Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference

Detalhes bibliográficos
Autor(a) principal: Costa, Raphael B. [UNESP]
Data de Publicação: 2015
Outros Autores: Camargo, Gregório M. F. [UNESP], Diaz, Iara D. P. S. [UNESP], Irano, Natalia [UNESP], Dias, Marina M. [UNESP], Carvalheiro, Roberto [UNESP], Boligon, Arione A. [UNESP], Baldi, Fernando [UNESP], Oliveira, Henrique N. [UNESP], Tonhati, Humberto [UNESP], Albuquerque, Lucia G. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1186/s12711-015-0146-0
http://hdl.handle.net/11449/131465
Resumo: An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer's rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved. Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs. The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.
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spelling Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inferenceAn important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer's rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved. Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs. The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. raphaelbcosta@gmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. gregoriocamargo@hotmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. iarasolar@hotmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. nattirano@hotmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. marina.mortati@gmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. rcar@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. arioneboligon@yahoo.com.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. fernandobaldiuy@gmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. holiveira@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. tonhati@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. lgalb@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. raphaelbcosta@gmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. gregoriocamargo@hotmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. iarasolar@hotmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. nattirano@hotmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. marina.mortati@gmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. rcar@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. arioneboligon@yahoo.com.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. fernandobaldiuy@gmail.com.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. holiveira@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. tonhati@fcav.unesp.br.UNESP, Universidade Estadual Paulista, Faculdade de Ciências Agrárias e Veterinárias, Jaboticabal, 14884-900, São Paulo, Brazil. lgalb@fcav.unesp.br.Genetics, Selection, Evolution : GseUniversidade Estadual Paulista (Unesp)Costa, Raphael B. [UNESP]Camargo, Gregório M. F. [UNESP]Diaz, Iara D. P. S. [UNESP]Irano, Natalia [UNESP]Dias, Marina M. [UNESP]Carvalheiro, Roberto [UNESP]Boligon, Arione A. [UNESP]Baldi, Fernando [UNESP]Oliveira, Henrique N. [UNESP]Tonhati, Humberto [UNESP]Albuquerque, Lucia G. [UNESP]2015-12-07T15:35:57Z2015-12-07T15:35:57Z2015info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article67application/pdfhttp://dx.doi.org/10.1186/s12711-015-0146-0Genetics, Selection, Evolution : Gse, v. 47, p. 67, 2015.1297-9686http://hdl.handle.net/11449/13146510.1186/s12711-015-0146-0PMC4541729.pdf744525496085815926286463PMC4541729PubMedreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengGenetics, Selection, Evolution : Gse1,745info:eu-repo/semantics/openAccess2024-06-07T18:44:00Zoai:repositorio.unesp.br:11449/131465Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:40:57.887511Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
title Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
spellingShingle Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
Costa, Raphael B. [UNESP]
title_short Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
title_full Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
title_fullStr Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
title_full_unstemmed Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
title_sort Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
author Costa, Raphael B. [UNESP]
author_facet Costa, Raphael B. [UNESP]
Camargo, Gregório M. F. [UNESP]
Diaz, Iara D. P. S. [UNESP]
Irano, Natalia [UNESP]
Dias, Marina M. [UNESP]
Carvalheiro, Roberto [UNESP]
Boligon, Arione A. [UNESP]
Baldi, Fernando [UNESP]
Oliveira, Henrique N. [UNESP]
Tonhati, Humberto [UNESP]
Albuquerque, Lucia G. [UNESP]
author_role author
author2 Camargo, Gregório M. F. [UNESP]
Diaz, Iara D. P. S. [UNESP]
Irano, Natalia [UNESP]
Dias, Marina M. [UNESP]
Carvalheiro, Roberto [UNESP]
Boligon, Arione A. [UNESP]
Baldi, Fernando [UNESP]
Oliveira, Henrique N. [UNESP]
Tonhati, Humberto [UNESP]
Albuquerque, Lucia G. [UNESP]
author2_role author
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 Costa, Raphael B. [UNESP]
Camargo, Gregório M. F. [UNESP]
Diaz, Iara D. P. S. [UNESP]
Irano, Natalia [UNESP]
Dias, Marina M. [UNESP]
Carvalheiro, Roberto [UNESP]
Boligon, Arione A. [UNESP]
Baldi, Fernando [UNESP]
Oliveira, Henrique N. [UNESP]
Tonhati, Humberto [UNESP]
Albuquerque, Lucia G. [UNESP]
description An important goal of Zebu breeding programs is to improve reproductive performance. A major problem faced with the genetic improvement of reproductive traits is that recording the time for an animal to reach sexual maturity is costly. Another issue is that accurate estimates of breeding values are obtained only a long time after the young bulls have gone through selection. An alternative to overcome these problems is to use traits that are indicators of the reproductive efficiency of the herd and are easier to measure, such as age at first calving. Another problem is that heifers that have conceived once may fail to conceive in the next breeding season, which increases production costs. Thus, increasing heifer's rebreeding rates should improve the economic efficiency of the herd. Response to selection for these traits tends to be slow, since they have a low heritability and phenotypic information is provided only later in the life of the animal. Genome-wide association studies (GWAS) are useful to investigate the genetic mechanisms that underlie these traits by identifying the genes and metabolic pathways involved. Data from 1853 females belonging to the Agricultural Jacarezinho LTDA were used. Genotyping was performed using the BovineHD BeadChip (777 962 single nucleotide polymorphisms (SNPs)) according to the protocol of Illumina - Infinium Assay II ® Multi-Sample HiScan with the unit SQ ™ System. After quality control, 305 348 SNPs were used for GWAS. Forty-two and 19 SNPs had a Bayes factor greater than 150 for heifer rebreeding and age at first calving, respectively. All significant SNPs for age at first calving were significant for heifer rebreeding. These 42 SNPs were next or within 35 genes that were distributed over 18 chromosomes and comprised 27 protein-encoding genes, six pseudogenes and two miscellaneous noncoding RNAs. The use of Bayes factor to determine the significance of SNPs allowed us to identify two sets of 42 and 19 significant SNPs for heifer rebreeding and age at first calving, respectively, which explain 11.35 % and 6.42 % of their phenotypic variance, respectively. These SNPs provide relevant information to help elucidate which genes affect these traits.
publishDate 2015
dc.date.none.fl_str_mv 2015-12-07T15:35:57Z
2015-12-07T15:35:57Z
2015
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/s12711-015-0146-0
Genetics, Selection, Evolution : Gse, v. 47, p. 67, 2015.
1297-9686
http://hdl.handle.net/11449/131465
10.1186/s12711-015-0146-0
PMC4541729.pdf
7445254960858159
26286463
PMC4541729
url http://dx.doi.org/10.1186/s12711-015-0146-0
http://hdl.handle.net/11449/131465
identifier_str_mv Genetics, Selection, Evolution : Gse, v. 47, p. 67, 2015.
1297-9686
10.1186/s12711-015-0146-0
PMC4541729.pdf
7445254960858159
26286463
PMC4541729
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Genetics, Selection, Evolution : Gse
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dc.format.none.fl_str_mv 67
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dc.publisher.none.fl_str_mv Genetics, Selection, Evolution : Gse
publisher.none.fl_str_mv Genetics, Selection, Evolution : Gse
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