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| Registros recuperados : 894 | |
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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: |
09/06/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
LIMA L. P.; AZEVEDO, C. F.; RESENDE, M. D. V. de; SILVA, F. F. e; SUELA, M. M.; NASCIMENTO, M.; VIANA, J. M. S. |
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Afiliação: |
Leísa Pires Lima, Universidade Federal de Viçosa; Camila Ferreira Azevedo, Universidade Federal de Viçosa; MARCOS DEON VILELA DE RESENDE, CNPF; Fabyano Fonseca e Silva, Universidade Federal de Viçosa; Matheus Massariol Suela, Universidade Federal de Viçosa; Moysés Nascimento, Universidade Federal de Viçosa; José Marcelo Soriano Viana, Universidade Federal de Viçosa. |
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Título: |
New insights into genomic selection through population-based non-parametric prediction methods. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Scientia Agricicola, v. 76, n. 4, p. 290-298, July/Aug. 2019. |
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DOI: |
10.1590/1678-992x-2017-0351 |
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Idioma: |
Inglês |
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Conteúdo: |
Genome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS are based on random regression or dimensionality reduction methods. In this study a new non-parametric method, called Delta-p was proposed, which was then compared to the Genomic Best Linear Unbiased Predictor (G-BLUP) method. Furthermore, a new selection index combining the genetic values obtained by the G-BLUP and Delta-p, named Delta-p/G-BLUP methods, was proposed. The efficiency of the proposed methods was evaluated through both simulation and real studies. The simulated data consisted of eight scenarios comprising a combination of two levels of heritability, two genetic architectures and two dominance status (absence and complete dominance). Each scenario was simulated ten times. All methods were applied to a real dataset of Asian rice (Oryza sativa) aiming to increase the efficiency of a current breeding program. The methods were compared as regards accuracy of prediction (simulation data) or predictive ability (real dataset), bias and recovery of the true genomic heritability. The results indicated that the proposed Delta-p/G-BLUP index outperformed the other methods in both prediction accuracy and predictive ability. |
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Palavras-Chave: |
Asian rice; Genetic gain; Genomic prediction. |
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Thesagro: |
Arroz; Oryza Sativa. |
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Thesaurus NAL: |
Selection index. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/199238/1/2019-M.Deon-SA-New-insights.pdf
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Marc: |
LEADER 02306naa a2200277 a 4500
001 2110406
005 2020-06-09
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1590/1678-992x-2017-0351$2DOI
100 1 $aLIMA L. P.
245 $aNew insights into genomic selection through population-based non-parametric prediction methods.$h[electronic resource]
260 $c2019
520 $aGenome-wide selection (GWS) is based on a large number of markers widely distributed throughout the genome. Genome-wide selection provides for the estimation of the effect of each molecular marker on the phenotype, thereby allowing for the capture of all genes affecting the quantitative traits of interest. The main statistical tools applied to GWS are based on random regression or dimensionality reduction methods. In this study a new non-parametric method, called Delta-p was proposed, which was then compared to the Genomic Best Linear Unbiased Predictor (G-BLUP) method. Furthermore, a new selection index combining the genetic values obtained by the G-BLUP and Delta-p, named Delta-p/G-BLUP methods, was proposed. The efficiency of the proposed methods was evaluated through both simulation and real studies. The simulated data consisted of eight scenarios comprising a combination of two levels of heritability, two genetic architectures and two dominance status (absence and complete dominance). Each scenario was simulated ten times. All methods were applied to a real dataset of Asian rice (Oryza sativa) aiming to increase the efficiency of a current breeding program. The methods were compared as regards accuracy of prediction (simulation data) or predictive ability (real dataset), bias and recovery of the true genomic heritability. The results indicated that the proposed Delta-p/G-BLUP index outperformed the other methods in both prediction accuracy and predictive ability.
650 $aSelection index
650 $aArroz
650 $aOryza Sativa
653 $aAsian rice
653 $aGenetic gain
653 $aGenomic prediction
700 1 $aAZEVEDO, C. F.
700 1 $aRESENDE, M. D. V. de
700 1 $aSILVA, F. F. e
700 1 $aSUELA, M. M.
700 1 $aNASCIMENTO, M.
700 1 $aVIANA, J. M. S.
773 $tScientia Agricicola$gv. 76, n. 4, p. 290-298, July/Aug. 2019.
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Embrapa Florestas (CNPF) |
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