Reactionary fringe meets mutation-biased adaptation. 1. The empirical case

This is the second in a series of guest posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution. The first post was: Reactionary fringe meets mutation-biased adaptation: Introduction.

---

Reactionary fringe meets mutation-biased adaptation. 1. The empirical case
by Arlin Stoltzfus
Reactionary fringe meets mutation-biased adaptation
Introduction
1. The empirical case
2. Some objections addressed
3. The causes and consequences of biases in the introduction process
4. What makes this new?
5. Beyond the "Synthesis" debate
    -Thinking about theories
    -Modern Synthesis of 1959
    -How history is distorted
    -Taking neo-Darwinism
      seriously
    -Synthesis apologetics
6. What "limits" adaptation?
7. Going forwardAs noted in the intro to this series, the appearance of an opinion piece on how mutation bias affects adaptation in Trends in Ecology and Evolution (TREE) appears to be a milestone for understanding this interesting new topic. The authors misrepresent a position on dual causation stated consistently in the literature for 20 years, ignore or misinterpret important new empirical work, and blithely repeat a self-serving view of history that my colleagues and I spent years debunking with careful scholarship.

In other words, as a colleague once said, "This is what victory looks like-- everyone butchering your ideas."

But it gets better. Scientists often invoke the cliche that new truths are first ridiculed as impossible, then opposed as unlikely, then claimed as traditional.  QuoteInvestigator has a piece on this "stages of truth" meme, with the following from Dr. J. Marion Sims, 1868:

For it is ever so with any great truth. It must first be opposed, then ridiculed, after a while accepted, and then comes the time to prove that it is not new, and that the credit of it belongs to some one else.

The idea that the course of evolution reflects internal biases in variation-- or, stated differently, that the generation of variation plays a dispositional role in evolution-- has been (1) ridiculed as an appeal to "the vagueness of inherent tendencies, vital urges, or cosmic goals, without known mechanism" (Simpson, 1967), and (2) ruled out by the famous "opposing pressures" argument from Fisher and Haldane that we will address later.

So, it was exciting that the TREE authors, who represent the reactionary fringe of evolutionary biology-- dedicating to shifting the "Synthesis" goal-posts to maintain the illusion that nothing is new--, not only butcher the idea of mutation-biased adaptation, try to minimize its importance, and misrepresent the evidence: they also want to claim it! Yes, they want to appropriate this unoriginal, unimportant, unsubstantiated idea for the legacy of Ronald Fisher, the closeted mutationist!

Seriously, you could not make this stuff up!

To dig out from under this mess will take some time. Let's begin by reviewing the evidence that the changes that occur during adaptation are enriched for mutationally likely changes.

The case for mutation-biased adaptation

First, consider 4 analyses of experimental evolution.

In the first stage of the compound study by Sackman, et al. (2017), Rokyta, et al. (2005) measured fitness for the beneficial changes-- 9 of them-- implicated in 20 replicate episodes of adaptation of phiX174, aka ID11. Because the fittest variant was found only once, yet the 4th most-fit was found 6 times, the authors explored a model of mutational effects, including transition bias and the multiplicity of mutational paths to an alternative amino acid (e.g., an ATG Met codon can mutate to Ile in 3 different ways, but an Ile codon such as ATC has only one mutational path to Met). An origin-fixation model with mutation bias fit the data better than the mutational landscape model of Orr, which considers only fixation probability. Sackman, et al. (2017) carried out this same 20-replicate protocol with 3 closely related phages: the combined results how a strong bias favoring transitions, 29:5 for paths, 74:6 for events (figure below).

Note the terminology. A "path" specifies the starting and ending genotype, e.g., "gene F, site 3665, C → T", and an event is an occurrence of change along a path-- in this case, a replicate culture in which a phage genome changes. Events along the same paths are parallel events.

MacLean, et al. (2010) repeatedly evolved Rifampicin-resistant Pseudomonas aeruginosa, with results showing a significant correlation between the chance of evolving and the measured mutation rate for 11 changes in rpoB (center panel below). All of these changes are nucleotide substitutions with mutation rates that differ due to unexamined context effects. The lack of correlation in the left panel is not too surprising, given that the calculated probability of fixation ranges only from 0.47 to 0.84, because s is so large (meanwhile, the mutation rate varies 50-fold).

