Bayesian analysis of pig growth curves combining pedigree and genomic information
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | LOCUS Repositório Institucional da UFV |
Texto Completo: | https://doi.org/10.1016/j.livsci.2017.03.024 http://www.locus.ufv.br/handle/123456789/21949 |
Resumo: | We proposed a genome association study for pig growth curves based on Bayesian hierarchical framework considering different sets of SNP markers and pedigree. Additionally, we aimed also to identify possible chromosome regions affecting the growth curve parameters using empirical weight-age data from an outbred F2 (Brazilian Piau vs commercial) pig population. Under the proposed hierarchical approach, individual growth trajectories were modeled by the nonlinear Gompertz function, so that the parameter estimates were considered to be affected by additive polygenic, systematic and SNP markers effects. The model assuming jointly pedigree and SNP markers presented the best fit based on Deviance Information Criterion. Heritability estimates ranged from 0.53 to 0.56 and from 0.55 to 0.57, respectively for the parameters mature weight (a) and maturing rate (k). Additionally, we found high and positive genetic correlation (0.78) between “a” and "k". The percentages of the genetic variances explained by each SNP allowed identifying the most relevant chromosome regions for each phenotype (growth curve parameters). The majority of these regions were closed to QTL regions previously reported for growth traits. However, we identified three relevant SNPs (55840514 bp at SSC17, 55814469 at SSC17 and 76475804 at SSC X) affecting "a" and "k" simultaneously, and three SNPs affecting only "a" (292758 bp at SSC1, 67319 bp at SSC8 and 50290193 bp at SSC17), that are located in regions not previously described as QTL for growth traits in pigs. |
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Lázaro, Sirlene FernandesEscriche, Noelia IbáñezVarona, LuisSilva, Fabyano Fonseca eBrito, Lais CostaGuimarães, Simone Eliza FacioniLopes, Paulo Sávio2018-09-24T13:39:24Z2018-09-24T13:39:24Z2017-071871-1413https://doi.org/10.1016/j.livsci.2017.03.024http://www.locus.ufv.br/handle/123456789/21949We proposed a genome association study for pig growth curves based on Bayesian hierarchical framework considering different sets of SNP markers and pedigree. Additionally, we aimed also to identify possible chromosome regions affecting the growth curve parameters using empirical weight-age data from an outbred F2 (Brazilian Piau vs commercial) pig population. Under the proposed hierarchical approach, individual growth trajectories were modeled by the nonlinear Gompertz function, so that the parameter estimates were considered to be affected by additive polygenic, systematic and SNP markers effects. The model assuming jointly pedigree and SNP markers presented the best fit based on Deviance Information Criterion. Heritability estimates ranged from 0.53 to 0.56 and from 0.55 to 0.57, respectively for the parameters mature weight (a) and maturing rate (k). Additionally, we found high and positive genetic correlation (0.78) between “a” and "k". The percentages of the genetic variances explained by each SNP allowed identifying the most relevant chromosome regions for each phenotype (growth curve parameters). The majority of these regions were closed to QTL regions previously reported for growth traits. However, we identified three relevant SNPs (55840514 bp at SSC17, 55814469 at SSC17 and 76475804 at SSC X) affecting "a" and "k" simultaneously, and three SNPs affecting only "a" (292758 bp at SSC1, 67319 bp at SSC8 and 50290193 bp at SSC17), that are located in regions not previously described