TY - JOUR
T1 - Genomic prediction for beef fatty acid profile in Nellore cattle
AU - Chiaia, Hermenegildo Lucas Justino
AU - Peripoli, Elisa
AU - Silva, Rafael Medeiros de Oliveira
AU - Aboujaoude, Carolyn
AU - Feitosa, Fabiele Loise Braga
AU - Lemos, Marcos Vinicius Antunes de
AU - Berton, Mariana Piatto
AU - Olivieri, Bianca Ferreira
AU - Espigolan, Rafael
AU - Tonussi, Rafael Lara
AU - Gordo, Daniel Gustavo Mansan
AU - Bresolin, Tiago
AU - Magalhães, Ana Fabrícia Braga
AU - Júnior, Gerardo Alves Fernandes
AU - Albuquerque, Lúcia Galvão de
AU - Oliveira, Henrique Nunes de
AU - Furlan, Joyce de Jesus Mangini
AU - Ferrinho, Adrielle Mathias
AU - Mueller, Lenise Freitas
AU - Tonhati, Humberto
AU - Pereira, Angélica Simone Cravo
AU - Baldi, Fernando
N1 - Funding Information:
This work was supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) with grant numbers (#2011/2141-0 and #2009/16118-5).
Publisher Copyright:
© 2017 The Authors
PY - 2017/6/1
Y1 - 2017/6/1
N2 - 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.
AB - 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.
KW - Bos indicus
KW - Genomic selection
KW - Lipid profile
KW - Meat quality
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U2 - 10.1016/j.meatsci.2017.02.007
DO - 10.1016/j.meatsci.2017.02.007
M3 - Article
C2 - 28214693
AN - SCOPUS:85013277893
SN - 0309-1740
VL - 128
SP - 60
EP - 67
JO - Meat Science
JF - Meat Science
ER -