Couce, et al. (2015) evolved cefotaxime resistance repeatedly in 2 different Escherichia coli mutator strains with distinctly different mutation spectra, resulting in two distinct distributions of changes among resistant strains, each with a strong correspondence to the respective parental mutation spectrum.

McCandlish and Stoltzfus (2017) gathered a large set of published cases of laboratory parallel adaptation due to recurrent amino acid replacements (389 events on 63 paths), and found that these data exhibit a substantial excess of transitions, relative to the null expectation for no mutation bias (a 1:2 ratio). Note that this study integrates data from MacLean, et al. (2010) and Rokyta, et al. (2005), but (1) this is a minority of the data (22 %), and (2) the test for transition bias is an independent result from the correlation shown earlier in data from MacLean, et al. (2010).

Next, consider 4 analyses of natural evolution. McCandlish and Stoltzfus (2017), in the same paper just mentioned, gathered data on natural parallelisms from 10 different study systems (231 events on 55 paths), and showed the same kind of transition bias. The summary table below shows that they draw from some famous adaptive stories in molecular evolution, including spectral tuning, resistance to cardiac glycosides (e.g., bird vs. monarch vs. milkweed), foregut fermentation, and echolocation.

The table above represents natural cases from Stoltzfus and McCandlish (2017). Cases 1, 4, 8 and 10 represent recent local adaptation of sub-populations (total 11:10 paths, 69:48 events), while the others represent species divergence (17:17 paths, 63:51 events).

Payne, et al. (2019) examined effects of transition bias in two different curated databases of causative mutations in antibiotic-resistant isolates of Mycobacterium tuberculosis, finding an excess of transition mutations. For instance, they take advantage of the unusual case of Met-to-Ile replacements, which can take place by 1 transition (ATG to ATA) or 2 different transversions (ATG to ATT or ATC). Instead of this 1:2 ratio of possibilities, they see a ratio of 88:49 (Basel dataset) or 96:39 (Manson dataset), roughly 4-fold above null expectations. Because all the replacements are the same type, the bias can not be due to selection preferring some replacements over others.

Storz, et al. (2019) examined changes in hemoglobins using 35 phylogenetically independent comparisons of low- and high-altitude bird populations. They identified adaptive changes in 20 comparisons, implicating 10 different paths and 22 events. (See Table below: Asterisks indicate CpG mutations.) The observation of 6 paths and 10 events associated with CpG mutations was about 6-fold over the null expectation, a statistically significant excess.

Finally, in a completely different type of study, Liu, et al. (2019) explore the emergence of imatinib resistance in leukemia patients, combining clinical data on the frequency of various resistant mutants (of the BCR-ABL oncogene) across 4 continents over 17 years, with laboratory characterization of engineered mutants. In a model for clinical frequency based on drug resistance (measured) and mutation biases (inferred from comparative data), they found that both factors were important, but the mutational factor was more important.

I mention Liu, et al. (2019) to draw attention to a fascinating, biomedically important study. However, I won't include it in future discussions about biological significance, because typically we do not include resistant tumor outgrowths in the category of natural adaptation (and I don't want to confuse people or invite distracting criticisms).

To summarize, various recent studies suggest that the changes that occur during adaptation are enriched for the kinds of changes that are mutationally likely. The spectrum of adaptive changes shows modest biases with the same orientation and magnitude as modest mutation biases (either known or suspected) that range in magnitude from a few-fold (transition bias) to 10-fold (CpG bias) to as large as 50-fold (the range of mutation rates measured by MacLean, et al., 2010).

Going further

Considered on their own, these results are perhaps uninteresting. Mutation biases are secretly influencing the details underlying adaptation. Perhaps this was not expected on classical grounds, but why should we care?

These results are important because they demonstrate a principle not previously accepted: modest quantitative biases in the generation of variation may impose predictable biases on evolution, without a requirement for absolute constraints, neutral evolution or high mutation rates, contradicting the classic logic of the opposing-pressures argument.

If this new principle is general, it would apply to other kinds of mutational biases, as well as to other types of biases, e.g., developmental biases induced by the structure of a genotype-phenotype map. That is, these results provide proof-of-principle for ideas long discussed in evo-devo. As argued by Stoltzfus (2019), the same results add plausibility to key ideas in the self-organization literature, regarding what Cowperthwaite and Ancel (2007) call "the large-scale patterns of mutational connectivity within genotype spaces."

