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The Edge of Evolution?

A few years ago, Intelligent Design researcher Professor Michael Behe wrote a thought-provoking book entitled The Edge of Evolution, which argued that design was much more pervasive in Nature than commonly thought. Professor Behe argued that each and every class of living things, and quite probably each and every family, had been intentionally designed. Now, a recent paper by Dr. Branko Kozulic, a biochemist who serves on the editorial board of the Intelligent Design journal Bio-Complexity, argues that each and every species of living things was intelligently designed, and that the biological concept of a species can best be defined in terms of the unique proteins and genes that characterize it. In a nutshell, Dr. Kozulic’s argument is that there are literally hundreds of chemically unique proteins in each and every species of living organism. These “singleton” proteins have no close chemical relatives, making their origin a baffling mystery. Dr. Kozulic contends that the presence of not one but hundreds of chemically unique proteins in each species is an event beyond the reach of chance, and that each species must therefore be the result of intelligent planning.

If Dr. Kozulic’s conclusion is correct, then it would have interesting implications for the creation-evolution controversy. On a material level, living things might still be biologically related, insofar as they sprang from a common ancestral stock: in other words, common descent could still be true. However, on a formal level, each and every species of living thing would be the product of Intelligent Design and could be viewed as a separate creation, as the unique genes and proteins that endow it with its defining characteristics were essentially built from scratch. In other words: living things might share a common ancestry, but their constituent proteins certainly do not. They were created.

That conclusion would mean that even animals as similar as rats and mice, which diverged between 12 and 24 million years ago) were designed separately. The common Norwegian rat (pictured above, courtesy of Wikipedia) is popularly imagined to be just a scaled up version of a mouse. However, scientists have identified no less than 75 unique genes (69 mouse genes and 6 rat genes) for which there is good evidence of de novo origin since the divergence of mouse and rat. Each of these genes is only found in either the mouse or rat lineages. If Dr. Kozulic is correct, that means that rats and mice have to be viewed as separate designs. Ditto for humans and chimps, both of which have chemically unique proteins and genes.

Before I go on, I’d like to introduce Dr. Kozulic to those readers who may not have heard of him. Dr. Branko Kozulic received a Ph.D. in biochemistry from the University of Zagreb, Croatia, in 1979. From 1983 to 1988, he worked at the Institute of Biotechnology, ETH-Zurich, in Switzerland. For about fifteen years, he worked for a private Swiss biotech company, of which he was a co-founder. He currently works for Gentius Ltd., a company based in Zadar, Croatia. In addition, he teaches at the Faculty of Food Technology and Biotechnology in Zagreb. His professional interests center mainly on methods used for the analysis, detection, characterization and purification of biological macromolecules. Dr. Kozulic has published about 30 scientific papers to date, and he is also the inventor or co-inventor of numerous patents, 18 of which were issued in the USA. Dr. Kozulic formerly served on the Editorial Board of Analytical Biochemistry, and he is currently a board member of Food Technology and Biotechnology.

Dr. Kozulic’s recent paper, which I’d like to discuss today, is titled, Proteins and Genes, Singletons and Species. The paper was submitted to VIXRA, an alternative archive of science and mathematics-related e-prints serving the entire scientific community, on 16 May 2011. In this post, I’m going to be quoting extensively from portions of Dr. Kozulic’s paper, in order to walk readers through his argument. Here’s the abstract:

Recent experimental data from proteomics and genomics are interpreted here in ways that challenge the predominant viewpoint in biology according to which the four evolutionary processes, including mutation, recombination, natural selection and genetic drift, are sufficient to explain the origination of species. The predominant viewpoint appears incompatible with the finding that the sequenced genome of each species contains hundreds, or even thousands, of unique genes – the genes that are not shared with any other species. These unique genes and proteins, singletons, define the very character of every species. Moreover, the distribution of protein families from the sequenced genomes indicates that the complexity of genomes grows in a manner different from that of self-organizing networks: the dominance of singletons leads to the conclusion that in living organisms a most unlikely phenomenon can be the most common one. In order to provide proper rationale for these conclusions related to the singletons, the paper first treats the frequency of functional proteins among random sequences, followed by a discussion on the protein structure space, and it ends by questioning the idea that protein domains represent conserved units of evolution.

And now, without further ado, here are the highlights of Dr. Kozulic’s paper.

How big is protein sequence space? Much bigger than some evolutionists (Dryden et al.) would like it to be

One strategy for defusing the problem associated with the finding of functional proteins by random search through the enormous protein sequence space has been to arbitrarily reduce the size of that space. Because the space size is related to protein length (L) as 20^L, where 20 denotes the number of different amino acids of which proteins are made, the number of unique protein sequences will rapidly decrease if one assumes that the number of different amino acids can be less than 20. The same is true if one takes small L values. Dryden et al. used this strategy to illustrate the feasibility of searching through the whole protein sequence space on Earth, estimating that the maximal number of different proteins that could have been formed on planet Earth in geological time was 4 x 10^43 [9]. In [the] laboratory, researchers have designed functional proteins with fewer than 20 amino acids [10, 11], but in nature all living organisms studied thus far, from bacteria to man, use all 20 amino acids to build their proteins. Therefore, the conclusions based on the calculations that rely on fewer than 20 amino acids are irrelevant in biology. Concerning protein length, the reported median lengths of bacterial and eukaryotic proteins are 267 and 361 amino acids, respectively [12]. Furthermore, about 30% of proteins in eukaryotes have more than 500 amino acids, while about 7% of them have more than 1,000 amino acids [13]. The largest known protein, titin, is built of more than 30,000 amino acids [14]. Only such experimentally found values for L are meaningful for calculating the real size of the protein sequence space, which thus corresponds to a median figure of 10^347 (20^267) for bacterial, and 10^470 (20^361) for eukaryotic proteins. (pp. 2-3)

What proportion of amino acid chains are capable of functioning as proteins?

While scientists generally agree that only a minority of all possible protein sequences has the property to fold and create a stable 3D structure, the figure adequate to quantify that minority has been a subject of much debate. (p. 6)

In 1976, Hubert Yockey estimated the probability of about 10^-65 [that's 1 in 100,000 million million million million million million million million million million - VJT] for finding one cytochrome c sequence among random protein sequences [48]. For bacteriophage λ[lambda] repressor, Reidhaar-Olson and Sauer estimated that the probability was about 10^-63 [49]. Based on β[beta]-lactamase mutation data, Douglas Axe estimated the prevalence of functional folds to be in the range of 10^-77 to 10^-53 [50]. A comparison of these estimates with those concerning the total number of protein molecules synthesized during Earth’s history – about 10^40 [9, 51, 52] – leads to the conclusion that random assembling of amino acids could not have produced a single enzyme during 4.5 billion years [48, 53]. On the other hand, Taylor et al. estimated that a random protein library of about 10^24 members would be sufficient for finding one chorismate mutase molecule [54]. Moreover, from an actual library of 6×10^12 proteins each containing 80 contiguous random amino acids, Keefe and Szostak isolated four ATP binding proteins and concluded that the frequency of functional proteins in the sequence space may be as high as 1 in 10^11 [1 in 100,000,000,000 - VJT], allowing for their discovery by entirely stochastic means [55]. However, subsequent in vivo studies with this man-made ATP binding protein showed that it disrupted the normal energetic balance of the cell, acting essentially as an antibiotic [56]. One can conclude, therefore: had this protein been formed by random mutations, the cell with it would have left no descendants. Furthermore, the probability of its formation in a cell would have been lower than 10^-11, because random DNA mutations introduce stop codons and frameshifts whereas Keefe and Szostak avoided stop codons and frameshift mutations by experimental design [55]. The importance of distinguishing the results of in vitro from in vivo studies is highlighted by the finding that only a tiny fraction, one in about 10^10, of the active mutants of triosephosphate isomerase functioned properly in vivo [57]. (pp. 6-7)

