Publications of NIPGR Scientists

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Author: search.filters.author.Mahtha, Sanjeet KumarHas files: No

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    Metabolomics and molecular physiology perspective for drought and salinity stress tolerance
    (Taylor & Francis Group, 2022) Jadhav, Sagar Sudam; Kumari, Renu; Mahtha, Sanjeet Kumar; Purama, Ravi Kiran; Lamba, Vinita; Yadav, Gitanjali
    Among abiotic stresses, drought and salinity are mainly affecting crop production. Reactive oxygen species are produced during most of abiotic stresses and can damage cellular components. Therefore, plants produce specific antioxidants (e.g. carotenoids, xanthophylls), metabolites (e.g. flavonoids, phenols), osmoregulatory solutes (e.g. proline, sucrose) and thylakoid stabilizing isoprenes. Plant metabolic networks are complex, and excessive demand for these stress-responsive metabolites during abiotic stress is met only by reconfiguring the metabolic network. This chapter mainly discusses drought and salt stress-specific plant metabolomic and molecular responses and gives insights into signaling network involved thereof. Metabolomics combined with conventional breeding approaches (using introgression lines) has proven to be able to map abiotic stress-responsive loci and key candidates. The role of kinases and argonautes and the prospecting of stress-responsive metabolic quantitative trait loci and alleles are also discussed. The importance of amino acid and hormone metabolism and its connection with epigenetics is reviewed.
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    Complex networks reveal biological functions of START domains in rice: Insights from computational systems biology
    (Springer Nature Publishing AG, 2022) Mahtha, Sanjeet Kumar; Citu; Prasad, Abhishek; Yadav, Gitanjali
    With the advancement of high throughput technologies, there has been a massive surge in the omics data generation and there is a growing need to integrate this data gain insights into the patterns that shape biological interactions. Complex networks not only enable representation of such interactions, but also offer a mechanism for visualization and understanding of big data at a systems level. In this work, we use a complex network approach to investigate functions of the plant amplified StAR-related lipid transfer (START) domains in rice. We analyse the data at three levels; namely the transcriptome, proteome, and regulome. Each of these distinct datasets was superimposed after generation of the respective co-expression, protein-protein interaction, and gene regulatory networks for rice START genes, to reveal domain specific features in the family. This work thus serves as a protocol for network-based approaches to understand biological processes of genes and to complement experimental strategy.