Selection bias in mutation accumulation

Wahl, Lindi M.; Agashe, Deepa

doi:10.1111/evo.14430

Cited by 16 publications

(16 citation statements)

References 43 publications

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“…With this large set of fitness effects, we constructed environment-specific empirical DFEs (WT data for some environments were previously reported (30)). Since bacterial MA experiments can cause over-sampling of beneficial mutations and under-sampling of deleterious mutations, we used a correction (32) that retains the measured selective effect ( s ) of each mutation, but estimates and corrects for selection bias by changing the frequency of mutations with a given selective effect (Fig. S1A–C, Supplementary Data).…”

Section: Resultsmentioning

confidence: 99%

Shifts in mutation spectra enhance access to beneficial mutations

Sane

Diwan

Bhat

et al. 2020

Preprint

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SUMMARYMutations are critical for evolutionary change. Although mutation spectra (mutational biases) vary greatly across organisms, we lack direct evidence of their evolutionary consequences. Here, we show experimentally that a biased spectrum alters the distribution of fitness effects in a bacterium, and should facilitate adaptation by increasing beneficial mutations and reducing genetic load. Adaptive walk simulations show that this advantage arises via better sampling of mutational classes that were poorly explored by the ancestor. Hence, reversing the spectrum of a biased ancestor is generally advantageous, while introducing bias in an unbiased ancestor is selectively neutral. Indeed, across bacterial lineages, evolutionary transitions in DNA repair enzymes – which shape spectra – typically reverse ancestral bias. These broad consequences of mutation spectra imply a major role in shaping evolutionary dynamics.

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Section: Resultsmentioning

confidence: 99%

Shifts in mutation spectra enhance access to beneficial mutations

Sane

Diwan

Bhat

et al. 2020

Preprint

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“…In the experiment described here, there were approximately 11 generations of growth between each transfer in the MA experiment, where selection could operate to change the frequencies of de novo mutations. To investigate the influence of selection on the estimated DFE, we implemented the method recently developed by Wahl and Agashe [ 37 ] to predict the extent of under- or over-contribution to the DFE for mutations with given selection coefficients, assuming that there is a doubling of cell number for t = 11 generations during mutation accumulation. Based on Eq ( 2 ) in [ 37 ], and assuming a two-sided gamma distribution with parameters specified in Table 4 , the corrected estimate for the frequency of positive effect mutations is q = 0.46 (uncorrected = 0.50).…”

Section: Discussionmentioning

confidence: 99%

“…To investigate the influence of selection on the estimated DFE, we implemented the method recently developed by Wahl and Agashe [ 37 ] to predict the extent of under- or over-contribution to the DFE for mutations with given selection coefficients, assuming that there is a doubling of cell number for t = 11 generations during mutation accumulation. Based on Eq ( 2 ) in [ 37 ], and assuming a two-sided gamma distribution with parameters specified in Table 4 , the corrected estimate for the frequency of positive effect mutations is q = 0.46 (uncorrected = 0.50). This suggests that selection during mutation accumulation had only a modest impact.…”

Section: Discussionmentioning

confidence: 99%

The distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii inferred using frequency changes under experimental evolution

et al. 2022

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The distribution of fitness effects (DFE) for new mutations is fundamental for many aspects of population and quantitative genetics. In this study, we have inferred the DFE in the single-celled alga Chlamydomonas reinhardtii by estimating changes in the frequencies of 254 spontaneous mutations under experimental evolution and equating the frequency changes of linked mutations with their selection coefficients. We generated seven populations of recombinant haplotypes by crossing seven independently derived mutation accumulation lines carrying an average of 36 mutations in the haploid state to a mutation-free strain of the same genotype. We then allowed the populations to evolve under natural selection in the laboratory by serial transfer in liquid culture. We observed substantial and repeatable changes in the frequencies of many groups of linked mutations, and, surprisingly, as many mutations were observed to increase as decrease in frequency. Mutation frequencies were highly repeatable among replicates, suggesting that selection was the cause of the observed allele frequency changes. We developed a Bayesian Monte Carlo Markov Chain method to infer the DFE. This computes the likelihood of the observed distribution of changes of frequency, and obtains the posterior distribution of the selective effects of individual mutations, while assuming a two-sided gamma distribution of effects. We infer that the DFE is a highly leptokurtic distribution, and that approximately equal proportions of mutations have positive and negative effects on fitness. This result is consistent with what we have observed in previous work on a different C. reinhardtii strain, and suggests that a high fraction of new spontaneously arisen mutations are advantageous in a simple laboratory environment.

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“…The frequency distribution of fitness effects may be shifted under hotter temperatures (Xu 2004; Chu et al 2020). However, direct effect of temperature on population growth rate in microbes, where population size limits (bottlenecks) are not imposed per generation, may allow greater opportunity for selection to shift the observed frequency of mutations at hot relative to cool temperatures (Wahl and Agashe 2022), with stronger selection on deleterious mutations under hotter conditions (Berger et al 2021).…”

Section: Discussionmentioning

confidence: 99%

The contribution of mutation to variation in temperature-dependent sprint speed in zebrafish,Danio rerio

Miller

Sun

Thornton

et al. 2022

Preprint

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The contribution of new mutations to phenotypic variation, and the consequences of this variation for individual fitness, are fundamental concepts for understanding genetic variation and adaptation. Here, we investigated how mutation influenced variation in a complex trait in zebrafish, Danio rerio. Typical of many ecologically relevant traits in ectotherms, swimming speed in fish is temperature-dependent, with evidence of adaptive evolution of thermal performance. We chemically induced novel germline point mutations in males, and measured sprint speed in their sons at six temperatures (between 16C and 34C). Mutational effects on speed were strongly positively correlated among temperatures, resulting in statistical support for only a single axis of mutational variation, reflecting temperature-independent variation in speed (faster-slower mode). While these results suggest pleiotropic effects on speed across different temperatures, when mutation have consistent directional effects on each trait, spurious correlations arise via linkage, or heterogeneity in mutation number. However, mutation did not change mean speed, indicating no directional bias in mutational effects. The results contribute to emerging evidence that mutations may predominantly have synergistic cross-environment effects, in contrast to conditionally neutral or antagonistic effects which underpin thermal adaptation. However, aspects of experimental design might limit resolution of mutations with non-synergistic effects.

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Selection bias in mutation accumulation

Cited by 16 publications

References 43 publications

Shifts in mutation spectra enhance access to beneficial mutations

Shifts in mutation spectra enhance access to beneficial mutations

The distribution of fitness effects of spontaneous mutations in Chlamydomonas reinhardtii inferred using frequency changes under experimental evolution

The contribution of mutation to variation in temperature-dependent sprint speed in zebrafish,Danio rerio

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