Premium
Fisher's geometric model predicts the effects of random mutations when tested in the wild
Author(s) -
Stearns Frank W.,
Fenster Charles B.
Publication year - 2016
Publication title -
evolution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.84
H-Index - 199
eISSN - 1558-5646
pISSN - 0014-3820
DOI - 10.1111/evo.12858
Subject(s) - biology , adaptation (eye) , arabidopsis thaliana , range (aeronautics) , evolutionary biology , fitness landscape , genetic fitness , selection (genetic algorithm) , natural selection , genetics , ecology , gene , mutant , population , demography , composite material , materials science , neuroscience , artificial intelligence , sociology , computer science
Fisher's geometric model of adaptation (FGM) has been the conceptual foundation for studies investigating the genetic basis of adaptation since the onset of the neo Darwinian synthesis. FGM describes adaptation as the movement of a genotype toward a fitness optimum due to beneficial mutations. To date, one prediction of FGM, the probability of improvement is related to the distance from the optimum, has only been tested in microorganisms under laboratory conditions. There is reason to believe that results might differ under natural conditions where more mutations likely affect fitness, and where environmental variance may obscure the expected pattern. We chemically induced mutations into a set of 19 Arabidopsis thaliana accessions from across the native range of A. thaliana and planted them alongside the premutated founder lines in two habitats in the mid‐Atlantic region of the United States under field conditions. We show that FGM is able to predict the outcome of a set of random induced mutations on fitness in a set of A. thaliana accessions grown in the wild: mutations are more likely to be beneficial in relatively less fit genotypes. This finding suggests that FGM is an accurate approximation of the process of adaptation under more realistic ecological conditions.