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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Animal Genomics and Improvement Laboratory » Research » Publications at this Location » Publication #295298

Title: Accuracy of genomic predictions in Nellore beef cattle

item CARVALHEIRO, ROBERTO - Universidade Estadual Paulista (UNESP)
item MCEWAN, JOHN - Agresearch
item NEVES, HAROLDO H.R. - Universidade Estadual Paulista (UNESP)
item UTSUNOMIYA, YURI - Sao Paulo State University (UNESP)
item PEREZ O'BRIEN, ANA - Botanik University
item BOISON, ANA - Botanik University
item SOLKNER, JOHANN - Botanik University
item SCHENKEL, FLAVIO - University Of Guelph
item Van Tassell, Curtis - Curt
item Sonstegard, Tad
item GARCIA, FERNANDO - Sao Paulo State University (UNESP)

Submitted to: Genetics Selection Evolution
Publication Type: Proceedings
Publication Acceptance Date: 9/3/2013
Publication Date: 10/20/2013
Citation: Carvalheiro, R., Mcewan, J.C., Neves, H., Utsunomiya, Y.T., Perez O'Brien, A.M., Boison, A., Solkner, J., Schenkel, F., Van Tassell, C.P., Sonstegard, T.S., Garcia, F. 2013. Accuracy of genomic predictions in Nellore beef cattle. Genetics Selection Evolution. 20:171-174.

Interpretive Summary:

Technical Abstract: This study was carried out to assess the quality of genomic predictions in a Nellore beef cattle population, for 14 growth, carcass composition and reproduction traits, evaluated either at weaning or as yearlings. A forward prediction scheme was applied, so that information on a set of older animals (bulls and cows with accurate proofs in 2007) was employed to derive genomic prediction equations, while information on younger bulls (2012 proofs) was considered for validation purposes. The validation accuracies of genomic predictions averaged 0.47, consistent with the expectation for such statistics. Accuracies for two selection indices including either weaning traits (WI) or both weaning and yearling traits (FI) were 0.44 and 0.58, respectively. For younger animals with own performance, genomic predictions increased by 10% (on average) the individual accuracies for both WI and FI.