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Unpredictable repeatability in molecular evolution

The extent of parallel evolution at the genotypic level is quantitatively linked to the distribution of beneficial fitness effects (DBFE) of mutations. The standard view, based on light-tailed distributions (i.e., distributions with finite moments), is that the probability of parallel evolution in d...

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Autores principales: Das, Suman G., Krug, Joachim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522380/
https://www.ncbi.nlm.nih.gov/pubmed/36122210
http://dx.doi.org/10.1073/pnas.2209373119
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author Das, Suman G.
Krug, Joachim
author_facet Das, Suman G.
Krug, Joachim
author_sort Das, Suman G.
collection PubMed
description The extent of parallel evolution at the genotypic level is quantitatively linked to the distribution of beneficial fitness effects (DBFE) of mutations. The standard view, based on light-tailed distributions (i.e., distributions with finite moments), is that the probability of parallel evolution in duplicate populations is inversely proportional to the number of available mutations and, moreover, that the DBFE is sufficient to determine the probability when the number of available mutations is large. Here, we show that when the DBFE is heavy-tailed, as found in several recent experiments, these expectations are defied. The probability of parallel evolution decays anomalously slowly in the number of mutations or even becomes independent of it, implying higher repeatability of evolution. At the same time, the probability of parallel evolution is non-self-averaging—that is, it does not converge to its mean value, even when a large number of mutations are involved. This behavior arises because the evolutionary process is dominated by only a few mutations of high weight. Consequently, the probability varies widely across systems with the same DBFE. Contrary to the standard view, the DBFE is no longer sufficient to determine the extent of parallel evolution, making it much less predictable. We illustrate these ideas theoretically and through analysis of empirical data on antibiotic-resistance evolution.
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spelling pubmed-95223802022-09-30 Unpredictable repeatability in molecular evolution Das, Suman G. Krug, Joachim Proc Natl Acad Sci U S A Biological Sciences The extent of parallel evolution at the genotypic level is quantitatively linked to the distribution of beneficial fitness effects (DBFE) of mutations. The standard view, based on light-tailed distributions (i.e., distributions with finite moments), is that the probability of parallel evolution in duplicate populations is inversely proportional to the number of available mutations and, moreover, that the DBFE is sufficient to determine the probability when the number of available mutations is large. Here, we show that when the DBFE is heavy-tailed, as found in several recent experiments, these expectations are defied. The probability of parallel evolution decays anomalously slowly in the number of mutations or even becomes independent of it, implying higher repeatability of evolution. At the same time, the probability of parallel evolution is non-self-averaging—that is, it does not converge to its mean value, even when a large number of mutations are involved. This behavior arises because the evolutionary process is dominated by only a few mutations of high weight. Consequently, the probability varies widely across systems with the same DBFE. Contrary to the standard view, the DBFE is no longer sufficient to determine the extent of parallel evolution, making it much less predictable. We illustrate these ideas theoretically and through analysis of empirical data on antibiotic-resistance evolution. National Academy of Sciences 2022-09-19 2022-09-27 /pmc/articles/PMC9522380/ /pubmed/36122210 http://dx.doi.org/10.1073/pnas.2209373119 Text en Copyright © 2022 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Biological Sciences
Das, Suman G.
Krug, Joachim
Unpredictable repeatability in molecular evolution
title Unpredictable repeatability in molecular evolution
title_full Unpredictable repeatability in molecular evolution
title_fullStr Unpredictable repeatability in molecular evolution
title_full_unstemmed Unpredictable repeatability in molecular evolution
title_short Unpredictable repeatability in molecular evolution
title_sort unpredictable repeatability in molecular evolution
topic Biological Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522380/
https://www.ncbi.nlm.nih.gov/pubmed/36122210
http://dx.doi.org/10.1073/pnas.2209373119
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