozygotes and delays AIDS onset in heterozygotes,8 CCR5–delta32 mutation,9 animal 10 11 melanism, and stickleback pelvic spine suppression ). Such results are not at all surprising in the light of the discovery that DNA undergoes up to a million damage and repair events per cell per day.12 Mutation physics Neo-Darwinian theory represents mutations as uniquely biological events that constitute the ‘engine’ of biological variation. However, now that we can see life working in molecular detail, it becomes obvious that mutations are not uniquely biological events—they are purely physical events.Life works via the constant (often lightning-fast) movement of molecular machinery in cells. Cells are totally filled with solids and liquids—there are no free spaces. The molecular machines and the cell architecture and internal structures are made up of long-chain organic polymers (e.g. proteins, DNA, RNA, carbohydrates, lipids) while the liquid is mostly water. All forms of movement are subject to the laws of motion, yet the consequences of this simple physical fact have been almost universally ignored in biology.Newton’s first law of motion says that a physical body will remain at rest, or continue to move at a constant velocity, unless an external force acts upon it. Think of a message molecule that is sent from one part of a cell to another. Since the cell is full of other molecules, with no empty spaces, the message molecule will soon hit other molecules and either slow down or stop altogether. This is the universal problem known as friction.Friction events can result from many causes, but can be crudely divided into two types: one is referred to as ploughing and the other is shearing. Ploughing involves the physical displacement of materials to facilitate the motion of an object, while shearing arises from the disruption of adhesive interactions between adjacent surfaces. 13Molecular machines in cells owe a great deal of their structure to hydrogen bonds, but these are rather weak and fairly easily broken. For example, most proteins are long, strongly-bonded chains of amino acids, but these long chains are coiled up into 3dimensional machine components, and the 3-dimensional structures are held together by hydrogen bonds.14 When such structures suffer mechanical impacts, the transfer of momentum can distort or break the hydrogen bonds and critically damage the molecule’s function. The inside of a cell has a density and viscosity somewhat similar to yogurt (figure 1). The stewed fruit (dark colour) added to the yogurt during manufacture can be seen swirling out into the white yogurt. The fruit has not continued to disperse throughout the yogurt. It was completely stopped by the initial friction. This is like what happens in a cell—any movement is quickly dampened by friction forces of all kinds coming from all directions. Figure 1. A transparent carton of fruit yogurt illustrates how friction in the viscous fluid stopped the motion initiated by mixing the fruit (dark colour) with the yogurt (white colour). How do cells cope with this friction? In at least five different ways. First, there are motor proteins available all over the cell that attach to mobile molecules and carry them along the filaments and tubules that make up the cytoskeleton of the cell. Second, these motor proteins are continually re-energized after friction collisions by energy inputs packaged in the form of ATP molecules. Third, there are ‘address labels’ attached to mobile molecules to ensure they are delivered to the correct destination (friction effects continually divert mobile molecules from their course). Fourth, thin films of water cover all the molecular components of cells and provide both a protective layer and a lubricant that reduces the frequency and severity of friction collisions. Fifth, there is a wide range of maintenance and repair mechanisms available to repair the damage that friction causes.The friction problem—and the damage that results from it—is orders of magnitude greater in cells than it is in larger mechanical systems. Biomolecules are very spiky objects with extremely rough and highly adhesive surfaces. They cannot be manufactured and honed to the smoothness that we achieve in our vehicle engine components such as pistons and flywheel pivots, nor can ball-bearings be inserted to reduce the surface area, such as we do in wheel axles. As a biological example, consider the rotary motor that drives the bacterial flagellum. The major wear surfaces are on the rotor (attached to the flagellum) and the stator (the housing for the rotor, attached to the cell wall). The stator consists of 22 molecules, set in 11 pairs. The wear rate is so great that the average residence time for a stator molecule in the stator is only about 30 seconds. 15 The cell’s maintenance system keeps a pool of about 200 stator molecules in reserve to cope with this huge turnover rate.Finding suitable lubricants to overcome friction is a major focus in the nanotechnology industry. A special technique called ‘friction force microscopy’ has been developed to quantitatively evaluate potential lubricants.16This shows that the laws of physics, operating among the viscous components of the cell, both predict and explain the high rate of molecular damage that we observe in DNA. Between 50% and 80% of the DNA in a cell is continually consulted for the information necessary for everyday metabolism. This consultation requires numerous steps that each involve physical deformation of the DNA—moving around within the nucleus, winding and unwinding of the chromatin structures, unzipping the double-helix, binding and unbinding of the transcription machinery, re-zipping the

double-helix, rewinding the chromatin structures and shuffling around within the nucleus. Each step of motion is powered by ATP discharges and inevitably causes mechanical damage among the components. While most of this damage is repaired, the repair mechanisms are not 100% perfect because they suffer mechanical damage themselves.17 Mutations rapidly destroy Within neo-Darwinian theory, natural selection is supposed to be the guardian of our genomes because it weeds out unwanted deleterious mutations and favours beneficial ones. Not so, according to genetics expert Professor John Sanford.18 Natural selection can only weed out mutations that have a significant negative effect upon fitness (number of offspring produced). But such ‘fitness’ is affected by a huge variety of factors, and the vast majority of mutations have too small an effect for natural selection to be able to detect and remove them.Furthermore, if the average mutation rate per person per generation is around 1 or more, then everyone is a mutant and no amount of selection can stop degeneration of the whole population. As it turns out, the mutation rate in the human population is very much greater than 1. Sanford estimates at least 100, probably about 300, and possibly more. All multicellular life suffers Two recent reviews of the mutation literature not only confirm Sanford’s claims, but extend them to all multi-cellular life.In a review of the distribution of fitness effects (DFE) of mutations, 19 the authors are unable to give any examples of beneficial mutations for humans. In their calculations regarding the rate of deleterious mutations (MD) and neutral mutations (MN), they use the equalities MD = 1 –MN and MN = 1 – MD which both imply that the rate of beneficial mutations is zero. They do give a few non-zero values for beneficial mutation rates in some experimental organisms, but qualify these results by noting the interference of other variables.In a review of mutation rate variations in eukaryotes, 20 the authors it that all multicellular organisms are undergoing inexorable genome decay from mutations because natural selection cannot remove the damage.21 Their Box 2 and Table 1 list deleterious mutation rates for a wide range of multicellular organisms, noting they are all underestimates, with the possible exception of those for the fruit fly Drosophila melanogaster with a value of 1.2. The value given for humans is ‘~3’.Thus, all multicellular life on earth is undergoing inexorable genome decay because the deleterious mutation rates are so high, the effects of the most individual mutations are so small, there are no compensatory beneficial mutations, and natural selection is ineffective in removing the damage. The wheels have come off the neo-Darwinian juggernaut! How long to extinction? How long could multicellular life survive in the face of universal genetic degradation? This is a very important question, and I will attempt to answer it by using several different lines of evidence. Human ageing and cancer We have recently discovered that there is a common biology in cancer and ageing—both are the result of accumulating molecular damage in cells.22 This confirms the arguments outlined above, that for purely physical reasons molecular machinery suffers extremely high damage rates, clearly evident within the lifespan of a single human. Every cell has a builtin time clock to limit this damage and minimize the chance of it becoming cancerous. At every cell division, each telomere (the caps on both ends of a chromosome that stop the double-helix from unravelling) is shortened by a small amount, until they reach the Hayflick Limit—discovered in 1965 to be a little over 50 cell divisions. The cells then stop dividing and they are dismantled and their parts are recycled.By adding the enzyme telomerase, the telomere shortening problem can be circumvented, but that then exposes the cell to a greater risk of becoming cancerous because of accumulating damage elsewhere in the cell. The overall balance between protection from damage and the need for longevity determines fitness (reproductive success) and life span.23 The body’s normal reaction to increasing genome damage is to kill off the damaged cells via programmed senescence (of which the telomere clock with its Hayflick limit is but one part). But cells become malignant (cancerous) when mutation disables the senescence mechanism itself, which then enables the damaged cells to proliferate without limit. 22 The Hayflick limit of around 50 cell divisions for humans seems to provide the optimum balance.Fifty human generations of 20 years each gives us only 1,000 years as a timescale over which a human lineage would begin to experience a significant mutation load in its genome. This is alarmingly rapid compared with the supposed evolutionary time scale of millions and billions of years. Reproductive cells Figure 2. Schematic representation of human life expectancy (—), male fertility (∙∙∙), and risk of fetal abnormality with mother’s age (---). Despite the protective Hayflick limit on cell divisions and life expectancy, very significant molecular damage accumulates in humans even during the most productive years of life. Mutations do even more damage than the Hayflick limit and associated cancer rates suggest.Ever since August Weismann published The Germ-Plasm: A Theory of Heredity24 in 1893, a discrete separation has been shown to exist between body cells (the soma) and germ-line cells (germplasm). Germ-line cells were thought to be more protected from mutation than other body cells. However, another recently discovered cause of ageing is that our stem cells grow old as a result of heritable DNA damage and degeneration of their ing niches(the special ‘nest’ areas in most organs and tissues of the body where stem cells grow and are nurtured and protected). The telomere shortening mechanism—intended to reduce cancer incidence—appears to also induce the unwanted side-effect of a decline in the replicative capacity of certain stem-cell types with advancing age. This decreased regenerative capacity has led to a ‘stem-cell hypothesis’ for human age-associated degenerative conditions.25Human fertility problems suggest that the decline in niche protection of stem cells also applies to our gametes (eggs and sperm). For males, fertility—as measured by sperm count, sperm vigor and chance of conception—begins to decline significantly by age 40 and the rate of certain paternal-associated birth defects increases rapidly during the 30s (figure 2).26 For females, the chance of birth defects increases rapidly from around the mid-30s, particularly because of chromosome abnormalities (figure 2). In the middle of the most productive part of our lives, our bodies are therefore showing clear evidence of decline through accumulation of molecular damage in our genomes.

