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Activity Number: 285
Type: Invited
Date/Time: Tuesday, August 2, 2016 : 8:30 AM to 10:20 AM
Sponsor: WNAR
Abstract #318298
Title: Statistical Methods for Joint Genetic Mapping Based on Sequence Data of Two Interactive Organisms
Author(s): Mary Sara McPeek* and Miaoyan Wang
Companies: The University of Chicago and The University of Chicago
Keywords: genetic mapping ; sequence data ; mixed models ; GWAS

We consider the problem of how to test for genetic association and gene-gene interaction in a genome-wide association study that involves two interactive organisms. Specifically, we consider a host-pathogen interactive system in which the response, infection, can depend on the specific pairing of host and pathogen. We develop both Gaussian and binomial-like, two-way, mixed-effects models whose features include random and fixed effects for the two organisms and interactions between organisms. We analyze an Arabidopsis-Xanthomonas data set from Joy Bergelson's lab. Because many SNP sites are present in only a subset of the sampled Xanthomonas strains, we extend the calculation of the empirical genetic relatedness matrix for Xanthomonas to this case. We test for association of the trait with individual SNPs and with SNP pairs that include one SNP from each organism. We find that the infection response in the Arabidopsis-Xanthomonas pathosystem has a clear host-pathogen specificity, i.e., certain Arabidopsis SNPs exhibit strong genetic effects only when paired with certain Xanthomonas SNPs. This is joint work with Hana Lee, Chris Meyers, Fabrice Roux and Joy Bergelson.

Authors who are presenting talks have a * after their name.

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