Sex speeds adaptation by altering the dynamics of molecular evolution

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.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The rate and molecular signatures of adaptation.
Figure 2: Fates of spontaneously arising mutations.
Figure 3: Fitness effects of individual mutations.

Accession codes

Primary accessions

NCBI Reference Sequence

References

  1. 1

    Bell, G. The Masterpiece of Nature: The Evolution and Genetics of Sexuality (Univ. California Press, 1982)

  2. 2

    Otto, S. P. & Lenormand, T. Resolving the paradox of sex and recombination. Nature Rev. Genet. 3, 252–261 (2002)

    CAS  Article  Google Scholar 

  3. 3

    Kondrashov, A. S. Classification of hypotheses on the advantage of amphimixis. J. Hered. 84, 372–387 (1993)

    CAS  Article  Google Scholar 

  4. 4

    Weismann, A. in Essays upon Heredity and Kindred Biological Problems (eds Poulton, E. B., Schonland, S. & Shipley, A. E. ) 251–332 (Clarendon, 1889)

  5. 5

    Fisher, R. A. The Genetical Theory of Natural Selection Ch. 6 (Oxford Univ. Press, 1930)

  6. 6

    Muller, H. Some genetic aspects of sex. Am. Nat. 66, 118–138 (1932)

    Article  Google Scholar 

  7. 7

    Peck, J. R. A ruby in the rubbish: beneficial mutations, deleterious mutations and the evolution of sex. Genetics 137, 597–606 (1994)

    CAS  PubMed  PubMed Central  Google Scholar 

  8. 8

    Johnson, T. & Barton, N. H. The effect of deleterious alleles on adaptation in asexual populations. Genetics 162, 395–411 (2002)

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9

    Gray, J. C. & Goddard, M. R. Sex enhances adaptation by unlinking beneficial from detrimental mutations in experimental yeast populations. BMC Evol. Biol. 12, 43 (2012)

    Google Scholar 

  10. 10

    Becks, L. & Agrawal, A. F. The evolution of sex is favoured during adaptation to new environments. PLoS Biol. 10, e1001317 (2012)

    CAS  Article  Google Scholar 

  11. 11

    Zeyl, C. & Bell, G. The advantage of sex in evolving yeast populations. Nature 388, 465–468 (1997)

    CAS  ADS  Article  Google Scholar 

  12. 12

    Goddard, M. R., Godfray, H. C. J. & Burt, A. Sex increases the efficacy of natural selection in experimental yeast populations. Nature 434, 636–640 (2005)

    CAS  ADS  Article  Google Scholar 

  13. 13

    Colegrave, N. Sex releases the speed limit on evolution. Nature 420, 664–666 (2002)

    CAS  ADS  Article  Google Scholar 

  14. 14

    Poon, A. & Chao, L. Drift increases the advantage of sex in RNA bacteriophage Φ6. Genetics 166, 19–24 (2004)

    Article  Google Scholar 

  15. 15

    Becks, L. & Agrawal, A. F. Higher rates of sex evolve in spatially heterogeneous environments. Nature 468, 89–92 (2010)

    CAS  ADS  Article  Google Scholar 

  16. 16

    Rice, W. R. & Chippindale, A. K. Sexual recombination and the power of natural selection. Science 294, 555–559 (2001)

    CAS  ADS  Article  Google Scholar 

  17. 17

    Cooper, T. F. Recombination speeds adaptation by reducing competition between beneficial mutations in populations of Escherichia coli. PLoS Biol. 5, e225 (2007)

    Article  Google Scholar 

  18. 18

    Weissman, D. B. & Barton, N. H. Limits to the rate of adaptive substitution in sexual populations. PLoS Genet. 8, e1002740 (2012)

    CAS  Article  Google Scholar 

  19. 19

    Crow, J. F. & Kimura, M. Evolution in sexual and asexual populations. Am. Nat. 99, 439–450 (1965)

    Article  Google Scholar 

  20. 20

    Maynard Smith, J. What use is sex? J. Theor. Biol. 30, 319–335 (1971)

