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Predictability shifts from local to global rules during bacterial adaptation

View ORCID ProfileAlejandro Couce, Melanie Magnan, View ORCID ProfileRichard E. Lenski, Olivier Tenaillon
doi: https://doi.org/10.1101/2022.05.17.492360
Alejandro Couce
1Unité Mixte de Recherche 1137 (IAME, INSERM), Université Sorbonne Paris Nord, 75018 Paris, FRANCE
2Department of Life Sciences, Imperial College London, SW7 2AZ London, UK
3Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM), 28223 Madrid, SPAIN
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  • For correspondence: a.couce@upm.es olivier.tenaillon@inserm.fr
Melanie Magnan
1Unité Mixte de Recherche 1137 (IAME, INSERM), Université Sorbonne Paris Nord, 75018 Paris, FRANCE
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Richard E. Lenski
4Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan 48824, USA
5Program in Ecology, Evolution, and Behavior, Michigan State University, East Lansing, Michigan 48824, USA
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Olivier Tenaillon
1Unité Mixte de Recherche 1137 (IAME, INSERM), Université Sorbonne Paris Nord, 75018 Paris, FRANCE
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  • For correspondence: a.couce@upm.es olivier.tenaillon@inserm.fr
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Abstract

The distribution of fitness effects of new mutations is central to predicting adaptive evolution, but observing how it changes as organisms adapt is challenging. Here we use saturated, genome-wide insertion libraries to quantify how the fitness effects of new mutations changed in two E. coli populations that adapted to a constant environment for 15,000 generations. The proportions of neutral and deleterious mutations remained constant, despite large fitness gains. In contrast, the beneficial fraction declined rapidly, approximating an exponential distribution, with strong epistasis profoundly changing the genetic identity of adaptive mutations. Despite this volatility, many important targets of selection were predictable from the ancestral distribution. This predictability occurs because genetic target size contributed to the fixation of beneficial mutations as much as or more than their effect sizes. Overall, our results demonstrate that short-term adaptation can be idiosyncratic but empirically predictable, and that long-term dynamics can be described by simple statistical principles.

One-Sentence Summary Couce et al. demonstrate that short-term bacterial adaptation is predictable at the scale of individual genes, while long-term adaptation is predictable at a global scale.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Apart from minor edits in the text and figures, we have added two new Figures (S4 and S9) as well as new panels in Figures S2 and S5. The most noticeable changes are to the title and the abstract, which now better emphasize the most novel and far-reaching contributions of our work: namely, short-term adaptation is predictable at the scale of individual genes, while long-term adaptation is predictable at a global scale.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted January 30, 2023.
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Predictability shifts from local to global rules during bacterial adaptation
Alejandro Couce, Melanie Magnan, Richard E. Lenski, Olivier Tenaillon
bioRxiv 2022.05.17.492360; doi: https://doi.org/10.1101/2022.05.17.492360
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Predictability shifts from local to global rules during bacterial adaptation
Alejandro Couce, Melanie Magnan, Richard E. Lenski, Olivier Tenaillon
bioRxiv 2022.05.17.492360; doi: https://doi.org/10.1101/2022.05.17.492360

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