Yet more on the historical Jesus IV

Yet more on the historical Jesus III

Yet more on the historical Jesus II

Yet more on the historical Jesus.

Why the case for design remains undeniable.

Losing the Forest by Fixating on the Trees — A Response to Venema’s Critique of Undeniable

Douglas Axe | @DougAxe

I was asked recently to take part in an online  symposium.  The journal Sapientia, published by the Carl F.H. Henry Center, invited four theistic evolutionists to review my book,  Undeniable: How Biology Confirms Our Intuition That Life Is Designed,  after which I was to provide a single response. Anticipating that the reviews would all be negative, I saw this not as an opportunity to convert my critics but rather as an opportunity to demonstrate to open-minded people the power of common-sense reasoning. This is, after all, the main theme of Undeniable: that ordinary curious people are well equipped to see through all the technical huff and bluff used by people with PhDs to defend the evolutionary explanation of life.

I agreed to participate, even though the deck was stacked against me in several respects. First, considering the critical view I take not just of Darwinism but also of the academic echo chamber that, with iron-lung-like artificiality, allows this otherwise dead theory to persist, it should be clear that I wrote primarily for people outside the echo chamber. The exclusion of anyone who fits that description from providing even one of the reviews of my book therefore raises questions about the true intent of the exercise. Second, although I was offered the advantage of having the last word, my response was restricted to about a third the total length of the four critiques (though I did get this adjusted upward a bit). And third, I only realized after my response was submitted that it would be published a full month after the first of the critiques became public.

I hereby unstack the deck.

My official symposium response, to be published March 5, doesn’t give much space to my first critic, Dennis Venema This is mostly because, not knowing the order in which the critiques would be published, I had already dealt with the problems that Venema’s piece shares with the others — his complete lack of engagement with the actual argument of Undeniable, his misconstrual of this as an argument from intuition, and his accompanying charge of anti-intellectualism. The second reason I chose not to spend many words on Venema is that he relied heavily on technical criticisms, whereas the whole point of Undeniable is to give people a better option than trying to follow the technical toing and froing. My claim is that you don’t need to be able to follow technical arguments about genes and proteins and mutations in order to understand why Darwin’s explanation of life can’t possibly be correct.

That said, I don’t want to give the impression that Venema’s technical criticisms can’t be answered. They can. My point is that people can have a perfectly solid basis for knowing that Venema’s position is wrong even if they can’t fully follow his technical points or my responses to those points (below). If I’m right about this, then Venema’s “Trust me — I’m a scientist” approach isn’t going to work. He’s going to have to enable intelligent non-scientists to make sense in their own minds of the claim that things like humming birds and cheetahs and humans just happen in a universe like ours.

I’m pretty sure he can’t do so (though I would welcome an attempt). Perhaps he has his own doubts about this, which would explain why he chose to ignore the main argument of Undeniable.

My forthcoming official response makes that point. Here I’d like to show why you should be cautious about trusting Venema’s take on this simply because he’s a scientist.

First, the fact that Venema looks to a non-scientist — Vincent Torley, an English teacher with a PhD in the philosophy of mind — as though he were an authority on my protein work serves as a strong indicator that Venema isn’t an authority either in this area. With that in mind, let’s consider Venema’s dual claims in order: 1) “we now know that proteins do not need to be stably folded in order to function,” and 2) “we also know that functional proteins are not rare within sequence space.”

Conditional Folding Is Still Folding

On the first point, Venema surely knows he’s misleading his readers. With respect to proteins, folding refers to the process by which initially floppy protein chains lock into well-defined three-dimensional structures that perform specific functions within cells. Venema cites a good review paper on so-called “intrinsically disordered proteins,” claiming the existence of this class of proteins shows that protein function doesn’t actually require folding. However, if Venema read the paper, he knows it has a section titled “Coupled folding and binding,” referring to the “mechanism by which disordered interaction motifs associate with and fold upon binding to their targets” (emphasis added). In other words, the term “intrinsically disordered proteins” is a misnomer (whoever coined the term evidently didn’t know what the word intrinsic means). A better term would be conditionally folded proteins.

