| |
|
|
 | Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Milho e Sorgo. |
|
Data corrente: |
24/07/2018 |
|
Data da última atualização: |
05/02/2019 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
DIAS, K. O. das G.; GEZAN, S. A.; GUIMARÃES, C. T.; NAZARIAN, A.; SILVA, L. da C. e; PARENTONI, S. N.; GUIMARAES, P. E. de O.; ANONI, C. de O.; PÁDUA, J. M. V.; PINTO, M. de O.; NODA, R. W.; RIBEIRO, C. A. G.; MAGALHAES, J. V. de; GARCIA, A. A. F.; SOUZA, J. C. de; GUIMARAES, L. J. M.; PASTINA, M. M. |
|
Afiliação: |
Kaio Olímpio das Graças Dias, Universidade Federal de Lavras; Salvador Alejandro Gezan, School of Forest Resources & Conservation, University of Florida, Gainesville.; CLAUDIA TEIXEIRA GUIMARAES, CNPMS; Alireza Nazarian, School of Forest Resources & Conservation, University of Florida, Gainesville.; Luciano da Costa e Silva, JMP Division, SAS Institute Inc., Cary.; SIDNEY NETTO PARENTONI, CNPMS; PAULO EVARISTO DE O GUIMARAES, CNPMS; Carina de Oliveira Anoni, Escola Superior de Agricultura “Luiz de Queiroz”; José Maria Villela Pádua, Universidade Federal de Lavras; MARCOS DE OLIVEIRA PINTO, CNPMS; ROBERTO WILLIANS NODA, CNPMS; Carlos Alexandre Gomes Ribeiro, Universidade Federal de Viçosa; JURANDIR VIEIRA DE MAGALHAES, CNPMS; Antonio Augusto Franco Garcia, Escola Superior de Agricultura “Luiz de Queiroz”; João Cândido de Souza, Universidade Federal de Lavras; LAURO JOSE MOREIRA GUIMARAES, CNPMS; MARIA MARTA PASTINA, CNPMS. |
|
Título: |
Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials. |
|
Ano de publicação: |
2018 |
|
Fonte/Imprenta: |
Heredity, London, v. 121, n. 1, p. 24-37, 2018. |
|
DOI: |
10.1038/s41437-018-0053-6 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Breeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multienvironment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids? genotypes were inferred based on their parents? genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single-cross hybrids. MenosBreeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multienvironment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids? genotypes were inferred based on their parents? genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS a... Mostrar Tudo |
|
Thesagro: |
Milho; Resistência a Seca. |
|
Categoria do assunto: |
-- |
|
Marc: |
LEADER 03081naa a2200349 a 4500
001 2093500
005 2019-02-05
008 2018 bl uuuu u00u1 u #d
024 7 $a10.1038/s41437-018-0053-6$2DOI
100 1 $aDIAS, K. O. das G.
245 $aImproving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials.$h[electronic resource]
260 $c2018
520 $aBreeding for drought tolerance is a challenging task that requires costly, extensive, and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here, we evaluated the accuracy of genomic selection (GS) using additive (A) and additive + dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multienvironment trials. Phenotypic data of five drought tolerance traits were measured in 308 hybrids along eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids? genotypes were inferred based on their parents? genotypes (inbred lines) using single-nucleotide polymorphism markers obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Two cross-validation (CV) schemes were tested: CV1 and CV2. The FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive-by-environment and the dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Results showed differences in the predictive accuracy between A and AD models, using both CV1 and CV2, for the five traits in both water conditions. For grain yield (GY) under WS and using CV1, the AD model doubled the predictive accuracy in comparison to the A model. Through CV2, GS models benefit from borrowing information of correlated trials, resulting in an increase of 40% and 9% in the predictive accuracy of GY under WS for A and AD models, respectively. These results highlight the importance of multi-environment trial analyses using GS models that incorporate additive and dominance effects for genomic predictions of GY under drought in maize single-cross hybrids.
650 $aMilho
650 $aResistência a Seca
700 1 $aGEZAN, S. A.
700 1 $aGUIMARÃES, C. T.
700 1 $aNAZARIAN, A.
700 1 $aSILVA, L. da C. e
700 1 $aPARENTONI, S. N.
700 1 $aGUIMARAES, P. E. de O.
700 1 $aANONI, C. de O.
700 1 $aPÁDUA, J. M. V.
700 1 $aPINTO, M. de O.
700 1 $aNODA, R. W.
700 1 $aRIBEIRO, C. A. G.
700 1 $aMAGALHAES, J. V. de
700 1 $aGARCIA, A. A. F.
700 1 $aSOUZA, J. C. de
700 1 $aGUIMARAES, L. J. M.
700 1 $aPASTINA, M. M.
