Letter | Published:

Sex speeds adaptation by altering the dynamics of molecular evolution

Nature volume 531, pages 233236 (10 March 2016) | Download Citation

Abstract

Sex and recombination are pervasive throughout nature despite their substantial costs1. Understanding the evolutionary forces that maintain these phenomena is a central challenge in biology2,3. One longstanding hypothesis argues that sex is beneficial because recombination speeds adaptation4. Theory has proposed several distinct population genetic mechanisms that could underlie this advantage. For example, sex can promote the fixation of beneficial mutations either by alleviating interference competition (the Fisher–Muller effect)5,6 or by separating them from deleterious load (the ruby in the rubbish effect)7,8. Previous experiments confirm that sex can increase the rate of adaptation9,10,11,12,13,14,15,16,17, but these studies did not observe the evolutionary dynamics that drive this effect at the genomic level. Here we present the first, to our knowledge, comparison between the sequence-level dynamics of adaptation in experimental sexual and asexual Saccharomyces cerevisiae populations, which allows us to identify the specific mechanisms by which sex speeds adaptation. We find that sex alters the molecular signatures of evolution by changing the spectrum of mutations that fix, and confirm theoretical predictions that it does so by alleviating clonal interference. We also show that substantially deleterious mutations hitchhike to fixation in adapting asexual populations. In contrast, recombination prevents such mutations from fixing. Our results demonstrate that sex both speeds adaptation and alters its molecular signature by allowing natural selection to more efficiently sort beneficial from deleterious mutations.

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Primary accessions

NCBI Reference Sequence

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Acknowledgements

We thank J.-Y. Leu and S. Akle-Serrano for help with strain construction and experimental evolution; S. Kryazhimskiy, E. Jerison, and J. Piper for help with sequencing library preparation; G. Lang, A. Murray, B. Good, D. van Dyken, K. Kosheleva, I. Cvijovic´, and other members of the Desai laboratory for discussions and comments on the manuscript; and P. Rogers and C. Daly for technical support. D.P.R. acknowledges support from an NSF graduate research fellowship. M.M.D. acknowledges support from the James S. McDonnell Foundation, the Alfred P. Sloan Foundation, the Harvard Milton Fund, the Simons Foundation (grant 376196), grant PHY 1313638 from the National Science Foundation, and grant GM104239 from the National Institutes of Health. Computational work was performed on the Odyssey cluster supported by the Research Computing Group at Harvard University.

Author information

Author notes

    • Michael J. McDonald
    •  & Daniel P. Rice

    These authors contributed equally to this work.

Affiliations

  1. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Michael J. McDonald
    • , Daniel P. Rice
    •  & Michael M. Desai
  2. FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Michael J. McDonald
    • , Daniel P. Rice
    •  & Michael M. Desai
  3. Department of Physics, Harvard University, Cambridge, Massachusetts 02138, USA

    • Michael M. Desai

Authors

  1. Search for Michael J. McDonald in:

  2. Search for Daniel P. Rice in:

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Contributions

M.J.M., D.P.R., and M.M.D. designed the project; M.J.M. conducted the experiments and generated the sequencing data; D.P.R. designed and conducted the bioinformatics analysis; M.J.M., D.P.R., and M.M.D. analysed the data and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Michael M. Desai.

Genome sequence data have been deposited in GenBank under BioProject identifier PRJNA308843.

Extended data

Supplementary information

Text files

  1. 1.

    Supplementary Data 1

    This tab-delimited text file contains the identity, frequency trajectory, and fitness data for all mutations in this study.

Excel files

  1. 1.

    Supplementary Data 2

    This excel file contains all primers and oligonucleotides used in this study.

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DOI

https://doi.org/10.1038/nature17143

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