Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://www.ufrgs.br/actavet/39-suple-1/04%20Supl_s23-s27.pdf http://hdl.handle.net/11449/73022 |
Resumo: | Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals. |
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Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattleDna markersGenetic evaluationGenomic Enhanced epdsGenomic selectionNellore cattleSnpAnimaliaBosBos indicusBovinaeBackground: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals.Universidade de São Paulo (USP), Ribeirão Preto, SPPfizer Animal Genetics Kalamazoo, MIAssociação Nacional de Criadores e Pesquisadores (ANCP), Ribeirão Preto, SPPfizer Animal Genetics, São Paulo, SPPfizer Saúde Animal, São Paulo, SPUniversidade Estadual Paulista (UNESP), Jaboticabal, SPEmpresa Brasileira de Pesquisa Agropecuária (EMBRAPA) Juiz de Fora, MGUniversidade Estadual Paulista (UNESP), Jaboticabal, SPUniversidade de São Paulo (USP)Kalamazoo, MIAssociação Nacional de Criadores e Pesquisadores (ANCP)Pfizer Animal GeneticsPfizer Saúde AnimalUniversidade Estadual Paulista (Unesp)Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA)Lôbo, Raysildo BarbosaNkrumah, DonaldGrossi, Daniela do AmaralDe Barros, Priscila SalesPaiva, PabloBezerra, Luiz Antônio FramatinoDe Oliveira, Henrique Nunes [UNESP]Da Silva, Marcos Vinícius Barbosa2014-05-27T11:26:18Z2014-05-27T11:26:18Z2011-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://www.ufrgs.br/actavet/39-suple-1/04%20Supl_s23-s27.pdfActa Scientiae Veterinariae, v. 39, n. SUPPL. 1, 2011.1678-03451679-9216http://hdl.handle.net/11449/730222-s2.0-848686149172-s2.0-84868614917.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengActa Scientiae Veterinariae0.2170,1440,144info:eu-repo/semantics/openAccess2024-01-05T06:26:27Zoai:repositorio.unesp.br:11449/73022Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:11:40.773011Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
title |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
spellingShingle |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle Lôbo, Raysildo Barbosa Dna markers Genetic evaluation Genomic Enhanced epds Genomic selection Nellore cattle Snp Animalia Bos Bos indicus Bovinae |
title_short |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
title_full |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
title_fullStr |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
title_full_unstemmed |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
title_sort |
Implementation of DNA markers to produce genomically - Enhanced EPDs in nellore cattle |
author |
Lôbo, Raysildo Barbosa |
author_facet |
Lôbo, Raysildo Barbosa Nkrumah, Donald Grossi, Daniela do Amaral De Barros, Priscila Sales Paiva, Pablo Bezerra, Luiz Antônio Framatino De Oliveira, Henrique Nunes [UNESP] Da Silva, Marcos Vinícius Barbosa |
author_role |
author |
author2 |
Nkrumah, Donald Grossi, Daniela do Amaral De Barros, Priscila Sales Paiva, Pablo Bezerra, Luiz Antônio Framatino De Oliveira, Henrique Nunes [UNESP] Da Silva, Marcos Vinícius Barbosa |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade de São Paulo (USP) Kalamazoo, MI Associação Nacional de Criadores e Pesquisadores (ANCP) Pfizer Animal Genetics Pfizer Saúde Animal Universidade Estadual Paulista (Unesp) Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) |
dc.contributor.author.fl_str_mv |
Lôbo, Raysildo Barbosa Nkrumah, Donald Grossi, Daniela do Amaral De Barros, Priscila Sales Paiva, Pablo Bezerra, Luiz Antônio Framatino De Oliveira, Henrique Nunes [UNESP] Da Silva, Marcos Vinícius Barbosa |
dc.subject.por.fl_str_mv |
Dna markers Genetic evaluation Genomic Enhanced epds Genomic selection Nellore cattle Snp Animalia Bos Bos indicus Bovinae |
topic |
Dna markers Genetic evaluation Genomic Enhanced epds Genomic selection Nellore cattle Snp Animalia Bos Bos indicus Bovinae |
description |