773 $tHeredity, London$gv. 121, n. 1, p. 24-37, 2018.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
| Registros recuperados : 387 | |
| 381. |  | JARDIM, J. N.; GUIMARAES, C. T.; MAGALHAES, J. V. de; SOUZA, I. R. P. de; LANA, U. G. de P.; CASELA, C. R.; COSTA, R. V. da; GUIMARAES, P. E. de O.; PARENTONI, S. N.; GUIMARAES, L. J. M.; PACHECO, C. A. P.; SILVA, A. R. da; OLIVEIRA, E. de. Mapeamento de QTLs visando a implementação de seleção assistida para resistência a doenças foliares em milho. In: SIMPÓSIO SOBRE INOVAÇÃO E CRIATIVIDADE CIENTÍFICA NA EMBRAPA, 1., 2008, Brasília, DF. Resumos... Brasília, DF: Embrapa, 2008.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Milho e Sorgo. |
|    |
| 382. | | MELO, J. O.; MARTINS, L. G. C.; BARROS, B. de A.; PIMENTA, M. R.; LANA, U. G. de P.; DUARTE, C. E. M.; PASTINA, M. M.; GUIMARÃES, C. T.; SCHAFFERT, R. E.; KOCHIAN, L. V.; FONTES, E. P. B.; MAGALHAES, J. V. de. Repeat variants for the SbMATE transporter protect sorghum roots from aluminum toxicity by transcriptional interplay in cis and trans. Proceedings of the National Academy of Sciences of the United States of America, Washington, v. 116, n. 1, p. 313-318, 2019. Publicado online em 13 dez. 2018.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Milho e Sorgo. |
|  |
| 383. | | CANIATO, F. F.; GUIMARAES, C. T.; HAMBLIN, M.; BILLOT, C.; RAMI, J.-F.; HUFNAGEL, B.; KOCHIAN, L. V.; LIU, J.; GARCIA, A. A. F.; HASH, C. T.; RAMU, P.; MITCHELL, S.; KRESIVICH, S.; OLIVEIRA, A. C. de; AVELLAR, G. de; BORÉM, A.; GLASZMANN, J.-C.; SCHAFFERT, R. E.; MAGALHAES, J. V. The relationship between population structure and aluminum tolerance in cultivated sorghum. Plos One, San Francisco, v. 6, n. 6, Jun. 2011.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Milho e Sorgo. |
| |
| 384. | | SABADIN, P. K.; MALOSETTI, M.; BOER, M. P.; TARDIN, F. D.; SANTOS, F. G.; GUIMARAES, C. T.; GOMIDE, R. L.; ANDRADE, C. L. T.; ALBUQUERQUE, P. E. P.; CANIATO, F. F.; MOLLINARI, M.; MARGARIDO, G. R. A.; OLIVEIRA, B. F.; SCHAFFERT, R. E.; GARCIA, A. A. F.; EEUWIJK, F. A. van; MAGALHAES, J. V. Studying the genetic basis of drought tolerance in sorghum by managed stress trials and adjustments for phenological and plant height differences. Theoretical and Applied Genetics, Berlin, v. 124, p. 1389-1402, 2012.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Milho e Sorgo. |
| |
| 385. | | VASCONCELOS, A. T. R. de; ALMEIDA, D. F. de; HUNGRIA, M.; GUIMARAES, C. T.; ANTONIO, R. V.; ALMEIDA, F. C.; ALMEIDA, L. G. P. de; ALMEIDA, R. de; ALVES-GOMES, J.A.; ANDRADE. E. M.; ARAUJO, J.; ARAUJO, M. F. R. de; ASTOLFI FILHO, S.; AZEVEDO, V, BAPTISTA, A. J.; BATATUS, L. A. M.; BATISTA, J. da S.; BEIO, A.; BERG, C. van den.; BOGO. M.; BONATTO, S.; BORDIGNON, J.; BRIGIDO, M. M.; BRITO, C. A.; BROCCHI, M.; BURITY, H. A.; CAMARGO, A. A.; CARDOSO, D. das D. de P.; CARNEIRO, N. P. The complete genome sequence of Chromobacterium violaceum reveals remarkable and exploitable bacterial adaptability. Proceedings of the National Academy of Sciences of the United States of America, Washington, v. 100, n. 20, p. 11660-11665, 2003.| Biblioteca(s): Embrapa Milho e Sorgo. |
