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Ann Gauger on genetic drift

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Science and Human Origins In “On Retrospective Analysis and Coalescent Theory” (Biologic Institute Perspectives August 5, 2012), Ann Gauger notes,

The theory is that in small populations (smaller than a trillion, say) drift can overwhelm the power of selection. In such a case, organisms do not have sufficient numbers for beneficial mutations to arise and be fixed with any frequency. Most mutations are lost to drift before becoming established, even when they are beneficial. The significance of natural selection is thus greatly reduced in shaping evolutionary history.

The idea that evolution is driven by drift has led to a way of retrospectively estimating past genetic lineages. Called coalescent theory, it is based on one very simple assumption — that the vast majority of mutations are neutral and have no effect on an organism’s survival. (For a review go here.) According to this theory, actual genetic history is presumed not to matter. Our genomes are full of randomly accumulating neutral changes. When generating a genealogy for those changes, their order of appearance doesn’t matter. Trees can be drawn and mutations assigned to them without regard to an evolutionary sequence of genotypes, since genotypes don’t matter.

18 Replies to “Ann Gauger on genetic drift

  1. 1
    Joe says:

    For Dr Gauger:

    Rapid proliferation of historecognition alleles in populations of a colonial ascidian


    Previous work on the distribution of historecognition alleles in botrylloid ascidians has revealed extensive polymorphism at this locus, but has yielded little information on the distribution of alleles among populations and the rate of allele proliferation within populations. We first present preliminary data on the genetics of historecognition in Botrylloides diegense, a West Coast native that was introduced to the East Coast in 1972. We then compare the distribution of alleles in 2 populations of different size in a Maine estuary. Finally, we compare the alleles in those 2 populations to the alleles in a population at Woods Hole, the site of the original introduction. Our results indicate that a small, peripheral population contains fewer alleles than a large population and suggest that alleles have proliferated rapidly since this species was introduced to the East Coast. The rapid proliferation of alleles reported here provides additional support for the hypothesis that historecognition systems are subject to frequency dependent selection in natural populations.

  2. 2
    A Gene says:

    Called coalescent theory, it is based on one very simple assumption — that the vast majority of mutations are neutral and have no effect on an organism’s survival.

    Nooo! It used to assume that some loci are neutral, but there are several models for the effects of selection on coalescent processes.

    The applications of coalescent theory usually assume that the markers being studied are neutral, but that’s not the same thing as assuming that all markers are neutral.

    According to this theory, actual genetic history is presumed not to matter.

    Rubbish. Coalescent theory models actual genetic history.

  3. 3
    bornagain77 says:

    A Gene you make a bold claim that:

    Rubbish. Coalescent theory models actual genetic history.

    And your observational evidence that it is actual genetic history is what exactly? Dr Gauger herself has been extensively involved in work that has brought into severe question the unfounded assumption in neo-Darwinan thought of the virtually unlimited plasticity of genetic/protein sequences?


    The Evolutionary Accessibility of New Enzyme Functions: A Case Study from the Biotin Pathway – Ann K. Gauger and Douglas D. Axe – April 2011
    Excerpt: We infer from the mutants examined that successful functional conversion would in this case require seven or more nucleotide substitutions. But evolutionary innovations requiring that many changes would be extraordinarily rare, becoming probable only on timescales much longer than the age of life on earth.

    When Theory and Experiment Collide — April 16th, 2011 by Douglas Axe
    Excerpt: Based on our experimental observations and on calculations we made using a published population model [3], we estimated that Darwin’s mechanism would need a truly staggering amount of time—a trillion trillion years or more—to accomplish the seemingly subtle change in enzyme function that we studied.

    Corticosteroid Receptors in Vertebrates: Luck or Design? – Ann Gauger – October 11, 2011
    Excerpt: if merely changing binding preferences is hard, even when you start with the right ancestral form, then converting an enzyme to a new function is completely beyond the reach of unguided evolution, no matter where you start.

    More from Ann Gauger on why humans didn’t happen the way Darwin said – July 2012
    Excerpt: Getting a feature that requires six neutral mutations is the limit of what bacteria can produce. For primates (e.g., monkeys, apes and humans) the limit is much more severe. Because of much smaller effective population sizes (an estimated ten thousand for humans instead of a billion for bacteria) and longer generation times (fifteen to twenty years per generation for humans vs. a thousand generations per year for bacteria), it would take a very long time for even a single beneficial mutation to appear and become fixed in a human population.
    ,,, One or two mutations simply aren’t sufficient to produce the necessary changes (in humans)— sixteen anatomical features—in the time available. At most, a new binding site might affect the regulation of one or two genes.

