P0904 Characterizing genetic architecture in recurrently selected populations: a new estimator of coancestry

Yogasudha Veturi , University of Delaware, Newark, DE
Randall J. Wisser , University of Delaware, Newark, DE
Association or linkage disequilibrium (LD) mapping allows for the identification of quantitative trait loci based on correlations between sequence and trait variation.  Genetic structure refers to different levels of genetic relatedness between individuals in a population.   Factors such as recombination, independent assortment, migration, mutation, and genetic drift influence the level of familial relatedness (coancestry) and consequently LD to create a hierarchy of genetic structure in the population.  Controlling for genetic structure in association analysis helps limit false positive associations and minimizes bias in the estimation of allele effects.  We are developing a new method to characterize the genetic basis of crop improvement, exploiting populations subjected to recurrent selection. Armed with knowledge of a population’s founders, an estimator is proposed for calculating coefficients of coancestry in a closed breeding population.  Weights based on identity-by-state information of the founders are used to arrive at estimates of identity-by-descent for the derived population.  Computer simulation is used to examine properties of the estimator.  The interplay of different genetic factors (recombination, selection, drift) on the performance of this estimator is studied.  Using the estimated coancestry or relationship matrix to model genetic covariance, the application of association mapping in different recurrently selected populations is examined.  The latest results of this study will be presented. Keywords: association mapping, covariance, kinship, identity-by-descent, linkage/ gametic-phase disequilibrium, recurrent selection