title: A statistical model for dissecting genomic imprinting through genetic mapping.
abstract: As a result of nonequivalent genetic contribution of maternal and paternal genomes to offsprings, genomic imprinting or called parent-of-origin effect, has been broadly identified in plants, animals and humans. Its role in shaping organism's development has been unanimously recognized. However, statistical methods for identifying imprinted quantitative trait loci (iQTL) and estimating the imprinted effect have not been well developed. In this article, we propose an efficient statistical procedure for genomewide estimating and testing the effects of significant iQTL underlying the quantitative variation of interested traits. The developed model can be applied to two different genetic cross designs, backcross and F(2) families derived from inbred lines. The proposed procedure is built within the maximum likelihood framework and implemented with the EM algorithm. Extensive simulation studies show that the proposed model is well performed in a variety of situations. To demonstrate the usefulness of the proposed approach, we apply the model to a published data in an F(2) family derived from LG/S and SM/S mouse stains. Two partially maternal imprinting iQTL are identified which regulate the growth of body weight. Our approach provides a testable framework for identifying and estimating iQTL involved in the genetic control of complex traits.
authors.affiliation: Department of Statistics and Probability, Michigan State University, A-411 Wells Hall, East Lansing, MI 48824, USA. cui@stt.msu.edu
authors.forename: Yuehua
authors.initials: Y
authors.lastname: Cui
authors.forename: James M
authors.initials: JM
authors.lastname: Cheverud
authors.forename: Rongling
authors.initials: R
authors.lastname: Wu
mesh_terms: D000465:Algorithms; D000818:Animals; D001835:Body Weight; D002874:Chromosome Mapping / Q000379:methods*; D003433:Crosses, Genetic; D005821:Genetic Techniques; D016678:Genome; D018392:Genomic Imprinting; D006801:Humans; D016013:Likelihood Functions; D051379:Mice; D008957:Models, Genetic; D015233:Models, Statistical; D040641:Quantitative Trait Loci; D012107:Research Design