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Registro Completo |
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Biblioteca(s): |
Embrapa Florestas; Embrapa Gado de Leite. |
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Data corrente: |
16/12/2019 |
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Data da última atualização: |
16/12/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
ROCHA, J. R. do A. S. de C.; MARÇAL, T. de S.; SALVADOR, F. V.; SILVA, A. C. da; CARNEIRO, P. C. S.; RESENDE, M. D. V. de; CARNEIRO, J. da C.; AZEVEDO, A. L. S.; PEREIRA, J. F.; MACHADO, J. C. |
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Afiliação: |
João Romero do Amaral Santos de Carvalho Rocha, UFV; Tiago de Souza Marçal, UFV; Felipe Vicentino Salvador, UFV; Adriel Carlos da Silva, UFV; Pedro Crescencio Souza Carneiro, UFV; MARCOS DEON VILELA DE RESENDE, CNPF; JAILTON DA COSTA CARNEIRO, CNPGL; ANA LUISA SOUSA AZEVEDO, CNPGL; JORGE FERNANDO PEREIRA, CNPGL; JUAREZ CAMPOLINA MACHADO, CNPGL. |
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Título: |
Unraveling candidate genes underlying biomass digestibility in elephant grass (Cenchrus purpureus). |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
BMC Plant Biology, v. 19, article 548, 2019. 12 p. |
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DOI: |
10.1186/s12870-019-2180-5 |
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Idioma: |
Inglês |
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Conteúdo: |
Background: Elephant grass [Cenchrus purpureus (Schumach.) Morrone] is used for bioenergy and animal feed. In order to identify candidate genes that could be exploited for marker-assisted selection in elephant grass, this study aimed to investigate changes in predictive accuracy using genomic relationship information and simple sequence repeats for eight traits (height, green biomass, dry biomass, acid and neutral detergent fiber, lignin content, biomass digestibility, and dry matter concentration) linked to bioenergetics and animal feeding. Results: We used single-step, genome-based best linear unbiased prediction and genome association methods to investigate changes in predictive accuracy and find candidate genes using genomic relationship information. Genetic variability (p < 0.05) was detected for most of the traits evaluated. In general, the overall means for the traits varied widely over the cuttings, which was corroborated by a significant genotype by cutting interaction. Knowing the genomic relationships increased the predictive accuracy of the biomass quality traits. We found that one marker (M28_161) was significantly associated with high values of biomass digestibility. The marker had moderate linkage disequilibrium with another marker (M35_202) that, in general, was detected in genotypes with low values of biomass digestibility. In silico analysis revealed that both markers have orthologous regions in other C4 grasses such as Setaria viridis, Panicum hallii, and Panicum virgatum, and these regions are located close to candidate genes involved in the biosynthesis of cell wall molecules (xyloglucan and lignin), which support their association with biomass digestibility. Conclusions: The markers and candidate genes identified here are useful for breeding programs aimed at changing biomass digestibility in elephant grass. These markers can be used in marker-assisted selection to grow elephant grass cultivars for different uses, e.g., bioenergy production, bio-based products, co-products, bioactive compounds, and animal feed. MenosBackground: Elephant grass [Cenchrus purpureus (Schumach.) Morrone] is used for bioenergy and animal feed. In order to identify candidate genes that could be exploited for marker-assisted selection in elephant grass, this study aimed to investigate changes in predictive accuracy using genomic relationship information and simple sequence repeats for eight traits (height, green biomass, dry biomass, acid and neutral detergent fiber, lignin content, biomass digestibility, and dry matter concentration) linked to bioenergetics and animal feeding. Results: We used single-step, genome-based best linear unbiased prediction and genome association methods to investigate changes in predictive accuracy and find candidate genes using genomic relationship information. Genetic variability (p < 0.05) was detected for most of the traits evaluated. In general, the overall means for the traits varied widely over the cuttings, which was corroborated by a significant genotype by cutting interaction. Knowing the genomic relationships increased the predictive accuracy of the biomass quality traits. We found that one marker (M28_161) was significantly associated with high values of biomass digestibility. The marker had moderate linkage disequilibrium with another marker (M35_202) that, in general, was detected in genotypes with low values of biomass digestibility. In silico analysis revealed that both markers have orthologous regions in other C4 grasses such as Setaria viridis, Panicum hallii, and ... Mostrar Tudo |
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Palavras-Chave: |
Gene annotation; Napier grass; SSR marker; Trait-marker association. |
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Thesagro: |
Biomassa; Capim Elefante; Digestibilidade; Pennisetum Purpureum. |
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Categoria do assunto: |
G Melhoramento Genético |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/207097/1/2019-M.Deon-BMCPB-Unraveling.pdf
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Marc: |
LEADER 03082naa a2200337 a 4500
001 2116956
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008 2019 bl uuuu u00u1 u #d
024 7 $a10.1186/s12870-019-2180-5$2DOI
100 1 $aROCHA, J. R. do A. S. de C.
245 $aUnraveling candidate genes underlying biomass digestibility in elephant grass (Cenchrus purpureus).$h[electronic resource]
260 $c2019
520 $aBackground: Elephant grass [Cenchrus purpureus (Schumach.) Morrone] is used for bioenergy and animal feed. In order to identify candidate genes that could be exploited for marker-assisted selection in elephant grass, this study aimed to investigate changes in predictive accuracy using genomic relationship information and simple sequence repeats for eight traits (height, green biomass, dry biomass, acid and neutral detergent fiber, lignin content, biomass digestibility, and dry matter concentration) linked to bioenergetics and animal feeding. Results: We used single-step, genome-based best linear unbiased prediction and genome association methods to investigate changes in predictive accuracy and find candidate genes using genomic relationship information. Genetic variability (p < 0.05) was detected for most of the traits evaluated. In general, the overall means for the traits varied widely over the cuttings, which was corroborated by a significant genotype by cutting interaction. Knowing the genomic relationships increased the predictive accuracy of the biomass quality traits. We found that one marker (M28_161) was significantly associated with high values of biomass digestibility. The marker had moderate linkage disequilibrium with another marker (M35_202) that, in general, was detected in genotypes with low values of biomass digestibility. In silico analysis revealed that both markers have orthologous regions in other C4 grasses such as Setaria viridis, Panicum hallii, and Panicum virgatum, and these regions are located close to candidate genes involved in the biosynthesis of cell wall molecules (xyloglucan and lignin), which support their association with biomass digestibility. Conclusions: The markers and candidate genes identified here are useful for breeding programs aimed at changing biomass digestibility in elephant grass. These markers can be used in marker-assisted selection to grow elephant grass cultivars for different uses, e.g., bioenergy production, bio-based products, co-products, bioactive compounds, and animal feed.
650 $aBiomassa
650 $aCapim Elefante
650 $aDigestibilidade
650 $aPennisetum Purpureum
653 $aGene annotation
653 $aNapier grass
653 $aSSR marker
653 $aTrait-marker association
700 1 $aMARÇAL, T. de S.
700 1 $aSALVADOR, F. V.
700 1 $aSILVA, A. C. da
700 1 $aCARNEIRO, P. C. S.
700 1 $aRESENDE, M. D. V. de
700 1 $aCARNEIRO, J. da C.
700 1 $aAZEVEDO, A. L. S.
700 1 $aPEREIRA, J. F.
700 1 $aMACHADO, J. C.
773 $tBMC Plant Biology$gv. 19, article 548, 2019. 12 p.
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Registro original: |
Embrapa Florestas (CNPF) |
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