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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.)

Genomic prediction for beef fatty acid profile in Nellore cattle

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Justino Chiaia, Hermenegildo Lucas ; Peripoli, Elisa ; de Oliveira Silva, Rafael Medeiros ; Aboujaoude, Carolyn ; Braga Feitosa, Fabiele Loise ; Antunes de Lemos, Marcos Vinicius ; Berton, Mariana Piatto ; Olivieri, Bianca Ferreira ; Espigolan, Rafael ; Tonussi, Rafael Lara ; Mansan Gordo, Daniel Gustavo ; Bresolin, Tiago ; Braga Magalhaes, Ana Fabricia ; Fernandes Junior, Gerardo Alves ; de Albuquerque, Lucia Galvao ; de Oliveira, Henrique Nunes ; Mangini Furlan, Joyce de Jesus ; Ferrinho, Adrielle Mathias ; Mueller, Lenise Freitas ; Tonhati, Humberto ; Cravo Pereira, Angelica Simone ; Baldi, Fernando
Total Authors: 22
Document type: Journal article
Source: MEAT SCIENCE; v. 128, p. 60-67, JUN 2017.
Web of Science Citations: 4

The objective of this study was to compare SNP-BLUP, BayesC pi, BayesC and Bayesian Lasso methodologies to predict the direct genomic value for saturated, monounsaturated, and polyunsaturated fatty acid profile, omega 3 and 6 in the Longissimus thoracis muscle of Nellore cattle finished in feedlot. A total of 963 Nellore bulls with phenotype for fatty acid profiles, were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. The predictive ability was evaluated using cross validation. To compare the methodologies, the correlation between DGV and pseudo-phenotypes was calculated. The accuracy varied from -0.40 to 0.62. Our results indicate that none of the methods excelled in terms of accuracy, however, the SNP-BLUP method allows obtaining less biased genomic evaluations, thereby; this method is more feasible when taking into account the analyses' operating cost. Despite the lowest bias observed for EBV, the adjusted phenotype is the preferred pseudophenotype considering the genomic prediction accuracies regarding the context of the present study. (C) 2017 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license.. (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