Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1061094
Registro completo de metadados
Campo DCValorIdioma
dc.contributor.authorALMEIDA FILHO, J. E. dept_BR
dc.contributor.authorGUIMARÃES, J. F. R.pt_BR
dc.contributor.authorSILVA, F. F. ept_BR
dc.contributor.authorRESENDE, M. D. V. dept_BR
dc.contributor.authorMUÑOZ, P.pt_BR
dc.contributor.authorKIRST, M.pt_BR
dc.contributor.authorRESENDE JUNIOR, M. F. R.pt_BR
dc.date.accessioned2017-01-18T23:03:35Z-
dc.date.available2017-01-18T23:03:35Z-
dc.date.created2017-01-18pt_BR
dc.date.issued2016pt_BR
dc.identifier.citationHeredity, v. 117, p. 33-41, July 2016.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1061094pt_BR
dc.descriptionPedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive?dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.titleThe contribution of dominance to phenotype prediction in a pine breeding and simulated population.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2017-01-18T23:03:35Zpt_BR
dc.subject.thesagroÁrvore coníferapt_BR
riaa.ainfo.id1061094pt_BR
riaa.ainfo.lastupdate2017-01-18pt_BR
dc.identifier.doi10.1038/hdy.2016.23pt_BR
dc.contributor.institutionJ. E. de Almeida Filho, University of Florida; J. F. R. Guimarães, University of Florida; F. F. e SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; P. Muñoz, University of Florida; M. Kirst, University of Florida; M. F. R. Resende JUnior, RAPiD Genomics LLC.pt_BR
Aparece nas coleções:Artigo em periódico indexado (CNPF)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
2016M.DeonHTheContribution.pdf1.32 MBAdobe PDFThumbnail
Visualizar/Abrir
Mostrar registro simples do item Visualizar estatísticas

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace