Are introns mostly junk?

There are many reasons for thinking that introns are mostly junk DNA.

1. The size and sequence of introns in related species are not conserved and almost all of the sequences are evolving at the rate expected for neutral substitutions and fixation by drift.
2. Many species have lost introns or reduced their lengths drastically suggesting that the presence of large introns can be detrimental in some cases (probably large populations).
3. After decades of searching, there are very few cases where introns and/or parts of introns have been shown to be essential.
4. Researchers routinely construct intronless versions of eukaryotic genes and they function normally when re-inserted into the genome.
5. Intron sequences are often littered with transposon and viral sequences that have inserted into the intron and this is not consistent with the idea that intron sequences are important.
6. About 98% of the introns in modern yeast (Saccharomyces cerevisiae) have been eliminated during evolution form a common ancestor that probably had about 18,000 introns [Yeast loses its introns]. This suggests that there was no selective pressure to retain those introns over the past 100 million years.
7. About 245/295 of the remaining introns in yeast have been artificially removed by researchers who are constructing an artificial yeast genome suggesting that over 80% of the introns that survived evolutionary loss are also junk [Yeast loses its introns].

The evolution of citrate synthase

Citrate synthase [EC 2.3.3.1] is one of the key enzymes of the citric acid cycle. It catalyzes the joining of acetyl-CoA and oxaloacetate to produce citrate.

acetyl-CoA + H₂O + oxaloacetate → citrate + HS-CoA + H⁺

We usually think of this reaction in terms of energy production since acetyl-CoA is the end product of glycolysis and the citric acid cycle produces substrates that enter the electron transport system leading to production of ATP. However, it's important to keep in mind that the enzyme also catalyzes the reverse reaction.

The "standard" view of junk DNA is completely wrong

I was browsing the table of contents of the latest issue of Cell and I came across this ....

For decades, the miniscule protein-coding portion of the genome was the primary focus of medical research. The sequencing of the human genome showed that only ∼2% of our genes ultimately code for proteins, and many in the scientific community believed that the remaining 98% was simply non-functional “junk” (Mattick and Makunin, 2006; Slack, 2006). However, the ENCODE project revealed that the non-protein coding portion of the genome is copied into thousands of RNA molecules (Djebali et al., 2012; Gerstein et al., 2012) that not only regulate fundamental biological processes such as growth, development, and organ function, but also appear to play a critical role in the whole spectrum of human disease, notably cancer (for recent reviews, see Adams et al., 2017; Deveson et al., 2017; Rupaimoole and Slack, 2017).

Slack, F.J. and Chinnaiyan, A.M. (2019) The Role of Non-coding RNAs in Oncology. Cell 179:1033-1055 [doi: 10.1016/j.cell.2019.10.017]

Cell is a high-impact, refereed journal so we can safely assume that this paper was reviewed by reputable scientists. This means that the view expressed in the paragraph above did not raise any alarm bells when the paper was reviewed. The authors clearly believe that what they are saying is true and so do many other reputable scientists. This seems to be the "standard" view of junk DNA among scientists who do not understand the facts or the debate surrounding junk DNA and pervasive transcription.

Here are some of the obvious errors in the statement.

1. The sequencing of the human genome did NOT show that only ~2% of our genome consisted of coding region. That fact was known almost 50 years ago and the human genome sequence merely confirmed it.
2. No knowledgeable scientist ever thought that the remaining 98% of the genome was junk—not in 1970 and not in any of the past fifty years.
3. The ENCODE project revealed that much of our genome is transcribed at some time or another but it is almost certainly true that the vast majority of these low-abundance, non-conserved, transcripts are junk RNA produced by accidental transcription.
4. The existence of noncoding RNAs such as ribosomal RNA and tRNA was known in the 1960s, long before ENCODE. The existence of snoRNAs, snRNAs, regulatory RNAs, and various catalytic RNAS were known in the 1980s, long before ENCODE. Other RNAs such as miRNAs, piRNAS, and siRNAs were well known in the 1990s, long before ENCODE.

How did this false view of our genome become so widespread? It's partially because of the now highly discredited ENCODE publicity campaign orchestrated by Nature and Science but that doesn't explain everything. The truth is out there in peer-reviewed scientific publications but scientists aren't reading those papers. They don't even realize that their standard view has been seriously challenged. Why?

