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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Genetic parameter estimates for carcass traits and visual scores including or not genomic information

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Gordo, D. G. M. [1] ; Espigolan, R. [1] ; Tonussi, R. L. [1] ; Junior, G. A. F. [1] ; Bresolin, T. [1] ; Braga Magalhaes, A. F. [1] ; Feitosa, F. L. [1] ; Baldi, F. [1] ; Carvalheiro, R. [1] ; Tonhati, H. [1] ; de Oliveira, H. N. [1] ; Chardulo, L. A. L. [2] ; de Albuquerque, L. G. [1, 3]
Total Authors: 13
[1] Univ Estadual Paulista, Fac Ciencias Agr & Vet, BR-14884900 Jaboticabal, SP - Brazil
[2] Univ Estadual Paulista, Fac Med Vet & Zootecnia, BR-18618970 Botucatu, SP - Brazil
[3] Dept Zootecnia, Via Acesso Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP - Brazil
Total Affiliations: 3
Document type: Journal article
Source: JOURNAL OF ANIMAL SCIENCE; v. 94, n. 5, p. 1821-1826, MAY 2016.
Web of Science Citations: 7

The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix (A and H) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix (A) or combining the genomic and the numerator relationship matrices (H). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix A and 0.29, 0.16, and 0.23, respectively, using matrix H. The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix H was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of CS, FP, and MS could be used as selection criteria to improve HCW, BF, and LMA. The use of genomic information permitted the detection of greater additive genetic variability for LMA and BF. For HCW, the high magnitude of the genetic correlations with visual scores was probably sufficient to recover genetic variability. The methods provided similar breeding value accuracies, especially for the visual scores. (AU)

FAPESP's process: 09/16118-5 - Genomic tools to genetic improvement of direct economic important traits in Nelore cattle
Grantee:Lucia Galvão de Albuquerque
Support type: Research Projects - Thematic Grants
FAPESP's process: 14/11537-8 - Strategies for applying genomic selection in beef cattle breeding programs
Grantee:Daniel Gustavo Mansan Gordo
Support type: Scholarships in Brazil - Post-Doctorate