Do germ-line cells really suffer less damage? When DNA was discovered to be the carrier of inheritance, Weissman’s germ-plasm theory gave rise to the ‘immortal strand hypothesis.’ When the DNA of an embryonic stem cell replicates itself, it was thought that the ‘old’ strand would remain with the self-renewing ‘mother’ stem cell, while the newly constructed daughter strand proceeds down the path of differentiation into a body cell. In this way, the ‘old’ strand would remain error free—because it has not suffered any copying errors—and thus becomes effectively immortal.However, a research team at the Howard Hughes Memorial Institute recently tested this theory using the stem cells that produce blood, and found that they segregate their chromosomes randomly. 27 That is, the ‘immortal strand hypothesis’ is wrong. If stem cells are not given this kind of preferential treatment then it is reasonable to conclude that germ-line cells are also subject to the same molecular damage as somatic cells. This is confirmed by the observation that human fertility exhibits damage long before age-related diseases take over. A single human lifetime is enough to show very significant mutation damage, even in our reproductive cells. Haldane’s dilemma The severe contradictions that these findings pose for neo-Darwinian theory corroborate what has become known as Haldane’s dilemma. J.B.S. Haldane was one of the architects of neo-Darwinism who pioneered its application to population biology. He realized that it would take a long time for natural selection to fix an advantageous mutation in a population—fixation is when every member has two copies of an allele, having inherited it from both mother and father. He estimated that for vertebrates, about 300 generations would be required, on average, where the selective advantage is 10%. In humans, with a 20-year generation time and about 6 million years since our last common ancestor with the chimpanzee, only about 1,000 such advantageous mutations could have been fixed. Haldane believed that substitution of about 1,000 alleles would be enough to create a new species, but it is not nearly enough to explain the observed differences between us and our closest supposed relatives.The measured difference between the human and chimpanzee genomes amounts to about 125 million nucleotides, which are thought to have arisen from about 40 million mutation events. 28 If only 1000 of these mutations could have been naturally selected to produce the new (human) species, it means the other 39,999,000 mutations were deleterious, which is completely consistent with the reviews showing that the vast majority of mutations are deleterious. Consequently, we must have degenerated from the apes, which is an absurd conclusion.According to Kirschner and Gerhart’s facilitated variation theory,29 life consists of two main components—conserved core processes (the structure and machinery in cells) and modular regulatory processes (the signalling circuits and switches that operate the machinery and provide a built-in source of natural variation). The 40 million ‘mutation’ differences between humans and chimps are therefore much more reasonably explained as 40 million modular differences between the design of chimps and the design of humans. Quantitative estimates of time to extinction There are a number of different ways to estimate the time it would take for relentlessly accumulating mutations to send our species to extinction. Binomial estimates Some very rough estimates can be derived from the Binomial distribution, which can predict the likelihood of multiple mutations accumulating in an essential genetic functional module. A binomial model of a mutating genome could consist of the cell’s DNA being divided into N functional modules, of which Ne are essential; that is, the lineage fails to reproduce if any of the essential modules are disabled. For any given mutational event, p = 1/N is the probability of being ‘hit’, q is the probability of being ‘missed’, and p q = 1. What is the likely value of N? We can derive two estimates from the knowledge that there are about 25,000 genes, plus the discovery from the pilot study report of the ENCODE project that virtually the whole human genome is functional. 30For the first estimate, the average protein contains a few hundred amino acids and each amino acid requires three nucleotides of code, so the average gene would take up about 1,000 nucleotides of exon space (an exon is the protein-coding part of a gene). There are about 3 billion nucleotides in the whole human genome, so if we assume that the average protein represents an average functional unit then N = 3 million.The second estimate comes from the ENCODE report that gene regions produce on average 5 RNA transcripts per nucleotide, and the untranslated regions produce on average 7 RNA transcripts per nucleotide. There are about 33 times as many nucleotides in the untranslated regions as in the genic regions. Assuming that transcript size is approximately equal in each region, then there are 25,000 x 5 = 125,000 gene transcripts and 25,000 x 33 x 7 = 5,775,000 untranslated transcripts, making N= 5,900,000 in total. Our two estimates of N are therefore 3 to 6 million in round figures.What is the likely value of Ne? Experiments with mice indicate that 85% of genes can be knocked out one at a time without lethal effects. 31This is due to the robustness and failure-tolerance through fallback processes built into the genomic designs. That means any one of those remaining 15% genes will be fatal if disabled. Multiple mutations occur however, so the likely value of Ne when exposed to multiple mutations will be much higher than 15%. The maximum possible value is 100%. In a study of 2,823 human metabolic pathways, 96% produced disease conditions when disrupted by mutation,32 so if we take an average between this value and the minimum 15% then we get about 60% of functional units being essential.How many random mutations are required on average to disable an essential functional module? In rare cases, a single mutation is enough to disable a person’s ability to reproduce. A two-hit model is common in cancer. In a study of cell signalling networks, these two hits usually knocked out: (i) the programmed death system for dealing with damaged (cancerous) cells, and (ii) the normal controls on cell proliferation—so the damaged cancer cells can proliferate without limit. The proportion of cancer-associated genes was also found to increase with the number of linkages between genes. When a healthy gene is linked to more than 6 mutated genes, ~80% of all genes in the network are cancerous. Extrapolating from this, we find that by the time a normal gene is linked to about 10 mutated genes, then the whole network has become cancerous.33Almost 70% of known human genes can be causal agents of cancer when mutated.34 Cancers can result from as little as a single mutation in a stem cell, or multiple mutations in somatic cells. 35 The minimum possible value of 1 is known to be rare, so the more common occurrence of the 2-hit model makes it a reasonable best-estimate minimum. But it may require 10 modules to receive two hits each for the whole network to become dysfunctional.The maximum number of hits required to disable a single module may be 100 or more, but if the average functional module only contains 1,000 nucleotides then this figure, at 10% of the whole, seems rather large. An order-ofmagnitude average is perhaps more likely to be 10 random mutations per functional module.To provide some context for these estimates, recent work shows that the cell-cycle checkpoint damage repair system is activated when 10 to 20 doublestrand breaks accumulate in a cell undergoing division. 36 That is, life will tolerate only 10 to 20 DNA breaks per cell before it starts repair work, whereas we are examining scenarios in which there are thousands and millions of damage events per cell. Our numbers are clearly up in a region where the cell’s repair mechanisms are working at their hardest.What then is the likelihood of accumulating either 2 hits in 10 modules, or 10 hits in one module, in any one of either 15% or 60% of the 3 to 6 million functional modules? The binomial distribution in Microsoft Excel was used to make the following calculations, making the further assumption that the likelihood of the unit being a critical one must exceed 50% for extinction to be more likely than not in the next generation.Assuming 60% essentiality, only one functional module needs to be disabled for the

probability of its essential status to exceed 50%. For the 2-hit model, about 6,000 to 12,000 mutations are required to disable ten of the 3 to 6 million functional modules. For the 10-hit model, 3 to 6 million mutations are required to disable one functional module.Assuming 15% essentiality, four modules need to be disabled before the probability of at least one of them being essential exceeds 50%. For the 2-hit model, 250,000 to 500,000 mutations are required to disable ten modules with four mutations each among the 3 to 6 million functional modules. For the 10-hit model, 3.7 to 7.5 million mutations are required to disable four functional modules.If every individual produces 100 new mutations every generation (assuming a generation time of 20 years) and these mutations are spread among 3 to 6 million functional modules across the whole genome, then the average time to extinction is: 1,200 to 2,400 years for the 2-hits in 10 modules model and 60% essentiality 50,000 to 100,000 years for the 2-hits in 10 modules model and 15% essentiality 600,000 to 1,200,000 years for the 10-hit model and 60% essentiality 740,000 to 1,500,000 years for the 10-hit model and 15% essentiality. Truncation selection Evolutionary geneticist Dr James Crow argued that humans are probably protected by ‘truncation selection’. 26 Truncation occurs when natural selection preferentially deletes individuals with the highest mutation loads. Plant geneticist John Sanford put Crow’s claims to the test by developing a computer simulation of truncation. His assumptions were: 100 individuals in the population, 100 mutations per person per generation, 4 offspring per female, 25% non-genetic random deaths per generation, and 50% selection against the most mutant offspring per generation. He assumed an average fitness loss per mutation of 1 in 10,000. His species became extinct in only 300 generations. With a generation time of 20 years this corresponds to 6,000 years.37Sanford’s assumptions are somewhat unrealistic, but there are other ways to approach the problem. Mutations are pure chance events that follow a Poisson distribution, and this behaves like the normal curve when the average expected value is greater than about 30.38 In a Poisson distribution, the variance is equal to the average expected value, and the standard deviation is the square root of the variance. When the expected average value is 100, the standard deviation will be 10. The normal curve now tells us the following: Half the people will suffer about 100 mutations or more, and half the people will suffer about 100 mutations or less. About 84% of people will suffer 110 mutations or less, and so the remaining 16% of people will suffer 110 or more mutations. Alternatively, about 16% of people will suffer 90 or less. About 97.7% of the population will experience 120 mutations or less, and the remaining 2.3% will suffer 120 mutations or more. Alternatively, 2.3% will suffer 80 or less. About 99.9% of the population will suffer 130 mutations or less, and the remaining 0.1% will suffer 130 or more mutations. Alternatively, 0.1% will suffer 70 or less. If we remove the most mutant—those above 130 mutations per person per generation—then we will only remove 0.1% of the population and it will make virtually no difference. If we removed the most mutant 50% of the population that would not solve the problem either, for two reasons. First, the great majority of the remaining people still suffer between 70 and 100 mutations per person per generation, far above the value of 1 that ensures inexorable decline. Second, removing half the population each generation would send it extinct in a few dozen generations. Table 1. Estimated number of generations and years to extinction for populations of various sizes, when fitness declines by 1.5% in each generation.None of the above models include the effect of synergistic epistasis (if one gene is mutated, its impact is ameliorated by the coordinated activity of other genes) or of population size. We can include these by using Crow’s estimate that the fitness of the human race is currently degenerating at a rate of about 1 to 2% per generation. If we use an average value of 1.5% then only 98.5% of the next generation will produce reproductively viable offspring. The next generation after that will only have 98.5% of those survivors able to produce reproductively viable offspring, and so on.For any given stable population size N, the size of the next generation that can produce reproductively viable offspring will be 98.5% of N ,and for any given number of generations G, the number of survivors able to produce reproductively viable offspring will be (98.5%)G of N.Table 1 shows the approximate numbers of generations after which the population degenerates to extinction (only one individual is left, so breeding cannot continue). No population can sustain a continual loss of viability of 1.5%.The above model assumes that right from the beginning there will be 1.5% loss of fitness each generation. However, the binomial simulations earlier showed that individuals can tolerate somewhere between a few thousand to a few million mutations before the damage critically interferes with their ability to reproduce. This means that synergistic epistasis is a real phenomenon—life is robust in the face of mutational assault. Instead of the immediate loss of 1.5% every generation, the general population would remain apparently healthy for a much longer time before the damage became apparent.However, the rate at which mutations accumulate will remain the same because the cause remains the same—mechanical damage. This means that most people will be apparently healthy, but then approach the threshold of dysfunction over a much shorter period, creating a population crash rather than a slow decline.Either way, however, the time scales will be approximately the same because the rate of damage accumulation remains approximately the same. Summary Mutations are not uniquely biological events that provide an engine of natural variation for natural selection to work upon and produce all the variety of life. Mutation is the purely physical result of the all-pervading mechanical damage that accompanies all molecular machinery. As a consequence, all multicellular life on earth is undergoing inexorable genome decay because the deleterious mutation rates are so high, the effects of the individual mutations are so small, there are no compensatory beneficial mutations and natural selection is ineffective in removing the damage.So much damage occurs that it is clearly evident within a single human lifetime. Our reproductive cells are not immune, as previously thought, but are just

as prone to mechanical damage as our body cells. Somewhere between a few thousand and a few million mutations are enough to drive a human lineage to extinction, and this is likely to occur over a time scale of only tens to hundreds of thousands of years. This is far short of the supposed evolutionary time scales. Like rust eating away the steel in a bridge, mutations are eating away our genomes and there is nothing we can do to stop them. Evolution’s engine, when properly understood, becomes evolution’s end. Meiotic recombination—designed for inducing genomic change by Jean K. Lightner Creationary biologists have recognized that the diversity seen within created kinds today cannot be adequately explained by the shuffling of pre-existing gene versions (alleles) and accidental errors that accumulate within the genome.1 Within the context of creation, the development of genetic diversity has been a means by which the designer has enabled his creatures to adapt to the many different environmental niches they occupy today. Further, it has played an important role in adding variety, beauty, and productivity in various domesticated plants and animals.2There is certainly no logical reason to believe that unguided chance processes can bring about a functional genome.3 Neither is there sound reason to believe that accidental changes to the genome are a productive source of useful genetic diversity. Logically, therefore, the genome must contain biological information that allows it to induce variation from within. 4 One mechanism involved in this is meiotic recombination.5 Continued scientific research is elucidating some amazing details of this process.Meiosis is a special type of cell division necessary for the formation of gametes (eggs or sperm) so sexual reproduction can take place. In most plants and animals, chromosomes come in pairs (homologs, one derived from each parent), but gametes only carry one of each homolog. Early in meiosis, each chromosome must be drawn to its homolog and stably pair. Then each homolog will be pulled in the opposite direction so that the two cells that form during the division will have exactly one of each homolog. Meiotic recombination is no accident The meiosis was desined in a way that naturally tends to increase diversity. In order for the chromosomes to stably pair, recombination occurs between the homologs. The process is initiated by an enzyme which cuts the DNA on one homolog, forming a double-stranded break. Then each side of the break is resected in one direction. This leaves two tails, which are important in repairing the break (figure 1).The genome must contain biological information that allows it to induce variation from within. There are several pathways by which the break can be repaired. The best known resolution of the break is called crossing over. For this to occur, both of the tails must invade the homolog to form a double Holliday junction (dHJ). DNA synthesis occurs extending these tails. Then, depending on which enzymes are used to cut this structure apart, the distal ends of the chromosomes are swapped.This swapping between homologs is important in helping to shuffle alleles, which allows for new combinations that may be advantageous. The method of DNA repair described above is known as double-stranded break repair (DSBR). It does not always result in crossing over. A different enzyme can be used to cut the dHJ at a different location and gene conversion will result instead. In gene conversion, a segment from one homolog is copied onto the other. A second pathway for resolving double-stranded breaks is called synthesis-dependent strand annealing (SDSA). In this circumstance only one tail invades the intact homolog and gene conversion is the result.6 Meiotic recombination is mutagenic Technically, swapping portions of a chromosome and gene conversion are mutations when they alter the nucleotide sequence. Other mutations can also occur during the repair of double-stranded breaks. It appears to be more common with gene conversion. One study in yeast revealed a mutation rate 1,000 times higher during gene conversion than the normal spontaneous mutation rate for that locus. Most mutations were base pair substitutions. About 40% of the mutations were attributable to some form of template switching. In yeast strains with a proofreading defect in a DNA polymerase, template switch mutations were absent.7 This suggests that template switching is a complex, enzyme-driven process.There is a bias to where meiotic recombination occurs. In a study of Drosophila, crossing over tended to occur in specific hot spots, but these were not influenced by whether or not it was a genic region. Gene conversion had a more uniform distribution, was more common among genic sequences, and was seen where crossing over was rare or absent. The authors emphasized the importance of having information on rates of recombination to include in population genetics models. 8 Studies in plants indicate that a variety of genetic and epigenetic factors influence the frequency of crossing over. 9There are several other pathways by which double-stranded breaks can be repaired. One of the most interesting and mutagenic is break-induced replication (BIR). It has been shown to produce complex rearrangements including copy number variation (CNV) and nonreciprocal translocations. These often involve multiple rounds of template switching. Specific endonucleases are necessary for proper BIR; an absence of these endonucleases has been shown to significantly reduce template switching.10 Significance of mutations At times mutations are explained as the result of accidents which introduce errors into the DNA sequence. The concept of non-directed change is foundational in the standard evolutionary model. Logically, accidental changes in a complex system should be consistently harmful to some degree. Creationists have pointed this out in emphasizing the implausibility of accidents in ing for the complexity of life.

Figure 1. In meiotic recombination a doublestranded break is enzymatically induced and the ends are resected, forming tails. Repair of the break begins when one tail invades the corresponding region on the homolog and DNA synthesis takes place. From there several different pathways are possible. Crossing over can occur if the second tail also invades and a double Holliday junction forms. This pathway is called double-stranded break repair (DSBR). However, this pathway can have an alternative resolution, gene conversion (non-cross over). A second pathway is synthesis-dependent strand annealing (SDSA), which can also result in gene conversion.However, when diversity is examined within a creation model, it is evident that significant diversity has arisen since the time of the Flood. In contrast to the notion that all mutations are harmful, the observed diversity does not appear to be typically harmful, and much is considered to be healthy. It has been pointed out that this useful diversity is not logically the result of accidents, but some designed mechanism(s) must be producing it.1Several specific examples are worth noting. In a gene influencing coat colour, a pattern of in-frame indel (insertion or deletion) mutations was noted across several unrelated kinds. These generally result in a black coat colour. Statistically, only one in three indels should be in-frame. It does not appear that natural selection can explain this bias toward in-frame indels, and so a designed mechanism was suggested as its source. 11Resistance to organophosporous insecticides has been studied in sheep blowflies. There is a particular gene where specific mutations can confer resistance to one organophosphate or another. Resistance to one of these insecticides (malathion) was identified in pinned specimens that pre-dated the first use of that insecticide; therefore, selection would be a reasonable explanation for how it spread in the fly population. Resistance to a second insecticide (diazinon) appears to have arisen by mutation since the insecticide was introduced. This rapid appearance of resistance is quite impressive (though disheartening for those trying to get rid of this pest). In addition to this, flies have emerged that are resistant to both insecticides as a result of gene duplication (a form of CNV). It appears that such gene duplications have arisen at least three separate times in these flies, and always involve the resistant alleles.12The point here is that the mutagenic nature of meiosis appears to provide a plausible mechanism for inducing this type of variation within a creationary timeframe. The requirement of specific enzymes and non-random pattern of change in meiotic recombination suggests it could play a significant role in producing the observed useful genetic diversity. Gene conversion, a designed mechanism which can result in fixation of alleles Gene conversion can lead to a transmission distortion, a deviation from the expected ratio of alleles in the gametes. Studies in mice revealed an example of this due to a preferential induction of double-stranded breaks on one homolog, which yielded an over-transmission of the allele from the other. Given the distortion, population simulations predicted that the favoured allele would be fixed in the population in less than 1,200 generations. 6The mutagenic nature of meiosis appears to provide a plausible mechanism for inducing this type of variation within a creationary timeframe. Transmission distortion is extremely significant. Most models attempting to explain the changes in allele frequency of a population assume that a heterozygous parent would have an equal chance of ing either of the alleles on to the offspring. The fixation of alleles within a population is generally attributed to natural selection, although genetic drift is also recognized as a possibility. These are naturalistic explanations that fit well within the ‘anti-designer’ presuppositions of the evolutionary model.Despite the appeal of scenarios crediting natural selection, they may have little semblance to reality if designed mechanisms are involved in changing allele frequencies. One example in animals would be migration. Perhaps animals move to where they are most comfortable. This comfort factor may be related to having a genotype compatible with (adapted to) that environment. So essentially, animals with adaptive alleles stay, and the others leave. This is rather the reverse of natural selection (where the environment ‘selects’ the animals), as it is the animal making a conscious choice.Transmission distortion due to gene conversion, as described above in mice, may also prove to be an important mechanism for fixation of adaptive alleles in populations. If this turns out to be the case, it is a serious problem for evolutionists. It would be another major blow to the view that naturalistic processes adequately explain the origin of new species. Instead, designed mechanisms would be important for both the generation of diversity and fixing adaptive alleles within a population. If designed processes are necessary for adaptive changes even within created kinds, it points again to an awesome designer! Summary One thing is clear; the evolutionary based inference that mutations (any change in the DNA sequence) are always accidents or copying errors is false. Changes in DNA sequence can arise for a number of reasons. One reason is that meiotic recombination, an essential step in reproduction for many plants and animals, is designed to induce genetic changes. This is highlighted by the fact that enzymes are necessary for this complex processes, including enzymes which induce the doublestranded breaks and facilitate template switching. Since this is the case, I fully expect that better understanding meiotic recombination will be one piece in the puzzle to better understanding how diversity has risen so quickly within created kinds since the time of the Flood. Teenage mutant ninja people by Gordon Howard Chernobyl, Three Mile Island, Fukushima; Why are these names associated with fear and foreboding? Because we know the potential dangers, albeit often overstated, of radioactive materials leaking from damaged nuclear power plants. We have read about the disastrous effects they can have on people, crops and stock.But, isn’t there an upside to this? Surely the believers in evolution should be jumping with glee, hoping for some new mutation that will propel the human race to a new level of evolutionary progress? After all, we know about Spiderman, the Hulk, Teenage Mutant Ninja Turtles and the X-men,