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The evolution of de novo genes

De novo genes are new genes that arise spontaneously from junk DNA [De novo gene birth]. The frequency of de novo gene creation is important for an understanding of evolution. If it's a frequent event, then species with a large amount of junk DNA might have a selective advantage over species with less junk DNA, especially in a changing environment.

Last week I read a short Nature article on de novo genes [Levy, 2019] and I think the subject deserves more attention. Most new genes in a species appear to arise by gene duplication and subsequent divergence but de novo genes are genes that are unrelated to genes in any other clade so we can assume that they are created from junk DNA that accidentally becomes associated with a promoter causing the DNA to be transcribed. A new gene is formed if the RNA acquires a function. If the transcript contains an open reading frame then it may be translated to produce a polypeptide and if the polypeptide performs a new function then the resulting de novo gene is a new protein-coding gene.

The important question is whether the evolution of de novo genes is a common event or a rare event.

How many protein-coding genes in the human genome? (2)

It's difficult to know how many protein-coding genes there are in the human genome because there are several different ways of counting and the counts depend on what criteria are used to identify a gene. Last year I commented on a review by Abascal et al. (2018) that concluded there were somewhere between 19,000 and 20,000 protein-coding genes. Those authors discussed the problems with annotation and pointed out that the major databases don't agree on the number of gene [How many protein-coding genes in the human genome?].

Gerald Fink promotes a new definition of a gene

This is the 2019 Killian lecture at MIT, delivered in April 2019 by Gerald Fink. Fink is an eminent scientist who has done excellent work on the molecular biology of yeast. He was director of the prestigious Whitehead Institute at MIT from 1990-2001. With those credentials you would expect to watch a well-informed presentation of the latest discoveries in molecular genetics. Wouldn't you?

Contingency, selection, and the long-term evolution experiment

I'm a big fan of Richard Lenski's long-term evolution experiment (LTEE) and of Zachary Blount's work in particular. [Strolling around slopes and valleys in the adaptive landscape] [On the unpredictability of evolution and potentiation in Lenski's long-term evolution experiment] [Lenski's long-term evolution experiment: the evolution of bacteria that can use citrate as a carbon source]

The results of the LTEE raise some interesting questions about evolution. The Lenski experiment began with 12 (almost) identical cultures and these have now "evolved" for 31 years and more than 65,000 generations. All of the cultures have diverged to some extent and one of them (and only one) has developed the ability to use citrate as a carbon source. Many of the cultures exhibit identical, or very similar, mutations that have reached significant frequencies, or even fixation, in the cultures.

Several other laboratory evolution experiments have been completed or are underway in various labs around the world. The overall results are relevant to a discussion about the role of contingency and accident in the history of life [see Evolution by Accident]. Is it true that if you replay the tape of life the results will be quite different? [Replaying life's tape].

Evolution by Accident

Evolution by Accident
v1.43 ©2006 Laurence A. Moran
This essay has been transferred here from an old server that has been decommissioned.Modern concepts of evolutionary change are frequently attacked by those who find the notions of randomness, chance, and accident to be highly distasteful. Some of these critics are intelligent design creationists and their objections have been refuted elsewhere. In this essay I'm more concerned about my fellow evolutionists who go to great lengths to eliminate chance and accident from all discussions about the fundamental causes of evolution. This is my attempt to convince them that evolution is not as predictable as they claim. I was originally stimulated to put my ideas down on paper when I read essays by John Wilkins [Evolution and Chance] and Loren Haarsma [Chance from a Theistic Perspective] on the TalkOrigins Archive.

The privilege of living beings is the possession of a structure and of a mechanism which ensures two things: (i) reproduction true to type of the structure itself, and (ii) reproduction equally true to type, of any accident that occurs in the structure. Once you have that, you have evolution, because you have conservation of accidents. Accidents can then be recombined and offered to natural selection to find out if they are of any meaning or not.
Jacques Monod (1974) p.394The main conclusion of this essay is that a large part of ongoing evolution is determined by stochastic events that might as well be called "chance" or "random." Furthermore, a good deal of the past history of life on Earth was the product of chance events, or accidents, that could not have been predicted. When I say "evolution by accident" I'm referring to all these events. This phrase is intended solely to distinguish "accidental" evolution from that which is determined by non-random natural selection. I will argue that evolution is fundamentally a random process, although this should not be interpreted to mean that all of evolution is entirely due to chance or accident. The end result of evolution by accident is modern species that do not look designed.

