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Comparative Study
, 13 (8), e0201670
eCollection

Transcriptome and Metabolome Analysis Reveal Candidate Genes and Biochemicals Involved in Tea Geometrid Defense in Camellia Sinensis

Affiliations
Comparative Study

Transcriptome and Metabolome Analysis Reveal Candidate Genes and Biochemicals Involved in Tea Geometrid Defense in Camellia Sinensis

Wei-Wei Wang et al. PLoS One.

Abstract

Tea plant (Camellia sinensis (L) O. Kuntze) respond to herbivore attack through large changes in defense related metabolism and gene expression. Ectropis oblique (Prout) is one of the most devastating insects that feed on tea leaves and tender buds, which can cause severe production loss and deteriorate the quality of tea. To elucidate the biochemicals and molecular mechanism of defense against tea geometrid (TG), transcriptome and metabolome of TG interaction with susceptible (SG) and resistance (RG) tea genotypes were analyzed by using UPLC-Q-TOF-MS, GC-MS, and RNA-seq technologies. This revealed that jasmonic acid was highly induced in RG, following a plethora of secondary metabolites involved in defense against TG could be induced by jasmonic acid signaling pathway. However, the constitutively present of salicylic acid in SG might be a suppressor of jasmonate signaling and thus misdirect tea plants against TG. Furthermore, flavonoids and terpenoids biosynthesis pathways were highly activated in RG to constitute the chemical barrier on TG feeding behavior. In contrast, fructose and theanine, which can act as feeding stimulants were observed to highly accumulate in SG. Being present in the major hub, 39 transcription factors or protein kinases among putative candidates were identified as master regulators from protein-protein interaction network analysis. Together, the current study provides a comprehensive gene expression and metabolite profiles, which can shed new insights into the molecular mechanism of tea defense against TG. The candidate genes and specific metabolites identified in the present study can serve as a valuable resource for unraveling the possible defense mechanism of plants against various biotic stresses.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. KEGG pathway analysis of differentially expressed genes.
The color and size of the dots in the scatterplot represent the range of the negative log10-transformed P-value and the gene number, respectively. The heat map on the right showing the overall expression levels of enriched pathways.
Fig 2
Fig 2. GO enrichment of the genes that showed a higher expression level in RG.
The color of the dots in the scatterplot represents the range of the log10-transformed P-value.
Fig 3
Fig 3. Protein-protein interaction network analysis for the top 2000 genes which showed a higher expression level in RG.
This interaction network for the top 2000 genes which showed a higher expression level in RG was created using STRING. Unconnected genes were removed, and the network was visualized in Cytoscape. The diamond nodes represent TFs, the triangle nodes represent PKs, and the TFs or PKs with more than 10 edges were indicated in red color.
Fig 4
Fig 4. Relative intensity of putative metabolites that influence TG resistance in RG and SG.
Mean expression values of metabolite intensities with their standard error bars from eight biological replicates are represented. The asterisks indicate significant differences between different samples ("*" means P < 0.05; "**" means P < 0.01).

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Publication types

Grant support

This work was supported by the Ministry of Agriculture of China through the Earmarked Fund for China Agriculture Research System (CARS-019), and the Chinese Academy of Agricultural Sciences through the Agricultural Science and Technology Innovation Program (CAAS-ASTIP-2017-TRICAAS) to Liang Chen.
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