An efficient and robust ABC approach to infer the rate and strength of adaptation

Jesús Murga-Moreno, Sònia Casillas, Antonio Barbadilla, Lawrence Uricchio, David Enard

Research output: Contribution to journalArticlepeer-review

Abstract

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

Original languageEnglish (US)
Article numberjkae031
JournalG3: Genes, Genomes, Genetics
Volume14
Issue number4
DOIs
StatePublished - Apr 2024

Keywords

  • Mcdonald and Kreitman test
  • natural selection
  • viral interacting proteins

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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