First complete sequence of a human chromosome

A paper announcing the first complete sequence of a human chromosome has recently been posted on the bioRxiv server.

Miga, K. H., Koren, S., Rhie, A., Vollger, M. R., Gershman, A., Bzikadze, A., Brooks, S., Howe, E., Porubsky, D., Logsdon, G. A., et al. (2019) Telomere-to-telomere assembly of a complete human X chromosome. bioRxiv, 735928. doi: [doi: 10.1101/735928]

Abstract: After nearly two decades of improvements, the current human reference genome (GRCh38) is the most accurate and complete vertebrate genome ever produced. However, no one chromosome has been finished end to end, and hundreds of unresolved gaps persist. The remaining gaps include ribosomal rDNA arrays, large near-identical segmental duplications, and satellite DNA arrays. These regions harbor largely unexplored variation of unknown consequence, and their absence from the current reference genome can lead to experimental artifacts and hide true variants when re-sequencing additional human genomes. Here we present a de novo human genome assembly that surpasses the continuity of GRCh38, along with the first gapless, telomere-to-telomere assembly of a human chromosome. This was enabled by high-coverage, ultra-long-read nanopore sequencing of the complete hydatidiform mole CHM13 genome, combined with complementary technologies for quality improvement and validation. Focusing our efforts on the human X chromosome, we reconstructed the ∼2.8 megabase centromeric satellite DNA array and closed all 29 remaining gaps in the current reference, including new sequence from the human pseudoautosomal regions and cancer-testis ampliconic gene families (CT-X and GAGE). This complete chromosome X, combined with the ultra-long nanopore data, also allowed us to map methylation patterns across complex tandem repeats and satellite arrays for the first time. These results demonstrate that finishing the human genome is now within reach and will enable ongoing efforts to complete the remaining human chromosomes.

How much of the human genome has been sequenced?

It's been more than seven years since I posted information on how much of the human genome has been sequenced [How Much of Our Genome Is Sequenced?]. At that time, the latest version of the human reference genome was GRCh37.p7 (Feb. 3, 2012) and 89.6% of the genome had been sequenced. It's time to update that information.

We have a pretty good idea of the size of the human genome based on quantitative Feulgen staining (1940-1980) and reassociation kinetic experiments from the 1970s (Morton, 1991). We can safely assume that the correct size of the human genome is close to 3,200,000,000 bp (3,200,000 kb, 3,200 Mb, 3.2 Gb) [How Big Is the Human Genome?]. That's the value cited most often in the literature. However, the actual values calculated by Morton (1991) were 3.227 Gb for the haploid female genome and less than that for the haploid male genome. The human reference genome contains all 22 autosomes plus one copy of the X chromosome and one copy of the Y chromosome. This gives a total of 3.286 Gb.

Reactionary fringe meets mutation-biased adaptation. 7. Going forward

This the last of a series of posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution. Arlin has established that the role of mutation in evolution is much more important than most people realize. He has also built a strong case for the influence of mutation bias. How should we incorporate these concepts into modern evolutionary theory?

Click on the links in the box (below) to see the other posts in the series.

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Reactionary fringe meets mutation-biased adaptation.
7. Going forward
by Arlin Stoltzfus
Haldane (1922) argued that, because mutation is a weak pressure easily overcome by selection, the potential for biases in variation to influence evolution depends on neutral evolution or high mutation rates. This theory, like the Modern Synthesis of 1959, depends on the assumption that evolution begins with pre-existing variation. By contrast, when evolution depends on the introduction of new variants, mutational and developmental biases in variation may impose biases on evolution, without requiring neutral evolution or high mutation rates.

Reactionary fringe meets mutation-biased adaptation. 5.5 Synthesis apologetics

This is part of a continuing series of posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution. In this post, Arlin explains how defenders of the Modern Synthesis react in the face of serious challenges to the theory that was formulated in the 1940s and 50s. Rather than reject the theory, they engage in various forms of "synthesis apologetics."