Moreover, anyone who reads this review paper with open eyes will see that conditional folding is in fact a remarkable design feature. As the authors say, “An exciting recent finding is that many proteins containing low-complexity or prion-like sequences can promote phase separation to form membrane-less organelles within the cytoplasm or nucleoplasm, thus contributing to their compartmentalization in a regulated manner.” Speaking of conditionally folded proteins in general, the authors note that the levels of these proteins within cells are “tightly regulated to ensure precise signaling in time and space, and mutations in [them] or changes in their cellular abundance are associated with disease.”

So, if Venema pictures these conditional folders as being easy evolutionary onramps for mutation and selection to make unconditionally folded proteins, he’s badly mistaken. Both kinds of proteins are at work in cells in a highly orchestrated way, both requiring just the right amino-acid sequences to perform their component functions, each of which serves the high-level function of the whole organism. The point of Undeniable is that we don’t need to know the exact improbabilities of each of these component functions to know that the whole thing can’t happen by chance. We merely need to see that a great many things have to come together in the right way for systems like this to be made. The obvious fact that every one of these things is improbable if left to chance makes getting the whole thing utterly impossible.

Storytelling Isn’t Science

On the second point (the rarity of functional sequences) Venema appeals to two lines of evidence. First, he sees “strong evidence” that “new genes that code for novel, functional proteins can pop into existence from sequences that did not previously encode a protein.” The authors of the paper he cites in support of this are more cautious. Like all authors, they want to think the evidence they provide is strong, but considering the number of assumption involved, they are compelled to be more tentative: “These results suggest that BSC4 may be a newly evolved gene” (emphasis added).

The observable facts are what they are: brewers’ yeast has a gene that isn’t found intact in similar yeast species and appears to play a back-up role of some kind. The question is how to interpret these facts. And this is where Venema and I take different approaches. Like most biologists, Venema starts with the assumption that evolution works as claimed (or maybe he would say openness to the possibility that it does) and then he looks at genomes as if they were the record of evolutionary accomplishments — evolution’s CV, as it were. But once you go down this road of thinking you can divine the past by “reading” it from genomes, you tend to get sucked in. The distinction between stories and facts becomes blurred to the point where every new story is seen as confirmation of that initial assumption that evolution works. Then, having become hooked on this way of thinking, you have no inclination to step back and take a critical view of the whole thing.

A more critical approach is necessary for getting the science right. Stories about how things happened can’t become scientifically compelling until we show: 1) that things could have happened that way, and 2) that no other way they could have happened is comparably likely. Having taken this critical approach for decades, I’ve become convinced that all naturalistic explanations of life fail at step 1. That’s the point of Undeniable, and while Venema may dislike this point, his aversion to it is not an answer to it.

To ignore is not to refute.

If we retain an appropriate degree of skepticism about the grand evolutionary story, other interpretations of the facts surrounding BSC4 present themselves, one being that similar yeast species used to carry a similar gene which has now been lost. The fact that the version of this gene in brewers’ yeast is interrupted by a stop codon that reduces full-length expression to about 9 percent of what it would otherwise be seems to fit better with a gene on its way out than a gene on its way in. I admit that’s just another story, the point being that there’s usually more than one possible story.

The motives for telling these stories can be as interesting as the stories themselves, as  this paper in Nature Reviews Genetics reveals. The abstract starts by presenting a problem:

Gene evolution has long been thought to be primarily driven by duplication and rearrangement mechanisms. However, every evolutionary lineage harbours orphan genes that lack homologues in other lineages and whose evolutionary origin is only poorly understood.

Translation: Genomic sequencing has revealed something that contradicted evolutionary thinking — namely, an abundance of genes that don’t appear to have any evolutionary history (hence the name orphan genes).

