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Prediction of Genomic Breeding Values for Reproductive Traits in Nellore Heifers

Thursday, August 21, 2014
Posters (The Westin Bayshore)
Raphael B. Costa , Sao Paulo State University (UNESP), Jaboticabal, Brazil
Iara del Pilar S Diaz , Sao Paulo State University (UNESP), Jaboticabal, Brazil
Natalia Irano , Sao Paulo State University (UNESP), Jaboticabal, Brazil
Luciana Takada , Sao Paulo State University (UNESP), Jaboticabal, Brazil
Roberto Carvalheiro , Universidade Estadual Paulista “Júlio de Mesquita Filho”- UNESP, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, Brazil
Fernando Baldi , Sao Paulo State University (UNESP), Jaboticabal, Brazil
Henrique N Oliveira , Sao Paulo State University (UNESP), Jaboticabal, Brazil
Humberto Tonhati , State University of São Paulo, Faculty of Agriculture and Veterinary Sciences, Jaboticabal, Brazil
Lucia Galvão Albuquerque , State University of São Paulo, Faculty of Agriculture and Veterinary Sciences, Jaboticabal, Brazil
Abstract Text:

The objective of this study was to assess the quality of genomic predictions for rebreeding success or failure after calving, age at first calving, and early pregnancy occurrence in Nellore females. There were 1,853 individuals that had 305,348 SNPs each used in genomic selection analyses. Three genomic prediction methods were used: GBLUP, a Bayesian method (BAYESCπ), and a lasso method (IBLASSO). The dependent variables were: adjusted phenotype (CPHEN), and deregressed breeding value (DEBV). Predictive abilities were assessed by the average correlation between CPHEN and genomic estimated breeding value (GEBV) and by the average correlations between DEBV and GEBV in the validation population. Regression coefficients of CPHEN on GEBVs in the validation population were indicators of prediction bias of GEBV. BAYESCπ was more suitable for estimation of SNP effects and GEBVs for all traits. 

Keywords:

Genomic breeding value

Reproductive efficiency

SNP