Genome scan for postmortem carcass traits in nellore cattle

Detalhes bibliográficos
Autor(a) principal: Júnior, G. A. Fernandes [UNESP]
Data de Publicação: 2016
Outros Autores: Costa, R. B. [UNESP], De Camargo, G. M.F. [UNESP], Carvalheiro, R. [UNESP], Rosa, G. J.M., Baldi, F. [UNESP], Garcia, D. A. [UNESP], Gordo, D. G.M. [UNESP], Espigolan, R. [UNESP], Takada, L. [UNESP], Magalhães, A. F.B. [UNESP], Bresolin, T. [UNESP], Feitosa, F. L.B. [UNESP], Chardulo, L. A.L. [UNESP], De Oliveira, H. N. [UNESP], De Albuquerque, L. G. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.2527/jas.2016-0632
http://hdl.handle.net/11449/178750
Resumo: Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes (CDKN2A and CDKN2B) involved in the cell cycle biological process which affects many aspects of animal growth and development. The SLC38A1 and SLC38A2 genes, both from SLC38 AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (SORCS2, AQP3, AQP7, CDC42BPA, ASIP, and ACSS2) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the PLAG1. There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.
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spelling Genome scan for postmortem carcass traits in nellore cattleBackfat thicknessBeef cattleCarcass weightGenome-wide association studyRibeye areaSingle-step genomic BLUP approachCarcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes (CDKN2A and CDKN2B) involved in the cell cycle biological process which affects many aspects of animal growth and development. The SLC38A1 and SLC38A2 genes, both from SLC38 AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (SORCS2, AQP3, AQP7, CDC42BPA, ASIP, and ACSS2) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the PLAG1. There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Faculdade de Ciências Agrárias e Veterinárias UNESPCNPqUniversity of Wisconsin–MadisonFaculdade de Medicina Veterinária e Zootecnia UNESPDepartamento de Zootecnia, Via de acesso Paulo Donato Castellane s/nFaculdade de Ciências Agrárias e Veterinárias UNESPFaculdade de Medicina Veterinária e Zootecnia UNESPFAPESP: #2009/16118–5FAPESP: #2015/06140–4Universidade Estadual Paulista (Unesp)CNPqUniversity of Wisconsin–MadisonJúnior, G. A. Fernandes [UNESP]Costa, R. B. [UNESP]De Camargo, G. M.F. [UNESP]Carvalheiro, R. [UNESP]Rosa, G. J.M.Baldi, F. [UNESP]Garcia, D. A. [UNESP]Gordo, D. G.M. [UNESP]Espigolan, R. [UNESP]Takada, L. [UNESP]Magalhães, A. F.B. [UNESP]Bresolin, T. [UNESP]Feitosa, F. L.B. [UNESP]Chardulo, L. A.L. [UNESP]De Oliveira, H. N. [UNESP]De Albuquerque, L. G. [UNESP]2018-12-11T17:31:56Z2018-12-11T17:31:56Z2016-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article4087-4095application/pdfhttp://dx.doi.org/10.2527/jas.2016-0632Journal of Animal Science, v. 94, n. 10, p. 4087-4095, 2016.1525-31630021-8812http://hdl.handle.net/11449/17875010.2527/jas.2016-06322-s2.0-850164220862-s2.0-85016422086.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Animal Science0,848info:eu-repo/semantics/openAccess2023-11-15T06:12:30Zoai:repositorio.unesp.br:11449/178750Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462023-11-15T06:12:30Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Genome scan for postmortem carcass traits in nellore cattle
title Genome scan for postmortem carcass traits in nellore cattle
spellingShingle Genome scan for postmortem carcass traits in nellore cattle
Júnior, G. A. Fernandes [UNESP]
Backfat thickness
Beef cattle
Carcass weight
Genome-wide association study
Ribeye area
Single-step genomic BLUP approach
title_short Genome scan for postmortem carcass traits in nellore cattle
title_full Genome scan for postmortem carcass traits in nellore cattle
title_fullStr Genome scan for postmortem carcass traits in nellore cattle
title_full_unstemmed Genome scan for postmortem carcass traits in nellore cattle
title_sort Genome scan for postmortem carcass traits in nellore cattle
author Júnior, G. A. Fernandes [UNESP]
author_facet Júnior, G. A. Fernandes [UNESP]
Costa, R. B. [UNESP]
De Camargo, G. M.F. [UNESP]
Carvalheiro, R. [UNESP]
Rosa, G. J.M.
Baldi, F. [UNESP]
Garcia, D. A. [UNESP]
Gordo, D. G.M. [UNESP]
Espigolan, R. [UNESP]
Takada, L. [UNESP]
Magalhães, A. F.B. [UNESP]
Bresolin, T. [UNESP]
Feitosa, F. L.B. [UNESP]
Chardulo, L. A.L. [UNESP]
De Oliveira, H. N. [UNESP]
De Albuquerque, L. G. [UNESP]
author_role author
author2 Costa, R. B. [UNESP]
De Camargo, G. M.F. [UNESP]
Carvalheiro, R. [UNESP]
Rosa, G. J.M.