all of whom fictionally benefited hugely from with radioactive materials. Comic strips, movies and other popular publications have entrenched this positive idea of ‘mutants’ being superior to the ‘normal’ in the public mind. The reality, however, is vastly different.Darwin’s theory of evolution relies on the selection of the ‘fittest’ from a continually varying population; but at the time he was writing, the Austrian monk and scientist, Gregor Mendel, was demonstrating that there are definite limits to the variation possible. Darwin provided no mechanism for broadening these limits, but modern ‘NeoDarwinism’ suggests that extra variation can come through ‘mutations’. These are alterations to the normal genetic material that often produce alterations in the offspring, and these alterations can be selected for. They can and do occur naturally, as copying mistakes during cell replication, or under the influence of chemicals or radiation. They are the hope of evolutionists. However, if these mutations are so desirable, and are responsible for the marvellous supposed success of accidental evolutionary invention and progress, why do we want to keep people from living near the Fukushima power plant amongst the leaked radioactive materials? Won’t there be lots of mutations? Can’t we expect some beneficial ones to appear and elevate the human race to a superior level? Unfortunately not. The reality is that mutations caused by such influences as ionizing radiation are much more damaging than helpful. The DNA in a cell is like the instruction book for the cell’s workings, and any random changes will be like similar changes in an instruction book. Imagine a manual for the construction of something you know about. Now imagine making random changes to the letters and symbols in those instructions. Changes to “an” or “the” may not be significant, but a change from mm to m (millimetres to metres), or a 9 to a 2, or a change in the order of the pages, could be very damaging. Your construction would have significant faults (such as building the roof before the foundations), and might fail to work at all.Radiation does this to genes—it scrambles the genetic instructions, and functionality is reduced, unless the built-in (created) repair mechanisms1 are able to cope. Scrambled instructions in the reproductive cells are ed on to offspring, and the genetic errors accumulate over the generations faster than they can be eliminated by natural selection. 2When the above fictional characters were being invented and popularized, scientists were actively working to produce mutated marvels. Many experiments with this kind of aim were conducted through the twentieth century.3 One research project involved the irradiation of millions of pine tree seeds. The researchers hoped that the mutations would produce super trees, growing faster, thicker and higher, with denser timber and fewer branches. Most of the irradiated seeds failed to germinate. Of those that grew, many died because of such problems as lack of chlorophyll, or proper vascular systems, while many that managed to live grew along the ground, or sprouted many trunks, or fuzzy leaves, or spongy trunks or showed other signs of disorganization. The only ones to survive any length of time were those that escaped significant mutational damage, and grew normally.4Obviously, mutations were occurring in the DNA, but, just as obviously, the mutations were not creating the super-trees they were hoping for. Today, similar research continues, but usually with the expectation of a similarly damaged product, although the results may be useful to mankind. 5 Examples of successful mutation breeding are dwarfed crop plants (short wheat plants don’t fall over in stormy weather), seedlessness in fruit and change of colour in flowers due to eliminating specific pigments. But, again, even when mutations do something useful, in each case it involves damaging existing genetic instructions, not gain of new ones. Furthermore, a recent paper showed that even the rare beneficial mutations tend to work against each other—the phenomenon called antagonistic epistasis.6The same happens to any living thing, such as humans. If we receive a dose of radiation, we can expect at least some damage to the DNA in some of our cells. If it happens in only a couple of cells, we will hardly notice, so low doses (such as occasional X-rays) are OK. As the dose rises, the risk of damage also rises, so that one will begin to feel ill from ‘radiation poisoning’ as more cells get damaged. Higher doses may cause deformed offspring (if the damage occurs in a reproductive cell), or the shut-down of a specific organ, or cancer (which is, after all, a cell multiplying wrongly because its control genes have been damaged). Yet higher doses will cause irreparable damage in a large number of cells, leading to death 7 (as the workers who volunteered to repair the Fukushima plant accepted).Commercial irradiation of foodstuffs is deliberately used to kill all undesirable organisms within the packaging, and it does a thorough job by completely disrupting cell processes.It is fear of such damage that caused the Japanese government to provide an exclusion zone around Fukushima, and has led to countries importing Japanese goods checking for any residual radiation. No informed person believes that anyone will benefit from random changes (mutations) in their genes. No one wants to be irradiated in the hope of beneficial mutations. No one wants to be an evolutionary experiment.Our increasing knowledge of the content and activity of the genome assures us that the DNA of any creature is designed to produce exactly that creature, and any random change will damage the required set of instructions. It is even more obvious that the types of changes necessary for a Spiderman to exist are way beyond the bounds of possibility. Why then do some people believe that such changes have occurred in the past to make a bird out of a dinosaur, or a mammal out of a lizard, or a frog out of a fish? It is simply not possible. Mutations damage DNA. They don’t invent new, more complex traits.While geneticists may make ‘improvements’ by deliberately transferring genes from one creature to another, this is using already-created information from the biosphere. Random changes due to radiation are not going to produce a ‘super’ creature, and especially not a new kind of creature. The genetic information was originally given for each kind of creature represented the full measure of genetic information for that organism, and chance mutations will never add coordinated instructions for the kinds of ‘improvements’ required to make microbes-to-mankind evolution possible Critic ignores reality of Genetic Entropy The author of a landmark book on genomic decay responds to unsustainable criticisms. by Dr John Sanford Published: 7 March 2013 (GMT+10) I do not normally spend my time responding to bloggers, but several people have asked me to respond to Scott Buchanan’s polemic1 against my book Genetic Entropy. This article is a one-time clarification as I cannot afford the time to be drawn into the blog-o-sphere and its associated ‘death by a thousand emails’.Scott’s lengthy essay is certainly not an objective review of my book; it is an ideological attack based upon a commitment to the standard Darwinian theory. He does not acknowledge any of the legitimate concerns I raise regarding the Darwinian process, not even the many points widely acknowledged by my fellow geneticists. Shouldn’t even ardent Darwinists honestly acknowledge the known problems with current Darwinian theory? I will only briefly touch on each of his arguments. Scott gives his arguments in this order:

First, he claims, that my book is all about deliberate deception, and I am fundamentally a liar (but perhaps I am otherwise a nice man). He then spends three pages expressing how annoyed he is with the exact way in which I cite a Kimura reference—as I try to make clear the actual distribution of mutational effects. He argues that, while beneficial mutations are rare, they are not as rare as I suggest. Since beneficial mutations clearly happen, and since adaptation clearly happens, he imagines the Primary Axiom—that man is merely the product of random mutations plus natural selection—must then obviously be true. The Primary Axiom: Man is merely the product of random mutations plus natural selection. Scott cites a series of flawed ‘mutation accumulation’ experiments, which he thinks demonstrate extremely high rates of beneficial mutation. He points out that duplications can have real biological consequences. He also points out that we cannot generally see measurable degeneration in extended lab experiments. He argues that, if I were correct, then in just the last few thousand years all forms of life having short life cycles (bacteria, mice) should have gone extinct. Since we do not see obvious degeneration happening, the Primary Axiom must be true, according to him. Scott suggests that, since human life spans have increased in the last several centuries, this proves that man is not degenerating. He argues that Crow’s conclusion that the human race is presently degenerating at 1–2% per generation2 does not mean he stopped being faithful to the Primary Axiom. He also argues that synergistic epistasis3 really happens (at least to some extent), and cites those who feel this might aid in mutation elimination. Finally, he casually dismisses all the papers I cite in Appendix 1 of my book, where the leaders of the population genetics field acknowledge all of the basic problems with the Primary Axiom. It seems to me that Scott makes his arguments in the wrong order, starting with the trivial, and at the end simply waving off the most crucial issues, so I wish to address his points in reverse order: 10. What other geneticists say: Let me begin by going to the very end of my book (Appendix 1), where I quote key papers written by the leading experts within the field of population genetics. Scott refers to this as my “final shotgun-blast of misrepresentation to the gullible reader”. This seems grossly unfair, since I am simply quoting the leaders in the field where they acknowledge major aspects of my thesis. In my introduction to that section, I am careful NOT to imply that those scientists would agree with my personal viewpoint, but I point out that they all very clearly acknowledge the major problems which I outline in my book regarding the Primary Axiom. These experts in the field provide strong for all the main points of my book … Is man presently degenerating genetically? It would seem so, according the papers by Muller, Neal, Kondrashov, Nachman/Crowell, Walker/Keightley, Crow, Lynch et al., Howell, Loewe and also myself (in press). Scott suggests this is foolishness and dismisses the Crow paper (1–2% fitness decline per generation). But Kondrashov, an evolutionist who is an expert on this subject, has advised me that virtually all the human geneticists he knows agree that man is degenerating genetically. The most definitive findings were published in 2010 in the Proceedings of the National Academy of Scienceby Lynch.4 That paper indicates human fitness is declining at 3–5% per generation. I personally feel the average mutational effect on fitness is much more subtle than Lynch does—so I think the rate of human degeneration is much slower than he suggests—but we at least agree that fitness is going down, not up. Can Scott find any qualified geneticist who asserts man is NOT now degenerating genetically? There is really no debate on current human genetic degeneration—Scott is 100% wrong here, and is simply not well informed. Is there a theoretical problem associated with continuously growing genetic load due to subtle un-selectable deleterious mutations? Yes, according to Muller, Kondrashov, Loewe, and many others. Population geneticists all seem to acknowledge the fact that a large fraction of deleterious mutations are too subtle to be effectively selected away. The question is, what is that fraction? At what point does the fitness effect of a deleterious mutation become too small to be selected away? I have been studying this for about 7 years. Our numerical simulations indicate that for higher organisms, up to 90% of all deleterious mutations should be un-selectable (in press). This manuscript was previously sent to Scott, but it seems he did not read it. Can Scott explain away this theoretical problem? What is Dr. Ohta’s view on genetic degeneration? Dr. Tomoko Ohta was a key student of Kimura, and published extensively with Kimura. Dr Ohta came to be known as the ‘Queen of Population Genetics’, and is now an honorary member of the American Academy of Arts and Sciences, and an associate of the National Academy of Sciences, USA. She is the world’s authority on the topic of near-neutral mutations. One of my co-authors went to Japan to spend several days discussing with her a manuscript in which we used numerical simulation to clearly demonstrate that near-neutral deleterious mutations generally escape selective removal and lead to continuous and linear accumulation of genetic damage. She acknowledged that our numerical simulations appeared to be valid, and that our conclusions appeared to be valid. This clearly reflects a profound evolutionary paradox (it is the same paradox Kondrashov addressed in his paper “why have we not died 100 times over?”5). When asked about synergistic epistasis, she immediately acknowledged that synergistic epistasis should make the problem worse, not better, just as I argue in my book. Using numerical simulations, we have confirmed that synergistic epistasis fails to slow mutation accumulation and accelerates genetic decline (in press). I think Dr. Ohta would like me to clarify that she is a faithful Darwinist and remains committed to the Primary Axiom, and that she is in fact hostile to the thesis of my book. The other quotes: I encourage Scott to read all the other quotes in the appendix. It is clear that the leading population geneticists have recognized major theoretical problems with the Primary Axiom for a long time. Why try to deny this? 9. Synergistic Epistasis: Scott spends a lot of time selling synergistic epistasis. What he may not realize is that population geneticists almost universally understand that most mutations interact either additively or multiplicatively.Suppose two mutations each reduce fitness 10%. When both mutations are present, then fitness might be reduced by 20% (additive interaction), or less than 20% (multiplicative interaction), or more than 20% (synergistic epistasis). To the extent synergistic epistasis happens, it obviously will accelerate degeneration! The only reason synergistic epistasis is even invoked in a generalized sense is when trying to argue that more genetic damage might somehow induce more effective selection (we can now clearly show that

