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| 6. |  | GALVÃO, S. F. A.; LANA, U. G. de P.; GOMES, E. A.; OLIVEIRA-PAIVA, C. A.; YAMAGISHI, M. E. B.; VIANA, M. J. A.; SOUSA, S. M. de. Análise genômica de bactérias promotoras de crescimento de plantas visando a identificação de genes e desenvolvimento de marcadores estirpe-específicos. In: CONGRESSO NACIONAL DE MILHO E SORGO, 33., 2022, Sete Lagoas. Brasil: 200 anos de independência: sustentabilidade e desafios para a cadeia produtiva de grãos: resumos. Sete Lagoas: Associação Brasileira de Milho e Sorgo, 2022. Evento híbrido.| Biblioteca(s): Embrapa Agricultura Digital. |
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| 7. | | GALVÃO, S. F. A.; LANA, U. G. de P.; GOMES, E. A.; OLIVEIRA-PAIVA, C. A.; YAMAGISHI, M. E. B.; VIANA, M. J. A.; SOUSA, S. M. de. Análise genômica de bactérias promotoras de crescimento de plantas visando a identificação de genes e desenvolvimento de marcadores estirpe-específicos. In: CONGRESSO NACIONAL DE MILHO E SORGO, 33., 2022, Sete Lagoas. Brasil: 200 anos de independência: sustentabilidade e desafios para a cadeia produtiva de grãos: resumos. Sete Lagoas: Associação Brasileira de Milho e Sorgo, 2022. Evento online.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| Registros recuperados : 7 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital; Embrapa Milho e Sorgo. |
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Data corrente: |
08/02/2021 |
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Data da última atualização: |
19/02/2021 |
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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: |
VIANA, M. J. A.; ZERLOTINI NETO, A.; MUDADU, M. de A. |
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Afiliação: |
MARCOS JOSE ANDRADE VIANA, CNPMS; ADHEMAR ZERLOTINI NETO, CNPTIA; MAURICIO DE ALVARENGA MUDADU, CNPTIA. |
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Título: |
Plant Co-expression Annotation Resource: a web server for identifying targets for genetically modified crop breeding pipelines. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
BMC Bioinformatics, v. 22, article 46, 2021. |
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DOI: |
https://doi.org/110.1186/s12859-020-03792-z |
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Idioma: |
Inglês |
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Notas: |
Article 46. Na publicação: Adhemar Zerlotini. |
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Conteúdo: |
Abstract. The development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs) are interesting targets for GM crops breeding pipelines for the novelty associated with such targets and also to avoid copyright protection. One method of inferring the putative function of PUFs is by relating them to factors of interest such as abiotic stresses using orthology and co-expression networks, in a guilt-by-association manner. In this regard, we have downloaded, analyzed, and processed genomics data of 53 angiosperms, totaling 1,862,010 genes and 2,332,974 RNA. Diamond and InterproScan were used to discover 72,266 PUFs for all organisms. RNA-seq datasets related to abiotic stresses were downloaded from NCBI/GEO. The RNA-seq data was used as input to the LSTrAP software to construct co-expression networks. LSTrAP also created clusters of transcripts with correlated expression, whose members are more probably related to the molecular mechanisms associated with abiotic stresses in the plants. Orthologous groups were created (OrhtoMCL) using all 2,332,974 proteins in order to associate PUFs to abiotic stress-related clusters of co-expression and therefore infer their function in a guilt-by-association manner. A freely available web resource named "Plant Co-expression Annotation Resource" (https://www.machado.cnptia.embrapa.br/plantannot ), Plantannot, was created to provide indexed queries to search for PUF putatively associated with abiotic stresses. The web interface also allows browsing, querying, and retrieving of public genomics data from 53 plants. We hope Plantannot to be useful for researchers trying to obtain novel GM crops resistant to climate change hazards. MenosAbstract. The development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs) are interesting targets for GM crops breeding pipelines for the novelty associated with such targets and also