Please use this identifier to cite or link to this item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1070097
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dc.contributor.authorSOMAVILLA, A. L.eng
dc.contributor.authorREGITANO, L. C. de A.eng
dc.contributor.authorROSA, G. J. M.eng
dc.contributor.authorMOKRY, F. B.eng
dc.contributor.authorMUDADU, M. de A.eng
dc.contributor.authorTIZIOTO, P. C.eng
dc.contributor.authorOLIVEIRA, P. S. N. deeng
dc.contributor.authorSOUZA, M. M. deeng
dc.contributor.authorCOUTINHO, L. L.eng
dc.contributor.authorMUNARI, D. P.eng
dc.contributor.otherAdriana Luiza Somavilla, Unesp; LUCIANA CORREIA DE ALMEIDA REGITANO, CPPSE; Guilherme Jordão Magalhães Rosa, University of Wisconsin; Fabiana Barichello Mokry, UFSCar; MAURICIO DE ALVARENGA MUDADU, CNPTIA; Polyana Cristine Tizioto, UFSCar; Priscila Silva Neubern de Oliveira, UFSCar; Marcela Maria de Souza, UFSCar; Luiz Lehmann Coutinho, USP; Danísio Prado Munari, Unesp.eng
dc.date.accessioned2019-06-15T00:40:05Z-
dc.date.available2019-06-15T00:40:05Z-
dc.date.created2017-05-26
dc.date.issued2017
dc.identifier.other24052
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1070097-
dc.descriptionNelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increase beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic estimated breeding values for average daily gain in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications (Bayesian GBLUP, BayesA, and BayesCπ) were performed with four genotype panels (Illumina BovineHD BeadChip, TagSNPs, GeneSeek High and Low-density indicus). Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesCπ model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44) and sample size (568 animals in the training population). Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement genomic selection at lower costs.eng
dc.description.uribitstream/item/160256/1/g3.117.041442.full.pdf
dc.languageeneng
dc.language.isoengeng
dc.publisherG3: Genes, Genomes, Genetics, v. 7, p. 1-17, 2017.eng
dc.relation.ispartofEmbrapa Pecuária Sudeste - Artigo em periódico indexado (ALICE)eng
dc.subjectGenomic selectioneng
dc.subjectBos taurus indicuseng
dc.subjectGrowtheng
dc.titleGenome-enabled prediction of breeding values for feedlot average daily weight gain in nelore cattle.eng
dc.typeArtigo em periódico indexado (ALICE)eng
dc.date.updated2019-06-15T00:40:05Z
dc.ainfo.id1070097eng
dc.ainfo.lastupdate2019-06-14
dc.identifier.doihttps://doi.org/10.1534/g3.117.041442eng
Appears in Collections:Artigo em periódico indexado (CPPSE)

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