Hitchhiking effects of recurrent beneficial amino acid substitutions in the Drosophila melanogaster genome

Peter Andolfatto

Research output: Contribution to journalArticlepeer-review

152 Scopus citations

Abstract

Several recent studies have estimated that a large fraction of amino acid divergence between species of Drosophila was fixed by positive selection, using statistical approaches based on the McDonald-Kreitman test. However, little is known about associated selection coefficients of beneficial amino acid mutations. Recurrent selective sweeps associated with adaptive substitutions should leave a characteristic signature in genome variability data that contains information about the frequency and strength of selection. Here, I document a significant negative correlation between the level and the frequency of synonymous site polymorphism and the rate of protein evolution in highly recombining regions of the X chromosome of D. melanogaster. This pattern is predicted by recurrent adaptive protein evolution and suggests that adaptation is an important determinant of patterns of neutral variation genome-wide. Using a maximum likelihood approach, I estimate the product of the rate and strength of selection under a recurrent genetic hitchhiking model, λ̄2N es ∼ 3 × 10-8. Using an approach based on the McDonald-Kreitman test, I estimate that ∼50% of divergent amino acids were driven to fixation by positive selection, implying that beneficial amino acid substitutions are of weak effect on average, on the order of 10-5 (i.e., 2Nes ∼ 40). Two implications of these results are that most adaptive substitutions will be difficult to detect in genome scans of selection and that population size (and genetic drift) may be an important determinant of the evolutionary dynamics of protein adaptation.

Original languageEnglish (US)
Pages (from-to)1755-1762
Number of pages8
JournalGenome Research
Volume17
Issue number12
DOIs
StatePublished - Dec 2007

All Science Journal Classification (ASJC) codes

  • Genetics(clinical)
  • Genetics

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