Before exploring these implications in future posts, we need to take a more critical look at the evidence. The authors at TREE claim that nothing has been shown, and that the results are more likely to be due to selection. What is the status of this alternative hypothesis?

---

Cowperthwaite, M.C., Meyers, L.A. (2007) How Mutational Networks Shape Evolution: Lessons from RNA Models. Annual Review of Ecology, Evolution, and Systematics 38:203-230.[doi.org/10.1146/annurev.ecolsys.38.091206.095507]

Couce A., Rodríguez-Rojas A., and Blázquez J. (2015) Bypass of genetic constraints during mutator evolution to antibiotic resistance. Proc. Biol. Sci. Apr 7;282(1804):20142698 [doi: 10.1098/rspb.2014.2698]

Liu, C., Leighow, S., Inam, H., Zhao, B., and Pritchard, J.R. (2019) Exploiting the 'survival of the likeliest' to enable evolution-guided drug design. bioRxiv 557645; [doi: 10.1101/557645]

MacLean R.C., Perron G.G., and Gardner A. (2010) Diminishing returns from beneficial mutations and pervasive epistasis shape the fitness landscape for rifampicin resistance in Pseudomonas aeruginosa. Genetics 186: 1345-1354. [doi: 10.1534/genetics.110.123083]

Payne J.L., Menardo F., Trauner A., Borrell S., Gygli S.M., Loiseau C., et al. (2019) Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis. PLoS Biol 17(5): e3000265. [doi: 10.1371/journal.pbio.3000265]

Rokyta DR, Joyce P, Caudle SB, Wichman HA. (2005) An empirical test of the mutational landscape model of adaptation using a single-stranded DNA virus. Nat Genet 37:441-444. [https://doi.org/10.1038/ng1535]

Sackman, A.M., McGee, L.W., Morrison, A.J., Pierce, J., Anisman, J., Hamilton, H., Sanderbeck, S., Newman, C., and Rokyta, D.R. (2017) Mutation-Driven Parallel Evolution during Viral Adaptation. Mol. Biol. Evol. 34:3243-3253. [doi: 10.1093/molbev/msx257]

Simpson GG. (1967) The Meaning of Evolution. New Haven, Conn.: Yale University Press.

Stoltzfus, A. and McCandlish, D.M. (2017) Mutational Biases Influence Parallel Adaptation, Molecular Biology and Evolution 34:2163–2172, [doi: 10.1093/molbev/msx180]

Stoltzfus, A. (2019) Understanding bias in the introduction of variation as an evolutionary cause. [https://arxiv.org/abs/1805.06067]

Storz J.F., Natarajan C., Signore A.V., Witt C.C., McCandlish D.M. and Stoltzfus A. (2019) The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function. Phil. Trans. R. Soc. B [doi: 10.1098/rstb.2018.0238]

Reactionary fringe meets mutation-biased adaptation: Introduction

This is the first of a series of guest posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution.

---

Reactionary fringe meets mutation-biased adaptation: Introduction
by Arlin Stoltzfus
Theoreticians often formulate mathematical or computational models with the aim of exploring (or justifying) behavior anticipated from pre-existing verbal theories.  Yet, the resulting formalisms may exhibit behavior that was not expected.  Indeed, sometimes the model breaks the theory.

Reactionary fringe meets mutation-biased adaptation
Introduction
1. The empirical case
2. Some objections addressed
3. The causes and consequences of biases in the introduction process
4. What makes this new?
5. Beyond the "Synthesis" debate
    -Thinking about theories
    -Modern Synthesis of 1959
    -How history is distorted
    -Taking neo-Darwinism
      seriously
    -Synthesis apologetics
6. What "limits" adaptation?
7. Going forwardIn the 1970s, deterministic chaos was recognized in a number of dynamic models, including the Lotka-Volterra model used by ecologists for decades to illustrate notions of control via feedbacks between predator and prey abundance.  Depending on the delay in feedback, the system either oscillates predictably, crashes, or becomes chaotic.

