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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
05/07/2019 |
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Data da última atualização: |
30/10/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
VOLPATO, L.; ALVES, R. S.; TEODORO, P. E.; RESENDE, M. D. V. de; NASCIMENTO, M.; NASCIMENTO, A. C. C.; LUDKE, W. H.; SILVA, F. L. da; BORÉM, A. |
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Afiliação: |
Leonardo Volpato, Universidade Federal de Viçosa; Rodrigo Silva Alves, Universidade Federal de Viçosa; Paulo Eduardo Teodoro, Universidade Federal de Mato Grosso do Sul; MARCOS DEON VILELA DE RESENDE, CNPF; Moysés Nascimento, Universidade Federal de Viçosa; Ana Carolina Campana Nascimento, Universidade Federal de Viçosa; Willian Hytalo Ludke, Universidade Federal de Viçosa; Felipe Lopes da Silva, Universidade Federal de Viçosa; Aluízio Borém, Universidade Federal de Viçosa. |
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Título: |
Multi-trait multi-environment models in the genetic selection of segregating soybean progeny. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
PLoS ONE, v. 14, n. 4, e0215315, Apr. 2019. 22 p. |
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DOI: |
10.1371/journal.pone.0215315 |
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Idioma: |
Inglês |
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Conteúdo: |
At present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; h2 prog) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of h2 prog. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny. MenosAt present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; h2 prog) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided... Mostrar Tudo |
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Palavras-Chave: |
Bayesian-inference; Breeding values; Genomic selection; Inferência Bayesian; Mixed models; Modelo misto; Seed protein; Seleção genômica. |
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Thesagro: |
Soja. |
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Thesaurus Nal: |
Agronomic traits; Prediction; Soybeans. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/199239/1/2019-M.Deon-PO-Multi-trait.pdf
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Marc: |
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001 2110400
005 2019-10-30
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1371/journal.pone.0215315$2DOI
100 1 $aVOLPATO, L.
245 $aMulti-trait multi-environment models in the genetic selection of segregating soybean progeny.$h[electronic resource]
260 $c2019
520 $aAt present, single-trait best linear unbiased prediction (BLUP) is the standard method for genetic selection in soybean. However, when genetic selection is performed based on two or more genetically correlated traits and these are analyzed individually, selection bias may arise. Under these conditions, considering the correlation structure between the evaluated traits may provide more-accurate genetic estimates for the evaluated parameters, even under environmental influences. The present study was thus developed to examine the efficiency and applicability of multi-trait multi-environment (MTME) models by the residual maximum likelihood (REML/BLUP) and Bayesian approaches in the genetic selection of segregating soybean progeny. The study involved data pertaining to 203 soybean F2:4 progeny assessed in two environments for the following traits: number of days to maturity (DM), 100-seed weight (SW), and average seed yield per plot (SY). Variance components and genetic and non-genetic parameters were estimated via the REML/BLUP and Bayesian methods. The variance components estimated and the breeding values and genetic gains predicted with selection through the Bayesian procedure were similar to those obtained by REML/BLUP. The frequentist and Bayesian MTME models provided higher estimates of broad-sense heritability per plot (or heritability of total effects of progeny; h2 prog) and mean accuracy of progeny than their respective single-trait versions. Bayesian analysis provided the credibility intervals for the estimates of h2 prog. Therefore, MTME led to greater predicted gains from selection. On this basis, this procedure can be efficiently applied in the genetic selection of segregating soybean progeny.
650 $aAgronomic traits
650 $aPrediction
650 $aSoybeans
650 $aSoja
653 $aBayesian-inference
653 $aBreeding values
653 $aGenomic selection
653 $aInferência Bayesian
653 $aMixed models
653 $aModelo misto
653 $aSeed protein
653 $aSeleção genômica
700 1 $aALVES, R. S.
700 1 $aTEODORO, P. E.
700 1 $aRESENDE, M. D. V. de
700 1 $aNASCIMENTO, M.
700 1 $aNASCIMENTO, A. C. C.
700 1 $aLUDKE, W. H.
700 1 $aSILVA, F. L. da
700 1 $aBORÉM, A.
773 $tPLoS ONE$gv. 14, n. 4, e0215315, Apr. 2019. 22 p.