    Indeed this observational evidence has led Dr Axe to comment:

    Thou Shalt Not Put Evolutionary Theory to a Test – Douglas Axe – July 18, 2012
    Excerpt: “For example, McBride criticizes me for not mentioning genetic drift in my discussion of human origins, apparently without realizing that the result of Durrett and Schmidt rules drift out. Each and every specific genetic change needed to produce humans from apes would have to have conferred a significant selective advantage in order for humans to have appeared in the available time (i.e. the mutations cannot be ‘neutral’). Any aspect of the transition that requires two or more mutations to act in combination in order to increase fitness would take way too long (>100 million years).
    My challenge to McBride, and everyone else who believes the evolutionary story of human origins, is not to provide the list of mutations that did the trick, but rather a list of mutations that can do it. Otherwise they’re in the position of insisting that something is a scientific fact without having the faintest idea how it even could be.” Doug Axe PhD.

  4. 4
    Maus says:

    Interesting use of Markov models. I’ve no objection to the general idea, but a sample size of 6 is absurd. It’ll be entertaining to see what use they get out of it going forward.

  5. 5
    Joe says:

    A Gene:

    Coalescent theory models actual genetic history.

    That is the unverifiable propaganda, anyway.

  6. 6
    bornagain77 says:

    further notes on the severe limits found for the ability of protein to ‘randomly’ evolve to new functions:

    Stability effects of mutations and protein evolvability. October 2009
    Excerpt: The accepted paradigm that proteins can tolerate nearly any amino acid substitution has been replaced by the view that the deleterious effects of mutations, and especially their tendency to undermine the thermodynamic and kinetic stability of protein, is a major constraint on protein evolvability,,

    “Mutations are rare phenomena, and a simultaneous change of even two amino acid residues in one protein is totally unlikely. One could think, for instance, that by constantly changing amino acids one by one, it will eventually be possible to change the entire sequence substantially… These minor changes, however, are bound to eventually result in a situation in which the enzyme has ceased to perform its previous function but has not yet begun its ‘new duties’. It is at this point it will be destroyed” Maxim D. Frank-Kamenetski, Unraveling DNA, 1997, p. 72. (Professor at Brown U. Center for Advanced Biotechnology and Biomedical Engineering)

    Nature Paper,, Finds Darwinian Processes Lacking – Michael Behe – Oct. 2009
    Excerpt: Now, thanks to the work of Bridgham et al (2009), even such apparently minor switches in structure and function (of a protein to its supposed ancestral form) are shown to be quite problematic. It seems Darwinian processes can’t manage to do even as much as I had thought.

    Wheel of Fortune: New Work by Thornton’s Group Supports Time-Asymmetric Dollo’s Law – Michael Behe – October 5, 2011
    Excerpt: Darwinian selection will fit a protein to its current task as tightly as it can. In the process, it makes it extremely difficult to adapt to a new task or revert to an old task by random mutation plus selection.

    Warning: Do NOT Mutate This Protein Complex: – June 2009
    Excerpt: In each cell of your body there is a complex of 8 or more proteins bound together called the BBSome. This protein complex, discovered in 2007, should not be disturbed. Here’s what happens when it mutates: “A homozygous mutation in any BBSome subunit (except BBIP10) will make you blind, obese and deaf, will obliterate your sense of smell, will make you grow extra digits and toes and cause your kidneys to fail.”… the BBSome is “highly conserved” (i.e., unevolved) in all ciliated organisms from single-celled green algae to humans,…”

    Which begs the question, “If this complex of 8 proteins which is found throughout life, is severely intolerant to any mutations happening to it now, how in the world did it come to be in the first photosynthetic life in the first place?

    In fact the Ribosome, which makes the myriad of different, yet specific, types of proteins found in life, is found to be severely intolerant to any random mutations occurring to proteins.

    The Ribosome: Perfectionist Protein-maker Trashes Errors
    Excerpt: The enzyme machine that translates a cell’s DNA code into the proteins of life is nothing if not an editorial perfectionist…the ribosome exerts far tighter quality control than anyone ever suspected over its precious protein products… To their further surprise, the ribosome lets go of error-laden proteins 10,000 times faster than it would normally release error-free proteins, a rate of destruction that Green says is “shocking” and reveals just how much of a stickler the ribosome is about high-fidelity protein synthesis.

    And exactly how is the evolution of new forms of life suppose to ‘randomly’ occur if it is prevented from ‘randomly’ occurring at the base level of proteins in the first place?

    Or related note, the ‘protein factory’ of the ribosome, which is, as far as I know, the only known machine in the universe capable of making proteins of any significant length, is far more complicated than first thought:

    Honors to Researchers Who Probed Atomic Structure of Ribosomes – Robert F. Service
    Excerpt: “The ribosome’s dance, however, is more like a grand ballet, with dozens of ribosomal proteins and subunits pirouetting with every step while other key biomolecules leap in, carrying other dancers needed to complete the act.”

    As well, The Ribosome of the cell is found to be very similar to a CPU in a electronic computer:

    Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems – 2012
    David J D’Onofrio1*, David L Abel2* and Donald E Johnson3
    Excerpt: An operational analysis of the ribosome has revealed that this molecular machine with all of its parts follows an order of operations to produce a protein product. This order of operations has been detailed in a step-by-step process that has been observed to be self-executable. The ribosome operation has been proposed to be algorithmic (Ralgorithm) because it has been shown to contain a step-by-step process flow allowing for decision control, iterative branching and halting capability. The R-algorithm contains logical structures of linear sequencing, branch and conditional control. All of these features at a minimum meet the definition of an algorithm and when combined with the data from the mRNA, satisfy the rule that Algorithm = data + control. Remembering that mere constraints cannot serve as bona fide formal controls, we therefore conclude that the ribosome is a physical instantiation of an algorithm.,,,
    The correlation between linguistic properties examined and implemented using Automata theory give us a formalistic tool to study the language and grammar of biological systems in a similar manner to how we study computational cybernetic systems. These examples define a dichotomy in the definition of Prescriptive Information. We therefore suggest that the term Prescriptive Information (PI) be subdivided into two categories: 1) Prescriptive data and 2) Prescribed (executing) algorithm.
    It is interesting to note that the CPU of an electronic computer is an instance of a prescriptive algorithm instantiated into an electronic circuit, whereas the software under execution is read and processed by the CPU to prescribe the program’s desired output. Both hardware and software are prescriptive.

    On top of the lack of proteins to evolve into new shapes and functions What does the recent hard evidence say about novel protein-protein binding site generation. i.e. about the ability of protein with novel functions to combine with other proteins in a meaningful way to do something useful for the cell?

    “The likelihood of developing two binding sites in a protein complex would be the square of the probability of developing one: a double CCC (chloroquine complexity cluster), 10^20 times 10^20, which is 10^40. There have likely been fewer than 10^40 cells in the entire world in the past 4 billion years, so the odds are against a single event of this variety (just 2 binding sites being generated by accident) in the history of life. It is biologically unreasonable.”
    Michael J. Behe PhD. (from page 146 of his book “Edge of Evolution”)

    Protein-Protein Interactions (PPI) Fine-Tune the Case for Intelligent Design – Article with video – April 2011
    Excerpt: The most recent work by the Harvard scientists indicates that the concentration of PPI-participating proteins in the cell is also carefully designed.

  7. 7
    bornagain77 says:

    Dr. Behe’s, and others, empirical research agrees with the difficulty that is found for scientists trying to ‘purposely design’ a protein-protein binding site:

    Viral-Binding Protein Design Makes the Case for Intelligent Design Sick! (as in cool) – Fazale Rana – June 2011
    Excerpt: When considering this study, it is remarkable to note how much effort it took to design a protein that binds to a specific location on the hemagglutinin molecule. As biochemists Bryan Der and Brian Kuhlman point out while commenting on this work, the design of these proteins required:
    “…cutting-edge software developed by ~20 groups worldwide and 100,000 hours of highly parallel computing time. It also involved using a technique known as yeast display to screen candidate proteins and select those with high binding affinities, as well as x-ray crystallography to validate designs.2”
    If it takes this much work and intellectual input to create a single protein from scratch, is it really reasonable to think that undirected evolutionary processes could accomplish this task routinely?
    In other words, the researchers from the University of Washington and The Scripps Institute have unwittingly provided empirical evidence that the high-precision interactions required for PPIs requires intelligent agency to arise. Sick!

    Computer-designed proteins programmed to disarm variety of flu viruses – June 1, 2012
    Excerpt: The research efforts, akin to docking a space station but on a molecular level, are made possible by computers that can describe the landscapes of forces involved on the submicroscopic scale.,, These maps were used to reprogram the design to achieve a more precise interaction between the inhibitor protein and the virus molecule. It also enabled the scientists, they said, “to leapfrog over bottlenecks” to improve the activity of the binder.

    Moreover, there is, ‘surprisingly’, found to be ‘rather low’ conservation of Domain-Domain Interactions occurring in Protein-Protein interactions across various species:

    A Top-Down Approach to Infer and Compare Domain-Domain Interactions across Eight Model Organisms
    Excerpt: Knowledge of specific domain-domain interactions (DDIs) is essential to understand the functional significance of protein interaction networks. Despite the availability of an enormous amount of data on protein-protein interactions (PPIs), very little is known about specific DDIs occurring in them.,,, Our results show that only 23% of these DDIs are conserved in at least two species and only 3.8% in at least 4 species, indicating a rather low conservation across species.,,,

    There is even found to be severe difficulty in recombing different protein domains into novel protein structure

    “Why Proteins Aren’t Easily Recombined, Part 2” – Ann Gauger – May 2012
    Excerpt: “So we have context-dependent effects on protein function at the level of primary sequence, secondary structure, and tertiary (domain-level) structure. This does not bode well for successful, random recombination of bits of sequence into functional, stable protein folds, or even for domain-level recombinations where significant interaction is required.”

    Two Domain Protein – video (several binding sites required)

    As if all of the preceding was not bad enough for the unfounded assumption in Darwinian thought for the virtual unlimited plasticity of Protein/DNA sequences, it is now found that there is a fairly substantial percentage of completely novel ORFan sequences in each new genome sequenced:

    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.

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

    Genomes of similar species – Cornelius Hunter PhD.
    Excerpt: Different variants of the Escherichia coli bacteria, for instance, each have hundreds of unique genes. And some of these genes have been found to have important functions, such as helping to construct proteins. [8]
    Massive genetic differences were also found between different fruit fly species. The fruit fly is one of the most intensely researched organisms and in recent years a systematic study of the genomes of a dozen different species was undertaken. Evolutionists were surprised to find novel features in the genomes of each of these different fruit fly species. Thousands of genes showed up missing in many of the species, and some genes showed up in only a single species. [9] As one science writer put it, “an astonishing 12 per cent of recently evolved genes in fruit flies appear to have evolved from scratch.” [10] These so-called novel genes would have had to have evolved over a few million years—a time period previously considered to allow only for minor genetic changes. [11,12] ,,, etc.. etc…

    As alluded to above, completely contrary to evolutionary thought, these ‘new’ ORFan genes are found to be just as essential as ‘old’ genes for maintaining life:

    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.”

    New genes in Drosophila quickly become essential. – December 2010
    Excerpt: The proportion of genes that are essential is similar in every evolutionary age group that we examined. Under constitutive silencing of these young essential genes, lethality was high in the pupal (later) stage and (but was) also found in the larval (early) stages.

    Thus, despite whatever Darwinists may think of their hypothetical population genetics models which assume unlimited plasticity for protein/DNA sequences, the empirical fact is that there are now found to be severe limits for every parameter examined for protein evolvability as well as a large percentage of completely novel ORFan proteins which seemingly pop into existence out of nowhere 🙂

  8. 8
    bornagain77 says:

    Corrected link:

    Honors to Researchers Who Probed Atomic Structure of Ribosomes – Robert F. Service
    Excerpt: “The ribosome’s dance, however, is more like a grand ballet, with dozens of ribosomal proteins and subunits pirouetting with every step while other key biomolecules leap in, carrying other dancers needed to complete the act.”

    And a few more notes:

    Book Review: Creating Life in the Lab: How New discoveries in Synthetic Biology Make a Case for the Creator – Rich Deem – January 2011
    Excerpt: Despite all this “intelligent design,” the artificial enzymes were 10,000 to 1,000,000,000 times less efficient than their biological counterparts. Dr. Rana asks the question, “is it reasonable to think that undirected evolutionary processes routinely accomplished this task?”

    Research group develops more efficient artificial enzyme – November 2011
    Excerpt: Though the artificial enzyme is still many orders of magnitude less efficient than nature’s way of doing things, it is far more efficient than any other artificial process to date, a milestone that gives researchers hope that they will one day equal nature’s abilities.

