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Registro Completo |
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
26/01/2018 |
Data da última atualização: |
26/01/2018 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
MORAIS JÚNIOR, O. P.; DUARTE, J. B.; BRESEGHELLO, F.; COELHO, A. S. G.; BORBA, T. C. O.; AGUIAR, J. T.; NEVES, P. C. F.; MORAIS, O. P. |
Afiliação: |
ODILON PEIXOTO MORAIS JUNIOR; JOAO BATISTA DUARTE, UFG; FLAVIO BRESEGHELLO, CNPAF; ALEXANDRE S. G. COELHO, UFG; TEREZA CRISTINA DE OLIVEIRA BORBA, CNPAF; JORDENE T. AGUIAR; PERICLES DE CARVALHO FERREIRA NEVES, CNPAF; ORLANDO PEIXOTO DE MORAIS, CNPAF. |
Título: |
Relevance of additive and non-additive genetic relatedness for genomic prediction in rice population under recurrent selection breeding |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Genetics and Molecular Research, v. 16, n. 4, gmr16039849, Dec. 2017. |
ISSN: |
1676-5680 |
DOI: |
10.4238/gmr16039849 |
Idioma: |
Inglês |
Conteúdo: |
In genomic recurrent selection programs of self-pollinated crops, additive genetic effects (breeding values) are effectively relevant for selection of superior progenies as new parents. However, considering additive and nonadditive genetic effects can improve the prediction of genome-enhanced breeding values (GEBV) of progenies, for quantitative traits. In this study, we assessed the magnitude of additive and nonadditive genetic variances for eight key traits in a rice population under recurrent selection, using marker-based relationship matrices. We then assessed the goodness-to-fit, bias, stability and accuracy of prediction for breeding values and total (additive plus nonadditive) genetic values, in five genomic best linear unbiased prediction (GBLUP) models, ignoring or not nonadditive genetic effects. The models were compared using 6174 single nucleotide polymorphisms (SNP) markers from 174 S1:3 progenies evaluated in field yield trial. We found dominance effects accounting for a substantial proportion of the total genetic variance for the key traits in rice, especially for days to flowering. In average of the traits, the component of variance additive, dominance, and epistatic contributed to about 34%, 14% and 9% for phenotypic variance. Additive genomic models, ignoring nonadditive genetic effects, showed better fit to the data and lower bias, in addition to greater stability and accuracy for predict GEBV of progenies. These results improve our understanding of the genetic architecture of the key traits in rice, evaluated in early-generation testing. Clearly, this study highlighted the advantages of additive models using genome-wide information, for genomic prediction applied to recurrent selection in a self-pollinated crop. MenosIn genomic recurrent selection programs of self-pollinated crops, additive genetic effects (breeding values) are effectively relevant for selection of superior progenies as new parents. However, considering additive and nonadditive genetic effects can improve the prediction of genome-enhanced breeding values (GEBV) of progenies, for quantitative traits. In this study, we assessed the magnitude of additive and nonadditive genetic variances for eight key traits in a rice population under recurrent selection, using marker-based relationship matrices. We then assessed the goodness-to-fit, bias, stability and accuracy of prediction for breeding values and total (additive plus nonadditive) genetic values, in five genomic best linear unbiased prediction (GBLUP) models, ignoring or not nonadditive genetic effects. The models were compared using 6174 single nucleotide polymorphisms (SNP) markers from 174 S1:3 progenies evaluated in field yield trial. We found dominance effects accounting for a substantial proportion of the total genetic variance for the key traits in rice, especially for days to flowering. In average of the traits, the component of variance additive, dominance, and epistatic contributed to about 34%, 14% and 9% for phenotypic variance. Additive genomic models, ignoring nonadditive genetic effects, showed better fit to the data and lower bias, in addition to greater stability and accuracy for predict GEBV of progenies. These results improve our understanding of the ge... Mostrar Tudo |
Palavras-Chave: |
GBLUP models; Genetic architecture; Predictive accuracy; Variance components. |
Thesagro: |
Arroz; Melhoramento genético vegetal; Oryza sativa; Seleção recorrente. |
Thesaurus Nal: |
Plant breeding; quantitative traits; Rice. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/171723/1/CNPAF-2017-gmr-opmj.pdf
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Marc: |
LEADER 02867naa a2200361 a 4500 001 2086472 005 2018-01-26 008 2017 bl uuuu u00u1 u #d 022 $a1676-5680 024 7 $a10.4238/gmr16039849$2DOI 100 1 $aMORAIS JÚNIOR, O. P. 245 $aRelevance of additive and non-additive genetic relatedness for genomic prediction in rice population under recurrent selection breeding$h[electronic resource] 260 $c2017 520 $aIn genomic recurrent selection programs of self-pollinated crops, additive genetic effects (breeding values) are effectively relevant for selection of superior progenies as new parents. However, considering additive and nonadditive genetic effects can improve the prediction of genome-enhanced breeding values (GEBV) of progenies, for quantitative traits. In this study, we assessed the magnitude of additive and nonadditive genetic variances for eight key traits in a rice population under recurrent selection, using marker-based relationship matrices. We then assessed the goodness-to-fit, bias, stability and accuracy of prediction for breeding values and total (additive plus nonadditive) genetic values, in five genomic best linear unbiased prediction (GBLUP) models, ignoring or not nonadditive genetic effects. The models were compared using 6174 single nucleotide polymorphisms (SNP) markers from 174 S1:3 progenies evaluated in field yield trial. We found dominance effects accounting for a substantial proportion of the total genetic variance for the key traits in rice, especially for days to flowering. In average of the traits, the component of variance additive, dominance, and epistatic contributed to about 34%, 14% and 9% for phenotypic variance. Additive genomic models, ignoring nonadditive genetic effects, showed better fit to the data and lower bias, in addition to greater stability and accuracy for predict GEBV of progenies. These results improve our understanding of the genetic architecture of the key traits in rice, evaluated in early-generation testing. Clearly, this study highlighted the advantages of additive models using genome-wide information, for genomic prediction applied to recurrent selection in a self-pollinated crop. 650 $aPlant breeding 650 $aquantitative traits 650 $aRice 650 $aArroz 650 $aMelhoramento genético vegetal 650 $aOryza sativa 650 $aSeleção recorrente 653 $aGBLUP models 653 $aGenetic architecture 653 $aPredictive accuracy 653 $aVariance components 700 1 $aDUARTE, J. B. 700 1 $aBRESEGHELLO, F. 700 1 $aCOELHO, A. S. G. 700 1 $aBORBA, T. C. O. 700 1 $aAGUIAR, J. T. 700 1 $aNEVES, P. C. F. 700 1 $aMORAIS, O. P. 773 $tGenetics and Molecular Research$gv. 16, n. 4, gmr16039849, Dec. 2017.