Click on the links in the box (below) to see the other posts in the series.

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Reactionary fringe meets mutation-biased adaptation. 5.6 Synthesis apologetics
by Arlin Stoltzfus

Reactionary fringe meets mutation-biased adaptation. 5.4. Taking neo-Darwinism seriously

This is part of a continuing series of posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution. In this post Arlin discusses his view of neo-Darwinism and why it is inconsistent with macromutations and lateral gene transfer. He equates neo-Darwinism with the Modern Synthesis (1959 version), a comparison that might be challenged. Click on the links in the box (below) to see the other posts in the series.

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Reactionary fringe meets mutation-biased adaptation. 5.4. Taking neo-Darwinism seriously
by Arlin Stoltzfus
The Modern Synthesis is often described as the result of combining Darwinism and genetics. This description, in my opinion, is concise and historically accurate: the Modern Synthesis of 1959 is a sophisticated attempt to arrange the pieces of population genetics to justify a neo-Darwinian dichotomy in which variation merely supplies raw materials, and selection is the source of initiative, creativity and direction.

Religion vs science (junk DNA): a blast from the past

I was checking out the science books in our local bookstore the other day and I came across Evolution 2.0 by Perry Marshall. It was published in 2015 but I don't recall seeing it before.

The author is an engineer (The Salem Conjecture) who's a big fan of Intelligent Design. The book is an attempt to prove that evolution is a fraud.

I checked to see if junk DNA was mentioned and came across the following passages on pages 273-275. It's interesting to read them in light of what's happened in the past four years. I think that the view represented in this book is still the standard view in the ID community in spite of the fact that it is factually incorrect and scientifically indefensible.

Reactionary fringe meets mutation-biased adaptation. 6. What "limits" adaptation?

This is part of a continuing series of posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution. In this post Arlin discusses the role of adaptation and what determines the pathway that it will take over time. Is it true that populations will always adapt quickly to any change in the environment? (Hint: no it isn't!) Click on the links in the box (below) to see the other posts in the series.

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Reactionary fringe meets mutation-biased adaptation.
6. What "limits" adaptation?
by Arlin Stoltzfus
According to the hatchet piece at TREE, theoretical considerations dictate that biases in variation are unlikely to influence adaptation, because this requires small population sizes and reciprocal sign epistasis.

Yet, we have established that mutation-biased adaptation is real (see The empirical case and Some objections addressed). If theoretical population genetics tells us that mutation-biased adaptation is impossible or unlikely, what is wrong with theoretical population genetics?

Adaptation, before Equilibrium Day

Reactionary fringe meets mutation-biased adaptation. 5.3. How history is distorted.

This is the ninth in a series of guest posts by Arlin Stoltzfus on the role of mutation as a dispositional factor in evolution. Click on the links in the box (below) to see the other post in the series.

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Reactionary fringe meets mutation-biased adaptation.
5.3. How history is distorted.
by Arlin Stoltzus
In his famous Materials for the Study of Variation, Bateson (1894) refers to natural selection as "obviously" a "true cause" (p. 5). Punnett (1905) explains that mutations are heritable while environmental fluctuations are not, concluding that "Evolution takes place through the action of selection on these mutations" (p. 53). De Vries begins his major 1905 English treatise by writing that ...

"Darwin discovered the great principle which rules the evolution of organisms. It is the principle of natural selection. It is the sifting out of all organisms of minor worth through the struggle for life. It is only a sieve, and not a force of nature" (p. 6)

Morgan (1916), in his closing summary, writes:

"Evolution has taken place by the incorporation into the race of those mutations that are beneficial to the life and reproduction of the organism" (p. 194)

Reactionary fringe meets mutation-biased adaptation. 5.2. The Modern Synthesis of 1959

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

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Reactionary fringe meets mutation-biased adaptation. 5.2. The Modern Synthesis of 1959
by Arlin Stoltfus
As we learned in What makes it new?, the newness of the effect of biases in the introduction process results from a classical assumption that evolution can be understood as a process of shifting the frequencies of existing alleles. How did this position emerge? Was it a technical, mathematical issue?