even if synergistic epistasis was normally true, it makes the degeneration problem worse). Population genetic theory was built on the understanding that genetic interactions are primarily additive or multiplicative. If synergistic epistasis was generally true (it is just a rare exception to the norm), most of the papers ever published in the field of population genetics would be invalid! Yet synergistic epistasis would have to be the norm before it would even be conceivable that it might enhance selection.Naturally, all possible types of interactions occur in a complex genome, including instances of synergistic epistasis. Synergistic epistasis would be of little concern to population geneticists except for one thing; it is their last straw in the struggle to solve the degeneration problem. Careful consideration makes it clear that even if synergistic epistasis was the primary mode of interaction (rather than being a rare exception), it only makes the degeneration problem worse. I point this out in my book, and Ohta reaches the identical conclusion (see above). We have done extensive numerical simulations that show that this is true (in press). 8. Crow still believed in the Primary Axiom: Scott spends a lot of time showing that even though Crow believed mankind is degenerating at 1–2% per generation, he remained faithful to the Primary Axiom. That is certainly true, and I made that clear in my book. 7. Human life span has recently been increasing: It is obviously true that human longevity has increased in recent centuries, but that is not due to evolutionary advance. It is clearly due to improved diet, sanitation, and modern medicine. We have figured out how to keep people from dying in infancy and extended the life expectancy for those who catch many diseases associated with middle-age. Thus, the average has gone up. The maximum possible lifespan has not gone up. This is a simple concept.6 6. Genetic entropy is not obvious in lab experiments or in nature: It is true that most lab experiments do not show clear degeneration. But Scott should realize that anything alive today must have been degenerating slowly enough to still be here, even in a young earth scenario. All three of the downward decay curves I show in my book indicate that degeneration slows dramatically as it becomes more advanced. If a species is alive today and has been around for thousands of years, the rate of degeneration must be very slow (too subtle to measure in most cases). Obviously, genetic degeneration is not going to be clearly visible in most lab experiments.Regarding Scott’s argument about viruses and bacteria, such microbes should degenerate very slowly because mutation rate per genome is low, and selection is intense and continuous. Despite this, we have just published a paper showing that RNA viruses are clearly subject to genetic entropy.7 Another reason viruses (and bacteria) can persist in spite of genetic entropy is that they can be preserved in a dormant state for thousands of years. Therefore, even if most active strains continuously died out (say after a thousand years), new strains could be continuously reseeded into the environment from natural dormant reservoirs.Regarding mice, our numerical simulations suggest organisms like mice should last longer than longer-lived mammals because they have lower mutation rates per generation and much more frequent cycles of selection. The first species to go extinct due to mutation accumulation should be large, long-lived organisms.8 Even if species are not actually degenerating, the question of what sustains them would remain. Careful analysis shows mutations/selection could not be that sustaining force. 5. Duplications have biological effects: This is obviously true, but how is it relevant? Like the accidental duplications that happen in emails and student essays, duplications are almost universally deleterious. Very rarely, some are beneficial. A few rare beneficial duplications cannot offset the many accumulating deleterious duplications, let alone all the other accumulating mutations.9 4. Mutation accumulation experiments suggest extremely high rates of beneficial mutations: Mutation accumulation experiments are a very poor way to understand deleterious mutation accumulation. Such experiments do not study actual mutations, they only study performance of strains (the supposed ‘mutations’ are only inferred). In the papers of this type I have examined, zero mutations are actually documented. All that is observed is differential performance of strains. Non-genetic causes, including epigenetic effects or gain/loss of viruses in some bacterial culture, etc., cannot be precluded. More to the point, since the overwhelming majority of mutations are very subtle and do not express a clear phenotype, almost all mutations will be invisible in these experiments, which only monitor gross differences in performance. Only high-impact mutations can be observed in such experiments, and these represent a biased sampling of the actual mutational spectrum. Furthermore, high-impact deleterious mutations will still always be selected away in such experiments, no matter how hard the experimenter tries to preclude natural selection. Therefore there will be a strong tendency to preferentially observe only high-impact beneficials. Since the crux of the genetic entropy argument involves the low-impact deleterious mutations (which will always be invisible in such experiments), these types of experiments have no relevance to this discussion. A final point: in these experiments, fitness is always narrowly defined (i.e., ability to grow on a given medium). For simple, one-dimensional traits like this, any genetic change affecting that trait has a reasonable chance of being beneficial (in a one-dimensional system, any change can only be either up or down, as opposed to improving a real-world complex network of traits where fitness is enormously multi-dimensional). 3. Just how rare are beneficial mutations? Scott speaks as if I do not acknowledge there are beneficial mutations. I acknowledge them very openly in the book, but I also insist that beneficials must be very rare compared to deleterious mutations (as do nearly all geneticists). The critical question is “how rare?” Genomes are the genetic specifications that allow life to exist. Specifications are obviously inherently SPECIFIC. This means that random changes in specifications will disrupt information with a very high degree of certainty. This has become especially clear ever since the publication of the ENCODE results, which show that very little of our genome is actually ‘junk DNA’. 10 The ENCODE project also shows that most nucleotides play a role in multiple overlapping codes, making any beneficial mutations which are not deleterious at some level vanishingly rare (in preparation). Our own numerical simulations (in press) show that that unless beneficial mutations are extremely common, they are not sufficient to compensate for accumulating deleterious mutations. The bottom line is that selection removes only the

worst deleterious mutations and amplifies only the best beneficial mutations. This means that the accumulating damage is largely invisible (like rust on a car), while adaptations tend to be highly visible (e.g., antibiotic resistance). This means that even if Scott presents us with 1000 examples of adaptation via beneficial point mutation, he has still failed to address the key issue—net gain versus net loss. Adaptation explains fine-tuning to an environment; it does not explain the astounding internal workings of life. It does not begin to explain the mystery of the genome.Where are the beneficial mutations in man? It is very well documented that there are thousands of deleterious Mendelian mutations accumulating in the human gene pool, even though there is strong selection against such mutations. Yet such easily recognized deleterious mutations are just the tip of the iceberg. The vast majority of deleterious mutations will not display any clear phenotype at all. There is a very high rate of visible birth defects, all of which appear deleterious. Again, this is just the tip of the iceberg. Why are no beneficial birth anomalies being seen? This is not just a matter of identifying positive changes. If there are so many beneficial mutations happening in the human population, selection should very effectively amplify them. They should be popping up virtually everywhere. They should be much more common than genetic pathologies. Where are they? European adult lactose tolerance appears to be due to a broken lactase promoter [see Can’t drink milk? You’re ‘normal’! Ed.]. African resistance to malaria is due to a broken hemoglobin protein [see Sickle-cell disease. Also, immunity of an estimated 20% of western Europeans to HIV infection is due to a broken chemokine receptor—see CCR5-delta32: a very beneficial mutation. Ed.] Beneficials happen, but generally they are loss-of-function mutations, and even then they are very rare! Scott makes a big deal about Lenski’s long-term bacterial experiments, but these actually my thesis. Although a very trivial adaptation happened (optimal growth on a given medium), his bacteria shrank in genome size (the functional genome decreased). Evidently the more rapid growth was largely accomplished through genetic degeneration. Many useful genes not essential in that artificial environmentwere apparently lost. When transferred to a natural environment, those highly degenerated bacteria would essentially be dead-on-arrival.Scott seems to think that as long as beneficials happen (regardless of how rare they are) the Primary Axiom must be true. Likewise he thinks that, as long as he can show selective adaptations happen (no matter how trivial), this proves the Primary Axiom. I do not think he grasps just how difficult it is to build a genome apart from design. Nor does he seem to understand that a population can be undergoing genetic decline due to vast numbers of slightly deleterious mutations even while selection may be amplifying a handful of beneficial mutations. He seems to fail to realize that a species can undergo minor adaptive fine-tuning to its environment even while degenerating in many other ways. So let me try to make it even simpler. Picture a ten year old car. It is degenerating in all possible ways. Install new windshield wipers. Has the car stopped degenerating? There has certainly been an improvement, but not the type of improvement that can reverse the ubiquitous and systematic degeneration.In collaboration with other scientists, we have advanced the field of population genetics by developing the ‘state of the art’ in of numerical simulation of the mutation/selection process.11 Using biologically realistic parameters, the program ‘Mendel’s ant’ consistently shows genetic decline even given very generous rates of beneficial mutation. This strongly validates my book. Mendel’s ant cannot tell us the true history of life, but what it can do is tell us what selection can and cannot realistically do in the present. from Genetic Entropy pages 31 and 32 2. Kimura’s Figure: Scott makes a huge deal about my reference to a figure in Kimura’s work. He misrepresents me by arguing I misrepresented Kimura (I did not claim Kimura agrees with me). But this is a rabbit trail; the argument is not about Kimura. The crucial issue is about defining the correct distribution of mutation effects. For deleterious mutations, Kimura and most other population geneticists agree the distribution is essentially exponential. Figure 3c in my book (based upon Kimura) shows an exponential-type distribution of deleterious mutations, with most deleterious mutations being ‘nearly-neutral’ and hence unselectable (effectively neutral). But, as I point out, Kimura’s picture is not complete, because degeneration is all about the ratio of good to bad mutations. Kimura does not show the beneficial distribution, which is essential to the question of net gain versus net loss! When I show the beneficial distribution (while Kimura did not do this, I suspect he would have drawn it much as I did), anyone can see the problem: the vast majority of beneficial mutations will be un-selectable (Figure 3d). Scott does not appear to contest my representation of the mutational effect distribution, which is the main issue here. Scott should easily be able to see that most mutations fall within the ‘no-selection zone’ and that almost all of them are deleterious. So even with strong selection, this entire zone can only undergo degeneration. Outside this zone, the substantially bad mutations will be selected away, and an occasional rare high-impact beneficial will be amplified (which can explain isolated events such as antibiotic resistance). 1. Sanford is a liar: Scott repeatedly asserts that my book is all about deliberate deception, and I am fundamentally a liar. He bases this upon two things: a) there were a few references he thinks highly relevant, which I failed to cite and which he says proves I have withheld and suppressed evidence; b) He argues I must surely know that beneficial mutations happen, that natural selection happens, and also that long term lab experiments do not show rapid degeneration. Therefore, I must be dishonestly pretending to be ignorant of these things in order to deceive the ignorant. He has not considered these possibilities: a) given the mountain of relevant literature, I might legitimately miss a few papers; b) I do not share his view on which papers are significant. He cites a great many papers which only speak of the obvious: beneficials do happen, selection does happen, adaptation does happen. Any high school student knows these things. My argument only begins AFTER acknowledging these obvious things.Scott and I corresponded briefly before his posting, and I tried to explain to him why his criticisms were not correct. I did not find him to be a very good listener as I tried to explain how he was misrepresenting me. I then sent him a series of preprints (in press), which extensively and conclusively addressed all his objections. Upon reading his essay now, I can see he did not bother reading those preprints, which are very rigorously written scientific research papers. I also see from his current arguments, that he really did not give my book a fair read. If Scott has misrepresented both the book and myself, then which of us is lacking in integrity?This book cost me a great deal. I basically laid down my reputation and my career in order to say what I believe to be the truth. I believe the real deception is clearly the Primary Axiom. I am still convinced I can persuade any impartial person that the Primary Axiom is indefensible (if they will listen). So why would I lie? I am a sincere orthodox Christian, I believe God will judge me in a very literal sense, and I consider lying is a very serious sin. I am distinguished in my field and I greatly value my integrity as an honest scientist .That is why I have been willing to

