Design and Analysis of Reference Populations to Detect Signatures of Selection from Genomic Data

Discovery of QTLs in genomic data associated with traits of interest has long been a goal of biotechnology. This increasingly popular approach is intriguing, but not without risks, primarily those associated with false positives due to random genetic drift. Secondary to this concern is the ability to fine map regions under selection. Linkage disequilibrium (LD) often limits the ability fine map. The goal of this research, as related to poultry, was to develop recommendations for design and analysis of resource populations to minimize false positives and maximize the ability to fine map QTL. These recommendations are being implemented in a planned new resource population for Marek's disease in poultry

Source of funding: NIAAA P60 AA07611