Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1186/s12864-019-5520-9 http://hdl.handle.net/11449/190134 |
Resumo: | Background: Genome-wide association studies (GWAS) are utilized in cattle to identify regions or genetic variants associated with phenotypes of interest, and thus, to identify design strategies that allow for the increase of the frequency of favorable alleles. Visual scores are important traits of cattle production in Brazil because they are utilized as selection criteria, helping to choose more harmonious animals. Despite its importance, there are still no studies on the genome association for these traits. This study aimed to identify genome regions associated with the traits of conformation, precocity and muscling, based on a visual score measured at weaning. Results: Bayesian approaches with BayesC and Bayesian LASSO were utilized with 2873 phenotypes of Nellore cattle for a GWAS. The animals were genotyped with Illumina BovineHD BeadChip, and a total of 309,865 SNPs were utilized after quality control. In the analyses, phenotype and deregressed breeding values were utilized as dependent variables; a threshold model was utilized for the former and a linear model for the latter. The association criterion was the percentage of genetic variance explained by SNPs found in 1 Mb-long windows. The Bayesian approach BayesC was better adjusted to the data because it could explain a larger phenotypic variance for both dependent variables. Conclusions: There were no large effects for the visual scores, indicating that they have a polygenic nature; however, regions in chromosomes 1, 3, 5, 7, 14, 15, 16, 19, 20 and 23 were identified and explained a large part of the genetic variance. |
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Genome Association Study for Visual Scores in Nellore Cattle Measured at WeaningBayesCBayesian LASSOGrowth genesBackground: Genome-wide association studies (GWAS) are utilized in cattle to identify regions or genetic variants associated with phenotypes of interest, and thus, to identify design strategies that allow for the increase of the frequency of favorable alleles. Visual scores are important traits of cattle production in Brazil because they are utilized as selection criteria, helping to choose more harmonious animals. Despite its importance, there are still no studies on the genome association for these traits. This study aimed to identify genome regions associated with the traits of conformation, precocity and muscling, based on a visual score measured at weaning. Results: Bayesian approaches with BayesC and Bayesian LASSO were utilized with 2873 phenotypes of Nellore cattle for a GWAS. The animals were genotyped with Illumina BovineHD BeadChip, and a total of 309,865 SNPs were utilized after quality control. In the analyses, phenotype and deregressed breeding values were utilized as dependent variables; a threshold model was utilized for the former and a linear model for the latter. The association criterion was the percentage of genetic variance explained by SNPs found in 1 Mb-long windows. The Bayesian approach BayesC was better adjusted to the data because it could explain a larger phenotypic variance for both dependent variables. Conclusions: There were no large effects for the visual scores, indicating that they have a polygenic nature; however, regions in chromosomes 1, 3, 5, 7, 14, 15, 16, 19, 20 and 23 were identified and explained a large part of the genetic variance.Animal Science Department School of Agricultural and Veterinary Sciences São Paulo State University (Unesp)Animal Science Department São Paulo State University (Unesp), DracenaAnimal Science Department School of Agricultural and Veterinary Sciences São Paulo State University (Unesp)Animal Science Department São Paulo State University (Unesp), DracenaUniversidade Estadual Paulista (Unesp)Carreño, Luis Orlando Duitama [UNESP]Da Conceição Pessoa, Matilde [UNESP]Espigolan, Rafael [UNESP]Takada, Luciana [UNESP]Bresolin, Tiago [UNESP]Cavani, Ligia [UNESP]Baldi, Fernando [UNESP]Carvalheiro, Roberto [UNESP]De Albuquerque, Lucia Galvão [UNESP]Da Fonseca, Ricardo [UNESP]2019-10-06T17:03:28Z2019-10-06T17:03:28Z2019-02-20info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1186/s12864-019-5520-9BMC Genomics, v. 20, n. 1, 2019.1471-2164http://hdl.handle.net/11449/19013410.1186/s12864-019-5520-92-s2.0-8506196637003083523735455580000-0002-1163-6296Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengBMC Genomicsinfo:eu-repo/semantics/openAccess2024-06-07T18:45:08Zoai:repositorio.unesp.br:11449/190134Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-06T00:02:27.506912Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
