The power of randomization by sex in multilocus genetic evolution

Liudmyla Vasylenko, Marcus W. Feldman, Adi Livnat

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Many hypotheses have been proposed for how sexual reproduction may facilitate an increase in the population mean fitness, such as the Fisher-Muller theory, Muller’s ratchet and others. According to the recently proposed mixability theory, however, sexual recombination shifts the focus of natural selection away from favoring particular genetic combinations of high fitness towards favoring alleles that perform well across different genetic combinations. Mixability theory shows that, in finite populations, because sex essentially randomizes genetic combinations, if one allele performs better than another across the existing combinations of alleles, that allele will likely also perform better overall across a vast space of untested potential genotypes. However, this superiority has been established only for a single-locus diploid model. Results: We show that, in both haploids and diploids, the power of randomization by sex extends to the multilocus case, and becomes substantially stronger with increasing numbers of loci. In addition, we make an explicit comparison between the sexual and asexual cases, showing that sexual recombination is the cause of the randomization effect. Conclusions: That the randomization effect applies to the multilocus case and becomes stronger with increasing numbers of loci suggests that it holds under realistic conditions. One may expect, therefore, that in nature the ability of an allele to perform well in interaction with existing genetic combinations is indicative of how well it will perform in a far larger space of potential combinations that have not yet materialized and been tested. Randomization plays a similar role in a statistical test, where it allows one to draw an inference from the outcome of the test in a small sample about its expected outcome in a larger space of possibilities—i.e., to generalize. Our results are relevant to recent theories examining evolution as a learning process. Reviewers: This article was reviewed by David Ardell and Brian Golding.

Original languageEnglish
Article number26
JournalBiology Direct
Volume15
Issue number1
DOIs
StatePublished - Dec 2020

Bibliographical note

Funding Information:
AL was supported by the Israel Science Foundation (grant no. 1986/16). MWF was supported in part by the Center for Computational, Evolutionary and Human Genetics at Stanford. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Publisher Copyright:
© 2020, The Author(s).

Keywords

  • Epistasis
  • Interaction-based evolution
  • Multilocus models
  • Random sampling
  • Randomized algorithms
  • Sex and recombination

ASJC Scopus subject areas

  • Immunology
  • Ecology, Evolution, Behavior and Systematics
  • Modeling and Simulation
  • Biochemistry, Genetics and Molecular Biology (all)
  • Agricultural and Biological Sciences (all)
  • Applied Mathematics

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