Before the chaotic realm was named, characterized, and publicized, surely many researchers stumbled upon it, either when looking at data, or while working out numeric examples.  However, this did not elicit the phrase "Eureka!  I have discovered deterministic chaos!"  Chaotic dynamics did not fit with ideas about "control" or "feedback."  It existed in the world of nature but not in the world of science, even though it involves no new underlying processes.

In evolutionary genetics, the breeder's equation for change in a quantitative trait under selection once justified neo-Darwinism: invoking selection as the creative principle and source of direction in evolution had a rigorous mathematical basis, given abundant infinitesimal variation, and assuming that everything is a continuous trait (see Gould's excellent, well documented analysis in Ch. 4 of Ever Since Darwin, or ca. p. 140 of his 2002 book The Structure of Evolutionary Theory).

What Darwinism means for Ernst Mayr (Mayr and Provine 1980 p. 3).



Yet, after Lande and Arnold (1983) derived the multivariate generalization of quantitative genetics for the simultaneous change in multiple traits, Δz = Gβ, quantitative geneticists began to acknowledge that, in the words of Steppan, Phillips and Houle (2002) "Together with natural selection (the adaptive landscape), [the G matrix] determines the direction and rate of evolution." This new verbal theory, in which the rate and direction of evolution are jointly attributed to selection and standing variation, does not correspond to the old verbal theory, even though quantitative genetics is the branch of mathematical theory most closely aligned with neo-Darwinism, literally assuming abundant infinitesimal variation in every trait.

That is, Darwin's verbal theory led to Fisher's mathematical theory, then further developments along with empirical results (e.g., Schluter, 1996)) led to conflicts with the original verbal theory. As a result, quantitative genetics now tells us something different: the verbal theory of selection as a governing principle or independent shaping force, invoked by generations of neo-Darwinians, is mathematically impossible.

This series of posts relates to another unexpected twist that arises from another archaic ruling-principle theory: the view that the course of evolution largely reflects innate tendencies that shape variation, with selection playing only a minor role, traditionally known as orthogenesis.

A classic argument from Fisher and Haldane (based on their mutation-selection balance equation) says that variation-induced trends cannot be a cause of direction: for mutation to overcome the opposing force of selection would require abnormally high mutation rates. Mutation biases can influence neutral evolution, but otherwise, the only kind of bias that could possibly be influential is an absolute constraint distinguishing possible from impossible variants.

Yet Yampolsky and Stoltzfus (2001) used computer simulations of a simple 2-locus model, along with mathematical formulas based on origin-fixation dynamics, to show how parallelisms and trends may arise from mutational and developmental biases in variation, without requiring neutral evolution, absolute constraints, or high mutation rates.

We will delve into this theory later. For now, the important thing to note is the crucial prediction that the changes involved in adaptation may show the effects of modest quantitative biases in mutations with ordinary rates (e.g., transition-transversion bias in nucleotide substitution mutations).

When this theory was proposed, data on molecular changes involved in adaptation were rare—not sufficient to support statistical hypothesis-testing. In recent years, the data have become much more abundant, and we are seeing the predicted effect in both experimental adaptation (e.g. MacLean, et al. (2010), Couce, et al. (2015), Sackman, et al. (2017)), and more importantly, in retrospective analyses of natural adaptation (e.g., Payne, et al. (2019), Storz, et al. (2019), Liu, et al. (2019), and Stoltzfus and McCandlish (2017)).

That is, we are witnessing the establishment of a fundamental new principle of evolution, a principle that was not just unexpected, but rejected by the architects of the Modern Synthesis.

Thus, it was an odd choice for Trends in Ecology and Evolution (TREE) to publish a deeply deceptive article that attacks this new idea, from a pair of authors so unfamiliar with the topic that they literally mis-define "mutation bias." According to the authors, there are no new principles here, only "standard evolutionary theory" from Fisher, Haldane and Kimura. The appearance of mutation-biased adaptation is illusory, they argue, claiming that the evolutionary biases are due to selection.

What motivated such a gratuitous attack? A colleague who described the paper as "an abomination" assigned it to one of his advisees to study as an example of what a really bad paper looks like. How did it get published? Why didn't the editor get critical reviews?

