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Climbing Mount Probable: Mutation As a Cause of Nonrandomness in Evolution

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Climbing Mount Probable: Mutation As a Cause of Nonrandomness in Evolution Journal of Heredity 2009:100(5):637–647 Ó The American Genetic Association. 2009. All rights reserved. doi:10.1093/jhered/esp048 For permissions, please email: [email protected]. Advance Access publication July 22, 2009 Climbing Mount Probable: Mutation as a Cause of Nonrandomness in Evolution ARLIN STOLTZFUS AND LEV Y. YAMPOLSKY From the Center for Advanced Research in Biotechnology, Rockville, MD 20850 (Stoltzfus, Yampolsky); Biochemical Science Division, National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD (Stoltzfus); and Department of Biological Sciences, East Tennessee State University, Johnson City, TN 37614-1710 (Yampolsky). Address correspondence to: Arlin Stoltzfus, Center for Advanced Research in Biotechnology, Rockville, MD 20850, or e-mail: [email protected]. Abstract The classic view of evolution as ‘‘shifting gene frequencies’’ in the Modern Synthesis literally means that evolution is the modulation of existing variation (‘‘standing variation’’), as opposed to a ‘‘new mutations’’ view of evolution as a 2-step process of mutational origin followed by acceptance-or-rejection (via selection and drift). The latter view has received renewed attention, yet its implications for evolutionary causation still are not widely understood. We review theoretical results showing that this conception of evolution allows for a role of mutation as a cause of nonrandomness, a role that could be important but has been misconceived and associated misleadingly with neutral evolution. Specifically, biases in the introduction of variation, including mutational biases, may impose predictable biases on evolution, with no necessary dependence on neutrality. As an example of how important such effects may be, we present a new analysis partitioning the variance in mean rates of amino acid replacement during human–chimpanzee divergence to components of codon mutation and amino acid exchangeability. The results indicate that mutational effects are not merely important but account for most of the variance explained. The challenge that such results pose for comparative genomics is to address mutational effects as a necessary part of any analysis of causal factors. To meet this challenge requires developing knowledge of mutation as a biological process, understanding how mutation imposes propensities on evolution, and applying methods of analysis that incorporate mutational effects. Key words: evolution, genomics, mutation bias, population genetics Climbing Mount Probable step. The consequences seem intuitively obvious: The trajectory of the climber will be biased, not just upward, but Imagine, as a metaphor for evolution, a climber operating on to the left as well. Because the probability of proposal would the jagged and forbidding landscape of Les Drus (Figure 1). be greater on the left, the joint probability of proposal-and- A human climber would scout a path to a peak and plan acceptance would be greater (on average). If the landscape is accordingly, but a metaphor for evolution must disallow rough, the climber will tend to get stuck on a local peak that foresight and planning; therefore, let us imagine a blind is upward and to the left of its starting point. If the landscape robotic climber. The climber will move by a 2-step mecha- is perfectly smooth—a geometrical cone with a single nism. In the ‘‘proposal’’ step, the robotic climber reaches out peak—the climber will spiral upward and to the left until with one of its limbs to sample a point of leverage, some the peak is reached. nearby handhold or foothold. Each time this happens, there is Either way, one may recognize that the dual causation some probability of a second ‘‘acceptance’’ step, in which the inherent in the 2-step climbing algorithm allows for 2 com- climber commits to the point of leverage, shifting its center ponents of the climber’s trajectory that, in this imaginary case, of mass. Biasing the second step, such that relatively higher are separable: an upward bias caused by the bias in the points of leverage have relatively higher probabilities of ac- acceptance step and a lateral bias caused by the bias in the ceptance, causes the climber to ascend, resulting in a mecha- proposal step. In order to predict or explain the climber’s nism, not just for moving, but for climbing. overall path, one must take into account both causes, for What happens if a bias is imposed on the first step, the example, it would be incorrect to attribute the entire trajectory proposal step? Imagine that the robotic climber (perhaps by to the acceptance step. virtue of longer or more active limbs on one side) samples This metaphor of Climbing Mount Probable has the more points on the left than on the right during the proposal fascinating implications that 1) intrinsic biases in variation 637 Downloaded from https://academic.oup.com/jhered/article-abstract/100/5/637/782212/Climbing-Mount-Probable-Mutation-as-a-Cause-of by University of Zurich user on 27 September 2017 Journal of Heredity 2009:100(5) seen as a weak force opposed effectively by selection, given that mutation rates are so low (Yampolsky and Stoltzfus 2001; Stoltzfus 2006b). This view suggests that an effect of mutation would depend on special conditions such as unnaturally high rates of mutation, or absence of selection, that is, neutral evolution. Indeed, the research literature associates mutation-biased evolution with neutral evolution (Sueoka 1988; Gillespie 1991; Wolfe 1991; Gu et al. 1998; Lafay et al. 1999; Knight et al. 2001). To this classic conception of mutation as a weak ‘‘force,’’ we may add a quite different notion of individual mutation events as a source ‘‘chance’’ or ‘‘contingency’’ that ‘‘can cause unpredictability’’ (Johnson et al. 1995) as in Monod (1972), Gould (1989), Mani and Clarke (1990), Lenski and Travisano (1994), and Wahl and Krakauer (2000). Figure 1. Les Drus, a mountain in France that is particularly By contrast, the metaphor of Climbing Mount Probable rugged, with many local peaks (copyright Guillaume Dargaud, suggests a predictable effect of a bias in the proposal step used by permission). (mutation) that does not depend on neutrality or high mutation rates. Thus, to distinguish this way of thinking are fundamental causes of direction and that 2) by dual from pressure and chance (and also the classic idea of causation, adaptive evolution can be—simultaneously— mutation as a source of ‘‘fuel’’ or ‘‘raw materials’’), the key is both an adaptive process of fitting to conditions and an to look for a predictable effect of a bias in mutation for the expression of intrinsic propensities of change. case of beneficial (not neutral) changes, where new Are such effects important in evolution? To answer this mutations can occur. question requires more than just understanding a metaphor. The simplest possible model must allow for 2 types of First, it must be shown that the metaphor of Climbing alleles that are absent initially, so that a bias in their rates of Mount Probable faithfully conveys the operation of some introduction may be imposed. At minimum, then, one may proper cause defined, not metaphorically, but in biological consider a haploid 2-locus 2-allele model in which an initial terms, that is, something that can be shown theoretically population of ab individuals is subject to mutations that with a population-genetic model, or demonstrated experi- introduce genotypes Ab and aB at 2 different rates. For mentally with a model system. Below we review the fixations to occur, these mutations could be either neutral or conceptual and theoretical basis (Yampolsky and Stoltzfus beneficial, but as the present goal is to address selective allele 2001; Stoltzfus 2006a, 2006b) for recognizing mutational fixations, they must be beneficial. Of interest is the nontrivial bias in the introduction of variants as a cause of case in which the alternative genotype of relatively higher nonrandomness. fitness is introduced by mutation at the relatively lower rate. Second, one must have evidence that the postulated Figure 2 (inset) shows a genetic model of this type. Choosing cause operates in the natural world, and furthermore, Ab arbitrarily as the alternative genotype of higher fitness, accounts for effects that are important rather than trivial. the fitnesses of Ab and aB would be 1 þ s1 and 1 þ s2, Here, we present 2 narrow but compelling examples, the respectively, with s1 . s2 . 0, whereas the mutation rates first one showing that mutation bias is important in (from ab) would be l1 and l2, respectively, with l1 , l2. determining the course of experimental evolution in a case Of interest for a given set of conditions is the bias in (Rokyta et al. 2005) that is clearly adaptive, and the outcomes, that is, the number of times the population second—a new statistical analysis of sequence evolution— evolves to the mutationally favored peak (aB), divided by the showing that mutation is not just a significant factor, but the number of times it evolves to the peak of highest fitness most important known factor accounting for variance in (Ab). For convenience, the inequality in fitness of Ab and aB propensities of amino acid replacement. is defined as a bias in selection coefficients, K 5 s1/s2, with the bias in mutation defined oppositely as B 5 l2/l1. Figure 2 shows the bias in outcomes as a function of From Metaphor to Model mutation bias B for various population sizes. Clearly, the bias in outcomes increases as a function of the bias in Can mutation impose a bias or be a cause of direction in mutation. The dependence is linear through most of the evolution, and if so, how? In the classic view of the Modern range examined. Wherever the bias in outcomes exceeds 1, Synthesis, ‘‘evolution’’ is defined as shifting the frequencies mutation bias may be said to determine the predominant of genes in the ‘‘gene pool,’’ which maintains an abundance direction of evolution.
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