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Registros recuperados : 29 | |
8. | | ROSADO, A. M.; ROSADO, T. B.; RESENDE JÚNIOR, M. F. R.; BHERING, L. L.; CRUZ, C. D. Ganhos genéticos preditos por diferentes métodos de seleção em progênies de Eucalyptus urophylla Pesquisa Agropecuária Brasileira, Brasília, DF, v. 44, n. 12, p. 1653-1659, dez. 2009 Título em inglês: Predicted genetic gains by various selection methods in Eucalyptus urophylla progenies. Biblioteca(s): Embrapa Agroenergia; Embrapa Unidades Centrais. |
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9. | | RESENDE JUNIOR, M. F. R.; ALVES, A. A.; BARRERA SÁNCHES, C. F.; RESENDE, M. D. V. de; CRUZ, C. D. Seleção genômica ampla. In: CRUZ, C. D.; SALGADO, C. C.; BHERING, L. L. (Ed.). Genômica aplicada. Viçosa, MG: Suprema, 2013. p. 375-424. Biblioteca(s): Embrapa Agroenergia; Embrapa Florestas. |
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10. | | 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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11. | | RESENDE, M. D. V. de; RESENDE JUNIOR, M. F. R.; AGUIAR, A. M.; ABAD, J. I. M.; MISSIAGGIA, A. A.; SANSALONI, C. P.; PETROLI, C. D.; GRATTAPAGLIA, D. Computação da Seleção Genômica Ampla (GWS). Colombo: Embrapa Florestas, 2010. CD-ROM. (Embrapa Florestas. Documentos, 210). Biblioteca(s): Embrapa Florestas. |
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12. | | BHERING, L. L.; CRUZ, C. D.; VASCONCELOS, E. S. de; RESENDE JUNIOR, M. F. R. de; BARROS, W. S.; ROSADO, T. B. Efficiency of the multilocus analysis for the construction of genetic maps. Crop Breeding and Applied Biotechnology, Londrina, v. 9, n. 4, p. 308-312, Dec. 2009. Biblioteca(s): Embrapa Agricultura Digital; Embrapa Agroenergia. |
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13. | | MÜLLER, B. S. F.; NEVES, L. G.; RESENDE JÚNIOR, M. F. R.; MUÑOZ, P. R.; KIRST, M.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; GRATTAPAGLIA, D. Genomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM, 2015. Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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14. | | MÜLLER, B. S. F.; NEVES, L. G.; RESENDE JÚNIOR, M. F. R.; MUÑOZ, P. R.; KIRST, M.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; GRATTAPAGLIA, D. Genomic selection for growth traits in Eucalyptus benthamii and E. pellita populations using a genome-wide Eucalyptus 60K SNPs chip. In: IUFRO TREE BIOTECHNOLOGY CONFERENCE, 2015, Florence. Forests: the importance to the planet and society. [S.l.]: IBBR: ICCOM, 2015. Pen-drive. Biblioteca(s): Embrapa Florestas. |
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15. | | 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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17. | | AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F.; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; OLIVEIRA, E. J. de. New accuracy estimators for genomic selection with application in a cassava (Manihot esculenta) breeding program. Genetics and Molecular Research, v. 15, n. 4, gmr.15048838, Oct. 2016. Biblioteca(s): Embrapa Florestas; Embrapa Mandioca e Fruticultura. |
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18. | | SOUSA, T. V.; CAIXETA, E. T.; ALKIMIM, E. R.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; SAKIYAMA, N. S.; RESENDE JÚNIOR, M. F. R. de; ZAMBOLIM, L. Population structure and genetic diversity of coffee progenies derived from Catuaí and Híbrido de Timor revealed by genome-wide SNP marker. Tree Genetics & Genomes, v. 13, n. 6, Dec. 2017. Biblioteca(s): Embrapa Café. |
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19. | | AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; VIANA, J. M. S.; VALENTE, M. S. F.; RESENDE JUNIOR, M. F. R.; MUÑOZ, P. Ridge, Lasso and Bayesian additive dominance genomic models. BMC Genetics, v. 16, art. 105, Aug. 2015. 13 p. Biblioteca(s): Embrapa Florestas. |
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20. | | 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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Registros recuperados : 29 | |
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Registro Completo
Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
18/01/2017 |
Data da última atualização: |
18/01/2017 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
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. |
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. |
Título: |
The contribution of dominance to phenotype prediction in a pine breeding and simulated population. |
Ano de publicação: |
2016 |
Fonte/Imprenta: |
Heredity, v. 117, p. 33-41, July 2016. |
DOI: |
10.1038/hdy.2016.23 |
Idioma: |
Inglês |
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. |
Thesagro: |
Árvore conífera. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/153479/1/2016-M.Deon-H-TheContribution.pdf
|
Marc: |
LEADER 02158naa a2200217 a 4500 001 2061094 005 2017-01-18 008 2016 bl uuuu u00u1 u #d 024 7 $a10.1038/hdy.2016.23$2DOI 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 700 1 $aMUÑOZ, P. 700 1 $aKIRST, M. 700 1 $aRESENDE JUNIOR, M. F. R. 773 $tHeredity$gv. 117, p. 33-41, July 2016.
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