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Published online before print March 12, 2003, 10.1101/gr.387103
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Vol 13, Issue 4, 635-643, April 2003

METHODS

Novel Multilocus Measure of Linkage Disequilibrium to Estimate Past Effective Population Size

Ben J. Hayes1,4, Peter M. Visscher2, Helen C. McPartlan1 and Mike E. Goddard1,3

1Victorian Institute of Animal Science, Department of Natural Resources and Environment, Attwood, Victoria, 3049, Australia;2 University of Edinburgh, Edinburgh EH9 3JG, Scotland, UK;3 Institute of Land and Food Resources, University of Melbourne, Parkville, Victoria, 3052, Australia

Linkage disequilibrium (LD) between densely spaced, polymorphic genetic markers in humans and other species contains information about historical population size. Inferring past population size is of interest both from an evolutionary perspective (e.g., testing the "out of Africa" hypothesis of human evolution) and to improve models for mapping of disease and quantitative trait genes. We propose a novel multilocus measure of LD, the chromosome segment homozygosity (CSH). CSH is defined for a specific chromosome segment, up to the full length of the chromosome. In computer simulations CSH was generally less variable than the r2 measure of LD, and variability of CSH decreased as the number of markers in the chromosome segment was increased. The essence and utility of our novel measure is that CSH over long distances reflects recent effective population size (N), whereas CSH over small distances reflects the effective size in the more distant past. We illustrate the utility of CSH by calculating CSH from human and dairy cattle SNP and microsatellite marker data, and predicting N at various times in the past for each species. Results indicated an exponentially increasing N in humans and a declining N in dairy cattle. CSH is a valuable statistic for inferring population histories from haplotype data, and has implications for mapping of disease loci.


4 Corresponding author.

E-MAIL Ben.Hayes{at}nre.vic.gov.au; FAX 61 39217 4359.

Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.387103. Article published online before print in March 2003.


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