Evolution’s well-kept secret:
Mutations are not random!
For nearly a hundred years, evolutionists have been operating under the paradigm that is known as the “Neo-Darwinian Synthesis”, also known as the “Modern Synthesis”. This view has repeatedly been summarized as ‘natural selection working upon random mutations’. I have taken the liberty of adding emphasis in the quotes below to show you how common this language is.
This goes back decades. A biology textbook from the 1960s says:
“With the development of the gene theory the term ‘mutation’ has come to refer to sudden, discontinuous, random changes in the genes and chromosomes, although it is still used to some extent to refer to the new type of plant or animal.”1
To give an example from a somewhat newer biology textbook (from 1989), one study question asks:
“Based on your knowledge of DNA structure, the genetic code, and protein structure, what sorts of random mutations would you expect to persist in a lineage of organisms, generation after generation, unaffected by natural selection?”2
A Google search for “biology textbook” comes up with a free option through ‘openstax’ called Biology 2e. Here is what this online book (published in 2018) says:
“The diversity of life on Earth is a result of mutations, or random changes in hereditary material over time. These mutations allow the possibility for organisms to adapt to a changing environment. An organism that evolves characteristics fit for the environment will have greater reproductive success, subject to the forces of natural selection.”3
Think for a moment about randomness. Anything could happen, right? Is it not a limitless sea of opportunity? If you think of it like that, and if you apply the magic of seemingly limitless time, life evolving by chance can start to seem plausible. After all, that’s a lot of time for nature to gradually work with random variations and sort out only the best ones. But this has been a fairy tale all along!
According to famous evolutionist Dr. Stephen J. Gould, who said before he died:
“Textbooks of evolution still often refer to variation as ‘random’. We all recognize this designation as a misnomer, but continue to use the phrase by force of habit. Darwinians have never argued for ‘random’ mutation in the restricted and technical sense of ‘equally likely in all directions,’ as in tossing a die. But our sloppy use of ‘random’ … does capture, at least in a vernacular sense, the essence of the important claim that we do wish to convey—namely, that variation must be unrelated to the direction of evolutionary change; or, more strongly, that nothing about the process of creating new raw material biases the pathway of subsequent change in adaptive directions.”4
Wow, Dr. Gould, what a stunning admission! How convenient that this “sloppy” (and ongoing) use of language just so happens to gloss over a major fundamental problem facing evolutionary theory. If mutations are not random, like throwing a die, then that means certain outcomes are more likely. And if certain outcomes are more likely, then how could that not bias the direction of evolutionary change in the long term?
Apparently, this point is not lost on everyone. In 2014, one science writer, Kevin Kelly, came out with an article calling for the ‘retirement’ of this idea of random mutations:
“While we can’t say mutations are random, we can say there is a large chaotic component, just as there is in the throw of a loaded dice [sic]. But loaded dice should not be confused with randomness because over the long run—which is the time frame of evolution—the weighted bias will have noticeable consequences.”5
Why, then, do so many continue using this misleading word? Kelly has some shockingly honest answers for us:
“There are several related reasons why this unsubstantiated idea continues to be repeated without evidence [and actually, as I will show, against the evidence]. The first is fear that non-random mutations would be misunderstood and twisted by creationists to wrongly deny the reality and importance of evolution by natural selection. The second is that if mutations are not random and have some pattern, than [sic] that pattern creates a micro-direction in evolution. And since biological evolution is nothing but micro actions accumulating into macro actions, these micro-patterns leave open the possibility of macro directions in evolution. That raises all kinds of red flags. If there are evolutionary macro-directions, where do they originate? And what are the directions? To date, there is little consensus about evidence for macro-directions in evolution beyond an increase in complexity, but the very notion of evolution with any direction is so contrary to current dogma in modern evolution theory that it continues to embrace the assumption of randomness.”
There we have it! The use of the word “random” is (at least for some) a deliberate ploy to deceive people about the theory of evolution. Is that not what our science writer above has just admitted in writing? They don’t want us evil creationists to take the opportunity to point out all the problems that are inherent with this idea of non-random mutations. Well, too late, because now the cat is out of the bag. I’m going to sound the alarm about this major fundamental problem in evolution.
What is ‘mutational bias’?
If mutations are more likely to produce some results over others, then what is that tendency, exactly? The prevailing view as of now is that GC → AT mutations are more likely. To explain what that means, we need a quick refresher on basic DNA structure.
