Sex speeds adaptation by altering the dynamics of molecular evolution


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

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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




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.

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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)

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McDonald, M., Rice, D. & Desai, M. Sex speeds adaptation by altering the dynamics of molecular evolution. Nature 531, 233–236 (2016).

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