The Evolution of Low Mutation Rates in Experimental Mutator Populations of Saccharomyces cerevisiae

McDonald, Michael J.; Hsieh, Yu Ying; Yu, Yen Hsin; Chang, Shang Lin; Leu, Jun‐Yi

doi:10.1016/j.cub.2012.04.056

Cited by 53 publications

(63 citation statements)

References 33 publications

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“…We close this discussion by noting that in an experiment on Saccharomyces cerevisiae in which the adapted population reduced its genomewide mutation rate by almost a factor four in two of the experimental lines (McDonald et al. 2012), the fixation time seems to increase with the mutation rate, in contradiction with the experiment of Wielgoss et al. (2013) and the theory presented here.…”

Section: Discussioncontrasting

confidence: 92%

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Fixation probability of rare nonmutator and evolution of mutation rates

James

Jain

2016

Ecology and Evolution

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Although mutations drive the evolutionary process, the rates at which the mutations occur are themselves subject to evolutionary forces. Our purpose here is to understand the role of selection and random genetic drift in the evolution of mutation rates, and we address this question in asexual populations at mutation‐selection equilibrium neglecting selective sweeps. Using a multitype branching process, we calculate the fixation probability of a rare nonmutator in a large asexual population of mutators and find that a nonmutator is more likely to fix when the deleterious mutation rate of the mutator population is high. Compensatory mutations in the mutator population are found to decrease the fixation probability of a nonmutator when the selection coefficient is large. But, surprisingly, the fixation probability changes nonmonotonically with increasing compensatory mutation rate when the selection is mild. Using these results for the fixation probability and a drift‐barrier argument, we find a novel relationship between the mutation rates and the population size. We also discuss the time to fix the nonmutator in an adapted population of asexual mutators, and compare our results with experiments.

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Section: Discussioncontrasting

confidence: 92%

“…We also use the results for the fixation probability to find the time to lower the mutation rate in an adapted population of mutators and compare our theoretical results with recent experiments (McDonald et al. 2012; Wielgoss et al. 2013).…”

Section: Introductionmentioning

confidence: 99%

Fixation probability of rare nonmutator and evolution of mutation rates

James

Jain

2016

Ecology and Evolution

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“…Of course, it is not surprising that deleterious mutations play a small role here, since these populations have been studied precisely because they repeatedly adapt to their laboratory environment. In more well-adapted populations, mutator strains have been observed to evolve toward lower mutation rates (McDonald et al 2012;Maharjan et al 2013;Wielgoss et al 2013), suggesting that the deleterious load may eventually become more of a burden. However, without a more detailed estimate of the DFE, this hypothesis is merely speculative.…”

Section: Discussionmentioning

confidence: 99%

Deleterious Passengers in Adapting Populations

Good¹,

Desai

2014

Genetics

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Most new mutations are deleterious and are eventually eliminated by natural selection. But in an adapting population, the rapid amplification of beneficial mutations can hinder the removal of deleterious variants in nearby regions of the genome, altering the patterns of sequence evolution. Here, we analyze the interactions between beneficial "driver" mutations and linked deleterious "passengers" during the course of adaptation. We derive analytical expressions for the substitution rate of a deleterious mutation as a function of its fitness cost, as well as the reduction in the beneficial substitution rate due to the genetic load of the passengers. We find that the fate of each deleterious mutation varies dramatically with the rate and spectrum of beneficial mutations and the deleterious substitution rate depends nonmonotonically on the population size and the rate of adaptation. By quantifying this dependence, our results allow us to estimate which deleterious mutations will be likely to fix and how many of these mutations must arise before the progress of adaptation is significantly reduced. RECENT years have witnessed an increased interest in the evolutionary dynamics of rapid adaptation. Once regarded as an obscure limit of population genetics, this regime has since been observed in a variety of empirical settings, from laboratory evolution experiments (Barrick et al. 2009;Lang et al. 2013) to natural populations of pathogenic viruses (Strelkowa and Lässig 2012), bacteria (Lieberman et al. 2014), and certain cancers (Nik-Zinal et al. 2012). In these populations, natural selection plays a central role in driving beneficial variants to fixation, and significant theoretical and empirical effort has been devoted to the study of these beneficial mutations and the dynamics by which they spread through the population (see Sniegowski and Gerrish 2010 for a review). Yet even in the most rapidly adapting populations, the vast majority of new mutations are neutral or deleterious, and much less is known about how these variants influence (or are influenced by) adaptation in nearby regions of the genome. As a result, even the most basic questions about this process remain unanswered. How deleterious must a mutation be before it is effectively purged by selection? Which deleterious mutations have the largest influence on the spread of the adaptive mutations? And how do the answers to these questions depend on the size of the population and the spectrum of beneficial mutations? These questions are the focus of the present study.In the absence of other mutations, the fate of a deleterious variant is determined by the interplay between natural selection and genetic drift. Selection purges harmful variants from the population on a timescale inversely proportional to the fitness cost, s d , of the deleterious mutation. Meanwhile, random fluctuations from genetic drift can drive these variants to fixation, which requires a time proportional to the effective population size, N e . Deleterious mutations with s d ) N 21 e ...

