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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 |
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
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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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Registro original: |
Embrapa Florestas (CNPF) |
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Registros recuperados : 22 | |
7. | | 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.Tipo: Capítulo em Livro Técnico-Científico |
Biblioteca(s): Embrapa Agroenergia; Embrapa Florestas. |
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8. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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9. | | 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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10. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas. |
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11. | | 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.Tipo: Artigo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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13. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas; Embrapa Mandioca e Fruticultura. |
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14. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas. |
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15. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas. |
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16. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas. |
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17. | | GRATTAPAGLIA, D.; RESENDE, M. D. V. de; RESENDE JUNIOR, M. F. R.; SANSALONI, C. P.; PETROLI, C. D.; MISSIAGGIA, A. A.; TAKAHASHI, E. K.; ZAMPROGNO, K. C.; KILIAN, A. Breeding by genomic selection: capturing the missing heritability of complex traits in forest trees. In: NEW PHYTOLOGIST SYMPOSIUM, 26., 2011, Nancy. Bioenergy trees. [S.l.]: INRA, 2011. p. 9.Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Florestas. |
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18. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
Biblioteca(s): Embrapa Florestas. |
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19. | | MÜLLER, B. S. F.; NEVES, L. G.; ALMEIDA FILHO, J. E. de; RESENDE JUNIOR, M. F. R.; MUÑOZ, P. R.; SANTOS, P. E. T. dos; PALUDZYSZYN FILHO, E.; KIRST, M.; GRATTAPAGLIA, D. Genomic prediction in contrast to a genome-wide association study in explaining heritable variation of complex growth traits in breeding populations of Eucalyptus. BMC Genomics, v. 18, article 524, 2017. 17 p.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas; Embrapa Recursos Genéticos e Biotecnologia. |
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20. | | 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.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Florestas. |
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Registros recuperados : 22 | |
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Nenhum registro encontrado para a expressão de busca informada. |
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