    The Challenge to Darwinism from a Single Remarkably Complex Enzyme – Ann Gauger – May 1, 2012
    Excerpt: Meet carbamoyl phosphate synthetase (CPS), a remarkably complex enzyme. This enzyme uses bicarbonate, glutamine, ATP, and water to make carbamoyl phosphate via a multi-step reaction at three separate active sites, involving several unstable intermediates. See here for details.
    CPS is made of two protein chains with a combined length of over 1,400 amino acid residues. We now know from extensive biochemical data that a fully coupled CPS requires the hydrolysis of one glutamine and two molecules of MgATP for every molecule of carbamoyl phosphate formed. The three active sites of the enzyme maintain the overall stoichiometry of the reaction, without wasteful hydrolysis of glutamine and/or MgATP. In order to couple the reactions efficiently, the enzyme uses internal molecular tunnels for sequestering and rapid transfer of reactants between active sites, and allosteric conformational changes to synchronize their activity. This is remarkable, given that the first and last active sites are separated by nearly 100 Å. But even more remarkable is the fact that this enzyme carries out a series of reactions involving unstable intermediates with a half-life of seconds to milliseconds.
    How does a neo-Darwinian process evolve an enzyme like this? Even if enzymes that carried out the various partial reactions could have evolved separately, the coordination and combining of those domains into one huge enzyme is a feat of engineering beyond anything we can do.

  9. 9
    A Gene says:

    ba77 –

    And your observational evidence that it is actual genetic history is what exactly?

    That’s being modelled? I read the papers. I look at them. I see that they are modelling actual genetic histories.

    Joe –

    A Gene:

    Coalescent theory models actual genetic history.

    That is the unverifiable propaganda, anyway.

    Wow. It’s easy to verify this – just read the papers. You’ll see that they are models of the genetic history. Now, you could argue that the models are deficient, but claiming they can’t be shown to exist is, well, odd.

  10. 10
    bornagain77 says:

    A Gene: I don’t think actual genetic histories in the context you are using it means exactly what you think it means. I think it would be far more truthful if perhaps you stated they are modeling hypothetical genetic histories at least, or until, it is actually demonstrated such step by step transitions in protein and/or DNA sequences and/or functionality into drastically new kinds of species is even feasible. Until then would not you agree that the word actual as you are using it is overstating the strength of what is actually being done in these mathematical models?

    Somewhat related note:

    Waiting Longer for Two Mutations – Michael J. Behe
    Excerpt: Citing malaria literature sources (White 2004) I had noted that the de novo appearance of chloroquine resistance in Plasmodium falciparum was an event of probability of 1 in 10^20. I then wrote that ‘for humans to achieve a mutation like this by chance, we would have to wait 100 million times 10 million years’ (1 quadrillion years)(Behe 2007) (because that is the extrapolated time that it would take to produce 10^20 humans). Durrett and Schmidt (2008, p. 1507) retort that my number ‘is 5 million times larger than the calculation we have just given’ using their model (which nonetheless “using their model” gives a prohibitively long waiting time of 216 million years). Their criticism compares apples to oranges. My figure of 10^20 is an empirical statistic from the literature; it is not, as their calculation is, a theoretical estimate from a population genetics model. Generally, when the results of a simple model disagree with observational data, it is an indication that the model is inadequate.

    Please note that Dr. Behe, even though the numbers from their model still supported his overall conclusion for the rarity of spontaneous binding site formation, was indignant with the weight they were giving their model over what the evidence actually said!

    i.e. observational evidence trumps theory all the time in science why should now be any different?

  11. 11
    bornagain77 says:

    A Gene here is an example of ‘actual’ genetic history coming into conflict with ‘hypothetical’ genetic history:

    Fauna on mountaintops isolated for tens of millions of years found to defy evolutionary expectations (In evolutionary theory, a dog-like cow can become a whale in less time than 10 million years):

    Brazil’s Islands in the Sky Defy Evolution
    Excerpt: “analyses of two mitochondrial gene fragments evolving at different rates,” they were very surprised: “populations of a given species on individual summits are often closely related to those on other summits (e.g., Oreophrynella), or to those from the surrounding uplands (e.g., Tepuihyla).” Many of the differences were less than 1%. “Uncorrected pairwise distances in both genes indicate unexpectedly low genetic divergence — as low as zero — among multiple tepui summit species or populations in five of the six groups (Stefania being the only exception), as well as among some summit species or populations and uplands populations described as distinct species.”

    If you read the details of the article you will find that they go to some fairly amusing lengths trying to ‘explain away’ the observational evidence.

