Global transcriptome analysis reveals fungal disease responsive core gene regulatory landscape in tea

Fungal infections are the inevitable limiting factor for productivity of tea. Transcriptome reprogramming recruits multiple regulatory pathways during pathogen infection. A comprehensive meta-analysis was performed utilizing previously reported, well-replicated transcriptomic datasets from seven fun...

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Veröffentlicht in:Scientific reports 2023-10, Vol.13 (1), p.17186-17186, Article 17186
Hauptverfasser: Hazra, Anjan, Ghosh, Sanatan, Naskar, Sudipta, Rahaman, Piya, Roy, Chitralekha, Kundu, Anirban, Chaudhuri, Rituparna Kundu, Chakraborti, Dipankar
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Sprache:eng
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Zusammenfassung:Fungal infections are the inevitable limiting factor for productivity of tea. Transcriptome reprogramming recruits multiple regulatory pathways during pathogen infection. A comprehensive meta-analysis was performed utilizing previously reported, well-replicated transcriptomic datasets from seven fungal diseases of tea. The study identified a cumulative set of 18,517 differentially expressed genes (DEGs) in tea, implicated in several functional clusters, including the MAPK signaling pathway, transcriptional regulation, and the biosynthesis of phenylpropanoids. Gene set enrichment analyses under each pathogen stress elucidated that DEGs were involved in ethylene metabolism, secondary metabolism, receptor kinase activity, and various reactive oxygen species detoxification enzyme activities. Expressional fold change of combined datasets highlighting 2258 meta-DEGs shared a common transcriptomic response upon fungal stress in tea. Pervasive duplication events caused biotic stress-responsive core DEGs to appear in multiple copies throughout the tea genome. The co-expression network of meta-DEGs in multiple modules demonstrated the coordination of appropriate pathways, most of which involved cell wall organization. The functional coordination was controlled by a number of hub genes and miRNAs, leading to pathogenic resistance or susceptibility. This first-of-its-kind meta-analysis of host–pathogen interaction generated consensus candidate loci as molecular signatures, which can be associated with future resistance breeding programs in tea.
ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-023-44163-x