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Registro Completo |
Biblioteca(s): |
Embrapa Milho e Sorgo. |
Data corrente: |
24/09/2018 |
Data da última atualização: |
05/02/2019 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
OLIVEIRA, A. A. de; PASTINA, M. M.; SOUZA, V. F. de; PARRELLA, R. A. da C.; NODA, R. W.; SIMEONE, M. L. F.; SCHAFFERT, R. E.; MAGALHAES, J. V. de; DAMASCENO, C. M. B.; MARGARIDO, G. R. A. |
Afiliação: |
Amanda Avelar de Oliveira; MARIA MARTA PASTINA, CNPMS; Vander Filipe de Souza; RAFAEL AUGUSTO DA COSTA PARRELLA, CNPMS; ROBERTO WILLIANS NODA, CNPMS; MARIA LUCIA FERREIRA SIMEONE, CNPMS; ROBERT EUGENE SCHAFFERT, CNPMS; JURANDIR VIEIRA DE MAGALHAES, CNPMS; CYNTHIA MARIA BORGES DAMASCENO, CNPMS; Gabriel Rodrigues Alves Margarido. |
Título: |
Genomic prediction applied to high-biomass sorghum for bioenergy production. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Molecular Breeding, v. 38, n. 49, p. 1-16, 2018. |
DOI: |
10.1007/s11032-018-0802-5 |
Idioma: |
Inglês |
Conteúdo: |
The increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesC?, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs. MenosThe increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesC?, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction n... Mostrar Tudo |
Palavras-Chave: |
Genotipagem. |
Thesagro: |
Bioenergia; Biomassa. |
Categoria do assunto: |
G Melhoramento Genético |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/183412/1/Genomic-prediction.pdf
|
Marc: |
LEADER 02655naa a2200277 a 4500 001 2096210 005 2019-02-05 008 2018 bl uuuu u00u1 u #d 024 7 $a10.1007/s11032-018-0802-5$2DOI 100 1 $aOLIVEIRA, A. A. de 245 $aGenomic prediction applied to high-biomass sorghum for bioenergy production.$h[electronic resource] 260 $c2018 520 $aThe increasing cost of energy and finite oil and gas reserves have created a need to develop alternative fuels from renewable sources. Due to its abiotic stress tolerance and annual cultivation, high-biomass sorghum (Sorghum bicolor L. Moench) shows potential as a bioenergy crop. Genomic selection is a useful tool for accelerating genetic gains and could restructure plant breeding programs by enabling early selection and reducing breeding cycle duration. This work aimed at predicting breeding values via genomic selection models for 200 sorghum genotypes comprising landrace accessions and breeding lines from biomass and saccharine groups. These genotypes were divided into two sub-panels, according to breeding purpose. We evaluated the following phenotypic biomass traits: days to flowering, plant height, fresh and dry matter yield, and fiber, cellulose, hemicellulose, and lignin proportions. Genotyping by sequencing yielded more than 258,000 single-nucleotide polymorphism markers, which revealed population structure between subpanels. We then fitted and compared genomic selection models BayesA, BayesB, BayesC?, BayesLasso, Bayes Ridge Regression and random regression best linear unbiased predictor. The resulting predictive abilities varied little between the different models, but substantially between traits. Different scenarios of prediction showed the potential of using genomic selection results between sub-panels and years, although the genotype by environment interaction negatively affected accuracies. Functional enrichment analyses performed with the marker-predicted effects suggested several interesting associations, with potential for revealing biological processes relevant to the studied quantitative traits. This work shows that genomic selection can be successfully applied in biomass sorghum breeding programs. 650 $aBioenergia 650 $aBiomassa 653 $aGenotipagem 700 1 $aPASTINA, M. M. 700 1 $aSOUZA, V. F. de 700 1 $aPARRELLA, R. A. da C. 700 1 $aNODA, R. W. 700 1 $aSIMEONE, M. L. F. 700 1 $aSCHAFFERT, R. E. 700 1 $aMAGALHAES, J. V. de 700 1 $aDAMASCENO, C. M. B. 700 1 $aMARGARIDO, G. R. A. 773 $tMolecular Breeding$gv. 38, n. 49, p. 1-16, 2018.
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Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
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Registro Completo
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
25/01/2011 |
Data da última atualização: |
23/03/2011 |
Tipo da produção científica: |
Artigo em Anais de Congresso |
Autoria: |
OLIVEIRA, R. R. S. de; WATRIN, O. dos S.; SAMPAIO, S. M. N.; Pimentel, G. M. |
Afiliação: |
RODRIGO RAFAEL SOUZA DE OLIVEIRA, Bolsista Embrapa/UFPA; ORLANDO DOS SANTOS WATRIN, CPATU; SANDRA MARIA NEIVA SAMPAIO, CPATU; Gustavo Martinez Pimentel, Bolsista Embrapa/UFPA. |
Título: |
Análise espaço-temporal do uso e cobertura da terra nas microbacias hidrográficas dos igarapés Timboteua e Peripindeua, Nordeste Paraense. |
Ano de publicação: |
2010 |
Fonte/Imprenta: |
In: SEMINÁRIO DE INICIAÇÃO CIENTÍFICA, 14., 2010, Belém, PA. Bolsista de iniciação científica: um aporte ao desenvolvimento da pesquisa agropecuária: anais. Belém, PA: Embrapa Amazônia Oriental, 2010. |
Descrição Física: |
1 CD-ROM. |
Idioma: |
Português |
Palavras-Chave: |
Análise espacial; Brasil; Geoprocessamento; Pará. |
Thesagro: |
Cobertura do solo; Sensoriamento remoto; Uso da terra. |
Thesaurus NAL: |
Amazonia. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/25940/1/RodrigoOliveira.pdf
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Marc: |
LEADER 00909nam a2200241 a 4500 001 1874427 005 2011-03-23 008 2010 bl uuuu u00u1 u #d 100 1 $aOLIVEIRA, R. R. S. de 245 $aAnálise espaço-temporal do uso e cobertura da terra nas microbacias hidrográficas dos igarapés Timboteua e Peripindeua, Nordeste Paraense. 260 $aIn: SEMINÁRIO DE INICIAÇÃO CIENTÍFICA, 14., 2010, Belém, PA. Bolsista de iniciação científica: um aporte ao desenvolvimento da pesquisa agropecuária: anais. Belém, PA: Embrapa Amazônia Oriental$c2010 300 $c1 CD-ROM. 650 $aAmazonia 650 $aCobertura do solo 650 $aSensoriamento remoto 650 $aUso da terra 653 $aAnálise espacial 653 $aBrasil 653 $aGeoprocessamento 653 $aPará 700 1 $aWATRIN, O. dos S. 700 1 $aSAMPAIO, S. M. N. 700 1 $aPimentel, G. M.
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