    Science and Pseudoscience (transcript) –
    “In degenerating programmes, however, theories are fabricated only in order to accommodate known facts” – Lakatos

  12. 12
    A Gene says:

    ba77 – just to be clear. The models are models of actual genetic histories. This doesn’t necessarily mean that any of the histories the model produces is the actual history, but they should be close enough that they’re informative.

  13. 13
    bornagain77 says:

    But alas A Gene that ‘should be close enough that they’re informative’ assumption of yours is the very thing under question. ergo the reason why I object to your use of the word ‘actual’ as opposed to the more proper word hypothetical.

  14. 14
    bornagain77 says:

    Of related note as to trying to see whether these ‘hypothetical genetic trees’ drawn up by Darwinists with the models are even feasible as far as reality itself is concerned, this following video shows why Darwinists are grossly oversimplifying the complexity of what they are trying to explain the origination of:

    The Multi-dimensional Genome — by Dr Robert Carter – presentation starts approx 12:00 minute mark – video

  15. 15
    bornagain77 says:

    A Gene here are a few more examples of reality and Darwinian hypothesis colliding:

    Fantasy Island: Evolutionary Weirdness Does Not Favor Islands – July 2010
    Excerpt: “We concluded that the evolution of body sizes is as random with respect to ‘isolation’ as on the rest of the planet,” he said. “This means that you can expect to find the same sort of patterns on islands and on the mainland.”

    Amazing Insects Defy Evolution – October 2010
    Excerpt: India spent tens of millions of years as an island before colliding with Asia. Yet the fossil record contains no evidence that unique species evolved on the subcontinent during this time,

    Allopatric Speciation Tested in Martinique Cornelius Hunter – February 2012
    Excerpt: In spite of evolutionary expectations the different lizard populations, which had been separated for six to eight millions years, had no difficulty interbreeding as one species. The so-called allopatric speciation never happened. Undaunted as ever, evolutionist now call for “ecological speciation,” which didn’t occur either but it has the virtue that it can’t be falsified.

    here are incongruities from genetics

    Theory Creep: The Quiet Shift in Evolutionary Thought – Douglas Axe June 25, 2012
    Excerpt: But if we fast-forward two more decades, it becomes clear that the consistent picture that everyone expected — all genes confirming the same pattern of species relationships — is not to be. What we have instead is something of a mess, as James Degnan and Noah Rosenberg made clear in a paper published in 20093:
    “Many of the first studies to examine the conflicting signal of different genes have found considerable discordance across gene trees: studies of hominids, pines, cichlids, finches, grasshoppers and fruit flies have all detected genealogical discordance so widespread that no single tree topology predominates.”
    And despite consistent attempts to portray this as something less than a crisis for evolutionary theory, the news found its way into the popular press. That same year, The Telegraph jumped on the story with an article titled, “Charles Darwin’s tree of life is ‘wrong and misleading,’ claim scientists”4.

    Gene tree discordance, phylogenetic inference and the multispecies coalescent – 2009
    Excerpt: Many of the first studies to examine the conflicting signal of different genes have found considerable discordance across gene trees: studies of hominids, pines, cichlids, finches, grasshoppers and fruit flies have all detected genealogical discordance so widespread that no single tree topology predominates.

    This Paper Discusses Problems With the Evolutionary Tree That You Didn’t Learn in Biology Class – Cornelius Hunter – May 2012
    Excerpt: In fact, it is impossible to construct a realistic evolutionary tree using all the (genetic) data. Evolutionists routinely construct evolutionary trees using a select, more cooperative, subset of the data. And even then the resulting trees are unrealistic. That is, they require evolutionary change for which there is no known mechanism. This is true even according to evolutionists who are quite liberal in allowing for speculation.,,, So neighboring species on the evolutionary tree may have a great many similarities, but in many cases they have some big differences, which evolutionary theory cannot explain beyond vague speculation.

    Phylogeny: Rewriting evolution – Tiny molecules called microRNAs are tearing apart traditional ideas about the animal family tree. – Elie Dolgin – 27 June 2012
    Excerpt: “I’ve looked at thousands of microRNA genes, and I can’t find a single example that would support the traditional tree,” he says. “…they give a totally different tree from what everyone else wants.” (Phylogeny: Rewriting evolution, Nature 486,460–462, 28 June 2012) (molecular palaeobiologist – Kevin Peterson)
    Mark Springer, (a molecular phylogeneticist working in DNA states),,, “There have to be other explanations,” he says.
    Peterson and his team are now going back to mammalian genomes to investigate why DNA and microRNAs give such different evolutionary trajectories. “What we know at this stage is that we do have a very serious incongruence,” says Davide Pisani, a phylogeneticist at the National University of Ireland in Maynooth, who is collaborating on the project. “It looks like either the mammal microRNAs evolved in a totally different way or the traditional topology is wrong.