The answers relate to a dispute between advocates of an "Extended Evolutionary Synthesis" or EES, and defenders of a re-branded version of the Modern Synthesis called SET (Standard Evolutionary Theory). The authors of the hatchet piece are members of a fringe movement dedicated to arguing that (1) SET automagically updates itself to include valid new thinking, and (2) there is no valid new thinking, because anything that seems new actually traces back to important dead people. Thus, these guardians of orthodoxy were obliged to undermine the novelty and importance of mutation-biased adaptation, while at the same time claiming it for SET.

This peculiar set of circumstances—an unorthodox theory, powerful new results, and the backlash from reactionaries—defines a series of posts that Larry has offered to host here on SandWalk. The plan for the series is as follows:

1. The empirical case. Results from adaptation in the lab, and retrospective analyses of adaptation in nature, show that the changes involved in adaptation are enriched for mutationally-favored changes.
2. Some objections addressed. The evidence now available rules out the possibility that the observed evolutionary biases are due to a cryptic bias in fitness that happens to align with the mutational bias.
3. The causes and consequences of biases in the introduction process. The theory of Yampolsky and Stoltzfus (2001) addresses mutation biases, developmental biases, and effects of connectivity of genetic networks (invoked in the self-organization literature)
4. What makes this theory new. For a very long time, mutation-biased adaptation was not anticipated, due to the "gene pool" assumption that evolution begins with standing variation.
5. A diversion into the EES-SET culture war. Issues relevant to navigating high-level disputes in evolutionary biology are addressed in a series of 4 posts.
   5.1. Thinking about theories.
   5.2. The Modern Synthesis (1959 - 1969).
   5.3. The abuse of history.
   5.4. Synthesis sophistry.
6. What "limits" adaptation? What makes adaptation something other than an ideal process in which the best genotype arises in infinite time after all possibilities have been tested?
7. Future directions. Abundant opportunities exist to build a broader empirical and theoretical understanding of the evolutionary role of biases in the introduction of variation, and to leverage this role in evolutionary inference.

The posts will be released every few days, and will be linked in to this Introduction page (so you can bookmark this).

So, please join in the discussion, and invite your colleagues to do the same.

Next post: Reactionary fringe meets mutation-biased adaptation. 1. The empirical case.

---

Couce A., Rodríguez-Rojas A., and Blázquez J. (2015) Bypass of genetic constraints during mutator evolution to antibiotic resistance. Proc. Biol. Sci. Apr 7;282(1804):20142698 [doi: 10.1098/rspb.2014.2698]

Lande, R., and Arnold, S.J. (1983) The measurement of selection on correlated characters. Evolution, 37:1210-1226. [doi: 10.1111/j.1558-5646.1983.tb00236.x]

Liu, C., Leighow, S., Inam, H., Zhao, B., and Pritchard, J.R. (2019) Exploiting the 'survival of the likeliest' to enable evolution-guided drug design. bioRxiv 557645; [doi: 10.1101/557645]

MacLean R.C., Perron G.G., and Gardner A. (2010) Diminishing returns from beneficial mutations and pervasive epistasis shape the fitness landscape for rifampicin resistance in Pseudomonas aeruginosa. Genetics 186: 1345-1354. [doi: 10.1534/genetics.110.123083]

Payne J.L., Menardo F., Trauner A., Borrell S., Gygli S.M., Loiseau C., et al. (2019) Transition bias influences the evolution of antibiotic resistance in Mycobacterium tuberculosis. PLoS Biol 17(5): e3000265. [doi: 10.1371/journal.pbio.3000265]

Sackman, A.M., McGee, L.W., Morrison, A.J., Pierce, J., Anisman, J., Hamilton, H., Sanderbeck, S., Newman, C., and Rokyta, D.R. (2017) Mutation-Driven Parallel Evolution during Viral Adaptation. Mol. Biol. Evol. 34:3243-3253. [doi: 10.1093/molbev/msx257]

Schluter, D. (1996) Adaptive radiation along genetic lines of least resistance. Evolution, 50:1766-1774. [doi: 10.1111/j.1558-5646.1996.tb03563.x]

Steppan, S.J., Phillips, P.C., and Houle, D. (2002) Comparative quantitative genetics: evolution of the G matrix. Trends in Ecology & Evolution, 17:320-327. [doi: 10.1016/S0169-5347(02)02505-3]