title |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
spellingShingle |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning Carreño, Luis Orlando Duitama [UNESP] BayesC Bayesian LASSO Growth genes |
title_short |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
title_full |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
title_fullStr |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
title_full_unstemmed |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
title_sort |
Genome Association Study for Visual Scores in Nellore Cattle Measured at Weaning |
author |
Carreño, Luis Orlando Duitama [UNESP] |
author_facet |
Carreño, Luis Orlando Duitama [UNESP] Da Conceição Pessoa, Matilde [UNESP] Espigolan, Rafael [UNESP] Takada, Luciana [UNESP] Bresolin, Tiago [UNESP] Cavani, Ligia [UNESP] Baldi, Fernando [UNESP] Carvalheiro, Roberto [UNESP] De Albuquerque, Lucia Galvão [UNESP] Da Fonseca, Ricardo [UNESP] |
author_role |
author |
author2 |
Da Conceição Pessoa, Matilde [UNESP] Espigolan, Rafael [UNESP] Takada, Luciana [UNESP] Bresolin, Tiago [UNESP] Cavani, Ligia [UNESP] Baldi, Fernando [UNESP] Carvalheiro, Roberto [UNESP] De Albuquerque, Lucia Galvão [UNESP] Da Fonseca, Ricardo [UNESP] |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Carreño, Luis Orlando Duitama [UNESP] Da Conceição Pessoa, Matilde [UNESP] Espigolan, Rafael [UNESP] Takada, Luciana [UNESP] Bresolin, Tiago [UNESP] Cavani, Ligia [UNESP] Baldi, Fernando [UNESP] Carvalheiro, Roberto [UNESP] De Albuquerque, Lucia Galvão [UNESP] Da Fonseca, Ricardo [UNESP] |
dc.subject.por.fl_str_mv |
BayesC Bayesian LASSO Growth genes |
topic |
BayesC Bayesian LASSO Growth genes |
description |
Background: Genome-wide association studies (GWAS) are utilized in cattle to identify regions or genetic variants associated with phenotypes of interest, and thus, to identify design strategies that allow for the increase of the frequency of favorable alleles. Visual scores are important traits of cattle production in Brazil because they are utilized as selection criteria, helping to choose more harmonious animals. Despite its importance, there are still no studies on the genome association for these traits. This study aimed to identify genome regions associated with the traits of conformation, precocity and muscling, based on a visual score measured at weaning. Results: Bayesian approaches with BayesC and Bayesian LASSO were utilized with 2873 phenotypes of Nellore cattle for a GWAS. The animals were genotyped with Illumina BovineHD BeadChip, and a total of 309,865 SNPs were utilized after quality control. In the analyses, phenotype and deregressed breeding values were utilized as dependent variables; a threshold model was utilized for the former and a linear model for the latter. The association criterion was the percentage of genetic variance explained by SNPs found in 1 Mb-long windows. The Bayesian approach BayesC was better adjusted to the data because it could explain a larger phenotypic variance for both dependent variables. Conclusions: There were no large effects for the visual scores, indicating that they have a polygenic nature; however, regions in chromosomes 1, 3, 5, 7, 14, 15, 16, 19, 20 and 23 were identified and explained a large part of the genetic variance. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-10-06T17:03:28Z 2019-10-06T17:03:28Z 2019-02-20 |
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/10.1186/s12864-019-5520-9 BMC Genomics, v. 20, n. 1, 2019. 1471-2164 http://hdl.handle.net/11449/190134 10.1186/s12864-019-5520-9 2-s2.0-85061966370 0308352373545558 0000-0002-1163-6296 |
url |
http://dx.doi.org/10.1186/s12864-019-5520-9 http://hdl.handle.net/11449/190134 |
identifier_str_mv |
BMC Genomics, v. 20, n. 1, 2019. 1471-2164 10.1186/s12864-019-5520-9 2-s2.0-85061966370 0308352373545558 0000-0002-1163-6296 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
BMC Genomics |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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_ |
1808129575981416448 |