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MBE Advance Access published online on December 5, 2006
Molecular Biology and Evolution, doi:10.1093/molbev/msl191
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© The Author 2006. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Research Article

Microsatellite Null Alleles and Estimation of Population Differentiation

Marie-Pierre Chapuis1,2,3 and Arnaud Estoup1

1 Centre de Biologie et de Gestion des Populations, Institut National pour la Recherche Agronomique, Campus International de Baillarguet CS 30016, 34988 Montferrier / Lez, France
2 Génétique et Evolution des Maladies Infectieuses, UMR 274 CNRS-IRD, 911 avenue Agropolis, B.P. 64501, 34394 Montpellier Cedex 5, France
3 Centre de coopération internationale en recherche agronomique pour le développement, Campus International de Baillarguet, 34398 Montpellier Cedex 5, France

Correspondence: Marie-Pierre CHAPUIS, Centre de Biologie et de Gestion des Populations, Institut National de la Recherche Agronomique, Campus International de Baillarguet CS 30 016, 34988 Montferrier / Lez, FRANCE, Phone: +33 (0)4.99.62.33.31, Fax: +33 (0)4.99.62.33.45, E-mail: chapuimp{at}ensam.inra.fr

Microsatellite null alleles are commonly encountered in population genetics studies, yet little is known about their impact on the estimation of population differentiation. Computer simulations based on the coalescent were used to investigate the evolutionary dynamics of null alleles, their impact on FST and genetic distances, and the efficiency of estimators of null allele frequency. Further, we explored how the existing method for correcting genotype data for null alleles performed in estimating FST and genetic distances and we compared this method to a new method proposed here (for FST only). Null alleles were likely to be encountered in populations with a large effective size, with an unusually high mutation rate in the flanking regions, and that have diverged from the population from which the cloned allele state was drawn and the primers designed. When populations were significantly differentiated, FST and genetic distances were overestimated in the presence of null alleles. Frequency of null alleles was estimated precisely with the algorithm presented in Dempster, Laird, and Rubin (1977). The conventional method for correcting genotype data for null alleles did not provide an accurate estimate of FST and genetic distances. However, the use of the Cavalli-Sforza and Edwards’ (1967) genetic distance corrected by the conventional method gave better estimates than those obtained without correction. FST estimation from corrected genotype frequencies performed well when restricted to visible allele sizes. Both the proposed method and the traditional correction method have been implemented in a program that is available free of charge at http://www.montpellier.inra.fr/URLB/. We used two published microsatellite datasets based on original and redesigned pairs of primers to empirically confirm our simulation results.

Key Words: coalescent • microsatellite • null alleles • population differentiation • F-statistics • genetic distances


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