Stoltzfus, A. and McCandlish, D.M. (2017) Mutational Biases Influence Parallel Adaptation, Molecular Biology and Evolution 34:2163–2172, [doi: 10.1093/molbev/msx180]

Storz J.F., Natarajan C., Signore A.V., Witt C.C., McCandlish D.M. and Stoltzfus A. (2019) The role of mutation bias in adaptive molecular evolution: insights from convergent changes in protein function. Phil. Trans. R. Soc. B [doi: 10.1098/rstb.2018.0238]

The Evolutionary Synthesis: Perspectives on the Unification of Biology E. Mayr and W.B. Provine eds Harvard University Press, Cambridge MA, USA (1980)

Yampolsky, L.Y., and Stoltzfus, A. (2001) Bias in the introduction of variation as an orienting factor in evolution. Evolution & development, 3:73-83. [doi: 10.1046/j.1525-142x.2001.003002073.x]

My father on D-Day: 75 years ago

Today is the 75th anniversary of D-Day—the day British, Canadian, and American troops landed on the beaches of Normandy.¹

For us baby boomers it always meant a day of special significance for our parents. In my case, it was my father who took part in the invasions. That's him on the right as he looked in 1944. He was an RAF pilot flying rocket-firing typhoons in close support of the ground troops. His missions were limited to quick strikes and reconnaissance during the first few days of the invasion because Normandy was at the limit of their range from southern England. During the second week of the invasion (June 14th) his squadron landed in Crepon, Normandy and things became very hectic from then on with several close support missions every day [see Hawker Hurricanes and Typhoons in World War II].

The frequency of splicing errors reflects the balance between selection and drift

Splice variants are very common in eukaryotes. We know that it's possible to detect dozens of different splice variants for each gene with multiple introns. In the past, these variants were thought to be examples of differential regulation by alternative spicing but we now know that most of them are due to splicing errors. Most of the variants have been removed from the sequence databases but many remain and they are annotated as examples of alternative splicing, which implies that they have a biological function.

I have blogged about splice variants many times, noting that alternative splicing is a very real phenomenon but it's probably restricted to just a small percentage of genes. Most of splice variants that remain in the databases are probably due to splicing errors. They are junk RNA [The persistent myth of alternative splicing].

The ongoing controversy over the origin of splice variants is beginning to attract attention in the scientific literature although it's fair to say that most scientists are still unaware of the controversy. They continue to believe that abundant alternative splicing is a real phenomenon and they don't realize that the data is more compatible with abundant splicing errors.

Some molecular evolution labs have become interested in the controversy and have devised tests of the two possibilities. I draw your attention to a paper that was published 18 months ago.

Are multiple transcription start sites functional or mistakes?

If you look in the various databases you'll see that most human genes have multiple transcription start sites. The evidence for the existence of these variants is solid—they exist—but it's not clear whether the minor start sites are truly functional or whether they are just due to mistakes in transcription initiation. They are included in the databases because annotators are unable to distinguish between these possibilities.

Let's look at the entry for the human triosephosphate isomerase gene (TPI1; Gene ID 7167).

The correct mRNA is NM_0003655, third from the top. (Trust me on this!). The three other variants have different transcription start sites: two of them are upstream and one is downstream of the major site. Are these variants functional or are they simply transcription initiation errors? This is the same problem that we dealt with when we looked at splice variants. In that case I concluded that most splice variants are due to splicing errors and true alternative splicing is rare.

What is the dominant view of junk DNA?

I think that about 90% of our genome is junk and I know lots of other scientists who feel the same way. I'm pretty sure that this view is not shared by the majority of scientists but I don't know whether they are convinced that most of our genome is functional or whether they just think the question is unanswerable at the present time. I suspect that the latter view is more common but I'd like to hear your opinion.

Yeast loses its introns

Baker’s yeast (Saccharomyces cerevisiae) is one of the best studied eukaryotes. Its genome is just slightly larger than the largest bacterial genome and it was the first eukaryotic genome to be sequenced (Mewes at al., 1997). It has about 7000 genes in total and 6,604 of these genes are protein-coding genes but only 280 of these genes contain introns.¹ The rest have lost their introns over the course of several hundred million years of evolution (Hooks et al., 2014).

