A1190
Title: Development of a novel GWAS method to detect QTL effects interacting with discrete and continuous genetic architecture
Authors: Kosuke Hamazaki - Center for Advanced Intelligence Project (AIP), RIKEN (Japan) [presenting]
Hiroyoshi Iwata - The University of Tokyo (Japan)
Tristan Mary-Huard - INRAE (France)
Abstract: GWAS (Genome-Wide Association Study) aims at detecting candidate genes (QTL) associated with a target trait via statistical testing. Since a classical GWAS starts with the constitution of a panel of individuals, usually gathered from different populations, many methods have been proposed to control the false positive error rate in large datasets with a strong population structure. However, most methods assume the same QTL effect across populations, which is not always true in the natural biological process. A method has been previously proposed to consider population-specific QTL effects by testing marker effects in each population separately with prior information on population membership for each individual. However, this information on the population structure may only sometimes be available, and sometimes the population structure is more continuous than discrete, in which case the previous methodology cannot be applied. The proposed novel method does not require prior knowledge of the population structure. In the proposed models, we explicitly include an interaction term between an SNP/haplotype block of interest and the genetic background in the conventional SNP-based/haplotype block-based GWAS model. The proposed SNPxGB and HBxGB models can be justified because they can well consider the interaction between the QTLs and the discrete/continuous genetic architecture.