as QTL for growth traits in pigs.engLivestock ScienceVolume 201, Pages 34-40, July 2017Elsevier B. V.info:eu-repo/semantics/openAccessHierarchical nonlinear modelGompertzSNP markersBayesian analysis of pig growth curves combining pedigree and genomic informationinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfreponame:LOCUS Repositório Institucional da UFVinstname:Universidade Federal de Viçosa (UFV)instacron:UFVORIGINALartigo.pdfartigo.pdfTexto completoapplication/pdf431202https://locus.ufv.br//bitstream/123456789/21949/1/artigo.pdfe5ed211127a6f6d48d0c4f9d215a152aMD51LICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://locus.ufv.br//bitstream/123456789/21949/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52THUMBNAILartigo.pdf.jpgartigo.pdf.jpgIM Thumbnailimage/jpeg5858https://locus.ufv.br//bitstream/123456789/21949/3/artigo.pdf.jpgbe39b37a4a18cc8218d5df5f8741d1dfMD53123456789/219492018-09-24 23:00:39.428oai:locus.ufv.br:123456789/21949Tk9URTogUExBQ0UgWU9VUiBPV04gTElDRU5TRSBIRVJFClRoaXMgc2FtcGxlIGxpY2Vuc2UgaXMgcHJvdmlkZWQgZm9yIGluZm9ybWF0aW9uYWwgcHVycG9zZXMgb25seS4KCk5PTi1FWENMVVNJVkUgRElTVFJJQlVUSU9OIExJQ0VOU0UKCkJ5IHNpZ25pbmcgYW5kIHN1Ym1pdHRpbmcgdGhpcyBsaWNlbnNlLCB5b3UgKHRoZSBhdXRob3Iocykgb3IgY29weXJpZ2h0Cm93bmVyKSBncmFudHMgdG8gRFNwYWNlIFVuaXZlcnNpdHkgKERTVSkgdGhlIG5vbi1leGNsdXNpdmUgcmlnaHQgdG8gcmVwcm9kdWNlLAp0cmFuc2xhdGUgKGFzIGRlZmluZWQgYmVsb3cpLCBhbmQvb3IgZGlzdHJpYnV0ZSB5b3VyIHN1Ym1pc3Npb24gKGluY2x1ZGluZwp0aGUgYWJzdHJhY3QpIHdvcmxkd2lkZSBpbiBwcmludCBhbmQgZWxlY3Ryb25pYyBmb3JtYXQgYW5kIGluIGFueSBtZWRpdW0sCmluY2x1ZGluZyBidXQgbm90IGxpbWl0ZWQgdG8gYXVkaW8gb3IgdmlkZW8uCgpZb3UgYWdyZWUgdGhhdCBEU1UgbWF5LCB3aXRob3V0IGNoYW5naW5nIHRoZSBjb250ZW50LCB0cmFuc2xhdGUgdGhlCnN1Ym1pc3Npb24gdG8gYW55IG1lZGl1bSBvciBmb3JtYXQgZm9yIHRoZSBwdXJwb3NlIG9mIHByZXNlcnZhdGlvbi4KCllvdSBhbHNvIGFncmVlIHRoYXQgRFNVIG1heSBrZWVwIG1vcmUgdGhhbiBvbmUgY29weSBvZiB0aGlzIHN1Ym1pc3Npb24gZm9yCnB1cnBvc2VzIG9mIHNlY3VyaXR5LCBiYWNrLXVwIGFuZCBwcmVzZXJ2YXRpb24uCgpZb3UgcmVwcmVzZW50IHRoYXQgdGhlIHN1Ym1pc3Npb24gaXMgeW91ciBvcmlnaW5hbCB3b3JrLCBhbmQgdGhhdCB5b3UgaGF2ZQp0aGUgcmlnaHQgdG8gZ3JhbnQgdGhlIHJpZ2h0cyBjb250YWluZWQgaW4gdGhpcyBsaWNlbnNlLiBZb3UgYWxzbyByZXByZXNlbnQKdGhhdCB5b3VyIHN1Ym1pc3Npb24gZG9lcyBub3QsIHRvIHRoZSBiZXN0IG9mIHlvdXIga25vd2xlZGdlLCBpbmZyaW5nZSB1cG9uCmFueW9uZSdzIGNvcHlyaWdodC4KCklmIHRoZSBzdWJtaXNzaW9uIGNvbnRhaW5zIG1hdGVyaWFsIGZvciB3aGljaCB5b3UgZG8gbm90IGhvbGQgY29weXJpZ2h0LAp5b3UgcmVwcmVzZW50IHRoYXQgeW91IGhhdmUgb2J0YWluZWQgdGhlIHVucmVzdHJpY3RlZCBwZXJtaXNzaW9uIG9mIHRoZQpjb3B5cmlnaHQgb3duZXIgdG8gZ3JhbnQgRFNVIHRoZSByaWdodHMgcmVxdWlyZWQgYnkgdGhpcyBsaWNlbnNlLCBhbmQgdGhhdApzdWNoIHRoaXJkLXBhcnR5IG93bmVkIG1hdGVyaWFsIGlzIGNsZWFybHkgaWRlbnRpZmllZCBhbmQgYWNrbm93bGVkZ2VkCndpdGhpbiB0aGUgdGV4dCBvciBjb250ZW50IG9mIHRoZSBzdWJtaXNzaW9uLgoKSUYgVEhFIFNVQk1JU1NJT04gSVMgQkFTRUQgVVBPTiBXT1JLIFRIQVQgSEFTIEJFRU4gU1BPTlNPUkVEIE9SIFNVUFBPUlRFRApCWSBBTiBBR0VOQ1kgT1IgT1JHQU5JWkFUSU9OIE9USEVSIFRIQU4gRFNVLCBZT1UgUkVQUkVTRU5UIFRIQVQgWU9VIEhBVkUKRlVMRklMTEVEIEFOWSBSSUdIVCBPRiBSRVZJRVcgT1IgT1RIRVIgT0JMSUdBVElPTlMgUkVRVUlSRUQgQlkgU1VDSApDT05UUkFDVCBPUiBBR1JFRU1FTlQuCgpEU1Ugd2lsbCBjbGVhcmx5IGlkZW50aWZ5IHlvdXIgbmFtZShzKSBhcyB0aGUgYXV0aG9yKHMpIG9yIG93bmVyKHMpIG9mIHRoZQpzdWJtaXNzaW9uLCBhbmQgd2lsbCBub3QgbWFrZSBhbnkgYWx0ZXJhdGlvbiwgb3RoZXIgdGhhbiBhcyBhbGxvd2VkIGJ5IHRoaXMKbGljZW5zZSwgdG8geW91ciBzdWJtaXNzaW9uLgo=Repositório InstitucionalPUBhttps://www.locus.ufv.br/oai/requestfabiojreis@ufv.bropendoar:21452018-09-25T02:00:39LOCUS Repositório Institucional da UFV - Universidade Federal de Viçosa (UFV)false |
dc.title.en.fl_str_mv |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
title |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
spellingShingle |
