Estimating the parameters of selection on nonsynonymous mutations in Drosophila pseudoobscura and D. miranda

Penelope R Haddrill, Laurence Loewe, Brian Charlesworth

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

We present the results of surveys of diversity in sets of >40 X-linked and autosomal loci in samples from natural populations of Drosophila miranda and D. pseudoobscura, together with their sequence divergence from D. affinis. Mean silent site diversity in D. miranda is approximately one-quarter of that in D. pseudoobscura; mean X-linked silent diversity is about three-quarters of that for the autosomes in both species. Estimates of the distribution of selection coefficients against heterozygous, deleterious nonsynonymous mutations from two different methods suggest a wide distribution, with coefficients of variation greater than one, and with the average segregating amino acid mutation being subject to only very weak selection. Only a small fraction of new amino acid mutations behave as effectively neutral, however. A large fraction of amino acid differences between D. pseudoobscura and D. affinis appear to have been fixed by positive natural selection, using three different methods of estimation; estimates between D. miranda and D. affinis are more equivocal. Sources of bias in the estimates, especially those arising from selection on synonymous mutations and from the choice of genes, are discussed and corrections for these applied. Overall, the results show that both purifying selection and positive selection on nonsynonymous mutations are pervasive.

Original languageEnglish
Pages (from-to)1381-1396
Number of pages16
JournalGenetics
Volume185
Issue number4
DOIs
Publication statusPublished - Aug 2010

Keywords

  • adaptation, physiological
  • algorithms
  • amino acids
  • animals
  • drosophila
  • drosophila proteins
  • genes, x-linked
  • genetic variation
  • models, genetic
  • molecular sequence data
  • mutation
  • polymorphism, genetic
  • selection, genetic
  • sequence analysis, DNA
  • species specificity

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