Now, if biologists were as cautious about stories as they ought to be, this discovery would have been a huge wakeup call. Instead it was merely an occasion to recraft the story, keeping it true to the grand theme of life being the product of natural causes. By this constrained way of thinking, orphan genes must be able to pop into existence naturally because, well — here they are! Accordingly, the authors of the above paper “solve” the problem they posed by positing that “de novo evolution out of non-coding genomic regions is emerging as an important additional mechanism” for the origin of existing genes.

Don’t Forget: The Point in Dispute Is the Sufficiency of Chance

The focus should indeed be on mechanisms — detailed, self-critical, scientifically tested accounts of just how new functional genes would “pop into existence.” More specifically, with respect to the present debate, the key question is not what happened when and where. As interesting as that question is, the crucial question for our purposes is this: Could these things have happened by chance?

Venema and I both believe the universe popped (banged) into existence long ago, and we both recognize the implausibility of the claim that this just happened. Likewise, we both understand the profound significance of this distinction between an intended universe and an accidental one. Given all this agreement, Venema should be equally concerned to make the same distinction for life, all the way down to individual genes. The crucial question isn’t whether genes popped into existence but whether they popped into existence by chance. If he recognized this, he would be less distracted by the stories and more genuinely interested in the probabilities. After all, the only adjudicator on questions of chance is probability.

Rhetoric Isn’t Science

To his credit, Venema at least gives a nod in this direction by citing a piece of experimental work by Neme and coworkers that claims to show functional DNA sequences are highly probable — abundant within the space of possibilities. These scientists inserted synthetic pieces of DNA with random sequences into an existing genetic element that, when placed in bacterial cells, forces these cells to churn out loads of RNA from the inserts and also to churn out any protein chain they might happen to encode (by chance). After experimenting with these encumbered bacterial strains, they claim that “the majority of randomly generated sequences have reproducible biochemical activity.”

Though the shortcomings of this study wouldn’t be evident to every reader, they were evident to me when I read the paper last spring, just after it appeared. I was therefore pleased to see a polite explanation of some of the problems published in Current Biology last July. The authors of this critique left no doubt as to the magnitude of the flaws: “we have reservations about the correctness of the conclusion of Neme et al. that 25% of their random sequences have beneficial effects…”

Indeed, it’s hard to escape the conclusion that Neme and coworkers deliberately overstated their case. They concluded that most randomly generated sequences have “biochemical activity,” but what they showed is far less impressive. They merely showed that if you burden bacteria by forcing them to churn out RNA and protein from random inserts, it’s fairly easy to find sequence-dependent effects on growth — not because anything clever has been invented, but because the burden of making so much junk varies slightly with the kind of junk. That means any junk that slows the process of making more junk by gumming up the works a bit would provide a selective benefit. Such sequences are “good” only in this highly artificial context, much as shoving a stick into an electric fan is “good” if you need to stop the blades in a hurry.

Yes, junk sequences can have a measurable effect in situations like this, but the word function implies something considerably more than mere effect, and the term “biochemical activity” used by Neme et al. is so clearly incorrect that it’s hard to believe the reasons for choosing it weren’t more rhetorical than scientific.

In the end, then, Venema’s technical complaints come to nothing. In his position, I would probably be inclined to respond with more technical complaints. He is, of course, free to do so, but he would do himself a favor to hit pause and consider whether there really may be a clear logical reason that the natural causes he wants to credit with inventing life can’t actually deserve that credit.

Yet more in defense of Adam and Eve.

Adam and the Genome and “Predetermined Conclusions”
Evolution News | @DiscoveryCSC

In two previous posts (here and here), we saw that evolutionary genomicist Richard Buggs and biologist Dennis Venema have been debating online about Venema’s argument in Adam and the Genome that human genetic diversity refutes a traditional view of Adam and Eve. (Find the rest of our series of posts on the book here.)  Buggs explained that Venema’s allusion to human leukocyte antigen (HLA) genes (also called major histocompatibility complex, or MHC, genes) do not refute an original human couple. In his  Nature Ecology & Evolution blog post, Buggs writes, “Hyper-variable loci like MHC genes or microsatellites have so many alleles that they seem to defy the idea of a single couple bottleneck until we consider that they have very rapid rates of evolution, and could have evolved very many alleles since a bottleneck.” Buggs also explained in a  comment at The Skeptical Zone  that the ability of MHC genes to evolve rapidly isn’t a good argument for a large ancestral population size:

