Genetics, Vol. 165, 1579-1586, November 2003, Copyright © 2003

Detecting Population Growth, Selection and Inherited Fertility From Haplotypic Data in Humans

Frédéric Austerlitza, Luba Kalaydjievab,c, and Evelyne Heyerd
a Laboratoire Ecologie, Systématique et Evolution, Université Paris-Sud, F-91405 Orsay, France,
b Centre for Human Genetics, Edith Cowan University, Perth, Australia WA 6027,
c Western Australian Institute for Medical Research, Perth, Australia WA 6027
d Centre National de la Recherche Scientifique—Laboratoire d'Anthropologie Biologique, Musée de l'Homme (MNHN), F-75116 Paris, France

Corresponding author: Frédéric Austerlitz, Systématique et Evolution, UMR CNRS 8079, Université Paris-Sud, Bâtiment 362, F-91405 Orsay Cedex, France., frederic.austerlitz{at}ese.u-psud.fr (E-mail)

Communicating editor: M. A. ASMUSSEN

The frequency of a rare mutant allele and the level of allelic association between this allele and one or several closely linked markers are frequently measured in genetic epidemiology. Both quantities are related to the time elapsed since the appearance of the mutation in the population and the intrinsic growth rate of the mutation (which may be different from the average population growth rate). Here, we develop a method that uses these two kinds of genetic data to perform a joint estimation of the age of the mutation and the minimum growth rate that is compatible with its present frequency. In absence of demographic data, it provides a useful estimate of population growth rate. When such data are available, contrasts among estimates from several loci allow demographic processes, affecting all loci similarly, to be distinguished from selection, affecting loci differently. Testing these estimates on populations for which data are available for several disorders shows good congruence with demographic data in some cases whereas in others higher growth rates are obtained, which may be the result of selection or hidden demographic processes.





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