Publications of NIPGR Scientists

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Start date: 2020Subject: search.filters.subject.RNA-seq

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    AraNSdb: a dedicated database of stress-responsive non-coding RNAs in Arabidopsis thaliana
    (Springer Nature Publishing AG, 2026) Vivek, A.T.; Bhatia, Manika; Sahu, Namrata; Kalakoti, Garima; Kaushik, Love; Mukherjee, Kanka; Kumar, Shailesh
    Plants, as sessile organisms, are constantly exposed to biotic and abiotic stresses, making their ability to respond crucial for survival. Non-coding RNAs (ncRNAs) have emerged as key regulators in these stress responses, with several studies identifying numerous stress-responsive ncRNAs (SRNs). However, a comprehensive collection of SRNs derived from sequencing data in Arabidopsis thaliana has been lacking. To address this, we utilized high-throughput experimental data and mined published studies to construct AraNSdb (Arabidopsis ncRNA Stress Database), a systematic resource for storing and querying SRNs. AraNSdb documents over 1,000 expression profiles from diverse stress datasets, encompassing 6,616 SRNs, including microRNAs (miRNAs), small interfering RNAs (siRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). The database features an intuitive web interface for exploring SRNs associated with specific stress types and provides detailed ncRNA annotations to support functional and regulatory studies. AraNSdb offers a valuable platform for advancing our understanding of ncRNA-mediated stress responses and is freely accessible at http://www.nipgr.ac.in/AraNSdb.
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    Comparative transcriptome profiling of two contrasting foxtail millet cultivars provides insights into molecular mechanisms underlying dehydration stress response
    (Springer Nature Publishing AG, 2023) Muthamilarasan, Mehanathan; Suresh, Bonthala Venkata; Singh, Roshan Kumar; Choudhary, Pooja; Aggarwal, Pooja Rani; Prasad, Manoj
    Foxtail millet (Setaria italica L.) has emerged as a model system to understand its adaptation to environmental stresses in the past decade. However, studies on understanding the molecular mechanism underlying the adaptation to dehydration stress and the regulatory network involved in the process remain elusive. In the present study, RNA-seq was performed during dehydration stress in the tolerant (IC4) and sensitive (IC41) cultivars at different time points (0, 6, and 12 h). A total of 2467 and 3318 differentially expressed genes (DEGs) were identified in IC4, and 2535 and 5572 in IC41 at 6 h and 12 h compared to control (0 h), respectively. Gene ontology (GO) analysis revealed that the DEGs were enriched in water transport, response to water deprivation, oxidative stress, amino acid and sugar transport, lipid biosynthesis, and regulation of stomatal opening. Pathway analysis suggested a significant modulation of genes involved in the metabolism of glutathione and tryptophan and biosynthesis of flavonoid, ascorbate, arginine, and proline in IC4 compared to IC41. Genes encoding for DIVARICATA, SBP family protein (teosinte glume architecture 1), and SRS family proteins (LATERAL ROOT PRIMORDIUM 1 and SHI-RELATED SEQUENCE 1) were found to be exclusively upregulated in IC4 during dehydration stress. Gene co-expression networks constructed based on the expression data showed the key modules and hubs that play critical roles during dehydration stress. Altogether, the present study has identified key genes, pathways, and regulatory modules that would serve as a base for further studies to gain insights into the dehydration-responsive molecular circuitry in foxtail millet.
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    Root hair-specific transcriptome reveals response to low phosphorus in Cicer arietinum
    (Frontiers Media S.A., 2022) Kohli, Pawandeep Singh; Pazhamala, Lekha T; Mani, Balaji; Thakur, Jitendra K.; Giri, Jitender
    Root hairs (RH) are a single-cell extension of root epidermal cells. In low phosphorus (LP) availability, RH length and density increase thus expanding the total root surface area for phosphate (Pi) acquisition. However, details on genes involved in RH development and response to LP are missing in an agronomically important leguminous crop, chickpea. To elucidate this response in chickpea, we performed tissue-specific RNA-sequencing and analyzed the transcriptome modulation for RH and root without RH (Root-RH) under LP. Root hair initiation and cellular differentiation genes like RSL TFs and ROPGEFs are upregulated in Root-RH, explaining denser, and ectopic RH in LP. In RH, genes involved in tip growth processes and phytohormonal biosynthesis like cell wall synthesis and loosening (cellulose synthase A catalytic subunit, CaEXPA2, CaGRP2, and CaXTH2), cytoskeleton/vesicle transport, and ethylene biosynthesis are upregulated. Besides RH development, genes involved in LP responses like lipid and/or pectin P remobilization and acid phosphatases are induced in these tissues summarizing a complete molecular response to LP. Further, RH displayed preferential enrichment of processes involved in symbiotic interactions, which provide an additional benefit during LP. In conclusion, RH shows a multi-faceted response that starts with molecular changes for epidermal cell differentiation and RH initiation in Root-RH and later induction of tip growth and various LP responses in elongated RH.
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    Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq
    (Oxford University Press, 2021) Vivek, A.T.; Kumar, Shailesh
    Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.