The importance of maintaining the correct order of amino acids

In general, there are two aspects of biological function of every protein, and both depend on correct 3D structure. Each protein specifically recognizes its cellular or extracellular counterpart: for example an enzyme its substrate, hormone its receptor, lectin sugar, repressor DNA, etc. In addition, proteins interact continuously or transiently with other proteins, forming an interactive network. This second aspect is no less important, as illustrated in many studies of protein-protein interactions [59, 60]. Exquisite structural requirements must often be fulfilled for proper functioning of a protein. For example, in enzymes spatial misplacement of catalytic residues by even a few tenths of an angstrom can mean the difference between full activity and none at all [54]. And in the words of Francis Crick, “To produce this miracle of molecular construction all the cell need do is to string together the amino acids (which make up the polypeptide chain) in the correct order” [61, italics in original]. (pp. 7-8)

Dr. Kozulic’s very generous estimate of the odds of building a protein by random trials: 1 in 1,000,000,000,000,000,000,000

Explanatory note: the term in vitro (Latin: within the glass) refers to the technique of performing a given experiment in a controlled environment outside of a living organism; for example in a test tube. In vivo (Latin: within the living) means that which takes place inside an organism. In science, in vivo refers to experimentation done in or on the living tissue of a whole, living organism as opposed to a partial or dead one or a controlled environment. Source.

Let us assess the highest probability for finding this correct order by random trials and call it, to stay in line with Crick’s term, a “macromolecular miracle”. The experimental data of Keefe and Szostak indicate – if one disregards the above described reservations – that one from a set of 10^11 randomly assembled polypeptides can be functional in vitro, whereas the data of Silverman et al. [57] show that of the 10^10 in vitro functional proteins just one may function properly in vivo. The combination of these two figures then defines a “macromolecular miracle” as a probability of one against 10^21. For simplicity, let us round this figure to one against 10^20. (p. 8)

It is important to recognize that the one in 10^20 represents the upper limit, and as such this figure is in agreement with all previous lower probability estimates. Moreover, there are two components that contribute to this figure: first, there is a component related to the particular activity of a protein – for example enzymatic activity that can be assayed in vitro or in vivo – and second, there is a component related to proper functioning of that protein in the cellular context: in a biochemical pathway, cycle or complex. Taking into account both contributions is an essential requirement because a synthetic protein nicely active in the test tube can be lethal in the cellular context, as shown by Stomel et al. for the ATP-binding protein of Keefe and Szostak [55, 56]. (p. 8)

To put the 10^20 figure in the context of observable objects, about 10^20 squares each measuring 1 mm^2 would cover the whole surface of planet Earth (5.1 x 10^14 m^2). Searching through such squares to find a single one with the correct number, at a rate of 1000 per second, would take 10^17 seconds, or 3.2 billion years. Yet, based on the above discussed experimental data, one in 10^20 is the highest probability that a blind search has for finding among random sequences an in vivo functional protein. This figure denotes the minimal height of the brick wall. (p. 9)

Proteins are distributed according to a power law

A power law distribution. Popularity rankings (e.g. ratings of actors) often follow this kind of distribution. To the right is the long tail, and to the left are the few individuals that dominate (also known as the 80–20 rule). Image courtesy of Wikipedia.

What have we learned from these tens of millions of protein sequences originating from the genomes of more than one thousand species? When proteins of similar sequences are grouped into families, their distribution follows a power-law [65-72], prompting some authors to suggest that the protein sequence space can be viewed as a network similar to the World Wide Web, electrical power grid or collaboration network of movie actors, due to the similarity of respective distribution graphs. There are thus small numbers of families with thousands of member proteins having similar sequences, while, at the other extreme, there are thousands of families with just a few members. The most numerous are “families” with only one member; these lone proteins are usually called singletons. (pp. 9-10)

By plotting, on a log-log scale, the number of citations per paper against the total number of citations one obtains the graph shown in Figure 2a, characterized by a disperse tail and a dense head. At the tail, there are groups of small numbers of papers (1, 2, 3 and 4, approximately) achieving citations thousands of times. Only a few individual papers from this dataset approach the 10,000 citations mark. On the other hand, many papers are cited 100 times, even more of them 10 times, while the most numerous are the papers cited just once (apart from those never cited). An analogous plot of earthquake distribution shows many earthquakes of low magnitudes, and an ever decreasing number of stronger earthquakes (Fig. 2b). Moreover, based on common appearance of actors in the same movie, actors’ collaboration network also shows a power-law distribution (Fig 2c). At the tail there are a few superstars who collaborated with thousands of other actors, while newcomers at the head collaborated with just a few. (pp. 10-11)

Distribution of protein families in sequenced genomes is illustrated by a similar graph (Fig. 2d). Comparable distributions have been observed with protein datasets from individual sequenced genomes [65, 80], as well as with the datasets that encompassed all sequenced genomes at various time points [66-72]. Here, at the tail of the distribution there are a few large families each consisting of thousands of proteins having similar sequences, while at the head there are many singletons. The evident similarity of this distribution curve with those of Figure 2a-c has been interpreted as evidence for self-organizing nature of protein networks in living organisms. It was thus inferred that the complexity of genomes grows in the same way as the complexity of WWW, or actors’ network. These interpretations, however, are in error because they have failed to take account of a fundamental difference, as described below. (p. 11)

The first condition that the networks of Figure 2 must fulfill is a continuous addition of new members [78]. Thus, continuously new actors appear in movies, new earthquakes happen and new scientific papers get published. Roughly one person in 10^5 [or 100,000 - VJT] acts in a movie, earthquakes make one of less than 10^5 geological phenomena, and the fraction of scientific papers among all publications is higher than one in 10^5. So, to enter the respective network – to become the first point at the head of the distribution – the newcomers must overcome a barrier not higher than one against 10^5. After the entry, to become prominent the newcomers have a chance of about one in 10^5 again. Evidently, the two barriers, of entering and of becoming prominent, are comparable, give or take a few orders of magnitude. What would happen if the entry barrier were one thousand trillion (10^15) times higher? Obviously, if just one in 10^20 persons could become an actor, we would know of no actors: there would be no records of them, and analogously, there would be no records of scientific papers and earthquakes. (p. 11)

The frequency of functional proteins among random sequences is at most one in 10^20 (see above). The proteins of unrelated sequences are as different as the proteins of random sequences [22, 81, 82] – and singletons per definition are exactly such unrelated proteins. (p. 11)

Thus, to enter the distribution graph as a newcomer (Fig. 2d), each new protein (singleton) must overcome the entry barrier of one against at least 10^20. After the entry, singleton’s chance of becoming prominent, that is to grow into one of the largest protein families, is about one in 10^5 (Fig. 2d). Thus, it is much more difficult for a protein to become biologically functional than to become, in many variations, widespread: the entry barrier is at least fifteen orders of magnitude higher than the prominence barrier. This huge difference between the entry and prominence barriers is what makes the protein family distribution graph unique. In spite of this high entry barrier, in the sequenced genomes the protein newcomers (singletons) always represent the largest, most common, group: if it were otherwise, the distribution graph would break down… [I]n living organisms the most unlikely phenomenon can be the most common one. This feature clearly distinguishes the complexity of living organisms from the complexity of self-organizing networks. (p. 12)

Protein domains follow the same power law distribution

The distribution of protein folds and domains also follows a power-law [21, 66, 67, 70, 72, 80, 83, 87], as predicted by Coulson and Moult [95]. That prediction was considered shocking [13]. Thus, in the sequenced genomes some domains are represented by thousands of different, non-homologous sequences, whereas other domains are represented by a few or by a single, unique sequence [21, 66, 67, 70, 72, 79, 83, 87, 95, 96]. For example, in a set of about 250,000 protein sequences Grant et al. found about 170,000 domains that remained as singletons [96]. These unique domains, called also orphan domains, represent the largest group among all domain groups that make the distributions. This is a feature in common with singletons from the distribution graph of protein sequence families. (p. 13)

Orphan genes do, too

In addition to the term singleton, other terms, with a similar if not synonymous meaning, have been used to denote proteins and genes having no relatives. Thus, Siew and Fischer define genomic ORFans as orphan open reading frames (ORF) with no significant sequence similarity to other ORFs [103, 104]. Wilson et al. suggest that orphans should be named “taxonomically restricted genes” (TRGs) [105, 106], and state that the abundance of orphan genes is amongst the greatest surprises uncovered by the sequencing of eukaryotic and bacterial genomes [105]. Earlier, Russell Doolittle affirmed that there are large numbers of unidentified genes in a variety of organisms, with the origin and function of these unique sequences remaining “baffling mysteries” [107]. (p. 15)

Why the discovery of “singleton” proteins and genes came as a great shock to evolutionists

In order to understand why the finding of singletons (ORF-ans, or TRG-s) represented such a great surprise, let us look at the contemporary expectations. They were possibly best outlined by Chothia et al. in 2003 [108]: “all but a small proportion of the protein repertoire is formed by members of families that go back to the origin of eukaryotes or the origin of the different kingdoms.” And further: “The earliest evolution of the protein repertoire must have involved the ab initio invention of new proteins. At a very low level, this may still take place. But it is clear that the dominant mechanisms for expansion of the protein repertoire, in biology as we know it, are gene duplication, divergence and recombination.” Consequently: “we will be able to trace much of the evolution of complexity by examining the duplication and recombination of these families in different genomes.” About 1000 evolutionary independent protein families were expected to encompass all protein diversity [109]. In line with the above, there was an additional expectation of forthcoming grand unification of biology [110]. However, the power-law distribution of protein families and the sheer abundance of singletons have exposed utopian nature of these expectations and, at the same time, opened several important issues. (p. 15)

Siew and Fischer succinctly described the issues at stake: “If proteins in different organisms have descended from common ancestral proteins by duplication and adaptive variation, why is that so many today show no similarity to each other?” And further: “Do these rapidly evolving ORFans correspond to nonessential proteins or to species determinants?” [103]. (p. 15)

Each species of living things has hundreds of unique proteins, each of which is like no other

A recent study, based on 573 sequenced bacterial genomes, has concluded that the entire pool of bacterial genes – the bacterial pan-genome – looks as though of infinite size, because every additional bacterial genome sequenced has added over 200 new singletons [111]. In agreement with this conclusion are the results of the Global Ocean Sampling project reported by Yooseph et al., who found a linear increase in the number of singletons with the number of new protein sequences, even when the number of the new sequences ran into millions [112]. The trend towards higher numbers of singletons per genome seems to coincide with a higher proportion of the eukaryotic genomes sequenced. In other words, eukaryotes generally contain a larger number of singletons than eubacteria and archaea. [Eukaryotes are organisms whose cells have a nucleus, unlike bacteria - VJT.] (p. 16)

When a relative to a singleton is found, together the two proteins create a family. In the absence of biochemical data, nothing can be said about biological function of that protein family as long as no established domain or structural motif is discernible from the amino acid sequences. Such proteins of obscure function, or POFs, make about 25% of the proteins found in each genome [113, 114]. POFs tend to be shorter than the proteins of defined function [114]. (p. 16)

Today, almost ten years since the announcement of the first draft of the human genome sequence, no structural assignment is available for about 38% of human proteins [64]: at present we thus lack basic information about a large fraction of the proteins of human proteome [115]. (p. 16)

Each species of living things has hundreds of unique genes, too

Based on the data from 120 sequenced genomes, in 2004 Grant et al. reported on the presence of 112,000 singletons within 600,000 sequences [96]. This corresponds to 933 singletons per genome. In 2005, Orengo and Thornton reported on the presence of about 150,000 singletons in 150 sequenced genomes [72]. In 2006, within 203 sequenced genomes and 633,546 nonidentical sequences Marsden et al. identified 158,798 singletons [97]; thus the singletons made 24% of all sequences and there were on average 782 singletons in each genome. In 2008, Yeats et al. [73] found around 600,000 singletons in 527 species – 50 eukaryotes, 437 eubacteria and 39 archaea – corresponding to 1,139 singletons per species. No information about the number of singletons is available in the most recent summary of the data from over 1100 sequenced genomes encompassing nearly 10 million sequences [64]. In spite of the missing recent data on singletons, the results of the above calculations are sufficient for an unambiguous conclusion: each species possesses hundreds, or even thousands, of unique genes – the genes that are not shared with any other species. This conclusion is in full agreement with the power-law distribution of protein families discussed above. (p. 17)

The genes and proteins that are unique to a given species can be used to define that species

Figure 3 shows how the number of unique genes (singletons), expressed as an average per each sequenced genome, was changing with the total number of the genomes sequenced. Evidently, the number of singletons tends to increase, from several hundreds to more than one thousand. The presence of a large number of unique genes in each species represents a new biological reality. Moreover, the singletons as a group appear to be the most distinctive constituent of all individuals of one species, because that group of singletons is lacking in all individuals of all other species. The conclusion that the singletons are the determinants of biological phenomenon of species then follows logically. In System of Logic, John Stuart Mill outlined his Second Canon or Method of Difference [133]: “If an instance in which the phenomenon under investigation occurs, and an instance in which it does not occur, have every circumstance in common save one, that one occurring only in the former; the circumstance in which alone the two instances differ, is the effect, or the cause, or an indispensable part of the cause, of the phenomenon.”(p. 18)

The discovery of hundreds of unique proteins in each species is at odds with the Darwinian theory of evolution

The idea that protein domains represent conserved units of evolution [72, 108, 151-155] hinges upon the presumed capability of evolutionary processes – consisting of random mutations, recombination, genetic drift and natural selection [156] – to maintain the 3D structure of a protein while changing its amino acid sequence. These blind processes – which do not know what kind of protein 3D structure they start with, how they change it and in which direction in the structure space they go – thus supposedly possess certain capabilities that are by far superior to those of tens of thousands of computers, or superior to those of tens of thousands people using the computers. (p. 20)

That hypothesis – that evolution strives to preserve a protein domain once it stumbles upon it – contradicts the power-law distribution of domains. The distribution graphs clearly show that unique domains are the most abundant of all domain groups [21, 66, 67, 70, 72, 79, 82, 86, 94, 95], contrary to their expected rarity. Here I predict that the idea of protein domains as the basic units of evolution will be refuted directly by finding in the genome of one species two singletons having identical domain structure. Such a finding will represent the unambiguous and definitive refutation. That finding requires structural characterization of numerous singletons, and it depends on an objective, mathematical rather than a curator’s, delineation of the protein structural elements and 3D identity. (p. 20)

Each unique gene, and accordingly each novel functional protein encoded by that gene, however, represents a major problem for evolutionary theory because unique proteins are as unrelated as the proteins of random sequences – and among random sequences functional proteins are exceedingly rare. Experimental data reviewed here suggest that at most one functional protein can be found among 10^20 proteins of random sequences. Hence every discovery of a novel functional protein (singleton) represents a testimony for successful overcoming of the probability barrier of one against at least 10^20, the probability defined here as a “macromolecular miracle”. More than one million of such “macromolecular miracles” are present in the genomes of about two thousand species sequenced thus far. Assuming that this correlation will hold with the rest of about 10 million different species that live on Earth [157], the total number of “macromolecular miracles” in all genomes could reach 10 billion. These 10^10 unique proteins would still represent a tiny fraction of the 10^470 possible proteins of the median eukaryotic size. (p. 21)

The appearance of hundreds of unique proteins and genes that characterize each species is an event beyond the reach of chance

If just 200 unique proteins are present in each species, the probability of their simultaneous appearance is one against at least 10^4,000. [The] Probabilistic resources of our universe are much, much smaller; they allow for a maximum of 10^149 events [158] and thus could account for a one-time simultaneous appearance of at most 7 unique proteins. The alternative, a sequential appearance of singletons, would require that the descendants of one family live through hundreds of “macromolecular miracles” to become a new species – again a scenario of exceedingly low probability. Therefore, now one can say that each species is a result of a Biological Big Bang; to reserve that term just for the first living organism [21] is not justified anymore. This view about species differs sharply from the predominant one according to which speciation is caused by reproductive isolation of two populations [159, 160] mediated by difficult to find speciation genes [161-163]. (p. 21)

Evolutionary biologists of earlier generations have not anticipated [164, 165] the challenge that singletons pose to contemporary biologists. By discovering millions of unique genes biologists have run into brick walls similar to those hit by physicists with the discovery of quantum phenomena. The predominant viewpoint in biology has become untenable: we are witnessing a scientific revolution of unprecedented proportions. (p. 21)

For a Darwinist take on orphan genes, see here, here and here. I haven’t been able to find anything which specifically addresses the problem of singleton proteins.

What do readers think of Dr. Kozulic’s paper?

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21 Responses to The Edge of Evolution?

  1. 1
    Chance Ratcliff

    VJ, great article, thanks.

    This paper is significant because it shows that several discoveries about the nature of proteins directly challenge the modern synthesis, and Darwinism in general. Works like this one merit direct responses, which will help reveal the strengths and weaknesses of evolutionary explanations, especially to the next generation of scientists, and eventually the general public. This paper aids the push to have serious, forthright discussions about specific issues relating to the presumed neo-Darwinian mechanisms which are supposed to account for protein evolution and the relatedness of species on a genetic level. Natural selection plays a minor role in morphological change. Random mutations can account for very little which is both adaptive and novel, increasing net function. Gradual adaptation is no longer able to account for the most significant genetic features which differentiate species. Most of that which was previously considered the result of “natural” forces is being revealed to be dependent upon features inherent to biological systems. Rapid morphological changes are often attributable to Rapid Evolution — a euphemism for phenotypic plasticity — a systemic mechanism responsive to environmental triggers. Convergent evolution, a euphemism for homoplasy, reveals that similar features, both morphological and genetic, exist in species unrelated by presumed common ancestors. Advanced biological sciences are un-reliant upon Darwinian explanations in order to progress. And every day it seems like more scientists, names such as James Shapiro, Lynn Margulis, and Denis Noble are abandoning Darwinian accounts and calling for a new synthesis.

    Have I overstated anything? Changes are happening rapidly. I don’t know what it means for ID, but evolutionary theory is in need of an overhaul, and much of the Modern Synthesis will need to be scrapped.

    Denis Noble, Physiology and the revolution in Evolutionary Biology – challenges each of the major rules of the Modern Synthesis and gives examples of how they’ve been broken.

    Homage to Darwin, Part 1 – Moderated by Denis Noble. Featuring Margulis, Dawkins, and a few others. Interesting and heterodox questions asked by audience members here.

  2. What do readers think of Dr. Kozulic’s paper? :-D :-)) ,,, How do neo-Darwinists feel? :@


    Widespread ORFan Genes Challenge Common Descent – Paul Nelson – video with references

    Estimating the size of the bacterial pan-genome – Pascal Lapierre and J. Peter Gogarten – 2008
    Excerpt: We have found greater than 139 000 rare (ORFan) gene families scattered throughout the bacterial genomes included in this study. The finding that the fitted exponential function approaches a plateau indicates an open pan-genome (i.e. the bacterial protein universe is of infinite size); a finding supported through extrapolation using a Kezdy-Swinbourne plot (Figure S3). This does not exclude the possibility that, with many more sampled genomes, the number of novel genes per additional genome might ultimately decline; however, our analyses and those presented in Ref. [11] do not provide any indication for such a decline and confirm earlier observations that many new protein families with few members remain to be discovered.

    The Dictionary of Life | Origins with Dr. Paul A. Nelson – video

    The essential genome of a bacterium – 2011
    Figure (C): Venn diagram of overlap between Caulobacter and E. coli ORFs (outer circles) as well as their subsets of essential ORFs (inner circles). Less than 38% of essential Caulobacter ORFs are conserved and essential in E. coli. Only essential Caulobacter ORFs present in the STING database were considered, leading to a small disparity in the total number of essential Caulobacter ORFs.

    Age doesn’t matter: New genes are as essential as ancient ones – December 2010
    Excerpt: “A new gene is as essential as any other gene; the importance of a gene is independent of its age,” said Manyuan Long, PhD, Professor of Ecology & Evolution and senior author of the paper. “New genes are no longer just vinegar, they are now equally likely to be butter and bread. We were shocked.”

    Orphan Genes (And the peer reviewed ‘non-answer’ from Darwinists) – video

    Genes from nowhere: Orphans with a surprising story – 16 January 2013 – Helen Pilcher
    Excerpt: When biologists began sequencing genomes they discovered up to a third of genes in each species seemed to have no parents or family of any kind. Nevertheless, some of these “orphan genes” are high achievers (are just as essential as ‘old’ genes),,,
    But where do they come from? With no obvious ancestry, it was as if these genes appeared out of nowhere, but that couldn’t be true. Everyone assumed that as we learned more, we would discover what had happened to their families. But we haven’t-quite the opposite, in fact.,,,
    The upshot is that the chances of random mutations turning a bit of junk DNA into a new gene seem infinitesmally small. As the French biologist Francois Jacob wrote 35 years ago, “the probability that a functional protein would appear de novo by random association of amino acids is practically zero”.,,,
    Orphan genes have since been found in every genome sequenced to date, from mosquito to man, roundworm to rat, and their numbers are still growing.

  3. How many ORFan genes in humans? Well, the number is still growing, but here are some preliminary numbers:

    Human Gene Count Tumbles Again – 2008
    Excerpt: Scientists on the hunt for typical genes — that is, the ones that encode proteins — have traditionally set their sights on so-called open reading frames, which are long stretches of 300 or more nucleotides, or “letters” of DNA, bookended by genetic start and stop signals.,,,, The researchers considered genes to be valid if and only if similar sequences could be found in other mammals – namely, mouse and dog. Applying this technique to nearly 22,000 genes in the Ensembl gene catalog, the analysis revealed 1,177 “orphan” DNA sequences.,,, the researchers compared the orphan sequences to the DNA of two primate cousins, chimpanzees and macaques. After careful genomic comparisons, the orphan genes were found to be true to their name — they were absent from both primate genomes.

    From Jerry Coyne, More Table-Pounding, Hand-Waving – May 2012
    Excerpt: “More than 6 percent of genes found in humans simply aren’t found in any form in chimpanzees. There are over fourteen hundred novel genes expressed in humans but not in chimps.”
    Jerry Coyne – ardent and ‘angry’ neo-Darwinist – professor at the University of Chicago in the department of ecology and evolution for twenty years. He specializes in evolutionary genetics.

