Large-effect flowering time mutations reveal conditionally adaptive paths through fitness landscapes in Arabidopsis thaliana

Proc Natl Acad Sci U S A. 2019 Sep 3;116(36):17890-17899. doi: 10.1073/pnas.1902731116. Epub 2019 Aug 16.

Abstract

Contrary to previous assumptions that most mutations are deleterious, there is increasing evidence for persistence of large-effect mutations in natural populations. A possible explanation for these observations is that mutant phenotypes and fitness may depend upon the specific environmental conditions to which a mutant is exposed. Here, we tested this hypothesis by growing large-effect flowering time mutants of Arabidopsis thaliana in multiple field sites and seasons to quantify their fitness effects in realistic natural conditions. By constructing environment-specific fitness landscapes based on flowering time and branching architecture, we observed that a subset of mutations increased fitness, but only in specific environments. These mutations increased fitness via different paths: through shifting flowering time, branching, or both. Branching was under stronger selection, but flowering time was more genetically variable, pointing to the importance of indirect selection on mutations through their pleiotropic effects on multiple phenotypes. Finally, mutations in hub genes with greater connectedness in their regulatory networks had greater effects on both phenotypes and fitness. Together, these findings indicate that large-effect mutations may persist in populations because they influence traits that are adaptive only under specific environmental conditions. Understanding their evolutionary dynamics therefore requires measuring their effects in multiple natural environments.

Keywords: branching; fitness landscape; flowering time; mutation; natural selection.

Publication types

  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adaptation, Biological*
  • Arabidopsis / physiology*
  • Biological Evolution
  • Computational Biology / methods
  • Flowers / physiology*
  • Gene Expression Profiling
  • Genetic Association Studies
  • Genotype
  • Mutation*
  • Phenotype
  • Seasons
  • Selection, Genetic*
  • Transcriptome