Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1111/jbg.12463 http://hdl.handle.net/11449/199851 |
Resumo: | The aim of this study was to evaluate the genomic predictions using the single-step genomic best linear unbiased predictor (ssGBLUP) method based on SNPs and haplotype markers associated with beef fatty acids (FAs) profile in Nelore cattle. The data set contained records from 963 Nelore bulls finished in feedlot (±90 days) and slaughtered with approximately 24 months of age. Meat samples from the Longissimus dorsi muscle were taken for FAs profile measurement. FAs were quantified by gas chromatography using a SP-2560 capillary column. Animals were genotyped with the high-density SNP panel (BovineHD BeadChip assay) containing 777,962 markers. SNPs with a minor allele frequency and a call rate lower than 0.05 and 0.90, respectively, monomorphic, located on sex chromosomes, and with unknown position were removed from the data set. After genomic quality control, a total of 469,981 SNPs and 892 samples were available for subsequent analyses. Missing genotypes were imputed and phased using the FImpute software. Haplotype blocks were defined based on linkage disequilibrium using the Haploview software. The model to estimate variance components and genetic parameters and to predict the genomic values included the random genetic additive effects, fixed effects of the contemporary group and the age at slaughter as a linear covariate. Accuracies using the haplotype-based approach ranged from 0.07 to 0.31, and those SNP-based ranged from 0.06 to 0.33. Regression coefficients ranged from 0.07 to 0.74 and from 0.08 to 1.45 using the haplotype- and SNP-based approaches, respectively. Despite the low to moderate accuracies for the genomic values, it is possible to obtain genetic progress trough selection using genomic information based either on SNPs or haplotype markers. The SNP-based approach allows less biased genomic evaluations, and it is more feasible when taking into account the computational and operational cost underlying the haplotypes inference. |
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Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattleBos taurus indicusgenetic markersheritabilitymeat qualityssGBLUPThe aim of this study was to evaluate the genomic predictions using the single-step genomic best linear unbiased predictor (ssGBLUP) method based on SNPs and haplotype markers associated with beef fatty acids (FAs) profile in Nelore cattle. The data set contained records from 963 Nelore bulls finished in feedlot (±90 days) and slaughtered with approximately 24 months of age. Meat samples from the Longissimus dorsi muscle were taken for FAs profile measurement. FAs were quantified by gas chromatography using a SP-2560 capillary column. Animals were genotyped with the high-density SNP panel (BovineHD BeadChip assay) containing 777,962 markers. SNPs with a minor allele frequency and a call rate lower than 0.05 and 0.90, respectively, monomorphic, located on sex chromosomes, and with unknown position were removed from the data set. After genomic quality control, a total of 469,981 SNPs and 892 samples were available for subsequent analyses. Missing genotypes were imputed and phased using the FImpute software. Haplotype blocks were defined based on linkage disequilibrium using the Haploview software. The model to estimate variance components and genetic parameters and to predict the genomic values included the random genetic additive effects, fixed effects of the contemporary group and the age at slaughter as a linear covariate. Accuracies using the haplotype-based approach ranged from 0.07 to 0.31, and those SNP-based ranged from 0.06 to 0.33. Regression coefficients ranged from 0.07 to 0.74 and from 0.08 to 1.45 using the haplotype- and SNP-based approaches, respectively. Despite the low to moderate accuracies for the genomic values, it is possible to obtain genetic progress trough selection using genomic information based either on SNPs or haplotype markers. The SNP-based approach allows less biased genomic evaluations, and it is more feasible when taking into account the computational and operational cost underlying the haplotypes inference.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Faculdade de Ciências Agrárias e Veterinárias Departamento de Zootecnia Universidade Estadual Paulista Júlio de Mesquita Filho UNESPFaculdade de Zootecnia e Engenharia de Alimentos Departamento de Nutrição e Produção Animal Universidade de São PauloZoetisDepartment of Animal Sciences Purdue UniversityFaculdade de Zootecnia e Engenharia de Alimentos Departamento de Medicina Veterinária Universidade de São PauloFaculdade de Ciências Agrárias e Veterinárias Departamento de Zootecnia Universidade Estadual Paulista Júlio de Mesquita Filho UNESPFAPESP: 2009/16118-5FAPESP: 2015/25304-8FAPESP: 2016/24085-3Universidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)ZoetisPurdue UniversityFeitosa, Fabieli Loise Braga [UNESP]Pereira, Angélica Simone CravoAmorim, Sabrina Thaise [UNESP]Peripolli, Elisa [UNESP]Silva, Rafael Medeiros de OliveiraBraz, Camila Urbano [UNESP]Ferrinho, Adrielle MatiasSchenkel, Flavio SchrammBrito, Luiz FernandoEspigolan, Rafaelde Albuquerque, Lucia Galvão [UNESP]Baldi, Fernando [UNESP]2020-12-12T01:51:04Z2020-12-12T01:51:04Z2020-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article468-476http://dx.doi.org/10.1111/jbg.12463Journal of Animal Breeding and Genetics, v. 137, n. 5, p. 468-476, 2020.1439-03880931-2668http://hdl.handle.net/11449/19985110.1111/jbg.124632-s2.0-85076909277Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of Animal Breeding and Geneticsinfo:eu-repo/semantics/openAccess2024-06-07T18:40:52Zoai:repositorio.unesp.br:11449/199851Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:38:24.934060Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