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Registro original: |
Embrapa Florestas (CNPF) |
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| Registros recuperados : 11 | |
| 1. |  | ROCA PAIXÃO, J. F.; GILLET, F. X.; RIBEIRO, T. P.; BOURNAUD, C.; LOURENCO-TESSUTTI, I. T.; NORIEGA, D. D.; MELO, B. P. de; ALMEIDA-ENGLER, J. de; GROSSI-DE-SA, M. F. Improved drought stress tolerance in Arabidopsis by CRISPR/ dCas9 fusion with a Histone AcetylTransferase. Scientific Reports, v. 9, n. 1, p. 1-9, 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 2. | | BASSO, M. F.; LOURENCO-TESSUTTI, I. T.; BUSANELLO, C.; PINTO, C. E. M.; FREITAS, E. de O.; RIBEIRO, T. P.; ENGLER, J. de A.; OLIVEIRA, A. C. de; MORGANTE, C. V.; ALVES-FERREIRA, M.; GROSSI-DE-SA, M. F. Insights obtained using different modules of the cotton uceA1.7 promoter. Planta, v. 251, n. 2, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Semiárido. |
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| 3. | | BASSO, M. F.; LOURENCO-TESSUTTI, I. T.; MENDES, R. A. G.; PINTO, C. E. M.; BOURNAUD, C.; GILLET, F.-X.; TOGAWA, R. C.; MACEDO, L. L. P. de; ENGLER, J. d A.; GROSSI-DE-SA, M. F. MiDaf16-like and MiSkn1-like gene families are reliable targets to develop biotechnological tools for the control and management of Meloidogyne incognita. Scientific Reports, v. 10, n. 1, p. 1-13, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 4. | | MELO, B. P. de; LOURENCO-TESSUTTI, I. T.; PAIXÃO, J. F. R.; NORIEGA, D. D.; SILVA, M. C. M.; ALMEIDA-ENGLER, J. de; FONTES, E. P. B.; GROSSI-DE-SA, M. F. Transcriptional modulation of AREB-1 by cRiSpRa improves plant physiological performance under severe water deficit. Scientific Reports, v. 10, 16231, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 5. | | MELO, B. P. de; LOURENCO-TESSUTTI, I. T.; MORGANTE, C. V.; SANTOS, N. C.; PINHEIRO, L. B.; LINS, C. B. de J.; SILVA, M. C. M.; MACEDO, L. L. P.; FONTES, E. P. B.; GROSSI-DE-SA, M. F. Soybean embryonic axis transformation: combining biolistic and Agrobacterium-Mediated Protocols to overcome typical complications of in vitro plant regeneration. Frontiers in Plant Science, v. 11, article 1228, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Semiárido. |
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| 6. | | LISEI-DE-SÁ, M. E.; ARRAES, F. B. N.; BRITO, G. G.; BENEVENTI, M. A.; LOURENCO-TESSUTTI, I.; BASSO, A. M. M.; AMORIM, R. M. S.; SILVA, M. C. M.; FAHEEM, M.; OLIVEIRA, N. G.; MIZOI, J.; YAMAGUCHI-SHINOZAKI, K.; GROSSI-DE-SA, M. F. AtDREB2A-CA influences root architecture and increases drought tolerance in transgenic cotton. Agricultural Sciences, v. 8, p. 1195-1225, 2017.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 3 |
| Biblioteca(s): Embrapa Clima Temperado; Embrapa Recursos Genéticos e Biotecnologia. |
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| 7. | | FREITA, E. O.; MELO, B. P.; LOURENCO-TESSUTTI, I. T.; ARRAES, F. B. M.; AMORIM, R. M.; LISEI-DE-SÁ, M. E.; COSTA, J. A.; LEITE, A. G. B.; FAHEEM, M.; FERREIRA, M. A.; MORGANTE, C. V.; FONTES, E. P. B.; GROSSI-DE-SA, M. F. Identification and characterization of the GmRD26 soybean promoter in response to abiotic stresses: potential tool for biotechnological application. BMC Biotechnology, v. 19, article 79, 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Semiárido. |
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| 8. | | FIRMINO, A. A. P.; PINHEIRO, D. H.; MOREIRA-PINTO, C. E.; ANTONINO, J. D.; MACEDO, L. L. P.; MARTINS-DE-SA, D.; ARRAES, F. B. M.; COELHO, R. R.; FONSECA, F. C. de A.; SILVA, M. C. M.; ENGLER, J. de A.; SILVA, M. S.; LOURENÇO-TESSUTTI, I. T.; TERRA, W. R.; GROSSI-DE-SA, M. F. RNAi-mediated suppression of Laccase2 impairs cuticle tanning and molting in the cotton boll weevil (Anthonomus grandis). Frontiers in Physiology, v. 11, article 591569, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 9. | | RIBEIRO, T. P.; ARRAES, F. B. M.; LOURENCO-TESSUTTI, I. T.; SILVA, M. S.; LISEI-DE-SÁ, M. E.; LUCENA, W. A.; MACEDO, L. L. P. de; LIMA, J. N.; AMORIM, R. M. S.; ARTICO, S.; ALVES-FERREIRA, M.; SILVA, M. C. M.; GROSSI-DE-SA, M. F. Transgenic cotton expressing Cry10Aa toxin confers high resistance to the cotton boll weevil. Plant Biotechnology Journal, v. 15, p. 997-1009, 2017. (Open Access).| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 10. | | OLIVEIRA, R. S. de; OLIVEIRA NETO, O. B.; MOURA, H. F. N.; MACEDO, L. L. P. de; ARRAES, F. B. M.; LUCENA, W. A.; LOURENCO TESSUTTI, I. T.; BARBOSA, A. A. de D.; SILVA, M. C. M. da; GROSSI DE SA, M. F. Transgenic cotton plants expressing Cry1Ia12 toxin confer resistance to fall armyworm (Spodoptera frugiperda) and cotton boll weevil (Anthonomus grandis). Frontiers in Plant Science, v. 7, article 165 , 2016.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 11. | | RIBEIRO, T. P.; BASSO, M. F.; CARVALHO, M. H. de; MACEDO, L. L. P. de; SILVA, D. M. L. da; LOURENCO-TESSUTTI, I. T.; OLIVEIRA-NETO, O. B. de; CAMPOS-PINTO, E. R. de; LUCENA, W. A.; SILVA, M. C. M. da; TRIPODE, B. M. D.; ABREU-JARDIM, T. P. F.; MIRANDA, J. E.; ALVES-FERREIRA, M.; MORGANTE, C. V.; GROSSI-DE-SA, M. F. Stability and tissue-specific Cry10Aa overexpression improves cotton resistance to the cotton boll weevil. Biotechnology Research and Innovation, v. 3, p. 27-41, 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 5 |
| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia; Embrapa Semiárido. |
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| Registros recuperados : 11 | |
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