    Article  Google Scholar 

  21. 21

    Lang, G. I. et al. Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500, 571–574 (2013)

    CAS  ADS  Article  Google Scholar 

  22. 22

    Kao, K. C. & Sherlock, G. Molecular characterization of clonal interference during adaptive evolution in asexual populations of Saccharomyces cerevisiae. Nature Genet. 40, 1499–1504 (2008)

    CAS  Article  Google Scholar 

  23. 23

    Miralles, R., Gerrish, P. J., Moya, A. & Elena, S. F. Clonal interference and the evolution of RNA viruses. Science 285, 1745–1747 (1999)

    CAS  Article  Google Scholar 

  24. 24

    Sella, G., Petrov, D. A., Przeworski, M. & Andolfatto, P. Pervasive natural selection in the Drosophila genome? PLoS Genet. 5, e1000495 (2009)

    Article  Google Scholar 

  25. 25

    Good, B. H. & Desai, M. M. Deleterious passengers in adapting populations. Genetics 198, 1183–1208 (2014)

    Article  Google Scholar 

  26. 26

    Schiffels, S., Szöllősi, G. J., Mustonen, V. & Lässig, M. Emergent neutrality in adaptive asexual evolution. Genetics 189, 1361–1375 (2011)

    Article  Google Scholar 

  27. 27

    Kondrashov, A. S. Deleterious mutations and the evolution of sexual reproduction. Nature 336, 435–440 (1988)

    CAS  ADS  Article  Google Scholar 

  28. 28

    Hartfield, M. & Otto, S. P. Recombination and hitchhiking of deleterious alleles. Evolution 65, 2421–2434 (2011)

    Article  Google Scholar 

  29. 29

    Birky, C. W. & Walsh, J. B. Effects of linkage on rates of molecular evolution. Proc. Natl Acad. Sci. USA 85, 6414–6418 (1988)

    CAS  ADS  Article  Google Scholar 

  30. 30

    Frenkel, E. M. et al. Crowded growth leads to the spontaneous evolution of semi-stable coexistence in laboratory yeast populations. Proc. Natl Acad. Sci. USA 112, 11306–11311 (2015)

    CAS  ADS  Article  Google Scholar 

  31. 31

    Tong, A. H. Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294, 2364–2368 (2001)

    CAS  ADS  Article  Google Scholar 

  32. 32

    Giaever, G. et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391 (2002)

    CAS  ADS  Article  Google Scholar 

  33. 33

    Lang, G. I., Botstein, D. & Desai, M. M. Genetic variation and the fate of beneficial mutations in asexual populations. Genetics 188, 647–661 (2011)

    Article  Google Scholar 

  34. 34

    Hall, B. M., Ma, C.-X., Liang, P. & Singh, K. K. Fluctuation AnaLysis CalculatOR: a web tool for the determination of mutation rate using Luria–Delbrück fluctuation analysis. Bioinformatics 25, 1564–1565 (2009)

    CAS  Article  Google Scholar 

  35. 35

    Frenkel, E. M., Good, B. H. & Desai, M. M. The fates of mutant lineages and the distribution of fitness effects of beneficial mutations in laboratory budding yeast populations. Genetics 196, 1217–1226 (2014)

    CAS  Article  Google Scholar 

  36. 36

    Kryazhimskiy, S., Rice, D. P., Jerison, E. R. & Desai, M. M. Global epistasis makes adaptation predictable despite sequence-level stochasticity. Science 344, 1519–1522 (2014)

    CAS  ADS  Article  Google Scholar 

  37. 37

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nature Methods 9, 357–359 (2012)

    CAS  PubMed  PubMed Central  Google Scholar 

  38. 38

    DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nature Genet. 43, 491–498 (2011)

    CAS  Article  Google Scholar 

  39. 39

    Anscombe, F. J. The transformation of poisson, binomial and negative-binomial data. Biometrika 35, 246–254 (1948)

