Recombination and mutational robustness in neutral fitness landscapes

PLoS Comput Biol. 2019 Aug 15;15(8):e1006884. doi: 10.1371/journal.pcbi.1006884. eCollection 2019 Aug.

Abstract

Mutational robustness quantifies the effect of random mutations on fitness. When mutational robustness is high, most mutations do not change fitness or have only a minor effect on it. From the point of view of fitness landscapes, robust genotypes form neutral networks of almost equal fitness. Using deterministic population models it has been shown that selection favors genotypes inside such networks, which results in increased mutational robustness. Here we demonstrate that this effect is massively enhanced by recombination. Our results are based on a detailed analysis of mesa-shaped fitness landscapes, where we derive precise expressions for the dependence of the robustness on the landscape parameters for recombining and non-recombining populations. In addition, we carry out numerical simulations on different types of random holey landscapes as well as on an empirical fitness landscape. We show that the mutational robustness of a genotype generally correlates with its recombination weight, a new measure that quantifies the likelihood for the genotype to arise from recombination. We argue that the favorable effect of recombination on mutational robustness is a highly universal feature that may have played an important role in the emergence and maintenance of mechanisms of genetic exchange.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology
  • Computer Simulation
  • Epistasis, Genetic
  • Evolution, Molecular
  • Female
  • Genetic Fitness*
  • Genotype
  • Male
  • Models, Genetic*
  • Mutation*
  • Recombination, Genetic*
  • Reproduction / genetics
  • Selection, Genetic

Grants and funding

AK and JK acknowledge support by Deutsche Forschungsgemeinschaft (DFG, https://www.dfg.de/) through CRC 1310 Predictability in evolution and SPP 1590 Probabilistic structures in evolution. SCP acknowledges support by the Basic Science Research Program through the National Research Foundation of Korea (NRF, https://www.nrf.re.kr/eng/main) funded by the Ministry of Science and ICT (Grant No. 2017R1D1A1B03034878). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.