Reactionary fringe meets mutation-biased adaptation. 5.1. Thinking about theories

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

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Reactionary fringe meets mutation-biased adaptation. 5.1. Thinking about theories
by Arlin Stoltzfus
A wikipedia page disambiguating "Modern Synthesis" defines neo-Darwinism as

"the state-of-the-art in evolutionary biology, as seen at any chosen time in history from the 1890s to the present day."

Because "neo-Darwinism" and the "Synthesis" are conflated with whatever is widely accepted, they are now regularly attacked on grounds that are completely unrelated to genuine neo-Darwinism or the original Modern Synthesis, e.g., as when a network of life (rather than a tree) is invoked as a contradiction of Darwinism. The attack by Noble (2015) on the

"... conceptual framework of neo-Darwinism, including the concepts of "gene," "selfish," "code," "program," "blueprint," "book of life," "replicator" and ˜"vehicle."

is entirely a critique of late-20th-century reductionism à la Dawkins, and addresses neither neo-Darwinism (selection and variation as the potter and the clay), nor the original Modern Synthesis, which is simply not reductionistic, but positively invokes emergent phenomena (population-level forces, the gene pool as dynamic buffer) in the service of selection as a high-level governing principle.

"The state of the art" is a phrase that needs no modification. Nothing good can come from linking it to the name of a dead person.

Reactionary fringe meets mutation-biased adaptation. 5. Beyond the "Synthesis" debate

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

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Reactionary fringe meets mutation-biased adaptation. 5. Beyond the "Synthesis" debate
by Arlin Stoltzfus
The authors of TREE's hatchet piece imply that the theory of Yampolsky and Stoltzfus (2001) is somehow not new, citing ancient work from Dobzhansky and Haldane. In Box 1, they argue that this theory is part of "standard evolutionary theory," showing a 4-step derivation ending in Eqn IV, which is Eqn 2 of Yampolsky and Stoltzfus (2001), and informing the reader that this is based on "classical" results from Fisher, Haldane and Kimura, who are named, while Yampolsky and Stoltzfus are not named.

Yet, Fisher, Haldane, and Kimura did not make the argument in Box 1, did not follow the 4 steps, and did not derive Eqn IV!

Reactionary fringe meets mutation-biased adaptation. 4. What makes this new?

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

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Reactionary fringe meets mutation-biased adaptation. 4. What makes this new?
by Arlin Stoltzfus
Scientists value novelty because it signifies untapped potential: a new idea has not been interrogated, applied, and extended. The more novel an idea, the greater its potential to re-shape our discourse and advance our understanding beyond the well tried ideas of the past.

Reactionary fringe meets mutation-biased adaptation. 3. The causes and consequences of biases in the introduction process

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

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Reactionary fringe meets mutation-biased adaptation. 3. The causes and consequences of biases in the introduction process
by Arlin Stoltzfus
As discussed previously, mutation-biased adaptation occurs in the laboratory and in nature. In the cases that have been examined, modest several-fold mutational biases have modest several-fold effects on the changes involved in adaptation.

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 forwardHow can this happen? Classical thinking says that mutation is a weak pressure easily overcome by selection. This "opposing pressures" argument was invoked by Fisher (1930), Haldane (1933) and Wright (1931), as well as Huxley, Ford, Stebbins, Simpson and others. On this basis, it is assumed that the effects of mutation bias will be seen only in neutral evolution, where the opposing pressure of selection is absent, or with unusually high mutation rates.

Reactionary fringe meets mutation-biased adaptation. 2. Some objections addressed.

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

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Reactionary fringe meets mutation-biased adaptation. 2. Some objections addressed.
by Arlin Stoltzfus
In the previous post Part 1, we reviewed evidence from 8 analyses suggesting that modest several-fold biases in mutation may impose modest several-fold biases on the spectrum of changes involved in adaptation, including some legendary cases of natural adaptation.

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 forwardIs the evidence strong enough already to conclude in favor of a bold new idea? The authors of the hatchet piece at TREE believe that nothing has been shown, arguing that the proposed effect is theoretically unlikely and is probably due to selection.

The focus of this post is on alternative hypotheses (theoretical arguments will be addressed later). For the sake of brevity, I will address just 2 of the many spurious objections offered by these authors in their quest to exemplify the Dunning-Kruger effect. For instance, they write "we stress that parallel genetic change underlying phenotypic convergence is not sufficient evidence for mutation bias being important in causing such convergence."

