ϟ
 
DOI: 10.1111/mec.16900
¤ OpenAccess: Hybrid
This work has “Hybrid” OA status. This means it is free under an open license in a toll-access journal.

Rapid adaptation of recombining populations on tunable fitness landscapes

Juan Li,André Amado,Claudia Bank

Epistasis
Biology
Fitness landscape
2023
Abstract How does standing genetic variation affect polygenic adaptation in recombining populations? Despite a large body of work in quantitative genetics, epistatic and weak additive fitness effects among simultaneously segregating genetic variants are difficult to capture experimentally or to predict theoretically. In this study, we simulated adaptation on fitness landscapes with tunable ruggedness driven by standing genetic variation in recombining populations. We confirmed that recombination hinders the movement of a population through a rugged fitness landscape. When surveying the effect of epistasis on the fixation of alleles, we found that the combined effects of high ruggedness and high recombination probabilities lead to preferential fixation of alleles that had a high initial frequency. This indicates that positive epistatic alleles escape from being broken down by recombination when they start at high frequency. We further extract direct selection coefficients and pairwise epistasis along the adaptive path. When taking the final fixed genotype as the reference genetic background, we observe that, along the adaptive path, beneficial direct selection appears stronger and pairwise epistasis weaker than in the underlying fitness landscape. Quantitatively, the ratio of epistasis and direct selection is smaller along the adaptive path () than expected. Thus, adaptation on a rugged fitness landscape may lead to spurious signals of direct selection generated through epistasis. Our study highlights how the interplay of epistasis and recombination constrains the adaptation of a diverse population to a new environment.
Loading...
    Cite this:
Generate Citation
Powered by Citationsy*
    Rapid adaptation of recombining populations on tunable fitness landscapes” is a paper by Juan Li André Amado Claudia Bank published in 2023. It has an Open Access status of “hybrid”. You can read and download a PDF Full Text of this paper here.