Publications of NIPGR Scientists
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Item AtFusionDB: A comprehensive database of fusion transcripts in model plant Arabidopsis thaliana(Springer Nature Publishing AG, 2026) Shree, Tanu; Kumar, ShaileshFusion transcripts are chimeric RNAs, produced by the joining of two different RNAs at the RNA level or as a product of gene fusion at the DNA level. In this era of high-throughput sequencing technologies, it is easy to identify novel molecules like fusion transcripts in different systems. That's because, initially, supposed to be the well-known cancer biomarkers, fusion transcripts are also validated in normal human physiology. In Planta, discrete reports are available, indicating the presence of fusion transcripts but no dedicated web resource is available for the plant-specific fusion transcripts. This chapter describes the first plant-specific database of fusion transcripts, i.e., AtFusionDB ( http://www.nipgr.res.in/AtFusionDB ), which contains the information on fusion transcripts identified in the model plant Arabidopsis thaliana. This database can be exploited to get significant information about gene/transcript fusion in plants.Item Validation of plant fusion peptides using proteomics data(Springer Nature Publishing AG, 2026) Hamid, Fiza; Aftab, Sahrish; Shree, Tanu; Kumar, ShaileshFusion transcripts and their fused protein products are emerging as exciting entities in molecular biology, offering potential applications in diagnostics and therapeutics. These fusion proteins, derived from the translation of fusion transcripts, hold promise as unique biomarkers and targets for intervention. While numerous algorithms exist to identify fusion RNAs, the detection and validation of their protein counterparts through proteomics remains a growing area of research. This challenge is particularly intriguing in plant biology, where fusion events may affect stress responses, development, and adaptation. This chapter provides an accessible and practical workflow for validating plant fusion peptides using publicly available proteomics datasets.Item 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, ShaileshBackground:- 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.Item ANNInter: A platform to explore ncRNA-ncRNA interactome of Arabidopsis thaliana(Elsevier B.V., 2025) Vivek, AT; Sahu, Namrata; Kalakoti, Garima; Kumar, ShaileshEukaryotic 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/.Item 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, ShaileshRibosomal 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.Item AtFusionDB: a database of fusion transcripts in Arabidopsis thaliana(Oxford University Press, 2019) Singh, Ajeet; Zahra, Shafaque; Das, Durdam; Kumar, ShaileshFusion transcripts are chimeric RNAs generated as a result of fusion either at DNA or RNA level. These novel transcripts have been extensively studied in the case of human cancers but still remain underexamined in plants. In this study, we introduce the first plant-specific database of fusion transcripts named AtFusionDB (http://www. nipgr.res.in/AtFusionDB). This is a comprehensive database that contains the detailed information about fusion transcripts identified in model plant Arabidopsis thaliana. A total of 82 969 fusion transcript entries generated from 17 181 different genes of A. thaliana are available in this database. Apart from the basic information consisting of the Ensembl gene names, official gene name, tissue type, EricScore, fusion type, AtFusionDB ID and sample ID (e.g. Sequence Read Archive ID), additional information like UniProt, gene coordinates (together with the function of parental genes), junction sequence, expression level of both parent genes and fusion transcript may be of high utility to the user. Two different types of search modules viz. ‘Simple Search’ and ‘Advanced Search’ in addition to the ‘Browse’ option with data download facility are provided in this database. Three different modules for mapping and alignment of the query sequences viz. BLASTN, SW Align and Mapping are incorporated in AtFusionDB. This database is a head start for exploring the complex and unexplored domain of gene/transcript fusion in plants. Database URL: http://www.nipgr.res.in/AtFusionDB