Bayesian analysis of pig growth curves combining pedigree and genomic information Lázaro, Sirlene Fernandes Hierarchical nonlinear model Gompertz SNP markers |
title_short |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
title_full |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
title_fullStr |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
title_full_unstemmed |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
title_sort |
Bayesian analysis of pig growth curves combining pedigree and genomic information |
author |
Lázaro, Sirlene Fernandes |
author_facet |
Lázaro, Sirlene Fernandes Escriche, Noelia Ibáñez Varona, Luis Silva, Fabyano Fonseca e Brito, Lais Costa Guimarães, Simone Eliza Facioni Lopes, Paulo Sávio |
author_role |
author |
author2 |
Escriche, Noelia Ibáñez Varona, Luis Silva, Fabyano Fonseca e Brito, Lais Costa Guimarães, Simone Eliza Facioni Lopes, Paulo Sávio |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Lázaro, Sirlene Fernandes Escriche, Noelia Ibáñez Varona, Luis Silva, Fabyano Fonseca e Brito, Lais Costa Guimarães, Simone Eliza Facioni Lopes, Paulo Sávio |
dc.subject.pt-BR.fl_str_mv |
Hierarchical nonlinear model Gompertz SNP markers |
topic |
Hierarchical nonlinear model Gompertz SNP markers |
description |
We proposed a genome association study for pig growth curves based on Bayesian hierarchical framework considering different sets of SNP markers and pedigree. Additionally, we aimed also to identify possible chromosome regions affecting the growth curve parameters using empirical weight-age data from an outbred F2 (Brazilian Piau vs commercial) pig population. Under the proposed hierarchical approach, individual growth trajectories were modeled by the nonlinear Gompertz function, so that the parameter estimates were considered to be affected by additive polygenic, systematic and SNP markers effects. The model assuming jointly pedigree and SNP markers presented the best fit based on Deviance Information Criterion. Heritability estimates ranged from 0.53 to 0.56 and from 0.55 to 0.57, respectively for the parameters mature weight (a) and maturing rate (k). Additionally, we found high and positive genetic correlation (0.78) between “a” and "k". The percentages of the genetic variances explained by each SNP allowed identifying the most relevant chromosome regions for each phenotype (growth curve parameters). The majority of these regions were closed to QTL regions previously reported for growth traits. However, we identified three relevant SNPs (55840514 bp at SSC17, 55814469 at SSC17 and 76475804 at SSC X) affecting "a" and "k" simultaneously, and three SNPs affecting only "a" (292758 bp at SSC1, 67319 bp at SSC8 and 50290193 bp at SSC17), that are located in regions not previously described as QTL for growth traits in pigs. |
publishDate |
2017 |
dc.date.issued.fl_str_mv |
2017-07 |
dc.date.accessioned.fl_str_mv |
2018-09-24T13:39:24Z |
dc.date.available.fl_str_mv |
2018-09-24T13:39:24Z |
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 |
https://doi.org/10.1016/j.livsci.2017.03.024 http://www.locus.ufv.br/handle/123456789/21949 |
dc.identifier.issn.none.fl_str_mv |
1871-1413 |
identifier_str_mv |
1871-1413 |
url |
https://doi.org/10.1016/j.livsci.2017.03.024 http://www.locus.ufv.br/handle/123456789/21949 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartofseries.pt-BR.fl_str_mv |
Volume 201, Pages 34-40, July 2017 |
dc.rights.driver.fl_str_mv |
Elsevier B. V. info:eu-repo/semantics/openAccess |
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Elsevier B. V. |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Livestock Science |
publisher.none.fl_str_mv |
Livestock Science |
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