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| Registros recuperados : 9 | |
| 4. |  | MUNOZ, P.; RESENDE JUNIOR, M.; RESENDE, M. D. V. de; GEZAN, S.; KIRST, M.; PETER, G. The re-discovery of the dominance variation by using the observed relationship matrix and itis implications in breeding. In: INTERNATIONAL CONFERENCE ON QUANTITATIVE GENETICS, 4., 2012, Edinburgh. Understanding Variation in Complex Traits. . [S.l.: s.n], 2012. Poster abstracts. P-367.| Biblioteca(s): Embrapa Florestas. |
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| 5. | | RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; ACOSTA, J. J.; PETER, G. F.; DAVIS, J. M.; GRATTAPAGLIA, D.; RESENDE, M. D. V. de; KIRST, M. Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. New Phytologist, v. 193, p. 617-624, 2012.| Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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| 6. | | RESENDE JUNIOR, M.; DELL VALLE, P. R. M.; RESENDE, M. D. V. de; GARRICK, D. J.; FERNANDO, R.; DAVIS, J. M.; PETER, G.; KIRST, M. Improvement of genomic selection using a ridge regression approach with selected markers. In: INTERNATIONAL CONFERENCE ON QUANTITATIVE GENETICS, 4., 2012, Edinburgh. Understanding Variation in Complex Traits. . [S.l.: s.n], 2012. Poster abstracts. P-199.| Biblioteca(s): Embrapa Florestas. |
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| 7. | | MUÑOZ, P. R.; RESENDE JUNIOR, M. F. R.; GEZAN, S. A.; RESENDE, M. D. V. de; CAMPOS, G. de los; KIRST, M.; HUBER, D.; PETER, G. F. Unraveling additive from nonadditive effects using genomic relationship matrices. Genetics, v. 198, p. 1759-1768, Dec. 2014.| Biblioteca(s): Embrapa Florestas. |
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| 8. | | RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; RESENDE, M. D. V. de; GARRICK, D. J.; FERNANDO, R. L.; DAVIS, J. M.; JOKELA, E. J.; MARTIN, T. A.; PETER, G. F.; KIRST, M. Accuracy of genomic selection methods in a standard data set of loblolly pine (Pinus taeda L.) Genetics, v. 190, p. 1503-1510, April 2012.| Biblioteca(s): Embrapa Florestas. |
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| 9. | | MUNOZ, P. R.; RESENDE JUNIOR, M. F. R.; HUBER, D. A.; QUESADA, T.; RESENDE, M. D. V. de; NEALE, D. B.; WEGRZYN, J. L.; KIRST, M.; PETER, G. F. Genomic relationship matrix for correcting pedigree errors in breeding populations: impact on genetic parameters and genomic selection accuracy. Crop Science, v. 54, p. 115-1123, May/June 2014.| Biblioteca(s): Embrapa Florestas. |
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| Registros recuperados : 9 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Florestas. Para informações adicionais entre em contato com cnpf.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
20/03/2012 |
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Data da última atualização: |
01/03/2023 |
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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: |
RESENDE JUNIOR, M. F. R.; MUÑOZ, P.; ACOSTA, J. J.; PETER, G. F.; DAVIS, J. M.; GRATTAPAGLIA, D.; RESENDE, M. D. V. de; KIRST, M. |
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Afiliação: |
MÁRCIO F. R. JÚNIOR RESENDE, University of Florida; University of Florida; University of Florida; University of Florida; UFV; DARIO GRATTAPAGLIA, CENARGEN; MARCOS DEON VILELA DE RESENDE, CNPF; University of Florida. |
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Título: |
Accelerating the domestication of trees using genomic selection: accuracy of prediction models across ages and environments. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
New Phytologist, v. 193, p. 617-624, 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
Genomic selection is increasingly considered vital to accelerate genetic improvement. However, it is unknown how accurate genomic selection prediction models remain when used across environments and ages. This knowledge is critical for breeders to apply this strategy in genetic improvement. Here, we evaluated the utility of genomic selection in a Pinus taeda population of c. 800 individuals clonally replicated and grown on four sites, and genotyped for 4825 singlenucleotide polymorphism (SNP) markers. Prediction models were estimated for diameter and height at multiple ages using genomic random regression best linear unbiased predictor (BLUP). Accuracies of prediction models ranged from 0.65 to 0.75 for diameter, and 0.63 to 0.74 for height. The selection efficiency per unit time was estimated as 53?112% higher using genomic selection compared with phenotypic selection, assuming a reduction of 50% in the breeding cycle. Accuracies remained high across environments as long as they were used within the same breeding zone. However, models generated at early ages did not perform well to predict phenotypes at age 6 yr. These results demonstrate the feasibility and remarkable gain that can be achieved by incorporating genomic selection in breeding programs, as long as models are used at the relevant selection age and within the breeding zone in which they were estimated. |
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Palavras-Chave: |
Seleção genômica. |
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Thesagro: |
Pinus Taeda. |
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Categoria do assunto: |
-- |
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Marc: |
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100 1 $aRESENDE JUNIOR, M. F. R.
245 $aAccelerating the domestication of trees using genomic selection$baccuracy of prediction models across ages and environments.$h[electronic resource]
260 $c2012
520 $aGenomic selection is increasingly considered vital to accelerate genetic improvement. However, it is unknown how accurate genomic selection prediction models remain when used across environments and ages. This knowledge is critical for breeders to apply this strategy in genetic improvement. Here, we evaluated the utility of genomic selection in a Pinus taeda population of c. 800 individuals clonally replicated and grown on four sites, and genotyped for 4825 singlenucleotide polymorphism (SNP) markers. Prediction models were estimated for diameter and height at multiple ages using genomic random regression best linear unbiased predictor (BLUP). Accuracies of prediction models ranged from 0.65 to 0.75 for diameter, and 0.63 to 0.74 for height. The selection efficiency per unit time was estimated as 53?112% higher using genomic selection compared with phenotypic selection, assuming a reduction of 50% in the breeding cycle. Accuracies remained high across environments as long as they were used within the same breeding zone. However, models generated at early ages did not perform well to predict phenotypes at age 6 yr. These results demonstrate the feasibility and remarkable gain that can be achieved by incorporating genomic selection in breeding programs, as long as models are used at the relevant selection age and within the breeding zone in which they were estimated.
650 $aPinus Taeda
653 $aSeleção genômica
700 1 $aMUÑOZ, P.
700 1 $aACOSTA, J. J.
700 1 $aPETER, G. F.
700 1 $aDAVIS, J. M.
700 1 $aGRATTAPAGLIA, D.
700 1 $aRESENDE, M. D. V. de
700 1 $aKIRST, M.
773 $tNew Phytologist$gv. 193, p. 617-624, 2012.
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