504
Genome-assisted multiple-trait analysis of carcass traits in Nellore cattle
Monday, August 18, 2014
Posters (The Westin Bayshore)
Gerardo A. Fernandes Júnior
,
Sao Paulo State University (UNESP), Jaboticabal, Brazil
Guilherme J.M. Rosa
,
University of Wisconsin - Madison, Madison, WI
Raphael B. Costa
,
Sao Paulo State University (UNESP), Jaboticabal, Brazil
Roberto Carvalheiro
,
Sao Paulo State University (UNESP), Jaboticabal, Brazil
Luis Arthur L Chardulo
,
Universidade Estadual Paulista, Botucatu, Brazil
Daniel G M Gordo
,
Sao Paulo State University (UNESP), Jaboticabal, Brazil
Fernando Baldi
,
Universidade Estadual Paulista “Júlio de Mesquita Filho”- UNESP, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, Brazil
Henrique N. Oliveira
,
Universidade Estadual Paulista “Júlio de Mesquita Filho”- UNESP, Faculdade de Ciências Agrárias e Veterinárias, 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
Rafael M.O. Silva
,
Sao Paulo State University (UNESP), Jaboticabal, Brazil
Abstract Text:
Records for carcass weight (CW), rib eye area (REA), backfat thickness (BFT), and marbling (MARB) were recorded for 1,594 Nellore males (821 genotyped). The single-step GBLUP approach was used to estimate (co)variance components by REML using a multi-trait model including the effects of contemporary group, direct additive genetic, and slaughter animal age. A Manhattan plot of the variance explained by 50 adjacent SNP windows was used to assess potential genome regions with major effects on each trait. Low heritability was verified for all traits and genetic correlations were moderate among REA, BFT, and MARB, and were low between them with CW. The highest genome association were found on chromosome 1 and 5 for CW, on 5 for REA, on 8 and 14 for BFT, and on 5, 6, 14, and 16 for MARB, which represent potential genome regions harboring genes affecting the traits.
Keywords:
genomic selection
genetic parameters
