Institutional Publications

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Integrative multi-omics analysis widens annotation and functional insights into long non-coding RNAs of Arabidopsis thaliana
(Springer Nature Publishing AG, 2026) Vivek, AT; Kiran, Harikumar; Sahu, Namrata; Kalakoti, Garima; Kumar, Shailesh
Background:- Long non-coding RNAs (lncRNAs) play key roles in regulating plant growth, development, and stress responses. Despite their increasing identification in plant transcriptomes, a systematic characterization of lncRNAs is still lacking, leaving a significant knowledge gap. To address this, we systematically identified and characterized Arabidopsis lncRNAs through integrative analysis of strand-specific RNA sequencing data and multi-omics datasets, revealing their genomic features, regulatory interactions, and evolutionary characteristics. Results:- Using a custom pipeline applied to hundreds of stranded RNA-seq datasets, we assembled a comprehensive catalog of 4,772 intergenic and antisense Arabidopsis lncRNAs. In comparing multiple key features of lncRNAs with those of protein-coding genes, we found that intergenic lncRNAs contain high transposable element-derived fragments and display broader TE diversity. Distinct DNA methylation and histone modification signatures further distinguished lncRNAs from protein-coding genes. We additionally uncovered R-loop connections and associations with sRNAs involved in post-transcriptional regulation and RNA-directed DNA methylation, with a minor subset classified as Pol V–transcribed. Of note, our results revealed lncRNAs mediating stress-responsive cis interactions and others linked to trait-associated loci. Probing further, an experimental evidence resource confirmed small peptide production from multiple lncRNA loci. Extending our investigation, comparative analyses across Brassicaceae species revealed syntenic lncRNAs enriched for shared sequence motifs despite substantial sequence divergence. Conclusions:- This study provides a valuable and extensively annotated catalog of Arabidopsis lncRNAs, revealing their diverse genomic features, regulatory interactions, and evolutionary characteristics. Altogether, our work advocates for multi-omics integrative analysis as a potent strategy to efficiently enhance lncRNA annotation, providing insights into functionality and addressing annotation limitations. Our comprehensive bioinformatic analyses of Arabidopsis lncRNAs pave the way for future functional characterization of these transcripts.
ANNInter: A platform to explore ncRNA-ncRNA interactome of Arabidopsis thaliana
(Elsevier B.V., 2025) Vivek, AT; Sahu, Namrata; Kalakoti, Garima; Kumar, Shailesh
Eukaryotic transcriptomes are remarkably complex, encompassing not only protein-coding RNAs but also an expanding repertoire of noncoding RNAs (ncRNAs). In plants, ncRNA-ncRNA interactions (NNIs) have emerged as pivotal regulators of gene expression, orchestrating development and adaptive responses to stress. Despite their critical roles, the functional significance of NNIs remains poorly understood, largely due to a lack of comprehensive resources. Here, we present ANNInter, a comprehensive platform that integrates computational predictions with experimental datasets to systematically identify and analyze NNIs. The current version catalogs over 90,000 interactions spanning eight categories of sRNA-to-longer ncRNAs, each extensively annotated with interaction types, identification methods, and functional descriptions. The integrated schema and advanced visualization framework in ANNInter enable users to explore intricate interaction networks, providing system-wide insights into ncRNA-mediated regulation. These interaction data provide unparalleled opportunities to uncover the regulatory roles of NNIs in key biological processes such as growth regulation, stress adaptation, and cellular signaling. By providing an extensive, curated repository of computational and degradome-based interaction data, ANNInter will provide a platform to the study of ncRNA biology, elucidating the complex mechanisms of NNIs and supporting the concept of competing endogenous RNAs (ceRNAs) in gene regulation. The platform is freely accessible at https://www.nipgr.ac.in/ANNInter/.
Comprehensive profiling of rRNA-derived small RNAs in Arabidopsis thaliana using rsRNAfinder pipeline
(Elsevier B.V., 2024) Kalakoti, Garima; Vivek, AT; Kamboj, Anshul; Singh, Ajeet; Chakraborty, Srija; Kumar, Shailesh
Ribosomal RNA (rRNA) gives rise to non-random small RNA fragments known as ribosomal-derived small RNAs (rsRNAs), which despite their biological importance, have been relatively understudied in comparison to other short non-coding RNAs. There exists a compelling necessity to develop a methodology for the identification, categorization, and quantification of rsRNAs from small RNA sequencing (sRNA-seq) data sets, considering the unique characteristics of ribosomal RNA (rRNA). To bridge this gap, we introduce 'rsRNAfinder' a specialized pipeline designed within the Snakemake framework. This analytical approach enables robust identification of rsRNAs using sRNA-seq datasets from Arabidopsis thaliana. Our methodology constitutes an integrated bioinformatic pipeline designed for different kinds of analysis.1.sRNA-seq data analysis: It performs in-depth analysis of reference-aligned sRNA-seq data, facilitating rsRNA annotation and quantification.2.Parametric reporting: Our pipeline provides comprehensive reports encompassing key parameters such as rsRNA size distributions, strandedness, genomic origin, and source rRNA origin.3.Illustrative validation: We have demonstrated the utility of our approach by conducting comprehensive rsRNA annotation in Arabidopsis thaliana. This validation reveals unique rsRNAs originating from all rRNA types, each of them distinguished by distinct identity, abundance, and length.

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