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| 2. |  | VISCHI FILHO, O. J.; SOUZA, Z. M. de.; SOUZA, G. S. de.; SOUSA, A. C. M. de.; SILVA, R. B.da. Intervalo hídrico ótimo em área de cana-de-açúcar com diferentes ciclos de colheita mecanizada. IRRIGA, Botucatu, v. 1, n. 1, p. 96-108, 2016.| Biblioteca(s): Biblioteca Rui Tendinha. |
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 | Acesso ao texto completo restrito à biblioteca da Biblioteca Rui Tendinha. Para informações adicionais entre em contato com biblioteca@incaper.es.gov.br. |
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Registro Completo |
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Biblioteca(s): |
Biblioteca Rui Tendinha. |
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Data corrente: |
24/06/2019 |
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Data da última atualização: |
24/06/2019 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
- - - |
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Autoria: |
PERON, F. N.; CALLONI, R.; VENTURA, J. A.; FERNANDES, P. M. B. |
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Afiliação: |
UFES; UFGRS; Jose Aires Ventura, Incaper; UFES. |
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Título: |
Bioinformatics approach to the study of the molecular behaviour of mealybug wilt of pineapple. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Acta Horticulturae, 1239, p. 177-184, 2019. |
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DOI: |
10.17660/ActaHortic.2019.1239.22 |
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Idioma: |
Inglês |
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Conteúdo: |
Mealybug wilt of pineapple (MWP) is a disease caused by the Pineapple mealybug wilt-associated virus (PMWaV) complex transmitted by Dysmicoccus brevipes and D. neobrevipes. MWP symptoms are characterized by root dessication, leaf wilting and consequent failure to produce a fruit. The molecular mechanisms involved in the pineapple-PMWaV interaction for MWP symptomatology are still unclear. In this work, mRNAs of asymptomatic and symptomatic pineapple plants were evaluated using Illumina RNA sequencing technology. From a total of 79 million reads per sample, 16,097 genes were identified using STAR aligner and HTseq for paired-end files. Differentially expressed genes (DEGs) between the evaluated groups were estimated using DESeq2 and edgeR, with an FDR cutoff of ≤0.05. A total of 207 DEGs were detected, with 61 upregulated and 146 downregulated in symptomatic plants infected by PMWaV-2. The methodologies improved by the assays presented in this article and the detected DEGs can substantiate further researches with pineapple and the MWP disease. |
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Palavras-Chave: |
Abacaxi. |
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Thesaurus NAL: |
Bioinformatics; DESeq2; EdgeR; Pineapple; PMWaV; STAR; Transcriptomic. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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Marc: |
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001 1021431
005 2019-06-24
008 2019 bl uuuu u00u1 u #d
024 7 $a10.17660/ActaHortic.2019.1239.22$2DOI
100 1 $aPERON, F. N.
245 $aBioinformatics approach to the study of the molecular behaviour of mealybug wilt of pineapple.$h[electronic resource]
260 $c2019
520 $aMealybug wilt of pineapple (MWP) is a disease caused by the Pineapple mealybug wilt-associated virus (PMWaV) complex transmitted by Dysmicoccus brevipes and D. neobrevipes. MWP symptoms are characterized by root dessication, leaf wilting and consequent failure to produce a fruit. The molecular mechanisms involved in the pineapple-PMWaV interaction for MWP symptomatology are still unclear. In this work, mRNAs of asymptomatic and symptomatic pineapple plants were evaluated using Illumina RNA sequencing technology. From a total of 79 million reads per sample, 16,097 genes were identified using STAR aligner and HTseq for paired-end files. Differentially expressed genes (DEGs) between the evaluated groups were estimated using DESeq2 and edgeR, with an FDR cutoff of ≤0.05. A total of 207 DEGs were detected, with 61 upregulated and 146 downregulated in symptomatic plants infected by PMWaV-2. The methodologies improved by the assays presented in this article and the detected DEGs can substantiate further researches with pineapple and the MWP disease.
650 $aBioinformatics
650 $aDESeq2
650 $aEdgeR
650 $aPineapple
650 $aPMWaV
650 $aSTAR
650 $aTranscriptomic
653 $aAbacaxi
700 1 $aCALLONI, R.
700 1 $aVENTURA, J. A.
700 1 $aFERNANDES, P. M. B.
773 $tActa Horticulturae, 1239, p. 177-184, 2019.
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