Meiotic recombination and the factors affecting its rate and fate in nature have inspired many studies in theoretical evolutionary biology. Classical theoretical models have inferred that recombination can be favored under a rather restricted parameter range. Thus, the ubiquity of recombination in nature remains an open question. However, these models assumed constant recombination with an equal rate across all individuals within the population, whereas empirical evidence suggests that recombination may display certain sensitivity to ecological stressors and/or genotype fitness. Models assuming condition-dependent recombination show that such a strategy can often be favored over constant recombination. Moreover, in our recent model with panmictic populations subjected to purifying selection, fitness-dependent recombination was quite often favored even when any constant recombination was rejected. By using numerical modeling, we test whether such a ‘recombination-rescuing potential’ of fitness dependence holds also beyond panmixia, given the recognized effect of mating strategy on the evolution of recombination. We show that deviations from panmixia generally increase the recombination-rescuing potential of fitness dependence, with the strongest effect under intermediate selfing or high clonality. We find that under partial clonality, the evolutionary advantage of fitness-dependent recombination is determined mostly by selection against heterozygotes and additive-by-additive epistasis, while under partial selfing, additive-by-dominance epistasis is also a driver.
Bibliographical noteFunding Information:
The study was supported by the Israel Science Foundation (grant 1844/17 for AK and grant 1154/19 for SH) and the Israeli Ministry of Aliyah and Integration (SR).
© 2021 Elsevier Ltd
- Fitness dependence
- Mixed mating system
- Purifying selection
ASJC Scopus subject areas
- Statistics and Probability
- Modeling and Simulation
- Biochemistry, Genetics and Molecular Biology (all)
- Immunology and Microbiology (all)
- Agricultural and Biological Sciences (all)
- Applied Mathematics