    Why Darwin was wrong about the (genetic) tree of life: – 21 January 2009
    Excerpt: Syvanen recently compared 2000 genes that are common to humans, frogs, sea squirts, sea urchins, fruit flies and nematodes. In theory, he should have been able to use the gene sequences to construct an evolutionary tree showing the relationships between the six animals. He failed. The problem was that different genes told contradictory evolutionary stories.,,, Syvanen says. .”We’ve just annihilated the tree of life. It’s not a tree any more, it’s a different topology entirely,” says Syvanen. “What would Darwin have made of that?”

    The universal ancestor – Carl Woese
    Excerpt: No consistent organismal phylogeny has emerged from the many individual protein phylogenies so far produced. Phylogenetic incongruities can be seen everywhere in the universal tree, from its root to the major branchings within and among the various taxa to the makeup of the primary groupings themselves.

  16. 16
    A Gene says:

    But alas A Gene that ‘should be close enough that they’re informative’ assumption of yours is the very thing under question. ergo the reason why I object to your use of the word ‘actual’ as opposed to the more proper word hypothetical.

    Are you suggesting that there isn’t an actual genetic history?

  17. 17
    bornagain77 says:

    A Gene you ask:

    Are you suggesting that there isn’t an actual genetic history?

    No, I’m claiming that the hypothetical Darwinian models of genetic history, from population genetics, which force fit the genetic evidence into their preconceived universal tree of common descent are a gross departure from what the actual genetic evidence is telling us, not to mention a gross oversimplification of the level of complexity being dealt with. A more accurate reflection of actual genetic history, from population genetics, that stays truest to what the observational evidence is actually telling us, is found in Dr. Sanford’s computer program ‘Mendel’s Accountant’:

    Using Computer Simulation to Understand Mutation Accumulation Dynamics and Genetic Load:
    Excerpt: We apply a biologically realistic forward-time population genetics program to study human mutation accumulation under a wide-range of circumstances.,, Our numerical simulations consistently show that deleterious mutations accumulate linearly across a large portion of the relevant parameter space.

    Here is a short sweet overview of Mendel’s Accountant:

    When macro-evolution takes a final, it gets an “F” – Using Numerical Simulation to Test the Validity of Neo-Darwinian Theory (Mendel’s Accountant)
    Excerpt of Conclusion: This (computer) program (Mendel’s Accountant) is a powerful teaching and research tool. It reveals that all of the traditional theoretical problems that have been raised about evolutionary genetic theory are in fact very real and are empirically verifiable in a scientifically rigorous manner. As a consequence, evolutionary genetic theory now has no theoretical support—it is an indefensible scientific model. Rigorous analysis of evolutionary genetic theory consistently indicates that the entire enterprise is actually bankrupt.

    Genetic Entropy – Dr. John Sanford – Evolution vs. Reality – video (Notes in description)

    In fact, when one looks at a bit of the history of Darwinism’s attempt to square, mathematically, with population genetics, one finds that it started off absurd and and has ended up going down hill until what it has finally reached a point that many top researchers consider neo-Darwinism completely defunct as a viable hypothesis.

    At the 2:45 minute mark of the following video the mathematical roots of the junk DNA argument, that is still used by Darwinists (though some Darwinists now try to deny that Darwinists ever predicted junk DNA), is traced through Haldane, Kimura, and Ohno’s work, in the 1950’s, 60’s and 70’s, in population genetics:

    What Is The Genome? It’s Not Junk! – Dr. Robert Carter – video – (Notes in video description)

    Haldane’s Dilemma
    Excerpt: Haldane was the first to recognize there was a cost to selection which limited what it realistically could be expected to do. He did not fully realize that his thinking would create major problems for evolutionary theory. He calculated that in man it would take 6 million years to fix just 1,000 mutations (assuming 20 years per generation).,,, Man and chimp differ by at least 150 million nucleotides representing at least 40 million hypothetical mutations (Britten, 2002). So if man evolved from a chimp-like creature, then during that process there were at least 20 million mutations fixed within the human lineage (40 million divided by 2), yet natural selection could only have selected for 1,000 of those. All the rest would have had to been fixed by random drift – creating millions of nearly-neutral deleterious mutations. This would not just have made us inferior to our chimp-like ancestors – it surely would have killed us. Since Haldane’s dilemma there have been a number of efforts to sweep the problem under the rug, but the problem is still exactly the same. ReMine (1993, 2005) has extensively reviewed the problem, and has analyzed it using an entirely different mathematical formulation – but has obtained identical results.
    John Sanford PhD. – “Genetic Entropy and The Mystery of the Genome” – pg. 159-160