MHC loci are pretty exotic. Several studies show that they evolve fast and may be under sexual selection, pathogen-mediated selection, and frequency-dependent selection; they may also have heterozygote advantage (see e.g. [link]). The maintenance of MHC polymorphism is still “an evolutionary puzzle” ([link]). There is some evidence for convergent evolution of HLA genes ([link, link, link, link]). If the whole case for large human ancestral population sizes rests on MHC loci, I think this is inadequate to prove the point, given our current state of knowledge on MHC evolution.

Buggs isn’t the only qualified biologist who has looked at arguments from MHC genes against Adam and Eve and found them lacking. In the book Science and Human Origins, Ann Gauger considered the evidence, and found it compatible with an initial couple. She recounts her investigation of this topic:

When I began this study, I was prepared to accept that there was too much genetic diversity among these genes to have passed through just two first parents. To my surprise, I found that even this most polymorphic (most varied) region of our genome does not rule out the possibility of a first couple.

(Science and Human Origins, p. 106)

As Gauger points out, the evolutionary biologist Francisco Ayala had calculated that there were 32 different HLA alleles in existence when the human lineage diverged from chimps, requiring “that the minimum size of the ancestral population was no fewer than 4,000, with a long-term average effective population size of 100,000.” She explains why this supposedly refuted Adam and Eve:

Because of this minimal estimate of 4,000, Ayala claimed that at no time was it possible for the human population to have passed through a bottleneck of two. In his view, there is just too much ancestral diversity in HLA-DRB1.

(Science and Human Origins, p. 111)

After reviewing Ayala’s arguments, however, she found that his model had both explicit and implicit assumptions that were dubious:

These explicit assumptions include a constant background mutation rate over time, lack of selection for genetic change on the DNA sequences being studied, random breeding among individuals, no migrations in or out of the breeding population, and a constant population size. If any of these assumptions turn out to be unrealistic, the results of a model may be seriously flawed.

There are also hidden assumptions buried in population genetics models, assumptions that rely upon the very thing they are meant to demonstrate. For example, tree-drawing algorithms assume that a tree of common descent exists. The population genetics equations also assume that random processes are the only causes of genetic change over time, an assumption drawn from naturalism. What if non-natural causes, or even unknown natural causes that do not act randomly, have intervened to produce genetic change?

(Science and Human Origins, p. 112)

Gauger realized that in this case, Ayala had wrongly assumed a lack of selection on these genes, and wrongly assumed a constant background mutation rate. Another study that corrected for these problems found that only seven copies of HLA need have existed, which Gauger calls a “dramatically lower estimate for the number of HLA-DRB1 alleles in the ancestral population than the number Ayala found in his study (i.e. seven alleles versus thirty-two).” (p. 113) A later paper reported that HLA-DRB1 alleles numbered only four or five at the time of our supposed split from chimps. This number is low enough to have passed through a single couple.

Now of course Venema cites papers that looked at many other genes and their various alleles in the human genome. So there’s a lot more data that remains to be evaluated. But note why Gauger chose to study HLA genes:

I chose to look at the HLA-DRB1 story because it seemed to provide the strongest case from population genetics against two first parents. If it were true that we share thirty-two separate lineages of HLA-DRB1 with chimps, it would indeed cause difficulties for an original couple. But as we have seen, the data indicate that it is possible for us to have come from just two first parents.

(Science and Human Origins, p. 120)

For a short online summary of Gauger’s argument, see here.

A Prescient Warning

If perhaps the strongest argument against Adam and Eve — from population genetics — has fallen apart, what will happen when other genes are similarly scrutinized? Of course we should wait and see what the evidence says, but Gauger’s warning is prescient:

[O]ne thing is clear right now: Adam and Eve have not been disproven by science, and those who claim otherwise are misrepresenting the scientific evidence.

