Genome-wide association study of reproductive traits in Nellore heifers using Bayesian inference
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , , , , , , |
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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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 1,745 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
67 application/pdf |
dc.publisher.none.fl_str_mv |
Genetics, Selection, Evolution : Gse |
publisher.none.fl_str_mv |
Genetics, Selection, Evolution : Gse |
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PubMed 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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1808129346242609152 |