Genetics, Vol. 148, 1269-1284, March 1998, Copyright © 1998

Heterogeneity of Microsatellite Mutations Within and Between Loci, and Implications for Human Demographic Histories

Anna Di Rienzoa,f, Peter Donnellyb, Chris Toomajiana, Bronwyn Siska, Adrian Hillc, Maria Luiza Petzl-Erlerd, G. Ken Hainese, and David H. Barchf
a Department of Anthropology, Northwestern University, Evanston, Illinois 60208,
b Department of Statistics, University of Oxford, Oxford, OX1 3TG, United Kingdom,
c Wellcome Trust Center for Human Genetics and Institute of Molecular Medicine, University of Oxford, Oxford, OX3 9DU United Kingdom,
d Department of Genetics, Federal University of Paraná, 81531-970 Curitiba, Brazil,
e Department of Pathology, Northwestern University Medical School, Chicago, Illinois 60611
f Lurie Cancer Center, Northwestern University Medical School, Chicago, Illinois 60611

Corresponding author: Anna Di Rienzo, Center for Medical Genetics, University of Chicago, 924 E. 57th St., BSLC Rm. 116, Chicago, IL 60637, dirienzo{at}genetics.uchicago.edu (E-mail).

Communicating editor: M. SLATKIN

Microsatellites have been widely used to reconstruct human evolution. However, the efficient use of these markers relies on information regarding the process producing the observed variation. Here, we present a novel approach to the locus-by-locus characterization of this process. By analyzing somatic mutations in cancer patients, we estimated the distributions of mutation size for each of 20 loci. The same loci were then typed in three ethnically diverse population samples. The generalized stepwise mutation model was used to test the predicted relationship between population and mutation parameters under two demographic scenarios: constant population size and rapid expansion. The agreement between the observed and expected relationship between population and mutation parameters, even when the latter are estimated in cancer patients, confirms that somatic mutations may be useful for investigating the process underlying population variation. Estimated distributions of mutation size differ substantially amongst loci, and mutations of more than one repeat unit are common. A new statistic, the normalized population variance, is introduced for multilocus estimation of demographic parameters, and for testing demographic scenarios. The observed population variation is not consistent with a constant population size. Time estimates of the putative population expansion are in agreement with those obtained by other methods.




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