4.7 Article

Transcriptomic characterization of Trichoderma harzianum T34 primed tomato plants: assessment of biocontrol agent induced host specific gene expression and plant growth promotion

Journal

BMC PLANT BIOLOGY
Volume 23, Issue 1, Pages -

Publisher

BMC
DOI: 10.1186/s12870-023-04502-6

Keywords

Trichoderma; Microarray; Transcriptional reprogramming; FDR correction; WCGNA analysis; DNA motif; Bottleneck genes; Hub genes

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In this study, the complex interaction between Trichoderma and the tomato genome was investigated, revealing transcriptional and metabolic changes triggered by Trichoderma colonization. Gene expression profile analysis identified differentially expressed significant genes, showing a positive correlation between the host and Trichoderma. Several genes were found to be consistently significant, with some showing upregulated expression and others downregulated expression during Trichoderma-tomato interaction. Transcription factors related to systemic defense and flowering were also differentially expressed. Protein-protein interaction network analysis and Weighted Correlation Gene Network Analysis further revealed the genes associated with carbohydrate metabolism, secondary metabolite biosynthesis, and nitrogen metabolism. Overall, this study highlights the importance of Trichoderma-induced microbial priming in reprogramming the host genome for transcriptional response and understanding the complex regulatory networks in beneficial microbial interactions.
In this study, we investigated the intricate interplay between Trichoderma and the tomato genome, focusing on the transcriptional and metabolic changes triggered during the late colonization event. Microarray probe set (GSE76332) was utilized to analyze the gene expression profiles changes of the un-inoculated control (tomato) and Trichoderma-tomato interactions for identification of the differentially expressed significant genes. Based on principal component analysis and R-based correlation, we observed a positive correlation between the two cross-comaparable groups, corroborating the existence of transcriptional responses in the host triggered by Trichoderma priming. The statistically significant genes based on different p-value cut-off scores [(p(adj)-values or q-value); p(adj)-value < 0.05], [(p(cal)-values); p(cal)-value < 0.05; p(cal) < 0.01; p(cal) < 0.001)] were cross compared. Through cross-comparison, we identified 156 common genes that were consistently significant across all probability thresholds, and showing a strong positive corelation between p-value and q-value in the selected probe sets. We reported TD2, CPT1, pectin synthase, EXT-3 (extensin-3), Lox C, and pyruvate kinase (PK), which exhibited upregulated expression, and Glb1 and nitrate reductase (nii), which demonstrated downregulated expression during Trichoderma-tomato interaction. In addition, microbial priming with Trichoderma resulted into differential expression of transcription factors related to systemic defense and flowering including MYB13, MYB78, ERF2, ERF3, ERF5, ERF-1B, NAC, MADS box, ZF3, ZAT10, A20/AN1, polyol sugar transporter like zinc finger proteins, and a novel plant defensin protein. The potential bottleneck and hub genes involved in this dynamic response were also identified. The protein-protein interaction (PPI) network analysis based on 25 topmost DEGS (pcal-value < 0.05) and the Weighted Correlation Gene Network Analysis (WGCNA) of the 1786 significant DEGs (pcal-value < 0.05) we reported the hits associated with carbohydrate metabolism, secondary metabolite biosynthesis, and the nitrogen metabolism. We conclude that the Trichoderma-induced microbial priming re-programmed the host genome for transcriptional response during the late colonization event and were characterized by metabolic shifting and biochemical changes specific to plant growth and development. The work also highlights the relevance of statistical parameters in understanding the gene regulatory dynamics and complex regulatory networks based on differential expression, co-expression, and protein interaction networks orchestrating the host responses to beneficial microbial interactions.

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