We know that introns have been lost in yeast because the genes of related species have lots of introns. The common ancestor of all fungi undoubtedly had genes with multiple introns because the available evidence indicates that introns invaded eukarotic genes very early in the evolution of eukaryotes. The fact that most introns have been purged from the yeast genome suggests that introns are not essential for gene function. In other words, introns are mostly junk.²

What happens when twins get their DNA tested?

The Canadian Broadcastng Company (CBC) has a TV show called Marketplace that promotes itself as an advocate of consumers' rights. It has a history of testing the claims of advertisers and usually shows that these claims are misleading or false. Here's what they say on their website.

On air since 1972, Marketplace is Canada’s consumer watchdog. We get the goods to help you shop smarter and protect yourself from slick scams and misleading marketing claims. We investigate the products and services we all use every day and push companies and government for answers. And we expose the truth on stories that matter to you and your family.

Most popular Sandwalk posts of 2018

Blogging was light last year because I was busy with other things and because the popularity of blogs is declining rapidly. The most popular post, based on the number of views, garnered only 9229 views, which is more than the most popular post of 2017 but only half as much as the most popular post of 2016. The post with the most comments (53) has almost 10X fewer comments than posts from a few years ago but that's partly because more people are commenting on Facebook and because I'm restricting blog comments in various ways.

On the accuracy of Ancestry.com DNA predictions

I'm very impressed with the DNA test administered by Ancestry.com. They report that I have over 600 fourth cousins or closer but I have confirmed some even more distant relationships. See below for the most distant relationship that the DNA tests reveal.

In the vast majority of cases the people who share DNA markers with me have no family tree that's on Ancestry.com so it's impossible to say for sure whether we are related. There are often clues based on who else shares our haplotypes but unless the person reveals their name and some of their ancestors that's all I can do. I usually contact those people who could hep me sort out some unknown relationships but I rarely get a reply.

Most popular Sandwalk posts of 2017

I was looking at some of my posts from the past few years and wondered which ones were the most popular. I had previously identified the most popular post of 2016 but not the most popular ones from 2017 so here they are.

The one with the most views (7481) is a link to a video by Michio Kaku who tells us that humans have stopped evolving [Another physicist teaches us about evolution].

The one with the most comments (259) is a post about my attempts to teach a creationist about glycolysis and evolution [Trying to educate a creationist (Otangelo Grasso)].

The post that I'm most proud of is: Historical evolution is determined by chance events

---

My DNA story

This is the latest update from Ancestry.com. Their algorithms are getting better and better. This corresponds very closely to what I know of my ancestors.

---

Alternative splicing in the nematode C. elegans

The importance of alternative splicing is highly controversial. In the case of humans, the competing views are: (a) more than 90% of human protein-coding genes are alternatively spliced to produce multiple protein isoforms, and (b) less than 10% of human genes are alternatively spliced and most of the splice variants detected are due to splicing errors.

In addition to this fundamental difference in how to interpret the data, there's a controversy over the meaning and significance of abundant alternative splicing, assuming that it exists. The consensus view among the workers in the field is that alternative splicing is ubiquitous and it explains why humans are so complex when they have only the same number of genes as "lower" species like the nematode C. elegans. This was the view expressed by Gil Ast in a 2005 Scientific American article on "The Alternative Genome."

The persistent myth of alternative splicing

I'm convinced that widespread alternative splicing does not occur in humans or in any other species. It's true that the phenomenon exists but it's restricted to a small number of genes—probably fewer than 1000 genes in humans. Most of the unusual transcripts detected by modern technology are rare and unstable, which is consistent with the idea that they are due to splicing errors. Genome annotators have rejected almost all of those transcripts.

You can see links to my numerous posts on this topic at: Alternative splicing and the gene concept and Are splice variants functional or noise?.

The textbook view of alternative splicing

As most of you know, I'm interested in the problem of alternative splicing. I believe that the number of splice variants that have been detected is perfectly consistent with the known rate of splicing errors and that there's no significant evidence to support the claim that alternative splicing leading to the production of biologically relevant protein variants is widespread. In fact, there's plenty of evidence for the opposite view; namely, splicing errors (lack of conservation, low abundance, improbable protein predictions, inability to detect the predicted proteins).

My preferred explanation is definitely the minority view. What puzzles me is not the fact that the majority is wrong () but the fact that they completely ignore any other explanation of the data and consider the case for abundant alternative splicing to be settled.