Basics of DNA composition
DNA is composed of 4 nucleotides, or bases, which function as the basic elements of the code (like letters). They are represented by the letters A, T, C and G. But DNA is a double helix, meaning that each base is paired on the other side of the helix with a corresponding base, and these correspond in a set way. G with C, and A with T. Thus, if you know the string of bases on one side of the double helix, you can predict the other side by simply exchanging G and C, and A and T. Scientists can look at the total sequence of DNA and compile statistics about that data. One such statistic, GC content, refers to the percentage of Gs and Cs as opposed to As and Ts.
The base bias
There is substantial evidence that a general bias exists in all mutations toward AT (GC nucleotides are more likely to mutate into AT).6,7 As one paper by Hildebrand et al. states:
“It has been suggested that there is a universal mutational bias in both prokaryotes and eukaryotes towards AT… Our analysis provides some limited support for this hypothesis.”7
The exact reasons for this bias have to do with things such as the basic laws of chemistry as well as the actions of various enzymes such as DNA polymerase, and there is still much speculation and debate swirling about in this area—which goes beyond the scope of this article to address.
But if this mutational bias against GC content is going on across the board, and mutations are the “raw material” for evolution, why do we have any GC-rich genomes (or sections of genomes) at all? Some hypothetical mechanisms of selection in favour of GC content have been proposed,6 but these all seem to ignore the problem that most mutations are so small as to have negligible effects in isolation (in accordance with ‘neutral theory’).8 The authors of the Hildebrand study admit the problem and rather sheepishly write:
“Such a general decrease in GC-content across GC-rich species is clearly unsustainable … This therefore suggests that selection, or some other force, is maintaining high GC49 in many bacteria.”
Considering this is a peer-reviewed scientific paper, that certainly doesn’t sound very scientific, does it? “Some other force?” Another paper by Couce et al., in which they analysed data from Lenski’s famous Long Term Evolution Experiment (LTEE) with E. Coli, is similarly speculative:
“Despite these mutational pressures, large GC-rich genomes are widespread across bacterial phyla, which points to strong forces driving genomes away from their mutational equilibrium. Many adaptive explanations have been suggested, including biosynthetic costs and the greater stability of GC-rich sequences under high-temperature, oxidizing, and UV irradiation conditions. Whatever the particular selection pressures …”6 [references omitted]
Much like in the Hildebrand paper, this amounts to an admission of ignorance, and completely ignores the problem that most mutations are too small to be selected in the first place. The idea of ‘strong forces’ at work preserving and building GC content is completely at odds with nearly neutral theory.
Can selection overcome this bias?
The speculation that selection may be responsible for maintaining GC content fails because most mutations are too small to be selected at all. They should have known that, given that one of the authors here (Dr Eyre-Walker) also authored a different paper where he stated, “ … particularly for multicellular organisms … most mutations, even if they are deleterious, have such small effects that one cannot measure their fitness consequences.”10
But if most mutations are that small, how can selection act on them? For a mutation to be ‘seen’ by natural selection it has to affect the organism’s ability to reproduce. Because of this it is understood, even by the secular evolutionary experts, that very small mutations are not subject to natural selection. This makes sense because natural selection is just another term for ‘differential reproduction’. If a mutation is too small to affect reproduction in any noticeable way, then selection cannot, even in principle, act on it:
“In terms of evolutionary dynamics, however, mutations whose effects are very small … are expected to be dominated by drift rather than selection.”11
Indeed, according to the commonly accepted ‘neutral theory’ of evolution, there is a limit at which mutations become too small to be selected.12 If most mutations are too small to make any detectable difference for reproduction, then it follows that most mutations are actually not being operated on by natural selection:
“Mutagenesis and mutation accumulation experiments can give us detailed information about the DFE [distribution of fitness effects] of mutations only if they have a moderately large effect, as these are the mutations that have detectable effects in laboratory assays. However, it seems likely that many and possibly the majority of mutations have effects that are too small to be detected in the laboratory.”10
Dr John Sanford, who developed the idea of Genetic Entropy using nothing but the assumptions of neutral theory, has done much work in recent years to test and confirm this hypothesis. A lot of this has been done with a biologically-realistic simulation program which he helped develop: ‘Mendel’s Accountant’. 13 It’s quite telling that the most realistic “evolution simulator” in the world was made by creationists. This program has been used to show that evolution is impossible due to the expected accumulation of damaging mutations in all evolutionary scenarios. Mendel’s Accountant shows that even with strong selection at work, fitness declines continuously over time. Some have tried to argue against it, unsuccessfully I might add, but after more than 10 years, nobody in the secular community has ventured to challenge these results by producing a simulation of their own.