defend what I believe to be true, even knowing that attacking this sacred cow (the Primary Axiom) would bring slander and scorn. Why would I write a book that would ruin a very good scientific reputation knowing it would make me a liar before God?In our personal correspondence, Scott closed our conversation saying he intended to present me as being intentionally deceitful. My last word to him was that while I might be technically in error on certain points, my book reflects what I really believe to be true. Any technical errors in my book show that I am human, but there certainly was no deliberate deception in my book. In of the scientific issues, I would ask Scott to append this response to his blog attack. I still welcome any fair-minded and balanced analysis of the scientific merits of my book and my subsequent studies. Genetic entropy and simple organisms If genetic entropy is true, why do bacteria still exist? by Robert Carter Published: 25 October 2012 (GMT+10) Summary Genetic entropy (GE) is eroding the genomes of all living organisms because mutations are inherited from one generation to the next. Many people wonder why, if GE is real, are bacteria still alive today? There are multiple reasons for this, including the fact that their genomes are simpler, they have high population sizes and short generation times, and they have lower overall mutation rates. This combination makes them the most resistant to extinction. Of all the forms of life on Earth, bacteria are the best candidates for surviving the effects of GE over the long term. This does not mean they can do so forever, but it explains why they are still around today. What is genetic entropy? After the landmark publication of Genetic Entropy and the Mystery of the Genome by Cornell University Professor Dr John Sanford, we have often been asked to supply further details of this major challenge to evolutionary theory. The central part of Sanford’s argument is that mutations (spelling mistakes in DNA) are accumulating so quickly in some creatures (particularly people) that natural selection cannot stop the functional degradation of the genome—let alone drive an evolutionary process that can turn apes into people.A simple analogy would be rust slowly spreading throughout a car over time. Each little bit of rust (akin to a single mutation in an organism) is almost inconsequential on its own, but if the rusting process cannot be stopped it will eventually destroy the car. A more accurate analogy would be to imagine a copy of Encyclopedia Britannica on a computer that has a virus that randomly swaps, switches, deletes, and inverts letters over time. For a while there would be almost no noticeable effect, but over time the text would contain more and more errors, until it became meaningless gibberish. In biological , ‘mutational meltdown’ would have occurred. When living things reproduce, they make a copy of their DNA and this to their progeny. From time to time, mistakes occur, and the next generation does not have a perfect copy of the original DNA. These copying errors are known as mutations. Most people think that ‘natural selection’ can dispose of harmful mutations by eliminating individuals that carry them. But ‘natural selection’ properly defined simply means ‘differential reproduction’, meaning some organisms leave more progeny than others based on the mutations they carry and the environment in which they live. Moreover, reproductive success is only affected by mutations that have a significant effect. Unless mutations cause a noticeable reduction in reproductive rates, the organisms that carry them will be just as successful in leaving offspring as all the others. In other words, if the mutations aren’t ‘bad’ enough, selection can’t ‘see’ them, cannot eliminate them, and the mutations will accumulate. The result is ‘genetic entropy’. Each new generation carries all the mutations of previous generations plus their own. Over time, all these very slightly harmful mutations build up to a point that, in combination, they start to have serious effects on reproductive fitness. The downward spiral becomes unstoppable, because every member of the population has the same problem: natural selection can’t choose between ‘fit’ and ‘less fit’ individuals if every member of the population is, more or less, equally mutated. The population descends into sickness and finally becomes extinct. There’s simply no way to stop it.Dr Sanford argues that humans could not possibly have been around for tens of thousands of years (let alone millions, or billions if one considers our supposed evolutionary animal ancestors) because, at the current rate of mutation and the number of generations that would have occurred, we should have already become extinct. Genetic entropy in bacteria From time to time, we are asked by honest people seeking a better understanding, as well as hostile people trying to challenge us, to explain why, if genetic entropy (GE) is true, do bacteria still exist? After all, bacteria have extremely short generation times. Some bacteria can reproduce every 20 minutes, so would be gaining far more mutations in a day than humans would in a hundred years. And bacteria are much simpler organisms, so it should take less time to break down their genetic instruction set compared to humans. Why, then, did they not go extinct long ago?There are several ways to answer this. First, the idea of GE was developed by population geneticists working on higher genomes (i.e. genomes of the more complex organisms with longer generation times). The big puzzle is why species like humans have not gone extinct if we have been around for tens of thousands of years as evolutionists maintain. 1 In a complex organism, a high mutation rate combined with a low reproduction rate makes it very difficult for ‘natural selection’ to remove deleterious mutations from the population. Thus, higher mammals like people and elephants are not good candidates for long-term survival because mutations accumulate from one generation to the next. For eukaryotic organisms (everything more complex than bacteria), the complexity of the genome makes the ‘mutation target’ quite large—in these more-complicated systems, there are more things that can go wrong, i.e. more machinery that can be broken.2

On the other hand, changes to simpler genomes will often have more of a profound effect. Changing one letter out of the three billion letters in the human genome is not likely to create a radical difference. But the genome of the bacterium E. coli, for example, is about 1,000 times smaller than that of humans; bacteria are more specialized and perform fewer functions. Any letter change is more likely to do something that natural selection can ‘see’. That is, it is more likely that a small change will produce a large enough effect that it will make a difference in the number of individuals carrying that trait generations later.It’s important to note that there are multiple things going on at once. We have to consider a combination of factors in order to understand why bacteria are still with us today. Let’s use an illustration. Bacteria are like bicycles. People are like sports cars. One can make a number of modifications to both without breaking them, but there are fewer parts in a bicycle, so any given modification is more likely to produce a non-working bicycle. They need two wheels, a handle bar, a frame, a chain, and at least two gear sprockets. There is very little you can remove from them or break before they can’t be used. Cars, on the other hand, don’t need a roof, windshield, or headlights. There are a lot more modifications you can make to a car and still drive it around. You may not get to work on time, because it does not operate at full potential, but the car can still be driven. But why, if mutation is more likely to kill or harm a bacterial cell, do they still exist? First, bacteria do suffer from GE. In fact, and perhaps counter intuitively, this is what allows them to specialize quickly.3 Many have become resistant to antibiotics4 and at least one has managed to pick up the ability to digest non-natural, man-made nylon.5 This is only possible with much ‘genetic experimentation’, mostly through mutation, but sometimes through the wholesale swapping of working genes from one species to another. Many mutations plus many generations gives lots of time for lots of genetic experiments. In fact, we have many examples, including those just mentioned, where breaking a perfectly good working system allows a new trait to develop. 6 Recently, it was discovered that oceanic bacteria tend to lose genes for vital functions as long as other species of bacteria are living in the area. Here we have an example of multiple species losing working genes but surviving because they are ed by the metabolic excretions of other species.7Since the changes are one-way and downhill, this is another form of GE. Lower mutation rates Another reason why bacteria still exist is that they have a lower overall mutation rate. The mutation rate in E. coli has been estimated to be about 1 in 10 –10, or one mutation for every 10 billion letters copied. 8 Compare this to the size of the E. coli genome (about 4.2 million letters) and you can see that mutation is rare per cell. Now compare this statistic to the estimated rate of mutation per newborn human baby (about 100 new mutations per child2) and one can begin to see the problem. Thus, there are nearly always non-mutated bacteria around, enabling the species to survive. However, there are also always mutated bacteria present, so the species are able to explore new ecological niches (although most known examples have arisen at the expense of long-term survival). Incredible growth potential Bacteria have an amazing growth rate. The entire world population of a species like E. coli turns over very fast (perhaps once per hour). Trillions upon trillions of these cells die for many different reasons each and every hour. Thus, this may be a system where natural selection can actually halt the inevitable decay. Why? Because any mutation that confers even a small disadvantage (and most do) can be removed through differential reproduction, given enough time. (Time in this case is measured in generations.)Bacteria can replace themselves after a population crash in a very short period of time. This is a key reason they do not suffer extinction. Thus, when exposed to antibiotics, for example, the few resistant cells within the population can grow into a large replacement population in short order, even though 99.99% of the original bacteria may have died. If the antibiotic is removed, the population can turn over again, with the non-resistant ones replacing the resistant ones (because antibiotic resistance is usually associated with impaired growth, so the originals grow faster and would dominate the population in a few generations). Humans cannot do this. It would take thousands of years to replace the current population of 7 billion people, and the inbreeding that would occur when the few survivors were forced to marry close relations might drive us to extinction anyway.9 Bacteria vastly outnumber people Population size is another consideration. There are many more bacteria than people. But since bacterial population sizes are relatively constant, there isn’t room for more, and competition is extreme. Most lineages die out in the long run. In large populations, with lots of competition, mutations can be purged more efficiently through differential reproduction. Any cell with a slight advantage over another is more likely, over generations, to persist. Environmental sources It is quite feasible that many bacterial species undergo significant periods of dormancy. Bacteria coming out of dormancy would serve as a continual source of older, less mutated versions and would help to prevent GE over the long term. Mutations can’t hide in prokaryotic genomes Eukaryotes, such as humans, inherit two copies of each chromosome—one from each parent. 10 Thus, any mutation on one human chromosome is often masked by the good copy on the other chromosome. This interferes with differential reproduction based on mutational differences (e.g. ‘natural selection’) and increases the mutation burden of our species. This is not true for bacteria, which reproduce asexually and inherit their DNA from only one parent. What about other fast-reproducing organisms? One might reply, “But mice have genomes about the size of the human genome and have much shorter generation times. Why do we not see evidence of GE in them?” Actually, we do. The common house mouse, Mus musculus, has much more genetic diversity than people do, including a huge range of chromosomal differences from one sub-population to the next. They are certainly experiencing GE. On the other hand, they seem to have a lower per-generation mutation rate. Couple that with a much shorter generation time and a much greater population size, and, like bacteria, there is ample opportunity to remove bad mutations from the population. Long-lived species with low population growth rates (e.g. humans) are the most threatened, but the others are not immune. Conclusions