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Embrapa Arroz e Feijão (CNPAF) |
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5. | | NASCIMENTO, A. C. do; JUNQUEIRA, N. T. V.; PEIXOTO, J. R.; MANICA, I.; KOSOK, R. M.; JUNQUEIRA, K. P. Comportamento de frutos de 10 genotipos de maracujazeiro-zedo em relacao a antracnose (Colletotrichium gloeosporioides) e a verrugose (Cladosporium spp.) no Distrito Federal. In: CONGRESSO BRASILEIRO DE FRUTICULTURA, 16., 2000, Fortaleza, CE. Fruticultura: agronegocio do 3º milenio: resumos. Fortaleza: Embrapa Agroindustria Tropical, 2000. p. 473.Biblioteca(s): Embrapa Cerrados. |
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10. | | ANSELMO, R. M.; JUNQUEIRA, N. T. V.; PINTO, A. C. de Q.; VARGAS RAMOS, V. H.; RANGEL, L. E. P.; NASCIMENTO, A. C. do. Comportamento de frutos de dez procedencias de maracujazeiro-doce (Passiflora alata Dryand) em dois ambientes de aramazenamento. In: CONGRESSO BRASILEIRO DE FRUTICULTURA, 16., 2000, Fortaleza, CE. Fruticultura: agronegocio do 3º milenio: resumos. Fortaleza: Embrapa Agroindustria Tropical, 2000. p. 480.Biblioteca(s): Embrapa Cerrados. |
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11. | | RANGEL, L. E. P.; JUNQUEIRA, N. T. V.; PEIXOTO, J. R.; JUNQUEIRA, K. P.; OLIVEIRA, J. de O.; NASCIMENTO, A. C. do. Determinacao do periodo de susceptibilidade de frutos de maracujazeiro-doce (Passiflora alata Dr.) as doencas de campo. In: CONGRESSO BRASILEIRO DE FRUTICULTURA, 16., 2000, Fortaleza, CE. Fruticultura: agronegocio do 3º milenio: resumos. Fortaleza: Embrapa Agroindustria Tropical, 2000. p. 472.Biblioteca(s): Embrapa Cerrados. |
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12. | | RANGEL, L. E. P.; JUNQUEIRA, N. T. V.; NASCIMENTO, A. C. do; FIALHO, J. de F.; R. M. KOSOSKI; RAMOS, V. H. V.; SILVA, J. A. da. Efeito de defensivos agrícolas naturais no controle de doenças de maracujá-doce e de goiaba na pós-colheita. In: CONGRESSO BRASILEIRO DE DEFENSIVOS AGRÍCOLAS NATURAIS, 1., 2000, Fortaleza. Anais... Fortaleza: Academia Cearense de Ciências, 2000. 1 p. Título em inglês: Effect of natural pesticides to control of post-harvest diseases on sweet passion fruit and guava.Biblioteca(s): Embrapa Cerrados. |
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15. | | JUNQUEIRA, N. T. V.; NASCIMENTO, A. C. do; VARGAS RAMOS, V. H.; LAGE, D. A. da C.; KRAHL, L. L.; ALMEIDA, D. A.; CABRAL, G. de A. Efeito de produtos biológicos e químicos no controle da antracnose e na conservação da manga cv. Palmer em pós-colheita. Planaltina, DF: Embrapa Cerrados, 2003. 14 p. (Embrapa Cerrados. Boletim de Pesquisa e Desenvolvimento, 95).Biblioteca(s): Embrapa Cerrados. |
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18. | | STORCH, E. R.; JUNQUEIRA, N. T. V.; RANGEL, L. E. P.; SANTOS, G. R. do; NASCIMENTO, A. C. do; FIALHO, J. de F.; KOSOSKI, R. M.; SILVA, J. A. da. Potencial de alguns defensivos agrícolas naturais para o controle de doenças de mamão papaya na pós-colheita. In: CONGRESSO BRASILEIRO DE DEFENSIVOS AGRÍCOLAS NATURAIS, 1., 2000, Fortaleza. Anais... Fortaleza: Academia Cearense de Ciências, 2000. 1 p. Título em inglês: Potential of some natural pesticides to control of post-harvest diseases on papaya.Biblioteca(s): Embrapa Cerrados. |
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