title |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
spellingShingle |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle Feitosa, Fabieli Loise Braga [UNESP] Bos taurus indicus genetic markers heritability meat quality ssGBLUP |
title_short |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
title_full |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
title_fullStr |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
title_full_unstemmed |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
title_sort |
Comparison between haplotype-based and individual snp-based genomic predictions for beef fatty acid profile in Nelore cattle |
author |
Feitosa, Fabieli Loise Braga [UNESP] |
author_facet |
Feitosa, Fabieli Loise Braga [UNESP] Pereira, Angélica Simone Cravo Amorim, Sabrina Thaise [UNESP] Peripolli, Elisa [UNESP] Silva, Rafael Medeiros de Oliveira Braz, Camila Urbano [UNESP] Ferrinho, Adrielle Matias Schenkel, Flavio Schramm Brito, Luiz Fernando Espigolan, Rafael de Albuquerque, Lucia Galvão [UNESP] Baldi, Fernando [UNESP] |
author_role |
author |
author2 |
Pereira, Angélica Simone Cravo Amorim, Sabrina Thaise [UNESP] Peripolli, Elisa [UNESP] Silva, Rafael Medeiros de Oliveira Braz, Camila Urbano [UNESP] Ferrinho, Adrielle Matias Schenkel, Flavio Schramm Brito, Luiz Fernando Espigolan, Rafael de Albuquerque, Lucia Galvão [UNESP] Baldi, Fernando [UNESP] |
author2_role |
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) Zoetis Purdue University |
dc.contributor.author.fl_str_mv |
Feitosa, Fabieli Loise Braga [UNESP] Pereira, Angélica Simone Cravo Amorim, Sabrina Thaise [UNESP] Peripolli, Elisa [UNESP] Silva, Rafael Medeiros de Oliveira Braz, Camila Urbano [UNESP] Ferrinho, Adrielle Matias Schenkel, Flavio Schramm Brito, Luiz Fernando Espigolan, Rafael de Albuquerque, Lucia Galvão [UNESP] Baldi, Fernando [UNESP] |
dc.subject.por.fl_str_mv |
Bos taurus indicus genetic markers heritability meat quality ssGBLUP |
topic |
Bos taurus indicus genetic markers heritability meat quality ssGBLUP |
description |
The aim of this study was to evaluate the genomic predictions using the single-step genomic best linear unbiased predictor (ssGBLUP) method based on SNPs and haplotype markers associated with beef fatty acids (FAs) profile in Nelore cattle. The data set contained records from 963 Nelore bulls finished in feedlot (±90 days) and slaughtered with approximately 24 months of age. Meat samples from the Longissimus dorsi muscle were taken for FAs profile measurement. FAs were quantified by gas chromatography using a SP-2560 capillary column. Animals were genotyped with the high-density SNP panel (BovineHD BeadChip assay) containing 777,962 markers. SNPs with a minor allele frequency and a call rate lower than 0.05 and 0.90, respectively, monomorphic, located on sex chromosomes, and with unknown position were removed from the data set. After genomic quality control, a total of 469,981 SNPs and 892 samples were available for subsequent analyses. Missing genotypes were imputed and phased using the FImpute software. Haplotype blocks were defined based on linkage disequilibrium using the Haploview software. The model to estimate variance components and genetic parameters and to predict the genomic values included the random genetic additive effects, fixed effects of the contemporary group and the age at slaughter as a linear covariate. Accuracies using the haplotype-based approach ranged from 0.07 to 0.31, and those SNP-based ranged from 0.06 to 0.33. Regression coefficients ranged from 0.07 to 0.74 and from 0.08 to 1.45 using the haplotype- and SNP-based approaches, respectively. Despite the low to moderate accuracies for the genomic values, it is possible to obtain genetic progress trough selection using genomic information based either on SNPs or haplotype markers. The SNP-based approach allows less biased genomic evaluations, and it is more feasible when taking into account the computational and operational cost underlying the haplotypes inference. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T01:51:04Z 2020-12-12T01:51:04Z 2020-09-01 |
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/10.1111/jbg.12463 Journal of Animal Breeding and Genetics, v. 137, n. 5, p. 468-476, 2020. 1439-0388 0931-2668 http://hdl.handle.net/11449/199851 10.1111/jbg.12463 2-s2.0-85076909277 |
url |
http://dx.doi.org/10.1111/jbg.12463 http://hdl.handle.net/11449/199851 |
identifier_str_mv |
Journal of Animal Breeding and Genetics, v. 137, n. 5, p. 468-476, 2020. 1439-0388 0931-2668 10.1111/jbg.12463 2-s2.0-85076909277 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Journal of Animal Breeding and Genetics |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
468-476 |
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_ |
1808128682103930880 |