A Statistical Variance Components Framework for Mapping Imprinted Quantitative Trait Locus in Experimental Crosses

Current methods for mapping imprinted quantitative trait locus (iQTL) with inbred linecrosses assume fixed QTL effects. When an iQTL segregates in experimental line crosses,combining different line crosses with similar genetic background can improve the accuracyof iQTLs inference. In this article, we develop a general interval-based statistical variancecomponents framework to map iQTLs underlying complex traits by combining differentbackcross line crosses. We propose a new iQTL variance partition method based on thenature of marker alleles shared identical-by-decent (IBD) in inbred lines. Maternal effect isadjusted when testing imprinting. Efficient estimation methods with the maximum likelihoodand the restricted maximum likelihood are derived and compared. Statistical properties ofthe proposed mapping strategy are evaluated through extensive simulations under differentsampling designs. An extension to multiple QTL analysis is given. The proposed methodwill greatly facilitate genetic dissection of imprinted complex traits in inbred line crosses