Estimation of additive, dominance and epistatic variance components using finite locus models implemented with a single-site Gibbs and a descent graph sampler

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dc.contributor.authorDu, F. X.en
dc.contributor.authorHoeschele, Inaen
dc.contributor.departmentDairy Scienceen
dc.date.accessed2014-07-15en
dc.date.accessioned2014-07-21T15:49:37Zen
dc.date.available2014-07-21T15:49:37Zen
dc.date.issued2000-10en
dc.description.abstractIn a previous contribution, we implemented a finite locus model (FLM) for estimating additive and dominance genetic variances via a Bayesian method and a single-site Gibbs sampler. We observed a dependency of dominance variance estimates on locus number in the analysis FLM. Here, we extended the FLM to include two-locus epistasis and implemented the analysis with two genotype samplers (Gibbs and descent graph) and three different priors for genetic effects (uniform and variable across loci, uniform and constant across loci, and normal). Phenotypic data were simulated for two pedigrees with 6300 and 12300 individuals in closed populations, using several different, non-additive genetic models. Replications of these data were analysed with FLMs differing in the number of loci. Simulation results indicate that the dependency of non-additive genetic variance estimates on locus number persisted in all implementation strategies we investigated. However, this dependency was considerably diminished with normal priors for genetic effects as compared with uniform priors (constant or variable across loci). Descent graph sampling of genotypes modestly improved variance components estimation compared with Gibbs sampling. Moreover, a larger pedigree produced considerably better variance components estimation, suggesting this dependency might originate from data insufficiency. As the FLM represents an appealing alternative to the infinitesimal model for genetic parameter estimation and for inclusion of polygenic background variation in QTL mapping analyses. further improvements are warranted and might be achieved via improvement of the sampler or treatment of the number of loci as an unknown.en
dc.description.sponsorshipUS Department of Agriculture's National Research Initiative Competitive Grants Program (grant 96-35205-3662)en
dc.description.sponsorshipNational Science Foundation (grant DBI-9723022)en
dc.description.sponsorshipNIH grant GM45344en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationDu, F. X.; Hoeschele, I. "Estimation of additive, dominance and epistatic variance components using finite locus models implemented with a single-site Gibbs and a descent graph sampler," Genet. Res., Camb. (2000), 76, 187-198. DOI: 10.1017/s0016672300004614en
dc.identifier.doihttps://doi.org/10.1017/s0016672300004614en
dc.identifier.issn0016-6723en
dc.identifier.urihttp://hdl.handle.net/10919/49630en
dc.identifier.urlhttp://journals.cambridge.org/action/displayAbstract?fromPage=online&aid=60597&fulltextType=RA&fileId=S0016672300004614en
dc.language.isoenen
dc.publisherCambridge University Pressen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectquantitative trait locien
dc.subjectpolygenic mixed-modelen
dc.subjectdairy-cattleen
dc.subjectalternative formulationen
dc.subjectrelationship matricesen
dc.subjectgenetic-variationen
dc.subjectlinkage analysisen
dc.subjectrapid inversionen
dc.subjectmilk-productionen
dc.subjectincluding sireen
dc.subjectgenetics & heredityen
dc.titleEstimation of additive, dominance and epistatic variance components using finite locus models implemented with a single-site Gibbs and a descent graph sampleren
dc.title.serialGenetical Researchen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten

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