A genome-wide approach to identify genetic loci with a signature of natural selection in the Irish population

Genome Biol. 2006;7(8):R74. doi: 10.1186/gb-2006-7-8-r74. Epub 2006 Aug 11.

Abstract

Background: In this study we present a single population test (Ewens-Waterson) applied in a genomic context to investigate the presence of recent positive selection in the Irish population. The Irish population is an interesting focus for the investigation of recent selection since several lines of evidence suggest that it may have a relatively undisturbed genetic heritage.

Results: We first identified outlier single nucleotide polymorphisms (SNPs), from previously published genome-wide data, with high FST branch specification in a European-American population. Eight of these were chosen for further analysis. Evidence for selective history was assessed using the Ewens-Watterson's statistic calculated using Irish genotypes of microsatellites flanking the eight outlier SNPs. Evidence suggestive of selection was detected in three of these by comparison with a population-specific genome-wide empirical distribution of the Ewens-Watterson's statistic.

Conclusion: The cystic fibrosis gene, a disease that has a world maximum frequency in Ireland, was among the genes showing evidence of selection. In addition to the demonstrated utility in detecting a signature of natural selection, this approach has the particular advantage of speed. It also illustrates concordance between results drawn from alternative methods implemented in different populations.

Publication types

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

MeSH terms

  • Cystic Fibrosis Transmembrane Conductance Regulator / genetics
  • DNA Primers
  • Gene Frequency
  • Genetic Variation*
  • Genome, Human / genetics*
  • Genomics / methods*
  • Humans
  • Ireland
  • Microsatellite Repeats / genetics
  • Polymorphism, Single Nucleotide / genetics
  • Selection, Genetic*

Substances

  • DNA Primers
  • Cystic Fibrosis Transmembrane Conductance Regulator