Genomic prediction for beef fatty acid profile in Nellore cattle
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , , , , , , , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1016/j.meatsci.2017.02.007 http://hdl.handle.net/11449/178657 |
Resumo: | 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. |
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Genomic prediction for beef fatty acid profile in Nellore cattleBos indicusGenomic selectionLipid profileMeat qualityThe 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.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Faculdade de Ciências Agrárias e Veterinárias UNESP JaboticabalFaculdade de Medicina Veterinária e Zootecnia USP PirassunungaFaculdade de Zootecnia e Engenharia de Alimentos USP PirassunungaFaculdade de Ciências Agrárias e Veterinárias UNESP JaboticabalFAPESP: #2009/16118-5FAPESP: (#2011/2141-0Universidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Chiaia, Hermenegildo Lucas Justino [UNESP]Peripoli, Elisa [UNESP]Silva, Rafael Medeiros de Oliveira [UNESP]Aboujaoude, Carolyn [UNESP]Feitosa, Fabiele Loise Braga [UNESP]Lemos, Marcos Vinicius Antunes de [UNESP]Berton, Mariana Piatto [UNESP]Olivieri, Bianca Ferreira [UNESP]Espigolan, Rafael [UNESP]Tonussi, Rafael Lara [UNESP]Gordo, Daniel Gustavo Mansan [UNESP]Bresolin, Tiago [UNESP]Magalhães, Ana Fabrícia Braga [UNESP]Júnior, Gerardo Alves Fernandes [UNESP]Albuquerque, Lúcia Galvão de [UNESP]Oliveira, Henrique Nunes de [UNESP]Furlan, Joyce de Jesus ManginiFerrinho, Adrielle MathiasMueller, Lenise FreitasTonhati, Humberto [UNESP]Pereira, Angélica Simone CravoBaldi, Fernando [UNESP]2018-12-11T17:31:30Z2018-12-11T17:31:30Z2017-06-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article60-67application/pdfhttp://dx.doi.org/10.1016/j.meatsci.2017.02.007Meat Science, v. 128, p. 60-67.0309-1740http://hdl.handle.net/11449/17865710.1016/j.meatsci.2017.02.0072-s2.0-850132778932-s2.0-85013277893.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengMeat Science1,643info:eu-repo/semantics/openAccess2024-06-07T18:43:35Zoai:repositorio.unesp.br:11449/178657Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T20:45:05.809305Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Genomic prediction for beef fatty acid profile in Nellore cattle |
title |
Genomic prediction for beef fatty acid profile in Nellore cattle |
spellingShingle |
Genomic prediction for beef fatty acid profile in Nellore cattle Chiaia, Hermenegildo Lucas Justino [UNESP] Bos indicus Genomic selection Lipid profile Meat quality |
title_short |
Genomic prediction for beef fatty acid profile in Nellore cattle |
title_full |
Genomic prediction for beef fatty acid profile in Nellore cattle |
title_fullStr |
Genomic prediction for beef fatty acid profile in Nellore cattle |
title_full_unstemmed |
Genomic prediction for beef fatty acid profile in Nellore cattle |
title_sort |
Genomic prediction for beef fatty acid profile in Nellore cattle |
author |
Chiaia, Hermenegildo Lucas Justino [UNESP] |
author_facet |
Chiaia, Hermenegildo Lucas Justino [UNESP] Peripoli, Elisa [UNESP] Silva, Rafael Medeiros de Oliveira [UNESP] Aboujaoude, Carolyn [UNESP] Feitosa, Fabiele Loise Braga [UNESP] Lemos, Marcos Vinicius Antunes de [UNESP] Berton, Mariana Piatto [UNESP] Olivieri, Bianca Ferreira [UNESP] Espigolan, Rafael [UNESP] Tonussi, Rafael Lara [UNESP] Gordo, Daniel Gustavo Mansan [UNESP] Bresolin, Tiago [UNESP] Magalhães, Ana Fabrícia Braga [UNESP] Júnior, Gerardo Alves Fernandes [UNESP] Albuquerque, Lúcia Galvão de [UNESP] Oliveira, Henrique Nunes de [UNESP] Furlan, Joyce de Jesus Mangini Ferrinho, Adrielle Mathias Mueller, Lenise Freitas Tonhati, Humberto [UNESP] Pereira, Angélica Simone Cravo Baldi, Fernando [UNESP] |
author_role |
author |
author2 |
Peripoli, Elisa [UNESP] Silva, Rafael Medeiros de Oliveira [UNESP] Aboujaoude, Carolyn [UNESP] Feitosa, Fabiele Loise Braga [UNESP] Lemos, Marcos Vinicius Antunes de [UNESP] Berton, Mariana Piatto [UNESP] Olivieri, Bianca Ferreira [UNESP] Espigolan, Rafael [UNESP] Tonussi, Rafael Lara [UNESP] Gordo, Daniel Gustavo Mansan [UNESP] Bresolin, Tiago [UNESP] Magalhães, Ana Fabrícia Braga [UNESP] Júnior, Gerardo Alves Fernandes [UNESP] Albuquerque, Lúcia Galvão de [UNESP] Oliveira, Henrique Nunes de [UNESP] Furlan, Joyce de Jesus Mangini Ferrinho, Adrielle Mathias Mueller, Lenise Freitas Tonhati, Humberto [UNESP] Pereira, Angélica Simone Cravo Baldi, Fernando [UNESP] |
author2_role |
author author author author author author author author author author author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade de São Paulo (USP) |
dc.contributor.author.fl_str_mv |
Chiaia, Hermenegildo Lucas Justino [UNESP] Peripoli, Elisa [UNESP] Silva, Rafael Medeiros de Oliveira [UNESP] Aboujaoude, Carolyn [UNESP] Feitosa, Fabiele Loise Braga [UNESP] Lemos, Marcos Vinicius Antunes de [UNESP] Berton, Mariana Piatto [UNESP] Olivieri, Bianca Ferreira [UNESP] Espigolan, Rafael [UNESP] Tonussi, Rafael Lara [UNESP] Gordo, Daniel Gustavo Mansan [UNESP] Bresolin, Tiago [UNESP] Magalhães, Ana Fabrícia Braga [UNESP] Júnior, Gerardo Alves Fernandes [UNESP] Albuquerque, Lúcia Galvão de [UNESP] Oliveira, Henrique Nunes de [UNESP] Furlan, Joyce de Jesus Mangini Ferrinho, Adrielle Mathias Mueller, Lenise Freitas Tonhati, Humberto [UNESP] Pereira, Angélica Simone Cravo Baldi, Fernando [UNESP] |
dc.subject.por.fl_str_mv |
Bos indicus Genomic selection Lipid profile Meat quality |
topic |
Bos indicus Genomic selection Lipid profile Meat quality |
description |
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. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-06-01 2018-12-11T17:31:30Z 2018-12-11T17:31:30Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.meatsci.2017.02.007 Meat Science, v. 128, p. 60-67. 0309-1740 http://hdl.handle.net/11449/178657 10.1016/j.meatsci.2017.02.007 2-s2.0-85013277893 2-s2.0-85013277893.pdf |
url |
http://dx.doi.org/10.1016/j.meatsci.2017.02.007 http://hdl.handle.net/11449/178657 |
identifier_str_mv |
Meat Science, v. 128, p. 60-67. 0309-1740 10.1016/j.meatsci.2017.02.007 2-s2.0-85013277893 2-s2.0-85013277893.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Meat Science 1,643 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
60-67 application/pdf |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808129242170392576 |