Genomic prediction for beef fatty acid profile in Nellore cattle

Hermenegildo Lucas Justino Chiaia, Elisa Peripoli, Rafael Medeiros de Oliveira Silva, Carolyn Aboujaoude, Fabiele Loise Braga Feitosa, Marcos Vinicius Antunes de Lemos, Mariana Piatto Berton, Bianca Ferreira Olivieri, Rafael Espigolan, Rafael Lara Tonussi, Daniel Gustavo Mansan Gordo, Tiago Bresolin, Ana Fabrícia Braga Magalhães, Gerardo Alves Fernandes Júnior, Lúcia Galvão de Albuquerque, Henrique Nunes de Oliveira, Joyce de Jesus Mangini Furlan, Adrielle Mathias Ferrinho, Lenise Freitas Mueller, Humberto TonhatiAngélica Simone Cravo Pereira, Fernando Baldi

Research output: Contribution to journalArticlepeer-review


The objective of this study was to compare SNP-BLUP, BayesCπ, 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.

Original languageEnglish (US)
Pages (from-to)60-67
Number of pages8
JournalMeat Science
StatePublished - Jun 1 2017
Externally publishedYes


  • Bos indicus
  • Genomic selection
  • Lipid profile
  • Meat quality

ASJC Scopus subject areas

  • Food Science


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