Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations

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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 40replicate Saccharomyces cerevisiae populations growing in rich medium for 1,000generations. 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.

At a glance


  1. The fates of individual spontaneously arising mutations.
    Figure 1: The fates of individual spontaneously arising mutations.

    We show the frequency of all identified mutations through 1,000generations in 6of the 40sequenced populations. Non-synonymous mutations are solid lines with solid circles, and synonymous and intergenic mutations are dotted lines with open circles and squares, respectively. Populations in the left and right columns were evolved at small (105) and large (106) population sizes, respectively. We observe qualitatively similar patterns in the other populations (Supplementary Fig. 1).

  2. Statistical analysis across 40[thinsp]replicate populations.
    Figure 2: Statistical analysis across 40replicate populations.

    a, The per-population number of total mutations, fixed mutations, extinct mutations and mutations that are currently polymorphic over the course of the 1,000generations. b, The distribution of the number of new mutations detected at each time point (solid blue line; see Methods for details) and a Poisson distribution with the same mean (dashed red line). c, d, Mutation fixation probability as a function of initial relative fitness. Data are mean±s.e.m.

  3. The dynamics of sequence evolution in BYB1-G07.
    Figure 3: The dynamics of sequence evolution in BYB1-G07.

    a, The trajectories of the 15 mutations that attain a frequency of at least 30%, hierarchically clustered into several distinct mutation ‘cohorts’, each of which is represented by a different colour (Methods). b, Muller diagram showing the dynamics of the six main cohorts in the population. The number of times a mutation was observed in a given gene across all 40populations is indicated in parentheses. Mutations in genes observed in more than three replicate populations (Table 1) are indicated in bold.

  4. Genetic dissection of BYS1-A08.
    Figure 4: Genetic dissection of BYS1-A08.

    a, The trajectories of observed mutations. b, We crossed evolved clones from generation 545(dotted grey line in a) to the ancestor; shown here are the fitnesses and genotypes of parental clones and 80haploid progeny.