(Science and Human Origins, p. 121)

Indeed, much data remains to be examined. And Gauger and some of her colleagues, such as Ola Hössjer, have been addressing that data. They have published two peer-reviewed papers that present models for potentially testing population genetics arguments against a first couple at our origin: 

• Ola Hössjer, Ann Gauger, and Colin Reeves, “Genetic Modeling of Human History Part 1: Comparison of Common Descent and Unique Origin Approaches,” BIO-Complexity, Vol. 2016 (3).
• Ola Hössjer, Ann Gauger, and Colin Reeves, “Genetic Modeling of Human History Part 2: A Unique Origin Algorithm,” BIO-Complexity, Vol. 2016 (4).

Their papers evaluate the assumptions underlying the standard evolutionary model of human origins and find “it is full of gaps and weaknesses.” The authors maintain that “a unique origin model where humanity arose from one single couple with created diversity seems to explain data at least as well, if not better.”

Created Founder Diversity

After reviewing five main mechanisms invoked by standard evolutionary models of population genetics to explain human genetic diversity (mutation, genetic drift, natural selection, recombination, and colonization and migration), the first paper observes:

Neo-Darwinism accounts for the above-mentioned mechanisms I-V, and among them germline mutations are essentially the only way by which novel DNA can arise. The theory does not allow for large amounts of new and suddenly appearing diversity. The reason is that neo-Darwinism is framed within methodological naturalism. This prevailing approach to science only allows for natural hypotheses. But if an intelligent designer is invoked as a possible explanation, and if humanity originates from one single couple, it is possible that their chromosomes were created with considerable diversity from the beginning.

Thus, the authors propose a sixth mechanism of genetic change, called created founder diversity. Created founder diversity is biologically plausible for DNA of non-sex chromosomes, and would allow for initial genetic diversity among all four sets of autosomes in the first couple.

The authors note that the “main argument against a unique origin is that the nucleotide diversity of human DNA data seems too high in order make a single founding couple possible.” But they argue it is possible that humans are descended from an initial couple if “they were created with genetic diversity in their autosomal and X-chromosome DNA.” They conclude: “Any common descent model faces a challenge to explain the genetic differences rather than the similarities with other species, the consequences of inbreeding depression and increased genetic entropy, human DNA mixture with archaic populations, and that our DNA resembles a mosaic of about four founder genomes.” Thus, they find, “The provisional conclusion is that a unique origin model seems more plausible.”

 Their second paper presents mathematical algorithms “for testing different historical scenarios of the human population,” including common ancestry models, and models where humans “all descend from one single couple.” Their mathematical approach can simulate human history by varying different parameters, including population expansion, bottlenecks, colonization and migration patterns, mating and reproduction schemes, and various types of mutations in autosomal chromosomes, sex chromosomes, and mitochondrial DNA. Additionally, “An important parameter of the model is the created diversity of the founder generation, since it facilitates a higher degree of genetic diversity for a relatively young population within autosomal and X chromosomal regions, and possibly also for mitochondrial DNA.”

Their algorithms incorporate what they identify as the six major mechanisms of genetic change: (i) genetic drift, (ii) genetic recombination, (iii) colonization and migration, (iv) mutations, (v) natural selection, and (vi) initial created founder diversity. They note that “common descent models only include the first five mechanisms, but (vi) is important in order to generate enough diversity for a population with only one founding couple.” Indeed, they observe that a “particularly important parameter is the created diversity, which makes it possible to obtain a substantial amount of genetic diversity for nuclear autosomal and X-chromosome DNA, during a relatively short period of time.”

After going through a detailed mathematical analysis of the model, they conclude, “In subsequent papers, we plan to simulate human DNA data from our proposed model in order to assess how well it fits real data,” with the ultimate goal of finding “the best fitting population history within a unique origin framework, and then to compare it with a best fitting common ancestry model.”