to avoid copyright protection. One method of inferring the putative function of PUFs is by relating them to factors of interest such as abiotic stresses using orthology and co-expression networks, in a guilt-by-association manner. In this regard, we have downloaded, analyzed, and processed genomics data of 53 angiosperms, totaling 1,862,010 genes and 2,332,974 RNA. Diamond and InterproScan were used to discover 72,266 PUFs for all organisms. RNA-seq datasets related to abiotic stresses were downloaded from NCBI/GEO. The RNA-seq data was used as input to the LSTrAP software to construct co-expression networks. LSTrAP also created clusters of transcripts with correlated expression, whose members are more probably related to the molecular mechanisms associated with abiotic stresses in the plants. Orthologous groups were created (OrhtoMCL) using all 2,332,974 proteins in order to associate PUFs to abiotic stress-related clusters of co-expression and therefore infer their function in a guilt-by-association manner. A freely available web resource named "Plant Co-expression Annotation Resource" (https://www.machado.cnptia.embrapa.br/plantannot ), Plantannot... Mostrar Tudo |
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Palavras-Chave: |
Annotation; Genetic modifed crops; Genetically modifed crop; Plantannot; Proteína de função desconhecida; Proteins of unknown function; Stress abiótico. |
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Thesagro: |
Base de Dados; Proteína. |
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Thesaurus NAL: |
Abiotic stress; Databases. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/221080/1/Plant-co-expression.pdf
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Marc: |
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024 7 $ahttps://doi.org/110.1186/s12859-020-03792-z$2DOI
100 1 $aVIANA, M. J. A.
245 $aPlant Co-expression Annotation Resource$ba web server for identifying targets for genetically modified crop breeding pipelines.$h[electronic resource]
260 $c2021
500 $aArticle 46. Na publicação: Adhemar Zerlotini.
520 $aAbstract. The development of genetically modified crops (GM) includes the discovery of candidate genes through bioinformatics analysis using genomics data, gene expression, and others. Proteins of unknown function (PUFs) are interesting targets for GM crops breeding pipelines for the novelty associated with such targets and also to avoid copyright protection. One method of inferring the putative function of PUFs is by relating them to factors of interest such as abiotic stresses using orthology and co-expression networks, in a guilt-by-association manner. In this regard, we have downloaded, analyzed, and processed genomics data of 53 angiosperms, totaling 1,862,010 genes and 2,332,974 RNA. Diamond and InterproScan were used to discover 72,266 PUFs for all organisms. RNA-seq datasets related to abiotic stresses were downloaded from NCBI/GEO. The RNA-seq data was used as input to the LSTrAP software to construct co-expression networks. LSTrAP also created clusters of transcripts with correlated expression, whose members are more probably related to the molecular mechanisms associated with abiotic stresses in the plants. Orthologous groups were created (OrhtoMCL) using all 2,332,974 proteins in order to associate PUFs to abiotic stress-related clusters of co-expression and therefore infer their function in a guilt-by-association manner. A freely available web resource named "Plant Co-expression Annotation Resource" (https://www.machado.cnptia.embrapa.br/plantannot ), Plantannot, was created to provide indexed queries to search for PUF putatively associated with abiotic stresses. The web interface also allows browsing, querying, and retrieving of public genomics data from 53 plants. We hope Plantannot to be useful for researchers trying to obtain novel GM crops resistant to climate change hazards.
650 $aAbiotic stress
650 $aDatabases
650 $aBase de Dados
650 $aProteína
653 $aAnnotation
653 $aGenetic modifed crops
653 $aGenetically modifed crop
653 $aPlantannot
653 $aProteína de função desconhecida
653 $aProteins of unknown function
653 $aStress abiótico
700 1 $aZERLOTINI NETO, A.
700 1 $aMUDADU, M. de A.
773 $tBMC Bioinformatics$gv. 22, article 46, 2021.
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Embrapa Milho e Sorgo (CNPMS) |
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