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Referenced accessions



  1. Weinreich, D. M., Delaney, N. F., DePristo, M. A. & Hartl, D. L. Darwinian evolution can follow only very few mutational paths to fitter proteins. Science 312, 111114 (2006)
  2. Strelkowa, N. & Lässig, M. Clonal interference in the evolution of influenza. Genetics 192, 671682 (2012)
  3. Levin, B. R. & Bull, J. J. Short-sighted evolution and the virulence of pathogenic microorganisms. Trends Microbiol. 2, 7681 (1994)
  4. Greaves, M. & Maley, C. C. Clonal evolution in cancer. Nature 481, 306313 (2012)
  5. Sprouffske, K., Merlo, L. M. F., Gerrish, P. J., Maley, C. C. & Sniegowski, P. D. Cancer in light of experimental evolution. Curr. Biol. 22, R762R771 (2012)
  6. Tenaillon, O. et al. The molecular diversity of adaptive convergence. Science 335, 457461 (2012)
  7. Woods, R., Schneider, D., Winkworth, C. L., Riley, M. A. & Lenski, R. E. Tests of parallel molecular evolution in a long-term experiment with Escherichia coli. Proc. Natl Acad. Sci. USA 103, 91079112 (2006)
  8. Saxer, G., Doebeli, M. & Travisano, M. The repeatability of adaptive radiation during long-term experimental evolution of Escherichia coli in a multiple nutrient environment. PLoS ONE 5, e14184 (2010)
  9. Atwood, K. C., Schneider, L. K. & Ryan, F. J. Periodic selection in Escherichia coli. Proc. Natl Acad. Sci. USA 37, 146155 (1951)
  10. Paquin, C. & Adams, J. Frequency of fixation of adaptive mutations is higher in evolving diploid than haploid yeast populations. Nature 302, 495500 (1983)
  11. Joseph, S. B. & Hall, D. W. Spontaneous mutations in diploid Saccharomyces cerevisiae: more beneficial than expected. Genetics 168, 18171825 (2004)
  12. Perfeito, L., Fernandes, L., Mota, C. & Gordo, I. Adaptive mutations in bacteria: high rate and small effects. Science 317, 813815 (2007)
  13. Gerrish, P. J. & Lenski, R. The fate of competing beneficial mutations in an asexual population. Genetica 102–103, 127144 (1998)
  14. Desai, M. M. & Fisher, D. S. Beneficial mutation-selection balance and the effect of linkage on positive selection. Genetics 176, 17591798 (2007)
  15. Rouzine, I. M., Wakeley, J. & Coffin, J. The solitary wave of asexual evolution. Proc. Natl Acad. Sci. USA 100, 587592 (2003)
  16. Good, B. H., Rouzine, I. M., Balick, D. J., Hallatschek, O. & Desai, M. M. The rate of adaptation and the distribution of fixed beneficial mutations in asexual populations. Proc. Natl Acad. Sci. USA 109, 49504955 (2012)
  17. Schiffels, S., Szöllősi, G. J., Mustonen, V. & Lässig, M. Emergent neutrality in adaptive asexual evolution. Genetics 189, 13611375 (2011)
  18. Desai, M. M., Fisher, D. S. & Murray, A. W. The speed of evolution and maintenance of variation in asexual populations. Curr. Biol. 17, 385394 (2007)
  19. de Visser, J. A. G. M., Zeyl, C. W., Gerrish, P. J., Blanchard, J. L. & Lenski, R. E. Diminishing returns from mutation supply rate in asexual populations. Science 283, 404406 (1999)
  20. Kao, K. C. & Sherlock, G. Molecular Characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae. Nature Genet. 40, 14991504 (2008)
  21. Lang, G. I., Botstein, D. & Desai, M. M. Genetic variation and the fate of beneficial mutations in asexual populations. Genetics 188, 647661 (2011)
  22. Barrick, J. E. et al. Genome evolution and adaptation in a long-term experiment with Escherichia coli. Nature 461, 12431247 (2009)
  23. Barrick, J. E. & Lenski, R. E. Genome-wide mutational diversity in an evolving population of Escherichia coli. Cold Spring Harb. Symp. Quant. Biol. 74, 119129 (2009)
  24. Dettman, J. R. et al. Evolutionary insight from whole-genome sequencing of experimentally evolved microbes. Mol. Ecol. 21, 20582077 (2012)
  25. Gresham, D. et al. The repertoire and dynamics of evolutionary adaptations to controlled nutrient-limited environments in yeast. PLoS Genet. 4, e1000303 (2008)
  26. Bollback, J. P. & Huelsenbeck, J. P. Clonal interference is alleviated by high mutation rates in large populations. Mol. Biol. Evol. 24, 13971406 (2007)
  27. Betancourt, A. J. Genomewide patterns of substitution in adaptively evolving populations of the RNA bacteriophage MS2. Genetics 181, 15351544 (2009)
  28. Miller, C. R., Joyce, P. & Wichman, H. A. Mutational effects and population dynamics during viral adaptation challenge current models. Genetics 187, 185202 (2011)
  29. Wichman, H. A., Badgett, M. R., Scott, L. A., Boulianne, C. M. & Bull, J. J. Different trajectories of parallel evolution during viral adaptation. Science 285, 422424 (1999)
  30. Nik-Zainal, S. et al. The life history of 21 breast cancers. Cell 149, 9941007 (2012)
  31. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 20782079 (2009)
  32. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 17541760 (2009)
  33. Robinson, J. T. et al. Integrative genomics viewer. Nature Biotechnol. 29, 2426 (2011)
  34. Thorvaldsdóttir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178192 (2013)
  35. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403410 (1990)
  36. Hartl, D. A Primer of Population Genetics. (Sinauer Associates, 2000)

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Author information

  1. These authors contributed equally to this work.

    • Gregory I. Lang &
    • Daniel P. Rice


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

    • Gregory I. Lang


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 financial interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to:

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

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Supplementary information

PDF files

  1. Supplementary Information (5.9 MB)

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

Excel files

  1. Supplementary Table 1 (412 KB)

    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).

Additional data