The divergence of mean phenotypes under persistent directional selection

Archana Devi, Gil Speyer, Michael Lynch

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Numerous organismal traits, particularly at the cellular level, are likely to be under persistent directional selection across phylogenetic lineages. Unless all mutations affecting such traits have large enough effects to be efficiently selected in all species, gradients in mean phenotypes are expected to arise as a consequence of differences in the power of random genetic drift, which varies by approximately five orders of magnitude across the Tree of Life. Prior theoretical work examining the conditions under which such gradients can arise focused on the simple situation in which all genomic sites affecting the trait have identical and constant mutational effects. Here, we extend this theory to incorporate the more biologically realistic situation in which mutational effects on a trait differ among nucleotide sites. Pursuit of such modifications leads to the development of semi-analytic expressions for the ways in which selective interference arises via linkage effects in single-effects models, which then extend to more complex scenarios. The theory developed clarifies the conditions under which mutations of different selective effects mutually interfere with each others' fixation and shows how variance in effects among sites can substantially modify and extend the expected scaling relationships between mean phenotypes and effective population sizes.

Original languageEnglish (US)
Article numberiyad091
JournalGenetics
Volume224
Issue number3
DOIs
StatePublished - Jul 2023

Keywords

  • evolutionary divergence
  • mutation bias
  • phenotypic divergence
  • phenotypic scaling
  • random genetic drift
  • selective interference

ASJC Scopus subject areas

  • General Medicine

Fingerprint

Dive into the research topics of 'The divergence of mean phenotypes under persistent directional selection'. Together they form a unique fingerprint.

Cite this