    MathSciNet  Article  Google Scholar 

  40. 40

    Donoho, D. L. & Johnstone, I. M. Adapting to unknown smoothness via wavelet shrinkage. J. Am. Stat. Assoc. 90, 1200–1224 (1995)

    MathSciNet  Article  Google Scholar 

  41. 41

    Shim, H. & Stephens, M. Wavelet-based genetic association analysis of functional phenotypes arising from high-throughput sequencing assays. Ann. Appl. Stat. 9, 665–686 (2015)

    MathSciNet  Article  Google Scholar 

  42. 42

    Dunham, M. J. et al. Characteristic genome rearrangements in experimental evolution of Saccharomyces cerevisiae. Proc. Natl Acad. Sci. USA 99, 16144–16149 (2002)

    CAS  ADS  Article  Google Scholar 

  43. 43

    Chang, S.-L., Lai, H.-Y., Tung, S.-Y. & Leu, J.-Y. Dynamic large-scale chromosomal rearrangements fuel rapid adaptation in yeast populations. PLoS Genet. 9, e1003232 (2013)

    CAS  Article  Google Scholar 

Download references

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

Affiliations

Authors

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.

Corresponding author

Correspondence to Michael M. Desai.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

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

Extended data figures and tables

Extended Data Figure 1 Genetic system and experimental protocol for evolution of sexual populations.

Genotypes of the two haploid mating types are indicated at bottom, with selectable markers that are expressed in each strain indicated in colour. Steps in our experimental protocols involving these markers are indicated in the corresponding colour. STE5pr is a haploid-specific promoter and STE2pr and STE3pr are a- and α-specific promoters respectively, so haploid a cells express URA3 and HIS3, while haploid α cells express URA3 and LEU2. The drug resistance markers KANMX and HPHB, tightly linked to the a and α mating loci respectively, are constitutively expressed. URA3 is counterselectable; it is not expressed in diploids, rendering them resistant to 5-FOA.

Extended Data Figure 2 Adaptation to 17 °C and sporulation conditions.

a, b, Relative fitness of evolved asexual (blue) and sexual (orange) populations over four days in 17 °C (a) and sporulation conditions (b). Fitness changes are reported averaged over a complete experimental cycle (90 generations; mean of three replicate fitness assays, error bars ± s.e.m.). Mean fitness differences between asexual and sexual evolved strains are not significant in either the 17 °C (two-sided t-test, P = 0.5) or sporulation (two-sided t-test, P = 0.8) treatment.

Extended Data Figure 3 Adaptation in mixed and non-mixed asexual populations.

Fitness increases after 990 generations of evolution in mixed (blue) and non-mixed (pink) alternative asexual control populations (mean of four replicate fitness measurements, error bars ± s.e.m.). Each non-mixed line was maintained independently. Subpopulations from mixed populations were mixed in pairs every 90 generations; each pair is indicated by a corresponding light and dark circle.

Extended Data Figure 4 Read-depth variation analysis of sequenced clones.

Denoised, normalized coverage in 100-bp windows along the genome (Methods). Each panel represents a clone isolated from one of four independent populations. Pairs of clones from the same population are adjacent and indicated by the population label on the left. Regions containing putative amplifications and deletions (Extended Data Table 4) are highlighted in orange.

Extended Data Table 1 Leakage of diploids through the sexual cycle
Extended Data Table 2 Mutation frequency in YPD, sporulation and 17 °C treatments
Extended Data Table 3 Classification of observed mutations
Extended Data Table 4 Larger-scale mutations

Supplementary information

Supplementary Data 1

This tab-delimited text file contains the identity, frequency trajectory, and fitness data for all mutations in this study. (TXT 322 kb)

Supplementary Data 2

This excel file contains all primers and oligonucleotides used in this study. (XLSX 12 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

McDonald, M., Rice, D. & Desai, M. Sex speeds adaptation by altering the dynamics of molecular evolution. Nature 531, 233–236 (2016). https://doi.org/10.1038/nature17143

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Sign up for the Nature Briefing newsletter for a daily update on COVID-19 science.
Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing