How predictable is adaptation from standing genetic variation? Experimental evolution in Drosophila highlights the central role of redundancy and linkage disequilibrium

Philos Trans R Soc Lond B Biol Sci. 2023 May 22;378(1877):20220046. doi: 10.1098/rstb.2022.0046. Epub 2023 Apr 3.

Abstract

Experimental evolution is well-suited to test the predictability of evolution without the confounding effects of inaccurate forecasts about future environments. Most of the literature about parallel (and thus predictable) evolution has been carried out in asexual microorganisms, which adapt by de novo mutations. Nevertheless, parallel evolution has also been studied in sexual species at the genomic level. Here, I review the evidence for parallel evolution in Drosophila, the best-studied obligatory outcrossing model for adaptation from standing genetic variation in the laboratory. Similar to asexual microorganisms, evidence for parallel evolution varies between the focal hierarchical levels. Selected phenotypes consistently respond in a very predicable way, but the underlying allele frequency changes are much less predictable. The most important insight is that the predictability of the genomic selection response for polygenic traits depends highly on the founder population and to a much lesser extent on the selection regime. This implies that predicting adaptive genomic response is challenging and requires a good understanding of the adaptive architecture (including linkage disequilibrium) in the ancestral populations. This article is part of the theme issue 'Interdisciplinary approaches to predicting evolutionary biology'.

Keywords: adaptive architecture; experimental evolution; laboratory natural selection; parallel evolution; predicting evolution; truncating selection.

Publication types

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

MeSH terms

  • Adaptation, Physiological* / genetics
  • Animals
  • Drosophila* / genetics
  • Evolution, Molecular
  • Gene Frequency
  • Genetic Variation
  • Linkage Disequilibrium
  • Selection, Genetic