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“…Many studies have documented the evolution of higher mutation rates as microbial populations adapt to changed environments (6,(8)(9)(10)(11)(12)35). However, despite long-standing theoretical interest (23)(24)(25), the complementary prediction-that populations should evolve lower rates once they are adapted to their environments-has received only limited and indirect support (7,20,(35)(36)(37)(38). Some of the limitations of earlier studies include reliance on comparative data (36), lack of information on the genetic basis for mutation rate changes (37,38), lack of quantification of effects on rates of sequence evolution (20,37,38), and the use of strains not well adapted to their environment (7,37,38).…”

Section: −7mentioning

confidence: 99%

“…However, despite long-standing theoretical interest (23)(24)(25), the complementary prediction-that populations should evolve lower rates once they are adapted to their environments-has received only limited and indirect support (7,20,(35)(36)(37)(38). Some of the limitations of earlier studies include reliance on comparative data (36), lack of information on the genetic basis for mutation rate changes (37,38), lack of quantification of effects on rates of sequence evolution (20,37,38), and the use of strains not well adapted to their environment (7,37,38). Moreover, reductions in mutation rates were observed surprisingly early in some studies (7,37), and even in nonmutator backgrounds (38), and hence, these results could be seen as counterexamples to the prediction that increased mutation rates should evolve during adaptation to changed conditions, rather than as support for the hypothesis that rates decline when populations become well adapted to their environments.…”

Section: −7mentioning

confidence: 99%

Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load

Wielgoss

Barrick

Tenaillon

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

256

302

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Mutations are the ultimate source of heritable variation for evolution. Understanding how mutation rates themselves evolve is thus essential for quantitatively understanding many evolutionary processes. According to theory, mutation rates should be minimized for well-adapted populations living in stable environments, whereas hypermutators may evolve if conditions change. However, the long-term fate of hypermutators is unknown. Using a phylogenomic approach, we found that an adapting Escherichia coli population that first evolved a mutT hypermutator phenotype was later invaded by two independent lineages with mutY mutations that reduced genome-wide mutation rates. Applying neutral theory to synonymous substitutions, we dated the emergence of these mutations and inferred that the mutT mutation increased the point-mutation rate by ∼150-fold, whereas the mutY mutations reduced the rate by ∼40-60%, with a corresponding decrease in the genetic load. Thus, the long-term fate of the hypermutators was governed by the selective advantage arising from a reduced mutation rate as the potential for further adaptation declined. experimental evolution | genomics | mutators | phylogenomics M utations are the ultimate source of heritable variation for evolution. Therefore, understanding how selection can change mutation rates is crucial for quantitatively describing evolutionary processes (1). More mutations are deleterious than beneficial (2), and organisms from bacteria to eukaryotes encode proofreading and repair enzymes that reduce mutation rates (3). If selection for beneficial mutations is weak relative to selection against deleterious mutations, then the rate of adaptation in asexual populations is maximized at some intermediate mutation rate (4). However, when populations encounter new environments, selection for beneficial mutations can be strong (5), and much higher mutation rates may evolve. Indeed, surveys of laboratory populations of microbes (6-10), clinical isolates of bacterial pathogens (11,12), and some types of eukaryotic tumors (13) have revealed a surprisingly high proportion of lineages that have evolved genetic defects in repair pathways. These hypermutators often have 10-to 100-fold increased mutation rates, and such elevated mutation rates can accelerate the progression of chronic diseases and the evolution of resistance to therapeutic agents.Hypermutable mutants can become established in asexual populations while they adapt to changed environments owing to their higher per capita probability of discovering rare beneficial mutations compared with nonmutators (14-18). Although hypermutable genotypes should produce beneficial mutations at a higher rate than their less mutable counterparts, they do not necessarily increase the rate of adaptation to a corresponding, or even measurable, degree. In large asexual populations, the waiting time for new beneficial mutations to occur may be short relative to the time required for a mutant to increase from one individual to fixation in the population, assuming the be...

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The Evolution of Low Mutation Rates in Experimental Mutator Populations of Saccharomyces cerevisiae

Cited by 53 publications

References 33 publications

Fixation probability of rare nonmutator and evolution of mutation rates

Fixation probability of rare nonmutator and evolution of mutation rates

Deleterious Passengers in Adapting Populations

Mutation rate dynamics in a bacterial population reflect tension between adaptation and genetic load

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