    An integrated encyclopedia of DNA elements in the human genome – Sept. 6, 2012
    Excerpt: Analysis,,, yielded 57 confidently identified unique peptide sequences in intergenic regions relative to GENCODE annotation. Taken together with evidence of pervasive genome transcription, these data indicate that additional protein-coding genes remain to be found.

    Ten years on, still much to be learned from human genome map – April 12, 2013
    Excerpt:,,,“What’s more, about 10 percent of the human genome still hasn’t been sequenced and can’t be sequenced by existing technology, Green added. “There are parts of the genome we didn’t know existed back when the genome was completed,” he said.,,,

    Verse and Music:

    However, as it is written: “No eye has seen, no ear has heard, no mind has conceived what God has prepared for those who love him.”
    —1 Corinthians 2:9

    Voice of Truth, Casting Crowns

  4. 4
    Chance Ratcliff

    I neglected to note that genetic changes previously thought to be random are the result of targeted mutations. Denis Noble covers some of this in his presentation linked above. James Shapiro deals with this in his book, Evolution: A View from the 21st Century.

    Some worthwhile reference videos by UD’s lifepsy:

    Non-random and Targeted Mutations

    Orphan Genes

    Phenotypic Plasticity

    More videos in the playlist.

  5. 5

    Instead of “designed separately” it might be better to say “intelligently altered.”

  6. OT: podcast – Dr. Stephen C. Meyer explains his inspiration for writing Darwin’s Doubt and discusses the main piece of evidence that Darwin could not explain in his theory.

  7. OT: Intelligent Design and the Cell – Jed C. Macosko, PhD – video
    Published on May 8, 2013
    Jed C. Macosko is an Assistant Professor of Biophysics at Wake Forest University, Winston-Salem, NC. He received his B.S. in Chemistry from MIT and his Ph. D. from UC Berkeley for his work on influenza hemagglutinin and HIV RNA. Macosko’s research involves the detection of forces in single biomolecules and molecular machines by using microspheres and centrifugal force. He studies protein motors and machines, mapping their potential energy surfaces. Surveying and mapping the potential energy surfaces of protein machines is essential for understanding their function and for developing drugs to halt their activity.

  8. 8

    This YEC disagrees with this.
    Same looking creatures, almost, are the same creatures from original biblical kinds.
    It doesn’t matter how different details in genes are.
    Genetic change can happen without a intelligent designer. Its within the design to allow mechanisms for important changes in biology.
    Creationism will not accept every species is created.
    The example is man.
    We have great differences in body but from ADam/Eve.
    Explain how this happened and one has explained largely mechanism in biology.
    Don’t get too impressed with the array of genetic material in biology.

  9. What is Intelligent Design? – William Dembski, PhD – video

    Anderson University hosted the 2013 Southeastern Regional Meeting which focused on “The Origins Debate.” ETS was privileged to have Dr. William Dembski, Senior Fellow with the Discovery Institute’s Center for Science and Culture, as the keynote speaker.

  10. Thanks for this good article!

    Dr. Kozulic contends that the presence of not one but hundreds of chemically unique proteins in each species is an event beyond the reach of chance, and that each species must therefore be the result of intelligent planning.

    I’m a creationist so I’m wondering how this would effect the creationist idea that evolution takes place on a limited basis – within the original created kinds of Genesis 1.

    Does this mitigate against this?

    Some creationists are open to the possibility of some type of God guided change or programmed change within the original created kind. I guess this would fit with that idea.

    At any rate, Dr. Kozulic’s ideas certainly wouldn’t seem to support the idea of common descent at all, in spite of what the author claims. I’m not so clear as to why the author is so intent on saving the idea of common descent. It is not a biblical idea at all(yes, I know, ID has nothing to do with the Bible), but still, if there is good evidence against it, why not go with the evidence instead of trying to find a way to rescue the idea?

  11. tjguy, I’m with you in that I don’t think common descent is supported by the evidence, but even though this singleton evidence is certainly antagonistic towards the idea of God ‘tinkering’ in a ‘bottom up’ fashion to semi-gradually create a new species, I hold that there is a more forceful piece of evidence which has recently come to light. A piece of evidence which, along with this ORFan/singleton evidence, makes the case for ‘top down’ creation of species much, much, more persuasive. This evidence is that the ‘top down’ alternative splicing codes for chimps and humans are found to be vastly different,,

    Evolution by Splicing – Comparing gene transcripts from different species reveals surprising splicing diversity. – Ruth Williams – December 20, 2012
    Excerpt: A major question in vertebrate evolutionary biology is “how do physical and behavioral differences arise if we have a very similar set of genes to that of the mouse, chicken, or frog?”,,,
    A commonly discussed mechanism was variable levels of gene expression, but both Blencowe and Chris Burge,,, found that gene expression is relatively conserved among species.
    On the other hand, the papers show that most alternative splicing events differ widely between even closely related species. “The alternative splicing patterns are very different even between humans and chimpanzees,” said Blencowe.,,,

    The reason why this is devastating to any bottom up gradualist scenario is that now not only do neo-Darwinists have to try to explain how hundreds of ORFan genes can pop out of nowhere by Darwinian mechanisms in each new species, (and believe me they will try), but now neo-Darwinists must try to explain how entire ‘species specific’ alternative splicing codes can pop out of nowhere. The particular reason why finding ‘species specific’ alternative splicing codes is so devastating to neo-Darwinian (bottom up) evolution, or even Theistic evolution, is best understood by taking a look at what Richard Dawkins said about what would happen if one were to ‘randomly’ change the regulatory genetic code once it is in place:

    Venter vs. Dawkins on the Tree of Life – and Another Dawkins Whopper – March 2011
    Excerpt:,,, But first, let’s look at the reason Dawkins gives for why the code must be universal:
    “The reason is interesting. Any mutation in the genetic code itself (as opposed to mutations in the genes that it encodes) would have an instantly catastrophic effect, not just in one place but throughout the whole organism. If any word in the 64-word dictionary changed its meaning, so that it came to specify a different amino acid, just about every protein in the body would instantaneously change, probably in many places along its length. Unlike an ordinary mutation…this would spell disaster.” (2009, p. 409-10)
    OK. Keep Dawkins’ claim of universality in mind, along with his argument for why the code must be universal, and then go here (linked site listing 23 variants of the genetic code).
    Simple counting question: does “one or two” equal 23? That’s the number of known variant genetic codes compiled by the National Center for Biotechnology Information. By any measure, Dawkins is off by an order of magnitude, times a factor of two.

    Bottom line is that if any regulatory code, such as the genetic code or the alternative splicing code, is ‘randomly changed’ in part, it throws the entire code out of whack and will be ‘instantly catastrophic’, to use Richard Dawkins’ most appropriate term! Installing a regulatory code is a all or nothing, ‘top down’, take it or leave it, deal. And that is what makes this particular piece of evidence so devastating for neo-Darwinists (or even Theistic evolutionists)!

    It is good to remember just how hard it was for researchers to crack the alternative splicing code:

    Breakthrough: Second Genetic Code Revealed – May 2010
    Excerpt: The paper is a triumph of information science that sounds reminiscent of the days of the World War II codebreakers. Their methods included algebra, geometry, probability theory, vector calculus, information theory, code optimization, and other advanced methods. One thing they had no need of was evolutionary theory,,,

    supplemental notes:

    Shannon Information – Channel Capacity – Perry Marshall – video

    “Because of Shannon channel capacity that previous (first) codon alphabet had to be at least as complex as the current codon alphabet (DNA code), otherwise transferring the information from the simpler alphabet into the current alphabet would have been mathematically impossible”
    Donald E. Johnson – Bioinformatics: The Information in Life

    “Our experience-based knowledge of information-flow confirms that systems with large amounts of specified complexity (especially codes and languages) invariably originate from an intelligent source — from a mind or personal agent.” (Stephen C. Meyer, “The origin of biological information and the higher taxonomic categories,” Proceedings of the Biological Society of Washington, 117(2):213-239 (2004).)

