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| Registros recuperados : 39 | |
| 3. |  | SOARES, D. C. P.; ALMEIDA FILHO, J. E.; TARDIN, F. D.; SOUZA, S. A. Resistência de genótipos de sorgo à Helmintosporiose em Vilhena-RO. In: CONGRESSO NACIONAL DE MILHO E SORGO, 28.; SIMPÓSIO BRASILEIRO SOBRE A LAGARTA DO CARTUCHO, 4., 2010, Goiânia. Potencialidades, desafios e sustentabilidade: resumos expandidos... Sete Lagoas: ABMS, 2010. 1 CD-ROM.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 4. | | SOARES, D. C. P.; ALMEIDA FILHO, J. E.; TARDIN, F. D.; SOUZA, S. A. Resistência de híbridos de sorgo à antracnose em Itumbiara-GO e Vilhena-RO. In: CONGRESSO NACIONAL DE MILHO E SORGO, 28.; SIMPÓSIO BRASILEIRO SOBRE A LAGARTA DO CARTUCHO, 4., 2010, Goiânia. Potencialidades, desafios e sustentabilidade: resumos expandidos... Sete Lagoas: ABMS, 2010. 1 CD-ROM.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 5. | | ALMEIDA FILHO, J. E. de; TARDIN, F. D.; SOUZA, S. A. de; GODINHO, V. de P. C.; CARDOSO, M. J. Desempenho agronômico e estabilidade fenotípica de híbridos de sorgo granífero. Revista Brasileira de Milho e Sorgo, Sete Lagoas, v. 9, n. 1, p. 54-64, 2010.| Biblioteca(s): Embrapa Meio-Norte; Embrapa Milho e Sorgo. |
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| 6. | | ALMEIDA FILHO, J. E. de; TARDIN, F. D.; SOUZA, S. A. de; GODINHO, V. de P. C.; CARDOSO, M. J. Desempenho agronômico e estabilidade fenotípica de híbridos de sorgo granífero. Revista Brasileira de Milho e Sorgo, Sete Lagoas, v. 9, n. 1, p. 54-64, 2010.| Biblioteca(s): Embrapa Rondônia. |
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| 8. | | RIOS, E.; RESENDE, M.; KIRST, M.; RESENDE, M. D. V. de; ALMEIDA FILHO, J. E. de; MUNOZ, P. Predictive ability of Genomic Estimated Family Values (GEFV). In: PLANT & ANIMAL GENOME CONFERENCE, 24., 2016, San Diego. [Abstracts...]. San Diego: [s.n.], 2016. Pôster P1186.| Biblioteca(s): Embrapa Florestas. |
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| 10. | | ALMEIDA FILHO, J. E. de; SOARES, D. C. de P.; SILVA, E. A.; CANDIDO, L. S.; TARDIN, F. D.; SOUZA, S. A. de. Avaliação agronômica de 25 híbridos simples de sorgo granífero (Sorghum bicolor) em distintas condições edafoclimáticas In: CONGRESSO NACIONAL DE MILHO E SORGO, 28.; SIMPÓSIO BRASILEIRO SOBRE A LAGARTA DO CARTUCHO, 4., 2010, Goiânia. Potencialidades, desafios e sustentabilidade: resumos expandidos... Sete Lagoas: ABMS, 2010. 1 CD-ROM.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 11. | | ALMEIDA FILHO, J. E. de; TARDIN, F. D.; LOPES, V. da S.; BARBÉ, T. C.; GODINHO, V. de P. C.; CARDOSO, M. J.; DAHER, R. F. Correlação entre parâmetros de estabilidade e adaptabilidade em híbridos de sorgo granífero. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 6., 2011, Búzios. Panorama atual e perspectivas do melhoramento de plantas no Brasil. [Búzios]: SBMP, 2011. 1 CD-ROM.| Biblioteca(s): Embrapa Rondônia. |
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| 12. | | ALMEIDA FILHO, J. E. de; TARDIN, F. D.; LOPES, V. da S.; BARBÉ, T. C.; GODINHO, V. de P. C.; CARDOSO, M. J.; DAHER, R. F. Correlação entre parâmetros de estabilidade e adaptabilidade em híbridos de sorgo granífero. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 6., 2011, Búzios. Panorama atual e perspectivas do melhoramento de plantas no Brasil. [Búzios]: SBMP, 2011. 1 CD-ROM.| Biblioteca(s): Embrapa Meio-Norte; Embrapa Milho e Sorgo. |
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| 13. | | 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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| 14. | | 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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| 15. | | ALMEIDA FILHO, J. E. de; TARDIN, F. D.; RESENDE, M. D. V. de; SILVA, F. F. e; GRANATO, I. S. C.; MENEZES, C. B. de. Genetic evaluation of grain sorghum hybrids in Brazilian environments using the REML/BLUP procedure. Scientia Agricola, Piracicaba, v. 71, n. 2, p. 146-150, Mar./Apr. 2014.| Biblioteca(s): Embrapa Florestas; Embrapa Milho e Sorgo. |
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| 16. | | ALMEIDA FILHO, J. E. de A.; RODRIGUES, J. F. G.; SILVA, F. F. e; RESENDE, M. D. V. de; RESENDE JÚNIOR, M.; MUÑOZ, P.; KIRST, M. Genomic prediction of assitive and non-additive effects using genetic markers and pedigrees in pines breeding. 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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| 17. | | TEODORO, P. E.; ALMEIDA FILHO, J. E.; DAHER, R. F.; MENEZES, C. B. de; CARDOSO, M. J.; GODINHO, V. de P. C.; TORRES, F. E.; TARDIN, F. D. Identification of sorghum hybrids with high phenotypic stability using GGE biplot methodology. Genetics and Molecular Research, Ribeirão Preto, v. 15, n. 2, p. 1-8, 2016.| Biblioteca(s): Embrapa Meio-Norte; Embrapa Milho e Sorgo; Embrapa Rondônia. |