Baldi, F. [UNESP]
Garcia, D. A. [UNESP]
Gordo, D. G.M. [UNESP]
Espigolan, R. [UNESP]
Takada, L. [UNESP]
Magalhães, A. F.B. [UNESP]
Bresolin, T. [UNESP]
Feitosa, F. L.B. [UNESP]
Chardulo, L. A.L. [UNESP]
De Oliveira, H. N. [UNESP]
De Albuquerque, L. G. [UNESP]
author2_role 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)
CNPq
University of Wisconsin–Madison
dc.contributor.author.fl_str_mv Júnior, G. A. Fernandes [UNESP]
Costa, R. B. [UNESP]
De Camargo, G. M.F. [UNESP]
Carvalheiro, R. [UNESP]
Rosa, G. J.M.
Baldi, F. [UNESP]
Garcia, D. A. [UNESP]
Gordo, D. G.M. [UNESP]
Espigolan, R. [UNESP]
Takada, L. [UNESP]
Magalhães, A. F.B. [UNESP]
Bresolin, T. [UNESP]
Feitosa, F. L.B. [UNESP]
Chardulo, L. A.L. [UNESP]
De Oliveira, H. N. [UNESP]
De Albuquerque, L. G. [UNESP]
dc.subject.por.fl_str_mv Backfat thickness
Beef cattle
Carcass weight
Genome-wide association study
Ribeye area
Single-step genomic BLUP approach
topic Backfat thickness
Beef cattle
Carcass weight
Genome-wide association study
Ribeye area
Single-step genomic BLUP approach
description Carcass traits measured after slaughter are economically relevant traits in beef cattle. In general, the slaughter house payment system is based on HCW. Ribeye area (REA) is associated with the amount of the meat in the carcass, and a minimum of backfat thickness (BFT) is necessary to protect the carcass during cooling. The aim of this study was to identify potential genomic regions harboring candidate genes affecting those traits in Nellore cattle. The data set used in the present study consisted of 1,756 Nellore males with phenotype records. A subset of 1,604 animals had both genotypic and phenotypic information. Genotypes were generated based on a panel with 777,962 SNPs from the Illumina Bovine HD chip. The SNP effects were calculated based on the genomic breeding values obtained by using the single-step GBLUP approach and a genomic matrix re-weighting procedure. The proportion of the variance explained by moving windows of 100 consecutive SNPs was used to assess potential genomic regions harboring genes with major effects on each trait. The top 10 non-overlapping SNP-windows explained 8.72%, 11.38%, and 9.31% of the genetic variance for REA, BFT, and HCW, respectively. These windows are located on chromosomes 5, 7, 8, 10, 12, 20, and 29 for REA; chromosomes 6, 8, 10, 13, 16, 17, 18, and 24 for BFT; and chromosomes 4, 6, 7, 8, 14, 16, 17, and 21 for HCW. For REA, there were identified genes (CDKN2A and CDKN2B) involved in the cell cycle biological process which affects many aspects of animal growth and development. The SLC38A1 and SLC38A2 genes, both from SLC38 AA transporter family, was also associated with REA. The AA transporters are essential for cell growth and proliferation, acting as carriers of tissue nutrient supplies. Various genes identified for BFT (SORCS2, AQP3, AQP7, CDC42BPA, ASIP, and ACSS2) have been associated with lipid metabolism in different mammal species. One of the most promising genes identified for HCW was the PLAG1. There is evidence, in the literature, that this gene is located in putative QTL affecting carcass weight in beef cattle. Our results showed several genomic regions containing plausible candidate genes that may be associated with carcass traits in Nellore cattle. Besides contributing to a better understanding of the genetic control of carcass traits, the identified genes can also be helpful for further functional genomic studies.
publishDate 2016
dc.date.none.fl_str_mv 2016-10-01
2018-12-11T17:31:56Z
2018-12-11T17:31:56Z
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/10.2527/jas.2016-0632
Journal of Animal Science, v. 94, n. 10, p. 4087-4095, 2016.
1525-3163
0021-8812
http://hdl.handle.net/11449/178750
10.2527/jas.2016-0632
2-s2.0-85016422086
2-s2.0-85016422086.pdf
url http://dx.doi.org/10.2527/jas.2016-0632
http://hdl.handle.net/11449/178750
identifier_str_mv Journal of Animal Science, v. 94, n. 10, p. 4087-4095, 2016.
1525-3163
0021-8812
10.2527/jas.2016-0632
2-s2.0-85016422086
2-s2.0-85016422086.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of Animal Science
0,848
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 4087-4095
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
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reponame_str Repositório Institucional da UNESP
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