ARS | Publication request: Characterization of Linkage Disequilibrium in a Rainbow Trout Broodstock Population

Submitted to: Plant and Animal Genome Conference
Publication Type: Abstract
Publication Acceptance Date: January 12, 2008
Publication Date: January 12, 2008
Citation: Rexroad III, C.E., Vallejo, R.L. 2008. Characterization of Linkage Disequilibrium in a Rainbow Trout Broodstock Population. Plant and Animal Genome Conference.

Technical Abstract: The development of selective breeding strategies employing marker assisted selection in species with low to medium density genetic maps must account for the non-random association of alleles between linked loci. To conduct efficient association studies and estimate the average size of haplotypes genome-wide, we characterized the extent of linkage disequilibrium in the USDA/ARS National Center for Cool and Cold Water Aquaculture selective breeding population. Unrelated individuals (n=96) representing the 2005/2006 brood classes were genotyped with all of the non-duplicated microsatellites (n=49) from four rainbow trout linkage groups. This included markers from the sex chromosome, the chromosome with the largest linkage group (in cM, Omy14), and paralogous regions of two chromosomes (Omy13, Omy17) containing duplicated loci resulting from an evolutionarily recent genome duplication event. Population genetic parameters including allele frequencies, observed heterozygosities, polymorphism information content, Hardy-Weinberg Equilibrium status, effective population size, and linkage disequilibrium (r2) were estimated. The average heterozygosity for all loci was estimated to be 78%, 19 loci were observed to depart from Hardy-Wienberg Equilibrium. The effective population size was estimated to be 406, in actuality 475 breeders contributed to the 2005/2006 brood class. The genome-wide estimate for extent of significant linkage disequilibrium (r2 >.2) was estimated to be about 4 cM which is very similar to other agriculturally important livestock species. This information will be useful as we design association studies with polymorphic markers representing genes and identify loci for use in marker assisted selection schemes.