The Best Treatment of This Issue

Probably the best treatment of this issue found anywhere is the chapter “An Alternative Population Genetics Model,” by Ann Gauger, Ola Hössjer, and Colin Reeves in the book  Theistic Evolution: A Scientific, Philosophical, and Theological Critique. There, they find key human genomic diversity evidence is highly compatible with Adam and Eve:

Block Structure of DNA. A large part of our autosomal and X-chromosomes have apparently been recombined into blocks of varying length. Many of them are of the order 10,000 nucleotides long, but the variation in length is large. But even though the blocks are long, there is still very little variation within them. Each block comes in just a few variants, four for many parts of the genome. Our chromosomes are different mosaics of these block variants.

This DNA block structure is remarkably consistent with a unique origin hypothesis. If Adam and Eve were created with DNA diversity, there would have been four different copies of each autosomal chromosome — two in Adam and two in Eve. Their four chromosomes have since been scrambled by ancestral recombinations, and today each of us has one mosaic of the four founder chromosomes inherited from our father, and another one from our mother.

After reviewing various aspects of the genetic evidence, they conclude:

We have argued that a unique origin model (with a young or old age of humanity) with created diversity should have at least the same explanatory power for human genetic data as the most popular common descent scenario of today. Any model must be able to explain the big genetic differences between humans and other species, solve the problem of inbreeding depression, support the viability of human and archaic population admixtures, and give reasons why our DNA resembles a mosaic of about four founder genomes. The conclusion is that the unique origin model seems more plausible.

They end their chapter by discussing the models they are currently in the process of testing (the aforementioned technical papers).

We are currently working on implementing a model based on backward simulation. The intent is to validate it with real data. This is a long-term project, whose outcome we hope to publish elsewhere. Using this approach, it may be possible to demonstrate that a unique origin model is able to replicate current human diversity as well or better than the common descent model. That is the purpose of the model—to test this possibility. Therefore, if more than one plausible account of human origins can explain the data, the common descent model of our origin from ape-like ancestors can no longer be claimed as conclusive proof that there could not have been a single first pair. Thus, it would be premature to discard traditional interpretations of the reality and historicity of Adam and Eve.

Obviously  more work remains to be done. But if Venema wants to maintain that Adam and Eve are truly refuted, he’s going to have to contend with this modelling research, which isn’t complete, but already points in a promising direction.

In fact, Venema did respond — though only very briefly, and very dismissively — to this work.  As we explained here,  on the BioLogos website Venema called the papers “a (poor) attempt to argue for a predetermined conclusion that humans were specially created as a pair in the Middle East. It does not offer a mechanism to deal with the obvious problems of such an approach other than an appeal to ‘created diversity.’” University of Stockholm mathematician Ola Hössjer, who co-authored the papers, responded:

Venema basically criticizes the Middle East version of the unique origin model, saying the African DNA looks older than non-European DNA, both from single locus allele frequency statistics and from two locus linkage disequilibrium patterns. But we also point out that this is a drawback of the Middle East unique origin model (on the other hand we argue that a ME origin has other advantages, for instance less inbreeding depression). We offer some tentative explanations (reference 50, for instance) of why African DNA could look older even if humanity originated in the Middle East. Venema rules out these explanations as inadequate. This may very well be true, but it remains to be seen when the model is implemented.

It’s worth stating that these papers offer a model that can be used to test many scenarios, not just that of a single couple at our origin. The model will allow the examination of the effects of mutation rate, selection, recombination, population structure, and population history on patterns of genetic variability, in order to determine which scenarios best reproduce modern genetic diversity. As for the hypothesis of a single pair with created diversity, which Venema labels a “predetermined conclusion,” it is simply one hypothesis to be tested among many.

Moreover, initial “created diversity” is a legitimate, testable mechanism. We know how genetics works and we can decide whether (within the bounds of genetics) initial high diversity could account for present-day observations.

Unfortunately, critics of this work seem to want to reject the proposed model before it’s even been fully implemented. Dr. Venema complains of “predetermined conclusions.” But the criticism could be turned right around and applied to him, instead.