    “A code system is always the result of a mental process (it requires an intelligent origin or inventor). It should be emphasized that matter as such is unable to generate any code. All experiences indicate that a thinking being voluntarily exercising his own free will, cognition, and creativity, is required. ,,,there is no known law of nature and no known sequence of events which can cause information to originate by itself in matter. Werner Gitt 1997 In The Beginning Was Information pp. 64-67, 79, 107.”
    (The retired Dr Gitt was a director and professor at the German Federal Institute of Physics and Technology (Physikalisch-Technische Bundesanstalt, Braunschweig), the Head of the Department of Information Technology.)

    “In the last ten years, at least 20 different natural information codes were discovered in life, each operating to arbitrary conventions (not determined by law or physicality). Examples include protein address codes [Ber08B], acetylation codes [Kni06], RNA codes [Fai07], metabolic codes [Bru07], cytoskeleton codes [Gim08], histone codes [Jen01], and alternative splicing codes [Bar10].
    Donald E. Johnson – Programming of Life – pg.51 – 2010

    “A number of hominid crania are known from sites in eastern and southern Africa in the 400- to 200-thousand-year range, but none of them looks like a close antecedent of the anatomically distinctive Homo sapiens…Even allowing for the poor record we have of our close extinct kin, Homo sapiens appears as distinctive and unprecedented…there is certainly no evidence to support the notion that we gradually became who we inherently are over an extended period, in either the physical or the intellectual sense.”
    Dr. Ian Tattersall: – paleoanthropologist – emeritus curator of the American Museum of Natural History – (Masters of the Planet, 2012)

    Verse and music:

    John 1:1-4
    In the beginning was the Word, and the Word was with God, and the Word was God. He was with God in the beginning. Through him all things were made; without him nothing was made that has been made. In him was life, and that life was the light of all mankind.

    Brooke Fraser – Hillsong: “Lord Of Lords” Worship and Praise Song(HQ)

  12. 12
    Chance Ratcliff

    tjguy @10,

    “I’m a creationist so I’m wondering how this would effect the creationist idea that evolution takes place on a limited basis – within the original created kinds of Genesis 1.”

    I think it would support the concept of original kinds, rather than count against it. Singletons might perhaps be an indicator of an objective demarcation for the concept of species, that is, kinds.

    “At any rate, Dr. Kozulic’s ideas certainly wouldn’t seem to support the idea of common descent at all, in spite of what the author claims. I’m not so clear as to why the author is so intent on saving the idea of common descent. It is not a biblical idea at all(yes, I know, ID has nothing to do with the Bible), but still, if there is good evidence against it, why not go with the evidence instead of trying to find a way to rescue the idea?”

    I think it’s clear that the presence of singletons lends no support to the notion of universal common ancestry. The same is true with homoplasy. However the presence of singletons, or the phenomenon of homoplasy, do not militate against UCA logically. There are still at least two design scenarios that would allow universal common ancestry to be true.

    1) Some sort of front loading scenario where the original UCA had a kind of “genome of eden” and ran a developmental program that unfolded over time, installing distinct genomic material in separate species as they diverged from the original.

    2) The designer intervened discretely at specific times to produce a new species from another, installing the necessary genomic information at the appropriate time, as well as the new body plan.

    In both of those cases, a design scenario is compatible with universal common ancestry, so it’s not strictly ruled out. Using homoplasy as an example, I put it this way on another thread:

    An engineer builds a single-celled self-replicator and wants a population of around a million, so he will let the creatures replicate for twenty generations. Since we want to track ancestry in the tree, in the genome of each offspring the engineer introduces a mechanism for storing two identifiers, one uniquely for the current offspring and one for its parent’s identifier. This is just a way for introducing an evolutionary component and a way to track ancestry back to the root organism.

    At generation ten he takes two creatures from disparate parts of the tree and adds a new function, let’s say bioluminescence. After ten more generations we have a one-million population master tree with two subtrees consisting of a thousand members each. Both subtrees have the common feature of bioluminescence, but each one traces ancestry from separate parts of the master tree, where neither of their parents have the trait. The engineer could have even taken two specimens from different generations and introduced bioluminescence.

    So in that example there is both universal common descent and convergent evolution by the injection of design in distantly related creatures. Nope, I don’t really buy it either in regards to actual history, but I think it shows that there’s no logical exclusivity between common descent and design where we see a horizontal introduction of features across distantly related specimens.

    If ID can accommodate both front loading and the incremental infusion of information over time, then it’s possible to imagine common descent and common design both being true at the same time. For a front loading scenario, we can imagine a genome loaded with information constituting a developmental program which allows for pre-programmed responses to environmental cues. This would allow for different organisms to develop similar features because of similar stressors or environmental conditions. In an incremental infusion of information scenario, the designer is free to add a heritable feature at any time to a specimen, allowing for similar features in unrelated organisms according to his goals and preferences. In both cases common descent has still occurred.

    It doesn’t make things pretty however. Both singletons (ORFans) and homoplasy are not supportive of UCA, and would seem to count as evidence against it, even though they don’t make it logically impossible.

    It would be interesting to see a direct comparison of the evidence in favor of, and calling into question, the concept of UCA, making note that both physical morphology, and protein similarity, can count as evidence in both columns. There are problems with homology as pointed out by Denton in Evolution: a theory in crisis. Chapter seven, The Failure of Homology, goes into some details. Protein homology is often determined based on sequence similarity, which only works in toto if one presumes UCA and excludes common design.

    I think that some of the ERV-based inferences to UCA might also have issues, specifically when those sequences are found to have vital function. There’s also the “objective nested hierarchy” argument, but I’ve never understood why this rules out common design.

    Anyway, I suppose my point here is that, while UCA is not logically ruled out by the presence of singletons, it certainly isn’t helped any; and I’m not entirely sure what the evidentiary status is with UCA, whether there is more evidence against it than in favor at this point, but the case doesn’t appear to be getting any stronger.

  13. 13
    Chance Ratcliff

    Ba77 @11, good information, thanks. I agree that a gradualistic scenario doesn’t seem very likely, nor elegant, even from a design point of view. Try to imagine transforming a motorcycle into a backhoe via slight, successive, functionally viable intermediates. I think it’s easier to imagine a hopeful monster.

  14. OT: signaling pathway – animation video

  15. Hi tjguy,

    Thank you for your comment. You wrote:

    Thanks for this good article! …

    I’m a creationist so I’m wondering how this would affect the creationist idea that evolution takes place on a limited basis – within the original created kinds of Genesis 1.

    At any rate, Dr. Kozulic’s ideas certainly wouldn’t seem to support the idea of common descent at all, in spite of what the author claims. I’m not so clear as to why the author is so intent on saving the idea of common descent. It is not a biblical idea at all (yes, I know, ID has nothing to do with the Bible), but still, if there is good evidence against it, why not go with the evidence instead of trying to find a way to rescue the idea?

    I quite agree with you that Dr. Kozulic’s research dovetails very nicely with the Biblical idea of “created kinds”.

    The reason why I argued that one could still hold to a notion of common descent even if the proteins that distinguish each species are the Creator’s handiwork is that I think there’s very powerful independent evidence for common descent. I’m thinking specifically of evidence such as vestigial legs in snakes and lizards, avatisms such as legs in baleen whales, and the evidence from endogenous retroviruses linking humans with other primates. What these pieces of evidence indicate is that snakes and whales had legged ancestors, and that humans and other primates share a common ancestor. This is just material evidence, of course: it says nothing about how humans, snakes or whales acquired the forms that they currently possess. That’s why I propose that common ancestry is true at the material level, but that Intelligent Design is needed to explain the form of each and every species of living thing.