Background: The sequencing and publication of the cattle genome and the identification of single nucleotide polymorphism (SNP) molecular markers have provided new tools for animal genetic evaluation and genomic-enhanced selection. These new tools aim to increase the accuracy and scope of selection while decreasing generation interval. The objective of this study was to evaluate the enhancement of accuracy caused by the use of genomic information (Clarifide® - Pfizer) on genetic evaluation of Brazilian Nellore cattle. Review: The application of genome-wide association studies (GWAS) is recognized as one of the most practical approaches to modern genetic improvement. Genomic selection is perhaps most suited to the improvement of traits with low heritability in zebu cattle. The primary interest in livestock genomics has been to estimate the effects of all the markers on the chip, conduct cross-validation to determine accuracy, and apply the resulting information in GWAS either alone [9] or in combination with bull test and pedigree-based genetic evaluation data. The cost of SNP50K genotyping however limits the commercial application of GWAS based on all the SNPs on the chip. However, reasonable predictability and accuracy can be achieved in GWAS by using an assay that contains an optimally selected predictive subset of markers, as opposed to all the SNPs on the chip. The best way to integrate genomic information into genetic improvement programs is to have it included in traditional genetic evaluations. This approach combines traditional expected progeny differences based on phenotype and pedigree with the genomic breeding values based on the markers. Including the different sources of information into a multiple trait genetic evaluation model, for within breed dairy cattle selection, is working with excellent results. However, given the wide genetic diversity of zebu breeds, the high-density panel used for genomic selection in dairy cattle (Ilumina Bovine SNP50 array) appears insufficient for across-breed genomic predictions and selection in beef cattle. Today there is only one breed-specific targeted SNP panel and genomic predictions developed using animals across the entire population of the Nellore breed (www.pfizersaudeanimal.com), which enables genomically - enhanced selection. Genomic profiles are a way to enhance our current selection tools to achieve more accurate predictions for younger animals. Material and Methods: We analyzed the age at first calving (AFC), accumulated productivity (ACP), stayability (STAY) and heifer pregnancy at 30 months (HP30) in Nellore cattle fitting two different animal models; 1) a traditional single trait model, and 2) a two-trait model where the genomic breeding value or molecular value prediction (MVP) was included as a correlated trait. All mixed model analyses were performed using the statistical software ASREML 3.0. Results: Genetic correlation estimates between AFC, ACP, STAY, HP30 and respective MVPs ranged from 0.29 to 0.46. Results also showed an increase of 56%, 36%, 62% and 19% in estimated accuracy of AFC, ACP, STAY and HP30 when MVP information was included in the animal model. Conclusion: Depending upon the trait, integration of MVP information into genetic evaluation resulted in increased accuracy of 19% to 62% as compared to accuracy from traditional genetic evaluation. GE-EPD will be an effective tool to enable faster genetic improvement through more dependable selection of young animals. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-12-01 2014-05-27T11:26:18Z 2014-05-27T11:26:18Z |
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://www.ufrgs.br/actavet/39-suple-1/04%20Supl_s23-s27.pdf Acta Scientiae Veterinariae, v. 39, n. SUPPL. 1, 2011. 1678-0345 1679-9216 http://hdl.handle.net/11449/73022 2-s2.0-84868614917 2-s2.0-84868614917.pdf |
url |
http://www.ufrgs.br/actavet/39-suple-1/04%20Supl_s23-s27.pdf http://hdl.handle.net/11449/73022 |
identifier_str_mv |
Acta Scientiae Veterinariae, v. 39, n. SUPPL. 1, 2011. 1678-0345 1679-9216 2-s2.0-84868614917 2-s2.0-84868614917.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Acta Scientiae Veterinariae 0.217 0,144 0,144 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
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 |
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1808129402804895744 |