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Volume 169, Issue 5

Distribution of mutation rates challenges evolutionary predictability Open Access

This article is part of the Microbial Evolution collection.

Abstract

Natural selection is commonly assumed to act on extensive standing genetic variation. Yet, accumulating evidence highlights the role of mutational processes creating this genetic variation: to become evolutionarily successful, adaptive mutants must not only reach fixation, but also emerge in the first place, i.e. have a high enough mutation rate. Here, we use numerical simulations to investigate how mutational biases impact our ability to observe rare mutational pathways in the laboratory and to predict outcomes in experimental evolution. We show that unevenness in the rates at which mutational pathways produce adaptive mutants means that most experimental studies lack power to directly observe the full range of adaptive mutations. Modelling mutation rates as a distribution, we show that a substantially larger target size ensures that a pathway mutates more commonly. Therefore, we predict that commonly mutated pathways are conserved between closely related species, but not rarely mutated pathways. This approach formalizes our proposal that most mutations have a lower mutation rate than the average mutation rate measured experimentally. We suggest that the extent of genetic variation is overestimated when based on the average mutation rate.

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  • Accepted:
  • Published Online:
Keyword(s): coupon collector's problem , distribution of mutation rates , mutation bias , mutation rate , predicting evolution and Pseudomonas
Funding
This study was supported by the:
  • Åke Wiberg Stiftelse (Award M18-0142)
    • Principle Award Recipient: PeterA Lind
  • Vetenskapsrådet (Award 2019-04859)
    • Principle Award Recipient: PeterA Lind
  • Carl Tryggers Stiftelse för Vetenskaplig Forskning (Award CTS 19:204)
    • Principle Award Recipient: PeterA Lind
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2023-05-03
2024-05-18
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Distribution of mutation rates challenges evolutionary predictability
Microbiology 169, 001323 (2023); https://doi.org/10.1099/mic.0.001323
/content/journal/micro/10.1099/mic.0.001323
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