    Kimura’s Quandary
    Excerpt: Kimura realized that Haldane was correct,,, He developed his neutral theory in responce to this overwhelming evolutionary problem. Paradoxically, his theory led him to believe that most mutations are unselectable, and therefore,,, most ‘evolution’ must be independent of selection! Because he was totally committed to the primary axiom (neo-Darwinism), Kimura apparently never considered his cost arguments could most rationally be used to argue against the Axiom’s (neo-Darwinism’s) very validity.
    John Sanford PhD. – “Genetic Entropy and The Mystery of the Genome” – pg. 161 – 162

    A graph featuring ‘Kimura’s Distribution’ being ‘properly used’ is shown in the following video:

    Evolution Vs Genetic Entropy – Andy McIntosh – video

    Further note:

    Majestic Ascent: Berlinski on Darwin on Trial – David Berlinski – November 2011
    Excerpt: The publication in 1983 of Motoo Kimura’s The Neutral Theory of Molecular Evolution consolidated ideas that Kimura had introduced in the late 1960s. On the molecular level, evolution is entirely stochastic, and if it proceeds at all, it proceeds by drift along a leaves-and-current model. Kimura’s theories left the emergence of complex biological structures an enigma, but they played an important role in the local economy of belief. They allowed biologists to affirm that they welcomed responsible criticism. “A critique of neo-Darwinism,” the Dutch biologist Gert Korthof boasted, “can be incorporated into neo-Darwinism if there is evidence and a good theory, which contributes to the progress of science.”
    By this standard, if the Archangel Gabriel were to accept personal responsibility for the Cambrian explosion, his views would be widely described as neo-Darwinian.

    and even today, after many revisions to basic Darwinian theory (reminiscent of the many added on epicycles in geocentric theory), we find that Darwinism is still far short of giving a adequate explanation for the evidence:

    The Fate of Darwinism: Evolution After the Modern Synthesis – January 2012
    Excerpt: We trace the history of the Modern Evolutionary Synthesis, and of genetic Darwinism generally, with a view to showing why, even in its current versions, it can no longer serve as a general framework for evolutionary theory. The main reason is empirical. Genetical Darwinism cannot accommodate the role of development (and of genes in development) in many evolutionary processes.

    further notes:

    Murray Eden, as reported in “Heresy in the Halls of Biology: Mathematicians Question Darwinism,” Scientific Research, November 1967, p. 64.
    “It is our contention that if ‘random’ is given a serious and crucial interpretation from a probabilistic point of view, the randomness postulate is highly implausible and that an adequate scientific theory of evolution must await the discovery and elucidation of new natural laws—physical, physico-chemical, and biological.” Murray Eden, “Inadequacies of Neo-Darwinian Evolution as a Scientific Theory,” Mathematical Challenges to the Neo-Darwinian Interpretation of Evolution, editors Paul S. Moorhead and Martin M. Kaplan, June 1967, p. 109.

    Excerpt: A number of mathematicians, familiar with the biological problems, spoke at that 1966 Wistar Institute,, For example, Murray Eden showed that it would be impossible for even a single ordered pair of genes to be produced by DNA mutations in the bacteria, E. coli,—with 5 billion years in which to produce it! His estimate was based on 5 trillion tons of the bacteria covering the planet to a depth of nearly an inch during that 5 billion years. He then explained that the genes of E. coli contain over a trillion (1012) bits of data. That is the number 10 followed by 12 zeros. *Eden then showed the mathematical impossibility of protein forming by chance.

  18. 18
    A Gene says:

    No, I’m claiming that the hypothetical Darwinian models of genetic history, from population genetics, which force fit the genetic evidence into their preconceived universal tree of common descent are a gross departure from what the actual genetic evidence is telling us, not to mention a gross oversimplification of the level of complexity being dealt with.

    Right. So you’re saying that the modelled histories aren’t very good. But aren’t they still trying to model the histories?

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