Estimating polygenic effects using markers of the entire genome.

摘要: Molecular markers have been used to map quantitative trait loci. However, they are rarely evaluate effects of chromosome segments the entire genome. The original interval-mapping approach and various modified versions it may limited use in evaluating genetic genome because require evaluation multiple models model selection. Here we present a Bayesian regression method simultaneously estimate associated with With method, were able handle situations which number is even larger than observations. key success that allow each marker effect its own variance parameter, turn has prior distribution so can be estimated from data. Under this hierarchical model, large most negligible effects. As result, possible Using data North American Barley Genome Mapping Project double-haploid barley, found gene follows closely an L-shaped Gamma distribution, contrast bell-shaped when interval mapping. In addition, show serves as alternative or better QTL mapping produces clearer signals for QTL. Similar results simulated sets F 2 backcross (BC) families.