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| 18. | | ALMEIDA FILHO, J. E.; TARDIN, F. D.; DAHER, R. F.; BARBÉ, T. C.; PAULA, C. M.; CARDOSO, M. J.; GODINHO, V. P. C. Stability and adaptability of grain sorghum hybrids in the off-season. Genetics and Molecular Research, Ribeirão Preto, Ribeirão Preto, v.13, n. 3, p. 7626-7635, mar. 2014.| Biblioteca(s): Embrapa Meio-Norte; Embrapa Milho e Sorgo; Embrapa Rondônia. |
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| 19. | | SILVA, V. Q. R. da; DAHER, R. F.; SOUZA, M. C. de; LEDO, F. J. da S.; GRAVINA, G. de A.; GOTTARDO, R. D.; BARBÉ, T. da C.; ALMEIDA FILHO, J. E. de. Análise dialélica parcial em capim-elefante sob dois cortes de avaliação em Campos dos Goytacazes, RJ. In: CONGRESSO BRASILEIRO DE MELHORAMENTO DE PLANTAS, 6., 2011, Búzios. Panorama atual e perspectivas do melhoramento de plantas no Brasil. [Búzios]: SBMP, 2011. 1 CD-ROM.| Biblioteca(s): Embrapa Agrossilvipastoril; Embrapa Gado de Leite. |
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| 20. | | ALMEIDA FILHO, J. E. de; SOARES, D. C. de P.; SILVA, E. A.; CANDIDO, L. S.; TARDIN, F. D.; SOUZA, S. A. de; GODINHO, V. de P. C.; CARDOSO, M. J. Adaptabilidade e estabilidade produtiva em híbridos simples de sorgo granífero (Sorghum bicolor). In: CONGRESSO NACIONAL DE MILHO E SORGO, 28.; SIMPÓSIO BRASILEIRO SOBRE A LAGARTA DO CARTUCHO, 4., 2010, Goiânia. Resumos expandidos... Goiânia: ABMS, 2010. p.2588-2594. CD-ROM.| Biblioteca(s): Embrapa Rondônia. |
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| Registros recuperados : 39 | |
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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. |
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Data corrente: |
08/11/2019 |
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Data da última atualização: |
08/11/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
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. |
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Afiliação: |
Janeo Eustáquio de Almeida Filho, Universidade Esatdual do Norte Fluminense e "Darcy Ribeiro"; João Filipi Rodrigues Guimarães, Futuragene Ltda; Fabyano Fonsceca e Silva, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; Patricio Muñoz, University of Florida; Matias Kirst, University of Florida; Marcio Fernando Ribeiro de Resende Júnior, University of Florida. |
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Título: |
Genomic prediction of additive and non-additive effects using genetic markers and pedigrees. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
G3: Genes, Genomes, Genetics, v. 9, p. 2739-2748, Aug. 2019. |
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Idioma: |
Inglês |
|
Conteúdo: |
The genetic merit of individuals can be estimated using models with dense markers and pedigree information. Early genomic models accounted only for additive effects. However, the prediction of non-additive effects is important for different forest breeding systems where the whole genotypic value can be captured through clonal propagation. In this study, we evaluated the integration of marker data with pedigree information, in models that included or ignored non-additive effects. We tested the models Reproducing Kernel Hilbert Spaces (RKHS) and BayesA, with additive and additive-dominance frameworks. Model performance was assessed for the traits tree height, diameter at breast height and rust resistance, measured in 923 pine individuals from a structured population of 71 full-sib families. We have also simulated a population with similar genetic properties and evaluated the performance of models for six simulated traits with distinct genetic architectures. Different cross validation strategies were evaluated, and highest accuracies were achieved using within family cross validation. The inclusion of pedigree information in genomic prediction models did not yield higher accuracies. The different RKHS models resulted in similar predictions accuracies, and RKHS and BayesA generated substantially better predictions than pedigree-only models. The additive-BayesA resulted in higher accuracies than RKHS for rust incidence and in simulated additive-oligogenic traits. For DBH, HT and additive dominance polygenic traits, the RKHS- based models