This is an inversion of the argument, common in the parallelism literature (see Bailey, et al. 2015), that the recurrence of exactly the same change is by itself evidence of selection.

In fact, the case for mutation-biased adaptation does not depend on such weak inferences. In the 8 analyses we reviewed, no change is designated as adaptive solely based on a pattern of recurrence. Instead, each mutational path has either (1) a genetic association with fitness or resistance, or (2) an experimentally verified molecular effect consistent with the adaptive story. Once adaptive changes have been identified, statistical tests are applied to detect an excess of changes of the mutationally favored class.

As another example, TREE's hatchet piece refers to selection as an independent force of adaptation, then attacks the strawman theory of mutation bias as an independent force of adaptation. To ensure that the reader is deceived about mutation-biased adaptation, and ill disposed toward this line of research, this strawman is repeated 5 times on the first page (figure).

Both arguments illustrate how reactionary minds fail to grasp new ideas, and see only perversions or inversions of cherished old ideas.

Now, let us set aside strawman arguments, to focus on genuine alternatives.

For instance, the authors suggest that transitions could be favored "owing to selection on genomic base composition," citing work on GC content. This hypothesis can not work. If the effect of selection is to conserve GC content, this can not explain a bias toward transitions, because the universe of GC-conserving mutations has a transition:transversion ratio of 0. Likewise, if the effect of selection is to change GC content, this can not explain the observed degree of bias, because the universe of GC-changing amino acid replacement mutations has roughly a 1:1 transition:transversion ratio, not large enough to explain results of Payne, et al. (2019) or Stoltzfus and McCandlish (2017).

A more plausible alternative raised by the authors, following Stoltzfus and Norris (2016), is that the observed evolutionary bias could be caused by a bias in protein-level fitness effects that happens to align with the mutation bias, e.g., they suggest that "selectively beneficial transitions and selectively beneficial transversions could also have different distributions of fitness effects."

Let us consider, for the 8 analyses addressed previously, the hypothesis that observed evolutionary biases are not due to mutation bias at all, but to a cryptic fitness bias that happens to align with the mutation bias.

First, in the studies by MacLean, et al. (2010), Sackman, et al. (2017) and Liu, et al. (2019), the authors measure fitness (or resistance). The data from MacLean, et al. (2010) reveal no correlation of mutation rate with fitness (figure).

In their model of effects in drug-resistant tumors, Liu, et al. (2019) find that the mutational factor (estimated mutation rate) explains more variance than the fitness-related factor (measured drug resistance). Results of one-step adaptation from Sackman, et al. (2017) are shown in the figure (left: transitions are in light gray, transversions are in dark gray; upper scale is selection coefficient, lower scale is number of evolved lineages out of 20). Here the mean selection coefficients for transitions and transversions are 0.37 (CI 0.053) and 0.40 (CI 0.18), respectively, i.e., transversions are insignificantly better (data from their Table 1).

Next, consider the experimental study by Couce, et al. (2015) shown in the figure below (courtesy of Alex Couce). Among resistant mutants in PBP3, the resistant mutT isolates (blue) overwhelmingly have the kind of mutations favored by mutT (left box), and the resistant mutH isolates (red) overwhelmingly have the kind of mutations favored by mutH (center box; other types of mutations are in the right box, which includes most of the black isolates indicating a wild-type parent).

The only way to explain this as a fitness effect would be to argue that (1) the mutT and mutH genotypes have widespread, strong, and utterly distinct epistatic effects on the fitness landscape for PBP3, i.e., each mut genotype induces a distinct set of beneficial alleles, and (2) the corresponding mutations for those alleles just happen to be (overwhelmingly) the same type of mutation favored by the mutator.  This is wildly implausible because it implies that the blue-red segregation of columns in the figure above is accidental.

What about the meta-analyses of transition-transversion bias? Could there be a fitness advantage of transitions that explains this effect?

Stoltzfus and Norris (2016) analyzed data on 544 transitions and 695 transversions with experimentally measured fitness effects. Comparing various binary predictors, they considered the chance that a nominally conservative mutation is more fit than a nominally radical one, aka the AUC, which ranges from 0 to 1, with a null expectation of 0.5. Transition-transversion class is a weak predictor (AUC = 0.53, figure), out-performed by most biochemical factors, all 200 of which are out-performed by a conservative-radical distinction based on Tang's U (AUC = 0.64), an empirical measure of relative fixation probability computed from a large set of sequence alignments. Yet, the conservative-radical distinction from Tang's U corresponds to a mere 2.7-fold fixation bias in evolution. Using this relationship, Stoltzfus and Norris (2016) estimate that the transition:transversion distinction corresponds to a 1.3-fold fixation bias, with a confidence interval from 1.0 (no effect) to 1.6.

But these results use the entire distribution of mutations, including the worst ones that (in nature) would be removed by selection. Therefore, Stoltzfus and Norris (2016) truncated the data to see if a stronger benefit would emerge among benign mutations. Instead of getting stronger, the effect disappeared (their Fig. 1).

Next, Stoltzfus and Norris (2016) set aside the above data, and looked at an independent set of data from 4 studies of laboratory adaptation implicating 111 beneficial mutations with measured fitness effects. In the table below, the AUC value in the penultimate column is the chance that a transition is ranked higher than a randomly chosen transversion: the values are all < 0.5. That is, beneficial transitions rank slightly lower than beneficial transversions. The later study by Sackman, et al. (2017) (above) represents a 5th independent case in which beneficial transitions rank slightly lower than beneficial transversions.

Thus, available data, reflecting multiple lines of evidence, indicate that transitions simply do not have a fitness advantage that could explain a several-fold effect on amino acid changes in evolution.

Finally, note that Payne, et al. (2019) report evolutionary biases that cannot be explained by protein-level selection, including transition bias in non-coding changes, and the excess of Met-to-Ile transitions over Met-to-Ile transversions (which are twice as likely without mutation bias).

To summarize, in our evaluation of the cryptic-fitness-difference hypothesis, we find that: in 3 cases, the fitness effects were measured, with results that do not support the hypothesis; in 3 cases (counting 2 meta-analyses in Stoltzfus and McCandlish, 2017), the evidence indicates that the mutationally favored class (transitions) does not have a sufficient fitness advantage; in 1 case, the hypothesis is wildly implausible (Couce, et al., 2015); and in 1 remaining case, Storz, et al. (2019) invoke a mutational effect without any clear justification for assuming an absence of differential fitness effects.

Concluding thoughts

In recent years, systematic data have begun to accumulate on molecular changes implicated in phenotypic adaptation. The pattern emerging from these data is that the molecular changes implicated in adaptation are enriched for the kinds of changes that are favored by mutation, and this enrichment cannot be explained by a cryptic fitness bias that happens to align with the mutation bias.

We could treat this merely as a pattern, as a new and useful empirical generalization.

But there is much more to the story. Mutation-biased adaptation was predicted under a theory that contrasts sharply with classical thinking, which holds that internal tendencies of variation cannot cause evolutionary trends or biases, because mutation rates are too small: in order for mutation biases to be important, mutation rates must be very large, or the opposing pressure of selection must be absent, i.e., effects of biases in ordinary mutations will be limited to neutral evolution.

Yampolsky and Stoltzfus (2001) argued that this view, which derives from the mutation-selection balance model of Fisher and Haldane, assumes that evolution can be treated as a short-term process of shifting the frequencies of pre-existing alleles, without considering the (potentially biased) introduction of new alleles. Using a simple model, they showed that the efficacy of biases in introduction does not require absolute constraints, neutral evolution, or high mutation rates. They argued that this conclusion applies to developmental biases as well as mutation biases.

Thus, it is time to understand this theory, what it implies, and why it differs from classical thinking-- the topic of the next post in the series.

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Bailey SF, Blanquart F, Bataillon T, Kassen R. (2017). What drives parallel evolution?: How population size and mutational variation contribute to repeated evolution. Bioessays 39:1-9.[doi.org/10.1002/bies.201600176]

Couce A., RodrÃ-guez-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]

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]

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, Norris RW. (2016). On the Causes of Evolutionary Transition:Transversion Bias. Mol Biol Evol 33:595-602. [doi.org/10.1093/molbev/msv274]

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. 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.

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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?

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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.

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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.

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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]