Genome wide selection (GWS) and maximization of the genetic improvement efficiency
Autor(a) principal: | |
---|---|
Data de Publicação: | 2010 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Pesquisa Florestal Brasileira (Online) |
Texto Completo: | https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/63 |
Resumo: | Genetic selection has been practiced by the best linear unbiased prediction (BLUP) method using phenotypic records. A first proposal for enhancement of the efficiency of this procedure was the marker assisted selection (MAS). Later, another method called genome wide selection - GWS was reported, which presents high accuracy for the selection based exclusively on markers, after predicting their genetic effects from phenotypic data in a sample of the population of selection. GWS is excellent for low heritable traits, while MAS is not. This paper presents the GWS methodology and simulates a case of its application, aiming at emphasizing its advantages over MAS. The relation between traditional BLUP and genomic BLUP is also detailed as well as the sample size required for precise estimation of the genetic values of the markers. Results revealed that the GWS can be worthy for genetic improvement. Practical experience is much needed to infer about its effectiveness. |
id |
EMBRAPA-5_6b62ad1c229c450e571cbb50bb4f1356 |
---|---|
oai_identifier_str |
oai:pfb.cnpf.embrapa.br/pfb:article/63 |
network_acronym_str |
EMBRAPA-5 |
network_name_str |
Pesquisa Florestal Brasileira (Online) |
repository_id_str |
|
spelling |
Genome wide selection (GWS) and maximization of the genetic improvement efficiencySeleção genômica ampla (GWS) e maximização da eficiência do melhoramento genéticoGenomic selectionlinkage disequilibrium analysisfine mappinggenetic markers.Seleção genômicaanálise de desequilíbrio de ligaçãomapeamento finomarcadores molecularesGenetic selection has been practiced by the best linear unbiased prediction (BLUP) method using phenotypic records. A first proposal for enhancement of the efficiency of this procedure was the marker assisted selection (MAS). Later, another method called genome wide selection - GWS was reported, which presents high accuracy for the selection based exclusively on markers, after predicting their genetic effects from phenotypic data in a sample of the population of selection. GWS is excellent for low heritable traits, while MAS is not. This paper presents the GWS methodology and simulates a case of its application, aiming at emphasizing its advantages over MAS. The relation between traditional BLUP and genomic BLUP is also detailed as well as the sample size required for precise estimation of the genetic values of the markers. Results revealed that the GWS can be worthy for genetic improvement. Practical experience is much needed to infer about its effectiveness.A seleção genética tem sido praticada pelo procedimento BLUP, usando dados fenotípicos avaliadosa campo. Uma primeira proposição realizada para aumentar a eficiência desse procedimento, baseado em dadosfenotípicos, foi a seleção auxiliada por marcadores (MAS) moleculares, a qual usa simultaneamente dadosfenotípicos e moleculares. Posteriormente, foi proposto um novo método de seleção denominado seleção genômicaampla (genome wide selection – GWS), o qual apresenta alta acurácia seletiva para a seleção, baseadaexclusivamente em marcadores, após terem seus efeitos genéticos estimados a partir de dados fenotípicos emuma amostra da população de seleção. A GWS é excelente para caracteres de baixa herdabilidade, ao contrário daMAS, que não é útil para caracteres de baixa herdabilidade. O presente trabalho tem como objetivos apresentara metodologia GWS e simular um caso de aplicação da mesma, visando enfatizar as suas vantagens sobre aMAS. Objetiva também demonstrar a relação entre o BLUP tradicional e o BLUP genômico associado à GWS.Adicionalmente, discute aspectos referentes ao tamanho amostral adequado para estimação dos efeitosgenotípicos dos marcadores. Os resultados revelam que a GWS poderá ter grande utilidade ao melhoramentogenético. No entanto, é preciso adquirir experiência prática com a GWS, visando inferir sobre sua efetividade.Embrapa Florestas2010-03-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/63Pesquisa Florestal Brasileira; n. 56 (2008): jan./jun.; 63Pesquisa Florestal Brasileira; No. 56 (2008): jan./jun.; 631983-26051809-3647reponame:Pesquisa Florestal Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/63/65Resende, Marcos Deon Vilela deLopes, Paulo SávioSilva, Rogério Luíz daPires, Ismael Eleotérioinfo:eu-repo/semantics/openAccess2017-04-28T14:07:52Zoai:pfb.cnpf.embrapa.br/pfb:article/63Revistahttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/PUBhttps://pfb.cnpf.embrapa.br/pfb/index.php/pfb/oaipfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br1983-26051809-3647opendoar:2017-04-28T14:07:52Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency Seleção genômica ampla (GWS) e maximização da eficiência do melhoramento genético |
title |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency |
spellingShingle |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency Resende, Marcos Deon Vilela de Genomic selection linkage disequilibrium analysis fine mapping genetic markers. Seleção genômica análise de desequilíbrio de ligação mapeamento fino marcadores moleculares |
title_short |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency |
title_full |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency |
title_fullStr |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency |
title_full_unstemmed |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency |
title_sort |
Genome wide selection (GWS) and maximization of the genetic improvement efficiency |
author |
Resende, Marcos Deon Vilela de |
author_facet |
Resende, Marcos Deon Vilela de Lopes, Paulo Sávio Silva, Rogério Luíz da Pires, Ismael Eleotério |
author_role |
author |
author2 |
Lopes, Paulo Sávio Silva, Rogério Luíz da Pires, Ismael Eleotério |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Resende, Marcos Deon Vilela de Lopes, Paulo Sávio Silva, Rogério Luíz da Pires, Ismael Eleotério |
dc.subject.por.fl_str_mv |
Genomic selection linkage disequilibrium analysis fine mapping genetic markers. Seleção genômica análise de desequilíbrio de ligação mapeamento fino marcadores moleculares |
topic |
Genomic selection linkage disequilibrium analysis fine mapping genetic markers. Seleção genômica análise de desequilíbrio de ligação mapeamento fino marcadores moleculares |
description |
Genetic selection has been practiced by the best linear unbiased prediction (BLUP) method using phenotypic records. A first proposal for enhancement of the efficiency of this procedure was the marker assisted selection (MAS). Later, another method called genome wide selection - GWS was reported, which presents high accuracy for the selection based exclusively on markers, after predicting their genetic effects from phenotypic data in a sample of the population of selection. GWS is excellent for low heritable traits, while MAS is not. This paper presents the GWS methodology and simulates a case of its application, aiming at emphasizing its advantages over MAS. The relation between traditional BLUP and genomic BLUP is also detailed as well as the sample size required for precise estimation of the genetic values of the markers. Results revealed that the GWS can be worthy for genetic improvement. Practical experience is much needed to infer about its effectiveness. |
publishDate |
2010 |
dc.date.none.fl_str_mv |
2010-03-22 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/63 |
url |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/63 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://pfb.cnpf.embrapa.br/pfb/index.php/pfb/article/view/63/65 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Embrapa Florestas |
publisher.none.fl_str_mv |
Embrapa Florestas |
dc.source.none.fl_str_mv |
Pesquisa Florestal Brasileira; n. 56 (2008): jan./jun.; 63 Pesquisa Florestal Brasileira; No. 56 (2008): jan./jun.; 63 1983-2605 1809-3647 reponame:Pesquisa Florestal Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Florestal Brasileira (Online) |
collection |
Pesquisa Florestal Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Florestal Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pfb@embrapa.br || revista.pfb@gmail.com || patricia.mattos@embrapa.br |
_version_ |
1783370931898417152 |