Fitness effects of mutation in natural populations of Arabidopsis thaliana reveal a complex influence of local adaptation. (31st December 2020)

• Record Type: Journal Article
• Authors: Weng, Mao‐Lun; Ågren, Jon; Imbert, Eric; Nottebrock, Henning; Rutter, Matthew T.; Fenster, Charles B.
• Is Part Of: Evolution. Volume 75:Number 2(2021)
• Page Start: 330
• Page End: 348
• Publication Date: 2020-12-31
• Subjects: Fisher's geometric model -- MA lines -- mutations -- mutational effect -- mutational variance -- standing genetic variation; Evolution -- Periodicals; Heredity -- Periodicals; Évolution (Biologie) -- Périodiques; Hérédité -- Périodiques; 338.47004094
• DOI: 10.1111/evo.14152
• Languages: English
• ISSNs: 0014-3820

Abstract

Abstract: Little is empirically known about the contribution of mutations to fitness in natural environments. However, Fisher's Geometric Model (FGM) provides a conceptual foundation to consider the influence of the environment on mutational effects. To quantify mutational properties in the field, we established eight sets of MA lines (7‐10 generations) derived from eight founders collected from natural populations of Arabidopsis thaliana from French and Swedish sites, representing the range margins of the species in Europe. We reciprocally planted the MA lines and their founders at French and Swedish sites, allowing us to test predictions of FGM under naturally occurring environmental conditions. The performance of the MA lines relative to each other and to their respective founders confirmed some and contradicted other predictions of the FGM: the contribution of mutation to fitness variance increased when the genotype was in an environment where its fitness was low, that is, in the away environment, but mutations were more likely to be beneficial when the genotype was in its home environment. Consequently, environmental context plays a large role in the contribution of mutations to the evolutionary process and local adaptation does not guarantee that a genotype is at or close to its optimum.