title: Bayesian analysis of additive epistasis arising from new mutations in mice.
abstract: The continuous uploading of polygenic additive mutational variability has been reported in several studies in laboratory species with an inbred genetic background. These studies have focused on the direct contribution of new mutations without considering the possibility of epistatic effects derived from the interaction of new mutations with pre-existing polymorphisms. In this work we focused on this main topic and analysed the statistical and biological relevance of the epistatic variance for 9 week body weight in two populations of inbred mice. We developed a new linear mixed model parameterization where founder-related additive genetic variability, additive mutational variability and the interaction terms between both sources of variation were accounted for under a Bayesian design and without requiring the inversion of a matrix of epistatic genetic covariances. The analyses focused on a six-generations data set from C57BL/6J mice (n = 3736) and a five-generations data set from C57BL/6J(hg/hg) mice (n = 2843). The deviance information criterion (DIC) clearly favoured the model accounting for epistatic variability with reductions larger than 50 DIC units in both populations. Modal estimates for founder related, mutational and epistatic heritabilities were 0·068, 0·011 and 0·095 in C57BL/6J and 0·060, 0·010 and 0·113 in C57BL/6J(hg/hg), ruling out any doubt about the biological relevance of epistasis originating from new mutations in mice. These results contribute new insights on the relevance of epistasis in the genetic architecture of mammals and serve as an important component of an additional source of genetic heterogeneity for inbred strains of laboratory mice.
authors.affiliation: Departament de Ciència Animal i dels Aliments,Universitat Autònoma de Barcelona,08193 Bellaterra, Barcelona,Spain.
authors.forename: Joaquim
authors.initials: J
authors.lastname: Casellas
authors.affiliation: Departments of Animal Sciences, Dairy Science and Biostatistics and Medical Information,University of Wisconsin,Madison, Wisconsin 53706,USA.
authors.forename: Daniel
authors.initials: D
authors.lastname: Gianola
authors.affiliation: Department of Animal Science,University of California,Davis, California 95616-8521,USA.
authors.forename: Juan F
authors.initials: JF
authors.lastname: Medrano
mesh_terms: D000818:Animals; D001499:Bayes Theorem; D001835:Body Weight / Q000235:genetics; D004843:Epistasis, Genetic / Q000235:genetics*; D018740:Genetic Heterogeneity; D016014:Linear Models; D051379:Mice; D008810:Mice, Inbred C57BL / Q000235:genetics*; D009154:Mutation / Q000235:genetics*; D010375:Pedigree; D010641:Phenotype