The definition of “mutation bias”
Mutation bias: a systematic difference in rates of occurrence for different types of mutations, e.g., transition-transversion bias, insertion-deletion bias
Brandolini’s law: it takes 10 times the effort to debunk bullshit as to generate it
If I were to misdefine “negative selection” or “G matrix”, evolutionary biologists would go nuts because theories and results that are familiar would be messed up by a wrong definition. Likewise, a wrong definition of mutation bias is obvious to those of us who are actual experts, because it induces contradictions and errors in things we know and care about.
The actual usage of “mutation bias” by scientists is broadly consistent with a systematic difference in rates of occurrence for different types of mutations and is not consistent with a forward-reverse bias or with heterogeneity in rates of mutation for different loci or sites. To demonstrate this, here is a simple table showing which meanings fit with actual scientific usage, starting with the 3 types of mutation bias invoked most commonly in PubMed (based on my own informal analysis), and continuing with some other examples. The last two refer to the literature of quantitative genetics, which occasionally makes reference to bias in mutational effects on quantitative traits (either on total variability, or on the direction of effects).
|Effect called a “mutation bias” in the literature||Heterogeneity per locus (or site)||Forward-reverse asymmetry||Systematic diff in rates for diff types|
|Male mutation bias||No||No||Yes|
|pattern in Monroe, et al (2022)||Yes*||No||Yes|
|Insertion or deletion bias||No||Yes||Yes|
|Diffs in mutational variability of traits||Possibly||No||Yes|
|Asymmetric effect on trait value||No||Possibly||Yes|
How does one concept of “mutation bias” cover such heterogeneity? Every mutation has a “from” and a “to” state, i.e., a source and a destination. A variety of different genetic and phenotypic descriptors can be applied to these “from” and “to” states, which means that we can define many different categories or types of mutations. Different applications of the concept of mutation bias always refer to types whose rates differ predictably, but there are many different ways of defining types, so there are many different possible mutation biases.
Let’s consider transition-transversion bias, GC vs. AT bias, and male mutation bias. The first is defined relative to the chemical categories of purine (A or G) and pyrimidine (C or T): we apply these categories to the source and destination states, and if they are in the same category, that is a transition, otherwise it is a transversion. The second example, GC/AT bias, is based on whether the shift from the “from” to the “to” increases or decreases GC content. This can be defined either as a forward-reverse asymmetry, or as a difference in mutability of the “from” state, e.g., if A and T are simply more mutable than G and C, the result is a net bias toward GC. In the case of male mutation bias, the categories of mutation are defined by whether the “from” context is male or female.
Note that transition-transversion bias is not a site-wise bias: every nucleotide site is the same in the sense of having 1 transition and 2 transversions (one blue arrow and 2 red arrows in the figure above). Also, transition bias is not a forward-reverse bias, but a difference between two types of fully reversible rates, e.g., under transition bias, the transitions A —> G and G —> A both have a higher rate than the transversions A —> T and T —> A. An insertion-deletion bias is a forward-reverse bias, but it is not a site-wise bias, in the sense that every site has the same set of possible insertions and deletions.
Thus, defining mutation bias as “differences between loci in mutation rates” (Svensson, 2022) is inconsistent with transition bias, GC/AT bias, and male mutation bias, the 3 most familiar and commonly invoked types of mutation bias in the scientific literature. The magnitude of this error is roughly the same as that of defining “genome” as the RNA molecules that store hereditary information. Some genomes are indeed made of RNA. We can imagine a novice RNA virus researcher, e.g., a summer student, who hears everyone in the lab talking about the “genome” which is RNA, and who assumes on this basis that all genomes are RNA, but no experienced scientist who has worked with a variety of organisms or read widely or attempted to teach students would make this kind of error of defining something in a way that excludes the most familiar cases.
Why is this called a “bias”? “Mutation bias” (“mutational bias”, “bias in mutation”) has been a term of art in molecular evolution for over half a century, since Cox and Yanofsky (1967). The term is perfectly apt and useful. A bias is a systematic or predictable asymmetry, and the term is most congenial when this asymmetry applies to categories with some structural symmetry, e.g., insertions vs. deletions. The term is used this way in various areas of science and engineering, e.g., a biased estimator in statistics is one that yields a systematically low or high estimate.
Nonetheless, some evolutionary biologists don’t want you to have this useful term in your vocabulary. Some will object that “bias” should be avoided because it implies an effect on fitness, but that is just because some people think everything is about fitness and want to restrict your language to force you into their belief system. Salazar-Ciudad rejects the use of “bias” on the grounds that it implies a background assumption of uniformity with no mechanistic justification.
Sadly, we also expect that traditionalists will dilute the concept of mutation bias as part of a cultural appropriation strategy that has gone completely off the rails in the past 20 years (see my blog on appropriation). That is, based on what we have seen here, here and in a recent anonymous review, traditionalists will undermine the distinctive concept of mutation bias by blurring it together with chance effects or heterogeneity, because this makes it easier to broaden the issue and claim it for tradition using “we have long known” arguments, e.g., “we have long known that mutation rates are not all the same” will be used to suggest that there is nothing new here.
The problem with this line of argument is that systematic and patterned differences in properties between classes of things are not the same thing as idiosyncratic or unpatterned heterogeneity among a set of items, and more importantly, what is novel is not the claim that mutation biases exist, but linking them theoretically and empirically with biases in evolutionary outcomes. More specifically, what is novel includes
- the emerging empirical proof of large and predictable effects of mutation biases on the changes involved in adaptation
- having a formal body of theory to leverage knowledge of mutation biases to make predictions about evolution including adaptative evolution
- how this formal body of theory creates an equivalence between mutational and developmental biases that was not known to exist
- how this theory provides a previously unrecognized causal grounding for ideas that used to be considered dubious or even heretical, including biases in variation causing directional trends, taxon-specific propensities, and a tendency for evolution to prefer intrinsically likely structures.
- the much broader theoretical recognition that including a rate-dependent process of introduction is a required post-Synthesis revision to our understanding of evolutionary dynamics
However, the traditionalists have a lot of power, which means that they can set the terms of debate and they can simply ignore arguments that work against them, or reframe things using straw-man arguments and excluded middle arguments, e.g., “we see nothing revolutionary with X” is utterly devoid of merit but has been an effective go-to argument for traditionalists in online discussions or when talking to reporters. It’s a very easy argument to make and can be applied using each of the claims of novelty above as the value of X. As a rhetorical device, it can be coupled very effectively with a misrepresentation of X that broadens it into something trivial, e.g., rather than saying
“we see nothing revolutionary with how this formal body of theory creates an equivalence between mutational and developmental biases that was not known to exist”
“we see nothing revolutionary with a theory that applies both to molecules and morphologies— we have long used such models”.
The defense of tradition often relies on fatuous arguments that broaden and trivialize new findings. Exploring them is a useful exercise to build awareness. I wish that reporters knew how to recognize this garbage.
By the way, Wikipedia gets the definition of mutation bias right. But many other sources get this wrong and say wrong things, e.g.,
- “Mutation bias. A pattern of mutation in DNA that is disproportional between the four bases, such that there is a tendency for certain bases to accumulate.” (Encyclopedia.com)
- “Mutation bias. Bias in the mutation frequencies of different codons, affecting the synonymous to nonsynonymous rate ratio. Mutation bias results in an accelerated rate of amino acid replacement in functionally less constrained regions.” [that statement is not true] (Oxford Reference)
And many sources simply do not define the term because it is not on the radar for most evolutionary biologists.
E. Cox and C. Yanofsky. Altered base ratios in the DNA of an Escherichia coli mutator strain. Proc. Natl. Acad. Sci. USA, 58:1895–1902, 1967.