| |
| 386. | | RUIZ, J. C.; D'AFONSECA, V.; SILVA, A.; ALI, A.; PINTO, A. C.; SANTOS, A. R.; ROCHA, A. A. M. C.; LOPES, D. O.; DORELLA, F. A.; PACHECO, L. G. C.; COSTA, M. P.; TURK, M. Z.; SEYFFERT, N.; MORAES, P. M. R. O.; SOARES, S. C.; ALMEIDA, S. S.; CASTRO, T. L. P.; ABREU, V. A. C.; TROST, E.; BAUMBACH, J.; TAUCH, A.; SCHNEIDER, M. P. C.; McCULLOCH, J.; CERDEIRA, L. T.; RAMOS, R. T. J.; ZERLOTINI, A.; DOMINITINI, A.; RESENDE, D. M.; COSER, E. M.; OLIVEIRA, L. M.; PEDROSA, A. L.; VIEIRA, C. U.; GUIMARAES, C. T.; BARTHOLOMEU, D. C.; OLIVEIRA, D. M.; SANTOS, F. R.; RABELO, E. M.; LOBO, F. P.; FRANCO, G. R.; COSTA, A. F.; CASTRO, I. M.; DIAS, S. R. C.; FERRO, J. A.; ORTEGA, J. M.; PAIVA, L. V.; ALMEIDA, J. F.; GOULART, L. R.; FERRO, M. I. T.; CARNEIRO, N. P.; FALCÃO, P. R. K.; GRYNBERG, P.; TEIXEIRA, S. M. R.; BROMMONSCHENKEL, S.; OLIVEIRA, S. C.; MEYER, R.; MOORE, R. J.; MIYOSHI, A.; OLIVEIRA, G. C.; AZEVEDO, V. Evidence for reductive genome evolution and lateral acquisition of virulence functions in two Corynebacterium pseudotuberculosis strains. Plos One, San Francisco, v. 6, n. 4, p. 1-16, 2011.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agricultura Digital; Embrapa Milho e Sorgo. |
| |
| 387. | | VASCONCELOS, A. T. R.; FERREIRA, H. B.; BIZARRO, C. V.; BONATTO, S. L.; CARVALHO, M. O.; PINTO, P. M.; ALMEIDA, D. F.; ALMEIDA, L. G. P.; ALMEIDA, R.; ALVES-FILHO, L.; ASSUNÇÃO, E. N.; AZEVEDO, V. A. C.; BOGO, M. R.; BRIGIDO, M. M.; BROCCHI, M.; BURITY, H. A.; CAMARGO, A. A.; CAMARGO, S. S.; CAREPO, M. S.; CARRARO, D. M.; CASCARDO, J. C. de M.; CASTRO, L. A.; CAVALCANTI, G.; CHEMALE, G.; COLLEVATTI, R. G.; CUNHA, C. W.; DALLAGIOVANNA, B.; DAMBRÓS, B. P.; DELLAGOSTIN, O. A.; FALCÃO, C.; FANTINATTI-GARBOGGINI, F.; FELIPE, M. S. S.; FIORENTIN, L.; FRANCO, G. R.; FREITAS, N. S. A.; FRÍAS, D.; GRANGEIRO, T. B.; GRISARD, E. C.; GUIMARÃES, C. T.; HUNGRIA, M.; JARDIM, S. N.; KRIEGER, M. A.; LAURINO, J. P.; LIMA, L. F. A.; LOPES, M. I.; LORETO, E. L. S. MADEIRA, H. M. F.; MANFIO, G. P.; MARANHÃO, A. Q.; MARTINKOVICS, C. T.; MEDEIROS, S. R. B.; MOREIRA, M. A. M.; NEIVA, M.; RAMALHO-NETO, C. E.; NICOLÁS, M. F.; OLIVEIRA, S. C.; PAIXÃO, R. F. C.; PEDROSA, F. O.; PENA, S. D. J.; PEREIRA, M.; PEREIRA-FERRARI, L.; PIFFER, I.; PINTO, L. S; POTRICH, D. P.; SALIM, A. C. M.; SANTOS, F. R.; SCHMITT, R.; SCHNEIDER, M. P. C.; SCHRANK, A.; SCHRANK, I. S.; SCHUCK, A. F.; SEUANEZ, H, N.; SILVA, D. W.; SILVA, R.; SILVA, S. C.; SOARES, C. M. A.; SOUZA, K. R.; SOUZA, R. C.; STAATS, C. C.; STEFFENS, M. B. R.; TEIXEIRA, S. M. R.; URMENYI, T. P.; VAINSTEIN, M. H.; ZUCCHERATO, L. W.; SIMPSON, A. J. G.; ZAHA, A. Swine and poultry pathogens: the complete genome sequences of two strains of Mycoplasma hyopneumoniae and a strain of Mycoplasma synoviae. Journal of Bacteriology, Washington, v. 187, n. 16, p. 5568-5577, Aug. 2005.| Biblioteca(s): Embrapa Soja. |
| |
| Registros recuperados : 387 | |
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