    I hope that helps.

  16. Dr. Torley as to your evidence for believing in common descent:

    I’m thinking specifically of evidence such as vestigial legs in snakes and lizards, avatisms such as legs in baleen whales, and the evidence from endogenous retroviruses linking humans with other primates. What these pieces of evidence indicate is that snakes and whales had legged ancestors, and that humans and other primates share a common ancestor.

    Color me unimpressed:

    The (snake) hind limbs are pretty useless, however, at less than an inch (about two centimeters) long. No toes were found fossilized, either, “but that may be because they are not preserved or because, as this is a vestigial leg, they were never present,” according to ESRF’s resident palaeontologist Paul Tafforeau.

    Dr. Torley, how do we know they were even legs?,, Dr. Torley you may ask, ‘why should you even ask such a simple question of such a supposedly obvious fact?’. This following article, humorously, shows why I would ask such a simple question:

    An Email Exchange Regarding “Vestigial Legs” Pelvic Bones in Whales by Jim Pamplin
    Excerpt: The pelvic bones (supposed Vestigial Legs) of whales serve as attachments for the musculature associated with the penis in males and its homologue, the clitoris, in females. The muscle involved is known as the ischiocavernosus and is quite a powerful muscle in males. It serves as a retractor muscle for the penis in copulation and probably provides the base for lateral movements of the penis. The mechanisms of penile motion are not well understood in whales. The penis seems to be capable of a lot of independent motion, much like the trunk of an elephant. How much of this is mediated by the ischiocavernosus is not known.
    In females the anatomical parts are smaller and more diffuse. I would imagine that there is something homologous to the perineal muscles in man and tetrapods, which affect the entire pelvic area – the clitoris, vagina and anus.
    The pelvic rudiments also serve as origins for the ischiocaudalis muscle, which is a ventral muscle that inserts on the tips of the chevron bones of the spinal column and acts to flex the tail in normal locomotion.

    ERV’s, which I was surprised that you included in your list of evidences for common descent Dr. Torley, are certainly found to be wanting as persuasive evidence for common descent as these many following references attest to:

    Refutation Of Endogenous Retrovirus – ERVs – Richard Sternberg, PhD Evolutionary Biology – video
    Sternberg, R. v. & J. A. Shapiro (2005). How repeated retroelements format genome function. Cytogenet. Genome Res. 110: 108-116.

    The definitive response on ERV’s and Creation, with Dr. Jean Lightner

    Interestingly, it seems these ERVs are ordered by usefulness in placental function, and not by common descent. This is a phenomenon predicted by common design not common descent.

    Endogenous retroviruses regulate periimplantation placental growth and differentiation – 2006

    Retrovirus in the Human Genome Is Active in Pluripotent Stem Cells – Jan. 23, 2013
    Excerpt: “What we’ve observed is that a group of endogenous retroviruses called HERV-H is extremely busy in human embryonic stem cells,” said Jeremy Luban, MD, the David L. Freelander Memorial Professor in HIV/AIDS Research, professor of molecular medicine and lead author of the study. “In fact, HERV-H is one of the most abundantly expressed genes in pluripotent stem cells and it isn’t found in any other cell types.

    The Human Lineage Was Somehow “Purged” – Cornelius Hunter – April 2012
    Excerpt: Another such feature is the lack of endemic infectious retroviruses in humans. The problem is that these viruses are present in the other primates, and so according to evolutionists these viruses must be present in their common ancestor which, again according to evolution, would be an ancestor of humans as well.,, In other words, when evolution spontaneously created humans our DNA must have been “purged.” We got a do-over! Hilarious.

    More Counterpoints on ERVs – JonathanM – May 2011
    Excerpt: ‘In the absence of a feasible naturalistic mechanism to account for how evolution from a common ancestor could have occurred, how can we be so sure that it did occur? In such a case, one ought to reasonably expect there to be some quite spectacular evidence for common ancestry. Unfortunately for Darwinists, however, the evidence for common ancestry is paper thin on the ground.’

    Transposable Elements Reveal a Stem Cell Specific Class of Long Noncoding RNAs – (Nov. 26, 2012)
    Excerpt: The study published by Rinn and Kelley finds a striking affinity for a class of hopping genes known as endogenous retroviruses, or ERVs, to land in lincRNAs. The study finds that ERVs are not only enriched in lincRNAs, but also often sit at the start of the gene in an orientation to promote transcription. Perhaps more intriguingly, lincRNAs containing an ERV family known as HERVH correlated with expression in stem cells relative to dozens of other tested tissues and cells. According to Rinn, “This strongly suggests that ERV transposition in the genome may have given rise to stem cell-specific lincRNAs. The observation that HERVHs landed at the start of dozens of lincRNAs was almost chilling; that this appears to impart a stem cell-specific expression pattern was simply stunning!”

  17. Here are some more inconsistencies of ERVs that don’t fit into the naturalistic evolutionary narrative of common descent:

    Retroviruses and Common Descent: And Why I Don’t Buy It – September 2011
    Excerpt: If it is the case, as has been suggested by some, that these HERVs are an integral part of the functional genome, then one might expect to discover species-specific commonality and discontinuity. And this is indeed the case.

    PTERV1 in chimpanzee, African great apes and old World monkeys but not in humans and asian apes (orangutan, siamang, and gibbon).

    Conservation and loss of the ERV3 open reading frame in primates.
    ERV3 sequences were amplified by PCR from genomic DNA of great ape and Old World primates but not from New World primates or gorilla, suggesting an integration event more than 30 million years ago with a subsequent loss in one species.

    From ancestral infectious retroviruses to bona fide cellular genes: role of the captured syncytins in placentation.
    We focus on the recent discovery of genes derived from the envelope glycoprotein-encoding (env) genes of endogenous retroviruses that have been domesticated by mammals to carry out an essential function in placental development…

    Remarkably, the capture of syncytin or syncytin-like genes, sometimes as pairs, was found to have occurred independently from different endogenous retroviruses in diverse mammalian lineages such as primates–including humans–, muroids, leporids, carnivores, caviids, and ovis, between around 10 and 85 million years ago.

    Retroviruses push the envelope for mammalian placentation

    Domestication of the syncytin genes represents a dramatic example of convergent evolution via the cooption of a retroviral gene for a key biological function in reproductive biology. In fact, syncytin domestication from a retroviral envelope gene has been previously shown to have independently occurred at least seven times during mammalian evolution…

    Based on this data, certain cases of widespread and similar retroviral genes are attributed to ‘convergent’ evolution.

    Many more cases of anomalous ERVs

  18. There are many studies suggesting non-random and preferential positioning of retrovirus sequences. This kind of data refutes the claims of re-used ERV sites having to be an ‘amazing coincidence’ if not by common descent.

    Perpetually mobile footprints of ancient infections in human genome

    Although not available for HERVs at this point (as far as I know), the results for other retroelements demonstrate that transcriptionally active genome regions might be preferred targets for retrovirus integration and that the site selection during retroposition can be influenced by many factors

    A good example of retroelement–host interaction gives the study of de novo insertions of Ty1 and Ty3 yeast retrotransposons that are analogues of endogenous retroviruses. Most of the integration sites were found clustered upstream of the genes transcribed by RNA polymerase III.

    There were identified `hot spots’ containing integration sites used up to 280 times more frequently than predicted mathematically. A recent study of the de novo retroviral integration demonstrated also preference for scaffold- or matrix-attachment regions (S/MARs) flanked by DNA with high bending potential.

