Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection.
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
Texto Completo: | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139183 https://doi.org/10.1590/1678-992X-2021-0074 |
Resumo: | The Fisher?s infinitesimal model is traditionally used in quantitative genetics and genomic selection, and it attributes most genetic variance to additive variance. Recently, the dominance maximization model was proposed and it prioritizes the dominance variance based on alternative parameterizations. In this model, the additive effects at the locus level are introduced into the model after the dominance variance is maximized. In this study, the new parameterizations of additive and dominance effects on quantitative genetics and genomic selection were evaluated and compared with the parameterizations traditionally applied using the genomic best linear unbiased prediction method. As the parametric relative magnitude of the additive and dominance effects vary with allelic frequencies of populations, we considered different minor allele frequencies to compare the relative magnitudes. We also proposed and evaluated two indices that combine the additive and dominance variances estimated by both models. The dominance maximization model, along with the two indices, offers alternatives to improve the estimates of additive and dominance variances and their respective proportions and can be successfully used in genetic evaluation. |
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Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection.Melhoramento Genético VegetalSeleção GenéticaMolecular modelsPlant selection guidesPlant breedingThe Fisher?s infinitesimal model is traditionally used in quantitative genetics and genomic selection, and it attributes most genetic variance to additive variance. Recently, the dominance maximization model was proposed and it prioritizes the dominance variance based on alternative parameterizations. In this model, the additive effects at the locus level are introduced into the model after the dominance variance is maximized. In this study, the new parameterizations of additive and dominance effects on quantitative genetics and genomic selection were evaluated and compared with the parameterizations traditionally applied using the genomic best linear unbiased prediction method. As the parametric relative magnitude of the additive and dominance effects vary with allelic frequencies of populations, we considered different minor allele frequencies to compare the relative magnitudes. We also proposed and evaluated two indices that combine the additive and dominance variances estimated by both models. The dominance maximization model, along with the two indices, offers alternatives to improve the estimates of additive and dominance variances and their respective proportions and can be successfully used in genetic evaluation.TAIANA LOPES RANGEL MIRANDA, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; CAMILA FERREIRA AZEVEDO, UFV; ANDREI CAÍQUE PIRES NUNES, UNIVERSIDADE FEDERAL DO SUL DA BAHIA; ELIZABETE KEIKO TAKAHASHI, CELULOSE NIPO-BRASILEIRA S.A; GUILHERME FERREIRA SIMIQUELI, UFV; FABYANO FONSECA E SILVA, UFV; RODRIGO SILVA ALVES, UFLA.MIRANDA, T. L. R.RESENDE, M. D. V. deAZEVEDO, C. F.NUNES, A. C. P.TAKAHASHI, E. K.SIMIQUELI, G. F.SILVA, F. F. eALVES, R. S.2022-01-19T16:00:25Z2022-01-19T16:00:25Z2022-01-192022info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleScientia Agricola, v. 79, n. 6, p. 1-7, 2022.http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139183https://doi.org/10.1590/1678-992X-2021-0074enginfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPA2022-01-19T16:00:35Zoai:www.alice.cnptia.embrapa.br:doc/1139183Repositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestopendoar:21542022-01-19T16:00:35falseRepositório InstitucionalPUBhttps://www.alice.cnptia.embrapa.br/oai/requestcg-riaa@embrapa.bropendoar:21542022-01-19T16:00:35Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
title |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
spellingShingle |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. MIRANDA, T. L. R. Melhoramento Genético Vegetal Seleção Genética Molecular models Plant selection guides Plant breeding |
title_short |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
title_full |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
title_fullStr |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
title_full_unstemmed |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
title_sort |
Evaluation of a new additive-dominance genomic model and implications for quantitative genetics and genomic selection. |
author |
MIRANDA, T. L. R. |
author_facet |
MIRANDA, T. L. R. RESENDE, M. D. V. de AZEVEDO, C. F. NUNES, A. C. P. TAKAHASHI, E. K. SIMIQUELI, G. F. SILVA, F. F. e ALVES, R. S. |
author_role |
author |
author2 |
RESENDE, M. D. V. de AZEVEDO, C. F. NUNES, A. C. P. TAKAHASHI, E. K. SIMIQUELI, G. F. SILVA, F. F. e ALVES, R. S. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
TAIANA LOPES RANGEL MIRANDA, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; CAMILA FERREIRA AZEVEDO, UFV; ANDREI CAÍQUE PIRES NUNES, UNIVERSIDADE FEDERAL DO SUL DA BAHIA; ELIZABETE KEIKO TAKAHASHI, CELULOSE NIPO-BRASILEIRA S.A; GUILHERME FERREIRA SIMIQUELI, UFV; FABYANO FONSECA E SILVA, UFV; RODRIGO SILVA ALVES, UFLA. |
dc.contributor.author.fl_str_mv |
MIRANDA, T. L. R. RESENDE, M. D. V. de AZEVEDO, C. F. NUNES, A. C. P. TAKAHASHI, E. K. SIMIQUELI, G. F. SILVA, F. F. e ALVES, R. S. |
dc.subject.por.fl_str_mv |
Melhoramento Genético Vegetal Seleção Genética Molecular models Plant selection guides Plant breeding |
topic |
Melhoramento Genético Vegetal Seleção Genética Molecular models Plant selection guides Plant breeding |
description |
The Fisher?s infinitesimal model is traditionally used in quantitative genetics and genomic selection, and it attributes most genetic variance to additive variance. Recently, the dominance maximization model was proposed and it prioritizes the dominance variance based on alternative parameterizations. In this model, the additive effects at the locus level are introduced into the model after the dominance variance is maximized. In this study, the new parameterizations of additive and dominance effects on quantitative genetics and genomic selection were evaluated and compared with the parameterizations traditionally applied using the genomic best linear unbiased prediction method. As the parametric relative magnitude of the additive and dominance effects vary with allelic frequencies of populations, we considered different minor allele frequencies to compare the relative magnitudes. We also proposed and evaluated two indices that combine the additive and dominance variances estimated by both models. The dominance maximization model, along with the two indices, offers alternatives to improve the estimates of additive and dominance variances and their respective proportions and can be successfully used in genetic evaluation. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-19T16:00:25Z 2022-01-19T16:00:25Z 2022-01-19 2022 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
Scientia Agricola, v. 79, n. 6, p. 1-7, 2022. http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139183 https://doi.org/10.1590/1678-992X-2021-0074 |
identifier_str_mv |
Scientia Agricola, v. 79, n. 6, p. 1-7, 2022. |
url |
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1139183 https://doi.org/10.1590/1678-992X-2021-0074 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
collection |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) |
repository.name.fl_str_mv |
Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA - Alice) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
cg-riaa@embrapa.br |
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1794503516805398528 |