showed slightly higher accuracies than BayesA. Our results indicate that BayesA performs the best for traits with few genes with major effects, while RKHS based models can best predict genotypic effects for clonal selection of complex traits MenosThe genetic merit of individuals can be estimated using models with dense markers and pedigree information. Early genomic models accounted only for additive effects. However, the prediction of non-additive effects is important for different forest breeding systems where the whole genotypic value can be captured through clonal propagation. In this study, we evaluated the integration of marker data with pedigree information, in models that included or ignored non-additive effects. We tested the models Reproducing Kernel Hilbert Spaces (RKHS) and BayesA, with additive and additive-dominance frameworks. Model performance was assessed for the traits tree height, diameter at breast height and rust resistance, measured in 923 pine individuals from a structured population of 71 full-sib families. We have also simulated a population with similar genetic properties and evaluated the performance of models for six simulated traits with distinct genetic architectures. Different cross validation strategies were evaluated, and highest accuracies were achieved using within family cross validation. The inclusion of pedigree information in genomic prediction models did not yield higher accuracies. The different RKHS models resulted in similar predictions accuracies, and RKHS and BayesA generated substantially better predictions than pedigree-only models. The additive-BayesA resulted in higher accuracies than RKHS for rust incidence and in simulated additive-oligogenic traits. For DBH, HT and ... Mostrar Tudo |
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Palavras-Chave: |
BayesA; Genomic Prediction; Genotypic Value; GenPred; Oligogenic; Polygenic; Predição genòmica; RKHS; Shared Data Resources. |
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Thesagro: |
Genótipo. |
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Categoria do assunto: |
G Melhoramento Genético |
|
Marc: |
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001 2114084
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100 1 $aALMEIDA FILHO, J. E. de A.
245 $aGenomic prediction of additive and non-additive effects using genetic markers and pedigrees.$h[electronic resource]
260 $c2019
520 $aThe genetic merit of individuals can be estimated using models with dense markers and pedigree information. Early genomic models accounted only for additive effects. However, the prediction of non-additive effects is important for different forest breeding systems where the whole genotypic value can be captured through clonal propagation. In this study, we evaluated the integration of marker data with pedigree information, in models that included or ignored non-additive effects. We tested the models Reproducing Kernel Hilbert Spaces (RKHS) and BayesA, with additive and additive-dominance frameworks. Model performance was assessed for the traits tree height, diameter at breast height and rust resistance, measured in 923 pine individuals from a structured population of 71 full-sib families. We have also simulated a population with similar genetic properties and evaluated the performance of models for six simulated traits with distinct genetic architectures. Different cross validation strategies were evaluated, and highest accuracies were achieved using within family cross validation. The inclusion of pedigree information in genomic prediction models did not yield higher accuracies. The different RKHS models resulted in similar predictions accuracies, and RKHS and BayesA generated substantially better predictions than pedigree-only models. The additive-BayesA resulted in higher accuracies than RKHS for rust incidence and in simulated additive-oligogenic traits. For DBH, HT and additive dominance polygenic traits, the RKHS- based models showed slightly higher accuracies than BayesA. Our results indicate that BayesA performs the best for traits with few genes with major effects, while RKHS based models can best predict genotypic effects for clonal selection of complex traits
650 $aGenótipo
653 $aBayesA
653 $aGenomic Prediction
653 $aGenotypic Value
653 $aGenPred
653 $aOligogenic
653 $aPolygenic
653 $aPredição genòmica
653 $aRKHS
653 $aShared Data Resources
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 JÚNIOR, M. F. R. de
773 $tG3: Genes, Genomes, Genetics$gv. 9, p. 2739-2748, Aug. 2019.
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