    Integration specificity of the hobo element of Drosophila melanogaster is dependent on sequences flanking the integration site
    We analyzed the integration specificity of the hobo transposable element of Drosophila melanogaster. Our results indicate that hobo is similar to other transposable elements in that it can integrate into a large number of sites, but that some sites are preferred over others, with a few sites acting as integration hot spots.

    Large-scale discovery of insertion hotspots and preferential integration sites of human transposed elements
    We first discovered that most TEs insert within specific ‘hotspots’ along the targeted TE… Finally, we performed a global assessment to determine the extent to which young TEs tend to nest within older transposed elements and identified a 4-fold higher tendency of TEs to insert into existing TEs than to insert within non-TE intergenic regions. Our analysis demonstrates that TEs are highly biased to insert within certain TEs, in specific orientations and within specific targeted TE positions. TE nesting events also reveal new characteristics of the molecular mechanisms underlying transposition.

    Retroviral DNA Integration: ASLV, HIV, and MLV Show Distinct Target Site Preferences
    Chromosomal regions rich in expressed genes were favored for HIV integration, but these regions were found to be interleaved with unfavorable regions at CpG islands. MLV vectors showed a strong bias in favor of integration near transcription start sites, as reported previously. ASLV vectors showed only a weak preference for active genes and no preference for transcription start regions.

    Thus, each of the three retroviruses studied showed unique integration site preferences, suggesting that virus-specific binding of integration complexes to chromatin features likely guides site selection.

    Integration of retroviral vectors – 2012
    Several members of the retrovirus family show distinct pattern for preferential integration into the host genome. Despite many years of investigation, precise mechanisms of target site selection and the fundamental interplay of viral integrase and host cell proteins are still unknown.

  19. Of semi-related note:

    A Critique of Douglas Theobald’s – “29 Evidences for Macroevolution” by Ashby Camp

  20. But Dr. Torley, I would like to get to the one main piece of evidence that neo-Darwinists continually trumpeted as evidence for common descent. Genetic similarity. For many years, perhaps decades, neo-Darwinists stated that the 99% genetic similarity between chimps and humans was irrefutable proof of common descent. And no matter how clearly you pointed out the fact that the mechanism of Random Variation and Natural Selection was grossly insufficient to account for even those minor changes, (at least 3 million base pairs), neo-Darwinists smugly held that this was their crowning piece of evidence that common descent was correct. Well, science progresses and old dogmas are humbled. The similarity has recently been dropping precipitously from its original 99% figure.


    Chimp chromosome creates puzzles – 2004
    Excerpt: However, the researchers were in for a surprise. Because chimps and humans appear broadly similar, some have assumed that most of the differences would occur in the large regions of DNA that do not appear to have any obvious function. But that was not the case. The researchers report in ‘Nature’ that many of the differences were within genes, the regions of DNA that code for proteins. 83% of the 231 genes compared had differences that affected the amino acid sequence of the protein they encoded. And 20% showed “significant structural changes”. In addition, there were nearly 68,000 regions that were either extra or missing between the two sequences, accounting for around 5% of the chromosome.,,, “we have seen a much higher percentage of change than people speculated.” The researchers also carried out some experiments to look at when and how strongly the genes are switched on. 20% of the genes showed significant differences in their pattern of activity.

    Mapping Human Genetic Ancestry,” Molecular Biology and Evolution, Vol. 24(10):2266-2276 (2007).)
    Excerpt: For about 23% of our genome, we share no immediate genetic ancestry with our closest living relative, the chimpanzee. This encompasses genes and exons to the same extent as intergenic regions. We conclude that about 1/3 of our genes started to evolve as human-specific lineages before the differentiation of human, chimps, and gorillas took place.

    Genomic monkey business – similarity re-evaluated using omitted data – by Jeffrey Tomkins and Jerry Bergman – 2012
    Excerpt: A review of the common claim that the human and chimpanzee (chimp) genomes are nearly identical was found to be highly questionable solely by an analysis of the methodology and data outlined in an assortment of key research publications.,,,
    Based on the analysis of data provided in various publications, including the often cited 2005 chimpanzee genome report, it is safe to conclude that human–chimp genome similarity is not more than ~87% identical, and possibly not higher than 81%. These revised estimates are based on relevant data omitted from the final similarity estimates typically presented.,,,

    and Please note the very conservative nature of the preceding study:

    Genome-Wide DNA Alignment Similarity (Identity) for 40,000 Chimpanzee DNA Sequences Queried against the Human Genome is 86–89% – Jeffrey P. Tomkins – December 28, 2011
    Concluding statement: Depending on the BLASTN parameter combination, average sequence identity for the thirty separate experiments between human and chimp varied between 86 and 89%. The average chimp query sequence length was 740 bases and depending on the BLASTN parameter combination, average alignment length varied between 121 and 191 bases.
    Excluding data for the number of clones that did not align or the large amount of bases within clones that did not align, an unbiased conservative estimate of genome-wide human-chimp DNA similarity is not more than 86–89% identical. The conservative nature of these estimates is further noted by the fact that the 40,000 sequence chimp sequences that were tested, represent pre-selected homologous sequence already known to align to the human genome.

    Comprehensive Analysis of Chimpanzee and Human Chromosomes Reveals Average DNA Similarity of 70% – by Jeffrey P. Tomkins – February 20, 2013
    Excerpt: For the chimp autosomes(not sex chromosomes), the amount of optimally aligned DNA sequence provided similarities between 66 and 76%, depending on the chromosome. In general, the smaller and more gene-dense the chromosomes, the higher the DNA similarity—although there were several notable exceptions defying this trend. Only 69% of the chimpanzee X chromosome was similar to human and only 43% of the Y chromosome. Genome-wide, only 70% of the chimpanzee DNA was similar to human under the most optimal sequence-slice conditions. While, chimpanzees and humans share many localized protein-coding regions of high similarity, the overall extreme discontinuity between the two genomes defies evolutionary timescales and dogmatic presuppositions about a common ancestor.


    Ten years on, still much to be learned from human genome map – April 12, 2013
    Excerpt:,,,”What’s more, about 10 percent of the human genome still hasn’t been sequenced and can’t be sequenced by existing technology, Green added. “There are parts of the genome we didn’t know existed back when the genome was completed,” he said.,,,

    A False Trichotomy
    Excerpt: The common chimp (Pan troglodytes) and human Y chromosomes are “horrendously different from each other”, says David Page,,, “It looks like there’s been a dramatic renovation or reinvention of the Y chromosome in the chimpanzee and human lineages.”

    whole genome comparisons drop the numbers even further:

    Do Human and Chimpanzee DNA Indicate an Evolutionary Relationship?
    Excerpt: the authors found that only 48.6% of the whole human genome matched chimpanzee nucleotide sequences. [Only 4.8% of the human Y chromosome could be matched to chimpanzee sequences.]

    A simple statistical test for the alleged “99% genetic identity” between humans and chimps – September 2010
    Excerpt: The results obtained are statistically valid. The same test was previously run on a sampling of 1,000 random 30-base patterns and the percentages obtained were almost identical with those obtained in the final test, with 10,000 random 30-base patterns. When human and chimp genomes are compared, the X chromosome is the one showing the highest degree of 30BPM similarity (72.37%), while the Y chromosome shows the lowest degree of 30BPM similarity (30.29%). On average the overall 30BPM similarity, when all chromosomes are taken into consideration, is approximately 62%.

    I think it is safe to say that as far as the evidence itself is concerned, the 99% genetic similarity talking point of neo-Darwinists is dead!

  21. OT: Flight: The Genius of Birds – Official Trailer

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