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| Registros recuperados : 7 | |
| 1. |  | SOUZA, D. A. de; MOREIRA, G. B. R.; GUIMARÃES, J. F. R.; LIBRELON, S. S.; FERNANDES, T. P.; NIETSCHE, S.; COSTA, M. R. Análise da diversidade genética intrapopulacional de pinhão-manso (Jatropha curcas L.) com marcadores ISSR. In: CONGRESSO BRASILEIRO DE PLANTAS OLEAGINOSAS, ÓLEOS, GORDURAS E BIODIESEL, 6., 2009. Montes Claros. Biodiesel: inovação tecnológica – anais. Lavras: UFLA, 2009.| Biblioteca(s): Embrapa Algodão. |
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| 2. | | ALMEIDA FILHO, J. E. de; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JUNIOR, M. F. R. The contribution of dominance to phenotype prediction in a pine breeding and simulated population. Heredity, v. 117, p. 33-41, July 2016.| Biblioteca(s): Embrapa Florestas. |
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| 3. | | GUIMARÃES, J. F. R.; ALMEIDA FILHO, J. E.; RESENDE JÚNIOR, M. F.; RESENDE, M. D. V. de; SILVA, F. F. e; MUÑOZ, P.; KIRST, M. Predictive ability behavior across sites after discard of SNPS with unstable effects. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 8., 2015, Goiânia. O melhoramento de plantas, o futuro da agricultura e a soberania nacional: anais. Goiânia: SBMP: UFG, 2015. Resumo.| Biblioteca(s): Embrapa Florestas. |
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| 4. | | PIMENTEL, A. J. B.; GUIMARÃES, J. F. R.; SOUZA, M. A. de; RESENDE, M. D. V. de; MOURA, L. M.; ROCHA, J. R. do A. S. de C.; RIBEIRO, G. Estimação de parâmetros genéticos e predição de valor genético aditivo de trigo utilizando modelos mistos. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 49, n. 11, p. 882-890, nov. 2014. Título em inglês: Estimation of genetic parameters and prediction of additive genetic value for wheat by mixed models.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 5. | | PIMENTEL, A. J. B.; GUIMARÃES, J. F. R.; SOUZA, M. A. de; RESENDE, M. D. V. de; MOURA, L. M.; ROCHA, J. R. do A. S. de C.; RIBEIRO, G. Estimação de parâmetros genéticos e predição de valor genético aditivo de trigo utilizando modelos mistos. Pesquisa Agropecuária Brasileira, Brasília, v. 49, n. 11, p. 882-890, nov. 2014.| Biblioteca(s): Embrapa Florestas; Embrapa Trigo. |
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| 6. | | ALMEIDA FILHO, J. E. de A.; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JÚNIOR, M. F. R. de. Genomic prediction of additive and non-additive effects using genetic markers and pedigrees. G3: Genes, Genomes, Genetics, v. 9, p. 2739-2748, Aug. 2019.| Biblioteca(s): Embrapa Florestas. |
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| 7. | | ALMEIDA FILHO, J. E.; TARDIN, F. D.; GUIMARAES, J. F. R.; RESENDE, M. D. V.; SILVA, F. F.; SIMEONE, M. L. F.; MENEZES, C. B. de; QUEIROZ, V. A. V. Multi-trait BLUP model indicates sorghum hybrids with genetic potential for agronomic and nutritional traits. Genetics and Molecular Research, Ribeirão Preto, v. 15, n. 1, p. 1-9, 2016.| Biblioteca(s): Embrapa Florestas; Embrapa Milho e Sorgo. |
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| Registros recuperados : 7 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
18/01/2017 |
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Data da última atualização: |
18/01/2017 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
ALMEIDA FILHO, J. E. de; GUIMARÃES, J. F. R.; SILVA, F. F. e; RESENDE, M. D. V. de; MUÑOZ, P.; KIRST, M.; RESENDE JUNIOR, M. F. R. |
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Afiliação: |
J. E. de Almeida Filho, University of Florida; J. F. R. Guimarães, University of Florida; F. F. e SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; P. Muñoz, University of Florida; M. Kirst, University of Florida; M. F. R. Resende JUnior, RAPiD Genomics LLC. |
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Título: |
The contribution of dominance to phenotype prediction in a pine breeding and simulated population. |
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Ano de publicação: |
2016 |
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Fonte/Imprenta: |
Heredity, v. 117, p. 33-41, July 2016. |
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DOI: |
10.1038/hdy.2016.23 |
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Idioma: |
Inglês |
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Conteúdo: |
Pedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive?dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait. |
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Thesagro: |
Árvore conífera. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/153479/1/2016-M.Deon-H-TheContribution.pdf
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Marc: |
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100 1 $aALMEIDA FILHO, J. E. de
245 $aThe contribution of dominance to phenotype prediction in a pine breeding and simulated population.$h[electronic resource]
260 $c2016
520 $aPedigrees and dense marker panels have been used to predict the genetic merit of individuals in plant and animal breeding, accounting primarily for the contribution of additive effects. However, nonadditive effects may also affect trait variation in many breeding systems, particularly when specific combining ability is explored. Here we used models with different priors, and including additive-only and additive plus dominance effects, to predict polygenic (height) and oligogenic (fusiform rust resistance) traits in a structured breeding population of loblolly pine (Pinus taeda L.). Models were largely similar in predictive ability, and the inclusion of dominance only improved modestly the predictions for tree height. Next, we simulated a genetically similar population to assess the ability of predicting polygenic and oligogenic traits controlled by different levels of dominance. The simulation showed an overall decrease in the accuracy of total genomic predictions as dominance increases, regardless of the method used for prediction. Thus, dominance effects may not be accounted for as effectively in prediction models compared with traits controlled by additive alleles only. When the ratio of dominance to total phenotypic variance reached 0.2, the additive?dominance prediction models were significantly better than the additive-only models. However, in the prediction of the subsequent progeny population, this accuracy increase was only observed for the oligogenic trait.
650 $aÁrvore conífera
700 1 $aGUIMARÃES, J. F. R.
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
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700 1 $aKIRST, M.
700 1 $aRESENDE JUNIOR, M. F. R.
773 $tHeredity$gv. 117, p. 33-41, July 2016.
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