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Information Journal Paper

Title

Meta-analysis of RNA-seq data of the medicinal plant Catharanthus roseus under some biotic and abiotic stresses

Pages

  209-234

Abstract

 Objective
The objectives of genetic and metabolic engineering can be greatly advanced through comprehending the molecular processes of the Stress response. Researchers may access an abundance of data through transcriptome studies. Using advanced statistical methods such as Meta-analysis to integrate data from many sources offers a new way to find differentially expressed genes (DEGs), get beyond biological complexity, and provide more accurate results. The current work used transcriptome data from RNA-seq meta-analysis to uncover Catharanthus roseus DEGs in response to stressors and the production of important secondary metabolites.
Materials and methods
The EMBL-EBI database provided the RNA-seq data, which was then pre-processed and mapped quality reads using STAR software to the reference genome of C. roseus. Each data set's changes in gene expression were examined independently using the edgeR package, and the output from these analyses was then utilized for a Meta-analysis with the use of the metaRNAseq program. Key genes in reaction to Stress and pathways were finally examined, along with the biological function and biological pathways involved in the different and significant expression of these genes in response to stress. Co-expression analysis was carried out using the WGCNA software and hub genes associated with Stress response and the production of important plant-related metabolites were found.
Results
The findings of the Meta-analysis show that 772 genes with average expression log2FC≥|1 and FDR≤0.05 were found, and that 305 and 467 of these genes, respectively, had up- and downregulated expression under stress. Of these, only a Meta-analysis enables the identification of 27 genes that were not identified as DEGs in individual analyses. The functional enrichment results of DEGs demonstrate their crucial importance in metabolic processes, response to stimuli, and cellular processes. They also lead multiple pathways, such as the MAPK signaling pathway, the biosynthesis of secondary metabolites, the transduction of plant hormones, and metabolic pathways under stress. Through co-expression network analysis, stress-responsive hubs genes and associated with the TIA biosynthesis pathways were found that may be potential genes involved in the synthesis of therapeutic compounds exclusive to plants.
Conclusions
In this study, we identified key and novel genes by investigating the molecular responses of C. roseus plant under various stresses using Meta-analysis and systems biology approaches. These genes have the potential to be employed as candidate genes in genetic and metabolic engineering projects aimed at enhancing the plant's capability to produce therapeutic metabolites in the future.

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