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Unravelling the molecular mechanism underlying drought stress response in chickpea via integrated multi-omics analysis

ABSTRACT: Drought stress affects growth and productivity significantly in chickpea. An integrated multi-omics analysis can provide a better molecular-level understanding of drought stress tolerance. In the present study, comparative transcriptome, proteome and metabolome analyses of two chickpea genotypes with contrasting responses to drought stress, ICC 4958 (drought-tolerant, DT) and ICC 1882 (drought-sensitive, DS), was performed to gain insights into the molecular mechanisms underlying drought stress response/tolerance. Pathway enrichment analysis of differentially abundant transcripts and proteins suggested the involvement of glycolysis/gluconeogenesis, galactose metabolism, and starch and sucrose metabolism in the DT genotype. An integrated multi-omics analysis of transcriptome, proteome and metabolome data revealed co-expressed genes, proteins and metabolites involved in phosphatidylinositol signaling, glutathione metabolism and glycolysis/gluconeogenesis pathways, specifically in the DT genotype under drought. These stress-responsive pathways were coordinately regulated by the differentially abundant transcripts, proteins and metabolites to circumvent the drought stress response/tolerance in the DT genotype. The QTL-hotspot associated genes, proteins and transcription factors may further contribute to improved drought tolerance in the DT genotype. Altogether, the multi-omics approach provided an in-depth understanding of stress-responsive pathways and candidate genes involved in drought tolerance in chickpea.

SUBMITTER: Singh V

PROVIDER: S-EPMC10242046 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Project description:Dinanath grass (Pennisetum pedicellatum Trin.) is an extensively grown forage grass known for its significant drought resilience. In order to comprehensively grasp the adaptive mechanism of Dinanath grass in response to water deficient conditions, transcriptomic and metabolomics were applied in the leaves of Dinanath grass exposed to two distinct drought intensities (48-hour and 96-hour). Transcriptomic analysis of Dinanath grass leaves revealed that a total of 218 and 704 genes were differentially expressed under 48- and 96-hour drought conditions, respectively. The genes that were expressed differently (DEGs) and the metabolites that accumulated in response to 48-hour drought stress mainly showed enrichment in the biosynthesis of secondary metabolites, particularly phenolics and flavonoids. Conversely, under 96-hour drought conditions, the enriched pathways predominantly involved lipid metabolism, specifically sterol lipids. In particular, phenylpropanoid pathway and brassinosteroid signaling played a crucial role in drought response to 48- and 96-hour water deficit conditions, respectively. This variation in drought response indicates that the adaptation mechanism in Dinanath grass is highly dependent on the intensity of drought stress. In addition, different genes associated with phenylpropanoid and fatty acid biosynthesis, as well as signal transduction pathways namely phenylalanine ammonia-lyase, putrescine hydroxycinnamoyl transferase, abscisic acid 8'-hydroxylase 2, syntaxin-61, lipoxygenase 5, calcium-dependent protein kinase and phospholipase D alpha one, positively regulated with drought tolerance. Combined transcriptomic and metabolomic analyses highlights the outstanding involvement of regulatory pathways related to secondary cell wall thickening and lignin biosynthesis in imparting drought tolerance to Dinanath grass leaves. These findings collectively contribute to an enhanced understanding of candidate genes and key metabolites relevant to drought response in Dinanath grass. Furthermore, they establish a groundwork for the creation of a transcriptome database aimed at developing abiotic stress-tolerant grasses and major crop varieties through both transgenic and genome editing approaches.

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Unravelling the molecular mechanism underlying drought stress response in chickpea via integrated multi-omics analysis

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