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Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations

Nature 500, 571–574 (29 August 2013) | Download Citation

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Abstract

The dynamics of adaptation determine which mutations fix in a population, and hence how reproducible evolution will be. This is central to understanding the spectra of mutations recovered in the evolution of antibiotic resistance1, the response of pathogens to immune selection2,3, and the dynamics of cancer progression4,5. In laboratory evolution experiments, demonstrably beneficial mutations are found repeatedly6,7,8, but are often accompanied by other mutations with no obvious benefit. Here we use whole-genome whole-population sequencing to examine the dynamics of genome sequence evolution at high temporal resolution in 40 replicate Saccharomyces cerevisiae populations growing in rich medium for 1,000 generations. We find pervasive genetic hitchhiking: multiple mutations arise and move synchronously through the population as mutational ‘cohorts’. Multiple clonal cohorts are often present simultaneously, competing with each other in the same population. Our results show that patterns of sequence evolution are driven by a balance between these chance effects of hitchhiking and interference, which increase stochastic variation in evolutionary outcomes, and the deterministic action of selection on individual mutations, which favours parallel evolutionary solutions in replicate populations.

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Acknowledgements

We thank the production team led by L. Fulton and R. Fulton at the Genome Institute at Washington University for sample management and data production, and E. Lobos for coordinating the project. We thank L. Parsons and J. Wiggins for assistance with data management, P. Gibney for assistance with sample preparation, and T. DeCoste for assistance with flow cytometry. We thank K. Kosheleva for discussions, and A. Murray, C. Marx, M. McDonald, G. Sherlock and D. Kvitek for comments on the manuscript. D.P.R. acknowledges support from an NSF Graduate Research Fellowship. D.B. acknowledges support from NIGMS Centers of Excellence grant GM071508 and NIH grant GM046406. M.M.D. acknowledges support from the James S. McDonnell Foundation, the Alfred P. Sloan Foundation, and the Harvard Milton Fund.

Author information

    • Gregory I. Lang
    •  & Daniel P. Rice

    These authors contributed equally to this work.

    • Gregory I. Lang

    Present address: Department of Biological Sciences, Lehigh University, Bethlehem, Pennsylvania 18015, USA.

Affiliations

  1. Lewis-Sigler Institute for Integrative Genomics and Department of Molecular Biology, Princeton University, Princeton, New Jersey 08544, USA

    • Gregory I. Lang
    •  & David Botstein

  2. Departments of Organismic and Evolutionary Biology and of Physics, and FAS Center for Systems Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Daniel P. Rice
    •  & Michael M. Desai

  3. Departments of Biological Sciences and Chemistry & Biochemistry, Rowan University, Glassboro, New Jersey 08028, USA

    • Mark J. Hickman

  4. The Genome Institute, Washington University School of Medicine, St. Louis, Missouri 63108, USA

    • Erica Sodergren
    •  & George M. Weinstock

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Contributions

G.I.L., D.B. and M.M.D. designed the project; E.S. and G.M.W. generated the sequencing data; G.I.L., D.P.R., M.J.H. and M.M.D. analysed the sequencing data; G.I.L. performed the experiments; G.I.L., D.P.R., D.B. and M.M.D. wrote the paper. Co-senior authors, D.B. and M.M.D.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Gregory I. Lang or Michael M. Desai.

Genome sequence data have been deposited to GenBank under the BioProject identifier PRJNA205542.

Supplementary information

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  1. 1.

    Supplementary Information

    This file contains Supplementary Tables 2-3 (see separate file for Supplementary Table 1) and Supplementary Figures 1-3.

Excel files

  1. 1.

    Supplementary Table 1

    This file contains details of the 1,020 mutations identified in the 40 sequenced populations. It also contains complete descriptions of all mutations we observed in all 40 populations, and their frequency trajectories over the 1,000 generations of the experiment, as estimated by both independent pipelines (Methods).

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DOI

https://doi.org/10.1038/nature12344

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