There are attempted evolutionary counter arguments to the basic GE hypothesis. They are weak, but it is not the purpose of this article to give an all-comprehensive defense of the theory. It is sufficient to say, however, that bacteria, of all the life forms on Earth, are the best candidates for surviving the effects of GE over the long term. Their simpler genomes, high population sizes, short generation times, and lower overall mutation rates combine to make them the most resistant to extinction. The diminishing returns of beneficial mutations Low-temperature electron micrograph of a cluster of E. coli bacteria. Each individual bacterium is oblong shaped. by Shaun Doyle Published: 7 July 2011(GMT+10) Subsequently published in Journal of Creation 25(3) Beneficial mutations are often seen as the engine of evolution (Mutations: evolution’s engine becomes evolution’s end!). However, beneficial mutations by themselves don’t solve the problem (see Beetle Bloopers). Mutations not only have to be beneficial, but they have to add biological information, i.e.specified complexity. However, practically all beneficial mutations observed have been losses of specified complexity (The evolution train’s a-comin’), with only a few disputable examples of mutations increasing information ever found (e.g. bacteria that digest nylon, citrate or xylitol). Epistasis: how do mutations interact? However, mutations need to be more than beneficial and information-increasing to produce new coordinated structures and systems, as microbes-to-man evolution requires. Mutations don’t act alone; the effect of a mutation on an organism’s phenotype depends on other genes, and mutations in those genes, in the genome. This is calledepistasis; it is an important consideration for evolution because how mutations interact will determine if they could possibly build new structures in a stepwise manner.For microbes-to-man evolution to occur, mutations need to be not just (specified) information-increasing and beneficial, they also need to work together. This also has to be the main dominant trend in adaptive evolution so that the mutations can together produce new biological structures and systems. This phenomenon is called synergistic epistasis (SE), where the combined effect of mutations is greater together than the sum of their individual effects. This is obviously a good situation for beneficial mutations, but very bad for harmful mutations. In harmful mutations, SE can result in synthetic lethality1, where the combined effects of several harmful mutations are compounded by each other’s presence, resulting in such a bad effect that it kills the organism. 2 So evolution needs SE to be common only in beneficial mutations; it works against evolution when it occurs in harmful mutations.Antagonistic epistasis (AE) is the opposite of SE. It occurs when mutations have a negative influence on each other, such that their combined effect is less than the sum of the effect of the individual mutations. For harmful mutations, this is a good thing because it mutes the effect of individual mutations and stalls error catastrophe.3 This is obviously no help for evolution in the long run, since they are still harmful mutations. However, AE presents problems for evolution if it occurs in beneficial mutations. The benefits of individual mutations are muted by other beneficial mutations, resulting in a decreasing rate of fitness increase with every beneficial mutation added. How not to work together Two recent studies investigated the effects that beneficial mutations have on each other and came up with basically the same results. One study looked at the combined effect on fitness from some of the earliest beneficial mutations to occur in Richard Lenski’s “Long Term Evolution Experiment” on 12 Escherichia coli populations.4This is the same experiment that produced an E. coli population with the ability to utilize citrate under aerobic conditions, whereas it couldn’t before. This was widely hailed as an example of ‘evolution’, but see our response, Bacteria ‘evolving in the lab’?. Another study, published in the same issue of Science, looked at the effect beneficial mutations have on each other in an engineered strain of Methylobacterium extorquens.5Both studies found that beneficial mutations interacted under an overall trend of antagonistic epistasis. Khan et al., in comparing their study with Chou et al., pointed out the results of both studies were virtually identical:“Note that similar trends were seen by Chou et al. … . That study, like ours, found that four mutations interacted to yield diminishing fitness returns, whereas one mutation had the opposite effect.”6Therefore, the cumulative effect of the “beneficial” mutations together was smaller than it would be if the mutations were considered independently— i.e. they display an overall trend of antagonistic epistasis. Some individual mutations displayed synergistic epistasis, but they were a minority, and were not enough to reverse the overall trend. Khan et al. explain this as a result of environmental adaptation: “Mechanisms that may explain this deceleration include reductions in the number and effect-size of beneficial mutations as a population becomes better adapted to its environment … In other words, epistasis acts as a drag that reduces the contribution of later beneficial mutations.”But is this it? No doubt that this is a fair assessment of these results as far as they go. These experiments were done in strictly controlled environmental conditions, so the range of questions that can be answered is limited. However, these results didn’t take into environmental flexibility and change. Khan et al. observed examples of previous mutations that stymied the adaptive capabilities of some lines relative to others in the population.7 But the obvious question is this: what effect does antagonistic epistasis have when the environment changes? Are the organisms as robust to mutation and as adaptable as their ancestors?Humanity’s own long-term ‘experiments’ in artificial selection would probably present the clearest answer, and it would be “no”. For example, Dogs have been artificially selected for all sorts of traits for centuries, and the typical experience is that purebred dogs are weaker, have more congenital problems, and live shorter lives than ‘mongrel’ dogs (“A Parade of Mutants”—Pedigree Dogs and Artificial Selection). What is a beneficial mutation? Both studies stated they were studying beneficial mutations. But what do they mean by beneficial? Are these mutations universally beneficial, or only within a certain environmental context? These may seem like trite questions, but they become immensely important when we consider the context of these studies. As I stated above, these are laboratory studies conducted in strictly controlled environments, so the mutations observed are only known to be ‘beneficial’ within a strict environmental context.Moreover, Chou et al. conducted their experiments on an engineered bacterial strain that, even without mutations, grew three times slowerthan the wild-type in the same environment.8In the engineered strain Chou et al. eliminated an essential metabolic pathway and replaced it with another from a different species. All the ‘beneficial’ mutations

