Genetics, Vol. 158, 1811-1823, August 2001, Copyright © 2001

Interpretation of Variation Across Marker Loci as Evidence of Selection

Renaud Vitalisa,b,c, Kevin Dawsona,d, and Pierre Boursota
a Laboratoire Génome, Populations et Interactions, Université Montpellier II, 34095 Montpellier Cedex 05, France,
b Laboratoire Génétique et Environment, Institut des Sciences de l'Évolution de Montpellier, Université Montpellier II, 34095 Montpellier Cedex 05, France,
c Station Biologique de la Tour du Valat, 13200 Arles, France
d I.A.C.R. Long Ashton Research Station, Department of Agricultural Science, University of Bristol, Bristol BS41 9AF, United Kingdom

Corresponding author: Renaud Vitalis, Laboratoire Génétique et Environnement, C.C. 065, Institut des Sciences de l'Évolution de Montpellier, Université Montpellier II, Place Eugène Bataillon, 34095 Montpellier Cedex 05, France., vitalis{at}isem.univ-montp2.fr (E-mail)

Communicating editor: J. HEY

Population structure and history have similar effects on the genetic diversity at all neutral loci. However, some marker loci may also have been strongly influenced by natural selection. Selection shapes genetic diversity in a locus-specific manner. If we could identify those loci that have responded to selection during the divergence of populations, then we may obtain better estimates of the parameters of population history by excluding these loci. Previous attempts were made to identify outlier loci from the distribution of sample statistics under neutral models of population structure and history. Unfortunately these methods depend on assumptions about population structure and history that usually cannot be verified. In this article, we define new population-specific parameters of population divergence and construct sample statistics that are estimators of these parameters. We then use the joint distribution of these estimators to identify outlier loci that may be subject to selection. We found that outlier loci are easier to recognize when this joint distribution is conditioned on the total number of allelic states represented in the pooled sample at each locus. This is so because the conditional distribution is less sensitive to the values of nuisance parameters.





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