Open AccessEvolution of flowering time in a selfing annual plant: Roles of adaptation and genetic drift
Author(s) -
Gay Laurène,
Dhinaut Julien,
Jullien Margaux,
Vitalis Renaud,
Navascués Miguel,
Ranwez Vincent,
Ronfort Joëlle
Publication year - 2022
Publication title -
ecology and evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.17
H-Index - 63
ISSN - 2045-7758
DOI - 10.1002/ece3.8555
Subject(s) - selfing , biology , medicago truncatula , population , adaptation (eye) , selection (genetic algorithm) , trait , genetic drift , evolutionary biology , effective population size , local adaptation , experimental evolution , population size , ecology , genetic variation , genetics , gene , demography , symbiosis , neuroscience , artificial intelligence , sociology , bacteria , computer science , programming language
Abstract Resurrection studies are a useful tool to measure how phenotypic traits have changed in populations through time. If these trait modifications correlate with the environmental changes that occurred during the time period, it suggests that the phenotypic changes could be a response to selection. Selfing, through its reduction of effective size, could challenge the ability of a population to adapt to environmental changes. Here, we used a resurrection study to test for adaptation in a selfing population of Medicago truncatula , by comparing the genetic composition and flowering times across 22 generations. We found evidence for evolution toward earlier flowering times by about two days and a peculiar genetic structure, typical of highly selfing populations, where some multilocus genotypes (MLGs) are persistent through time. We used the change in frequency of the MLGs through time as a multilocus fitness measure and built a selection gradient that suggests evolution toward earlier flowering times. Yet, a simulation model revealed that the observed change in flowering time could be explained by drift alone, provided the effective size of the population is small enough (<150). These analyses suffer from the difficulty to estimate the effective size in a highly selfing population, where effective recombination is severely reduced.