bioRxiv · 10.1101/2021.09.25.461822
Stochastic modeling uncovers a novel mechanism underlying the evolution of mutation rates in sexually reproducing populations
Abstract
Natural selection is believed to universally work to lower mutation rates (MR) due to the negative impact of mutations on individual fitness. Mutator alleles can be co-selected by genetic linkage with adaptive alleles in asexual organisms. However, sexual reproduction disrupts genetic linkage, allowing selection to efficiently eradicate mutator alleles, lowering MR to the extent limited by the overall selection efficiency. In the present paper, we apply Monte Carlo in silico experimentation to study MR evolution in sexually reproducing populations. We demonstrate that both higher and lower MR can evolve depending on the mode of selection acting on adaptive phenotypic traits. We reveal a previously unreported co-selective process that determines the direction of MR evolution. We show that MR evolution is substantially influenced by multigenic inheritance of both MR and adaptive traits. Our study corroborates that MR evolution is significantly impacted by genetic drift; however, its primary source appears to be the amount of standing genetic variation, with a lesser role for population size. Based on our study, we propose an expanded population genetics theory of MR evolution in sexually reproducing populations, with potential implications for understanding rapid adaptive speciation and related macroevolutionary patterns, as well as for human health. Lay summaryNatural selection is believed to always work to lower mutation rates in sexual organisms. Here we apply a Monte Carlo model of a sexually reproducing population and demonstrate that both lower and higher mutation rates can evolve, contingent on selection acting on adaptive traits in a sexually reproducing population.
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Rozhok, A. I., Eldredge, N., DeGregori, J.. 2021-09-26. Stochastic modeling uncovers a novel mechanism underlying the evolution of mutation rates in sexually reproducing populations. https://doi.org/10.1101/2021.09.25.461822
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