in the engineered strain were merely compensating for the loss of the native metabolic pathway. The same mutations in the wild type would most likely be harmful.Finally, a beneficial mutation is not necessarily a mutation that increases specified complexity. Something is beneficial if it confers an advantage, not necessarily if it adds information. This points to an important issue: mutations not only have to add information to evolution, but they also have to be selectable. Since mutations (apart from a few trivial examples) are universally losses of specified complexity, and natural selection is incredibly slow and weak, beneficial mutations are ultimately no help to evolution. Genetic entropy and the mystery of epistasis These studies reflect a universally consistent trend in lab experiments on adaptation: “The most consistent finding across studies of laboratory-evolved populations has been a rapid deceleration of the rate of fitness increase.”The two scientific reports discussed above are in line with those consistent results, and serve as further confirmation of Dr John Sanford’s landmark book: Genetic Entropy and the Mystery of the Genome.9 Dr Sanford pointed out that the genome is in a state of inexorable decay because of mutations. If beneficial mutations generally get in the way of each other, their combined effects cannot stop this process of decay in the genome. Evolution thus has three strikes against it: most mutations are not beneficial, practically all mutations destroy specified complexity, and, now, even ‘beneficial’ mutations work against each other. While mutations may be of limited benefit to a single organism in a limited context (e.g., sickle cell anemia can protect against malaria even though the sickle cell trait is harmful), mutations seem to be no benefit whatsoever for microbes-to-man evolution, whether individually or together. Pesticide resistance is not evidence of evolution by David Catchpoole Published: 20 August 2009(GMT+10) Since aerial application of pesticides (“crop dusting”) first began in the 1920s, there have been tremendous improvements in knowledge, technology and safety. However, irrespective of the application method used, farmers must face the phenomenon of pesticide resistance.A favourite icon of evolutionists, i.e. oft-cited by them as evidence of evolution, is the phenomenon of pesticide resistance.On the evolution-proclaiming PBS1 website for example, the diminished efficacy of rodent poisons and insecticides is because “we have simply caused pest populations to evolve”. 2 And no doubt wanting to prove that evolutionary theory has practical relevance, the PBS Evolution Librarypaints a grim picture of how this “evolution” is making life harder for us:“It has the menacing sound of an Alfred Hitchcock movie: Millions of rats aren’t even getting sick from pesticide doses that once killed them. In one county in England, these ‘super rats’ have built up such resistance to certain toxins that they can consume five times as much poison as rats in other counties before dying. From insect larvae that keep munching on pesticide-laden cotton in the US to head lice that won’t wash out of children’s hair, pests are slowly developing genetic shields that enable them to survive whatever poisons humans give them.”2 (Emphasis added.)Having now got the reader’s attention, and warning that “the problem is getting worse”, the PBS article comfortingly (?) says, “but the pests are only following the rules of evolution”. However, looking past the evolutionary assertions, the PBS article makes it clear that pesticide resistance is not evidence of evolution at all:“Every time chemicals are sprayed on a lawn to kill weeds or ants for example, a few naturally resistant of the targeted population survive and create a new generation of pests that are poison-resistant.”2 (Emphasis added.) And again: “Individuals with a higher tolerance for our poisons survive and breed, and soon resistant individuals outnumber the ones we can control.”2 So the mechanisms that allow pests to tolerate pesticides are already present in “a few naturally resistant of the targeted population”, which survive to reproduce themselves, thus ing the genes conferring pesticide resistance to the next generation.Thus pests are not “slowly developing genetic shields” because the “genetic shield” already exists, i.e. it has not “evolved” out of thin air. What is happening is that the “genetic shield” becomes more widespread in the population, as an astute reader will discern from the PBS article’s subsequent explanation of what happens when farmers, noting lowered kill rates, increase the dosage: “Farmers spray higher doses of pesticide if the traditional dose doesn’t kill, so genetic mechanisms that enable the pests to survive the stronger doses rapidly become widespread as the offspring of resistant individuals come to dominate the population.”2 (Added emphasis.) And the spread of the genetic mechanisms conferring resistance can be very rapid indeed—coming to “dominate the population” in just a few generations, in fact. Rapid resistance in nematodes For example, when researchers exposed the nematode Caenorhabditis elegans to the widely used nematicide levamisole, they reported that resistance to that pesticide “accumulated within very few generations”.3 The researchers explained that this rapid adaptation was likely due to the “standing genetic variation” of the nematode population, i.e. that the genes conferring resistance were already present in the population, but at low frequency. Exposing the nematodes to levamisole selected for the resistant individuals, “providing a direct demonstration of the speed of this process”. (Emphasis added.) There are numerous other examples of rapid adaptation in the scientific literature.4Evolutionists are often needlessly surprised at the speed with which a population can adapt to a change in environment, because they are so used to thinking of such changes as being “evolution”, with evolution being inextricably associated with slow-and-gradual-over-millions-of-years processes (see Speedy Species Surprise). The changes are rapid alright, but they are not evolutionary—that is, relevant to the core claim of evolution that primordial microbes changed into mankind and all other living things.But even the nematode researchers were victims of their evolutionary mindset. Despite not having observed any evolution whatsoever (i.e. the sorts of changes that supposedly resulted in pond scum becoming pesticide scientists), they nevertheless peppered their scientific paper with claims it was rapid “evolution” they had witnessed. “Our results demonstrate that pesticide resistance can evolve at an extremely rapid pace,” they wrote. Their results demonstrated no such thing. Rapid rise in resistance to pesticides—yes; but “evolve”?—no, as individuals with the “genetic shield” conferring nematicide resistance were apparently already in the population. The price of resistance

Mechanisms of pesticide resistance can come at a cost, research has shown. Referred to as “fitness cost”, resistance genes are said to “alter some components of the basic physiology and interfere with fitness-related life history traits”. 5A famous example is that of warfarin resistance in rats, first detected in the late 1950s. 6 Rats resistant to that poison have a higher requirement for vitamin K than normal rats (more than 10 times!). When vitamin K is inadequate, warfarin-resistant rats suffer from blood clotting disorders—in fact, many will die from internal bleeding. Consequently, resistant individuals have a lower fitness under most field conditions, hence the proportion of rats having warfarin resistance in Britain was seen to decline when rat populations were no longer exposed to the rodenticide. Warfarin is an anti-coagulant (stops blood clotting) drug, used both in the treatment of human thromboses (unwanted blood clots) and as a poison for rats and mice. Obviously the amounts istered to people are carefully controlled, whereas the aim in giving it to rats is to kill them. It works by interfering with the normal blood-clotting mechanism, such that the normal rapid repair of small blood vessel leakages does not occur. The rat then dies from internal bleeding. Warfarin was first used in Britain in 1953, and was at first extremely effective at killing rodents. But colonies of resistant rats were first noticed in 1959 in Welshpool, then in the United States and continental Europe.So, the genetic makeup conferring warfarin resistance in rats is associated with increased survival when the pesticide is present, but decreased survival when the pesticide is absent.That “fitness cost” phenomenon occurs in insect pests too. Researchers monitoring Culex pipiens mosquitoes overwintering in a cave in southern (in an area where organophosphate insecticides are widely used) noted a decline in the overall frequency of insecticide-resistant mosquitoes relative to susceptible ones as the winter progressed, indicating “a large fitness cost”. 5 This is understandable in the light of the genetic mechanism conferring resistance in these mosquitoes. Organophosphate insecticides affect the ability of certain enzymes (proteins) called esterases to function properly, thus killing the insect. But the resistance genes “induce an overproduction of esterase, due to either gene amplification or gene regulation”.5 Note that having additional copies of existing genes or having genes that fail to switch off (regulate) production is not evidence for evolution because to change microbes into microbiologists, evolution needs a mechanism for adding new complex functions, not copying existing ones or breaking them (photocopying a chapter of a book or breaking an electric switch does not create new new complex functionality).Similar overproduction of proteins occurred in DDT-resistant strains of Anopheles mosquitoes, too.7 The proteins metabolize DDT (an organochlorinebased insecticide). In the researchers’ words, “the transcripts and their proteins are over-expressed in the resistant strains and, as a consequence, are allowing them to exhibit this resistance.”8 Similarly, in Drosophila fruit flies, insecticide resistance is associated with “overtranscription” of a particular gene, resulting in 10 to 100 times as much mRNA in resistant strains as in susceptible strains.9 Given the extra energy and resources needed for such overproduction, it’s hardly surprising then that pesticide resistance carries a fitness cost.10,11In all of the above examples, we’re not seeing the genes, the information, for complex new functions appearing out of nowhere, i.e. by evolution. Instead we’re seeing either possible “amplification” of genes (i.e. additional copies of existing genes) or, more usually, a loss-ofcontrol over regulation of genes. In other words, the mechanisms for pesticide resistance are not from new genes but from existing genes—and especially from damaged versions of existing genes. There has been no increase in meaningful genetic information but rather a loss of information.The old joke about “What’s worse than finding a worm in your apple?” [Answer: Half a worm!] is no joke for apple producers. The FAO has estimated that pests cost horticultural and agricultural producers thousands of millions of dollars annually in lost production. At least 520 insects and mites, 150 plant diseases and 113 weeds have become resistant to pesticides meant to control them.Thus the pesticide resistance “icon” of evolution actually gives no to molecules-to-man evolution whatsoever. We’re not seeing improvement in the genes, we see brokenness, for that is what mutations do—they break genes, not create brand new ones. In today’s world sometimes it’s beneficial to have “broken” genes (e.g. if you’re a rat and there’s warfarin around), but the genes are nevertheless broken—undeniably degraded genetic information. No evolution is in evidence.12 Not an “arms race” Evolutionists love to portray the development of pesticide resistance as a grim “arms race”, no doubt leaving many people with the perception that pests are evolving new features all the time. But now that we’ve seen that pesticide resistance is due to breaking things, not creating new complex features, we can see that “arms race” is a misnomer. Rather, the struggle is better likened to trench warfare,13 where the defending forces will destroy their own bridge, or blow up their own road, to impede the enemy’s advance. An arms race implies that the defending forces are inventing new weapons, but the processes of selection and mutation operating in pests facing a pesticide are not inventing new weapons. So the phenomenon of resistance to nematicides, rodenticides, insecticides, etc., cannot be construed in any way as giving to evolution’s Grand Idea that today’s life forms evolved from some single-celled organism billions of years ago. Rather, the “broken” genes conferring pesticide resistance have arisen in the time since the Fall. And as surveys have shown, in a world where pesticides are used widely, it doesn’t take long for a genetic mutation conferring resistance to rapidly spread around the world.14 Implications for (rather, from!) effective pest control in today’s world What are the practical implications for pest control programs today—i.e. how should pesticide strategies be changed?In fact, pesticide advisers15 at the pest control frontline are mostly already operating practically as if with a creationist perspective (even though as individuals they might not realize it, i.e. they might still accept evolution as being true16). They recognize: An individual rat or insect or other pest does not develop resistance over time. What changes over time is the susceptibility of a population to a pesticide.Resistance may be present in a population even before being exposed to a new pesticide—but in very low numbers. The resistance mechanism might affect the pest adversely in certain ways. But upon exposure to pesticide, those individuals that have the ability to break down a pesticide molecule that kills most other individuals in the population survive.Individuals surviving a pesticide application the genetic mechanisms conferring resistance to that

particular pesticide on to the next generation. Thus the resistant genes make up a greater proportion of the total gene pool than they did before.At first, a farmer might not notice a pest population’s increasing resistance to a pesticide. However, with the age of (pest) generations, there comes a point where the farmer is confronted by “control failure”. But the resistance hasn’t “suddenly appeared”, but rather built up steadily since first exposure to the pesticide. 17Notice that this has no relevance to microbes-to-mankind evolution. This is simply a human-imposed selection process (the same principles are at work with “natural selection”—i.e. no evolution at all).So what do the pest control experts advise growers to do when faced with loss of pesticide effectiveness? A key resistance management strategy that most farmers are aware of and practice as much as possible, is pesticide rotation.18,19 That is, alternating the use of pesticides that have differentmodes of action. (I.e., that affect different essential life functions of the pest, e.g. respiration, transmission of nerve signals, etc.) Pesticide rotation works on the principle that when resistance to, say, an organophosphate-based insecticide is beginning to build up in the population, the farmer switches to using, say, a pyrethroid insecticide. Then, as resistance builds up to that pesticide, he switches to a pesticide with a different chemical mode of action again, if one is legally available (e.g. a carbamate).There have been some instances where “multiple resistance” has developed—the worst case scenario for farmers.However, in no way does this represent evolution, as it involved the same processes as discussed above. The fitness cost of such multiple resistance becomes evident when pesticides are withheld for a period, and non-resistant individuals generally come to dominate the population once more. Thus effective pesticide rotation strategies can begin again.What are the implications from the day-to-day reality of pest responses to pesticides? Evolution is not in evidence, nor does evolutionary theory have any practical relevance to operational science or farming practise.