Additionally, in 2012 Drs Sanford and Carter did their own independent peer-reviewed research on the trajectory over time of the H1N1 (human strain) virus, starting from its outbreak in 1917 all the way through its final apparent demise in 2009.14 They showed that, just as Mendel’s Accountant predicted,15 mutations accumulated continuously in the population of flu viruses over time. But not only that—importantly, they also showed that the mutations accumulated “according to the laws of chemistry”. In other words, the mutations were not really being filtered or guided by anything (like selection). GC content went down over time.
The question stands unanswered: why is the GC content of many genomes (and, for that matter, sections of genomes) so much higher than the mutational bias would generate? The evolutionary process that supposedly built life—mutations—is biased against GC and for AT. After hundreds of millions of years of accumulating mutations, and acting upon the assumption that mutations are the source of our genetic information, we would predict to find a level of GC content in line with the overall mutational bias. But that is not what we find.
Conclusion: Evolution has no mechanism!
I have been studying creation apologetics for many years (most of my life, in fact), and I was stunned when I discovered this well-kept evolutionary secret. Most people, including those educated in biological science, have absolutely no idea this major issue exists. As I explored in some of the quotes above, it appears this general ignorance is no accident; those in the know about this deliberately decide not to bring it up, so as to avoid embarrassment for the sacred Primary Axiom of evolution. It is time for us creationists to break the silence in a big way! The fact that mutations are biased in a particular direction due to the laws of chemistry means that we have powerful evidence that mutations are not the original source of the information in DNA. This is by no means the only problem with Darwinian evolution, but this problem is particularly devastating because it shows a deep insufficiency in evolutionary theory at the most fundamental level. Evolution is like a blindfolded person trying to build the Notre Dame cathedral out of Legos® one haphazardly-placed block at a time. The more we learn, the more Darwinism is revealed to be a primitive myth, while the Bible’s account that life was authored by God is shown true.
References and notes
- Villee, C., Biology (4th ed), W.B. Saunders Company, Philadelphia, 1963, p. 517. Return to text.
- Curtis, H. and Barnes, S., Biology, Worth Publishers, New York, 1989. Return to text.
- Clark, M., Douglas, M., and Choi, J., Biology 2e, openstax.org/details/books/biology-2e, 28 Mar 2018. Return to text.
- Gould, S., The Structure of Evolutionary Theory, The Belknap Press of Harvard University Press, Cambridge, 2002, p. 144. Return to text.
- Kelly, K., Fully Random Mutations, edge.org/response-detail/25264, accessed 18 February 2020. Return to text.
- Couce, A. et al., Mutator genomes decay, despite sustained fitness gains, in a long-term experiment with bacteria, PNAS 114 (43) E9026–E9035, 24 October 2017. doi.org/10.1073/pnas.1705887114. Return to text.
- Hildebrand, F., Meyer, A., and Eyre-Walker, A., Evidence of Selection upon Genomic GC-Content in Bacteria, PLoS Genet 6(9): e1001107, 2010. doi: 10.1371/journal.pgen.1001107. Return to text.
- Price, P., Genetic Entropy: The Silent Killer, Creation 41(4):48–50, 2019. Return to text.
- Note the “4” here after GC; they are talking about a specific place called “fourfold degenerate” sites, where any of the 4 nucleotides would make no difference in the amino acid being specified in that codon (coding sequence). They do this because the GC content at those sites is strongly correlated to the overall GC content of the genome. Return to text.
- Eyre-Walker, A. and Keightley P.D., The distribution of fitness effects of new mutations, Nat. Rev. Genet. 8(8):610–8, 2007. doi.org/10.1038/nrg2146. Return to text.
- Shaw, R., Shaw, F., and Geyer, C., What Fraction of Mutations Reduces Fitness? A Reply to Keightley and Lynch, Evolution 57(3):686–689, 2003. jstor.org/stable/3094782. Return to text.
- For example, see ref. 7. Return to text.
- Carter, R., A successful decade for ‘Mendel’s Accountant’, Journal of Creation 33(2):51–56, 2019. Return to text.
- Carter, R. and Sanford, J., A new look at an old virus: patterns of mutation accumulation in the human H1N1 influenza virus since 1918, Theor. Biol. Med. Model. 9:42, 2012; doi:10.1186/1742-4682-9-42. Return to text.
- Brewer, W., Smith, F.D., and Sanford, J.C., Information loss: potential for accelerating natural genetic attenuation of RNA viruses; in: Marks II, R.J., Behe, M.J., Dembski, W.A., Gordon, B., and Sanford, J.C. (Eds.), Biological Information—New Perspectives, World Scientific, Singapore, pp. 369–384, 2013. Return to text.
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