Identifying key information in transcriptomic data is very important, especially when the "omic" study deals with plant responses to stresses in field conditions where a high number of variables and disturbing factors may affect the analysis. In this meta-analysis we collected 12 transcriptomic works in Malus in order to identify which key genes, proteins, gene categories are involved in general plant pathological conditions and those features linked with exclusive biotic stress responses. Those genes that are only related with molecular responses to pathogen attacks and those linked with other plant physiological processes were identified. A pipeline composed by pathway and gene set enrichment analysis, protein-protein interaction networks and gene visualization tools was employed. A total of 13,230 genes of the 12 studies were analyzed with functional data mining tools: 5,215 were upregulated, 8,015 were downregulated. Gene set enrichment analysis pointed out that photosynthesis was inhibited by Erwinia amylovora and fungal pathogens. Different hormonal crosstalk was linked with responses to different pathogens. Gibberellin-related pathways, ABA-related were mostly repressed by fungal pathogens. Relating to transcription factors, genes encoding MYBs and WRKY2 were downregulated by fungal pathogens and 12 WRKYs were commonly regulated by different biotic stresses The protein-protein interaction analysis discovered the presence of several proteins affected by more than one biotic stress including a WRKY40 and some highly interactive proteins such as heat shock proteins. This study represents a first preliminary curated meta-analysis of apple transcriptomic responses to biotic stresses.

Balan, B. (2017). Gaining insight into exclusive and common transcriptomic features linked with biotic stress responses in Malus. FRONTIERS IN PLANT SCIENCE, 8, 1-11 [10.3389/fpls.2017.01569].

Gaining insight into exclusive and common transcriptomic features linked with biotic stress responses in Malus

Balan B;Caruso T;Martinelli F.
2017-01-01

Abstract

Identifying key information in transcriptomic data is very important, especially when the "omic" study deals with plant responses to stresses in field conditions where a high number of variables and disturbing factors may affect the analysis. In this meta-analysis we collected 12 transcriptomic works in Malus in order to identify which key genes, proteins, gene categories are involved in general plant pathological conditions and those features linked with exclusive biotic stress responses. Those genes that are only related with molecular responses to pathogen attacks and those linked with other plant physiological processes were identified. A pipeline composed by pathway and gene set enrichment analysis, protein-protein interaction networks and gene visualization tools was employed. A total of 13,230 genes of the 12 studies were analyzed with functional data mining tools: 5,215 were upregulated, 8,015 were downregulated. Gene set enrichment analysis pointed out that photosynthesis was inhibited by Erwinia amylovora and fungal pathogens. Different hormonal crosstalk was linked with responses to different pathogens. Gibberellin-related pathways, ABA-related were mostly repressed by fungal pathogens. Relating to transcription factors, genes encoding MYBs and WRKY2 were downregulated by fungal pathogens and 12 WRKYs were commonly regulated by different biotic stresses The protein-protein interaction analysis discovered the presence of several proteins affected by more than one biotic stress including a WRKY40 and some highly interactive proteins such as heat shock proteins. This study represents a first preliminary curated meta-analysis of apple transcriptomic responses to biotic stresses.
2017
Balan, B. (2017). Gaining insight into exclusive and common transcriptomic features linked with biotic stress responses in Malus. FRONTIERS IN PLANT SCIENCE, 8, 1-11 [10.3389/fpls.2017.01569].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/286472
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