Publications of NIPGR Scientists

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Author: search.filters.author.Kumar, ShaileshHas files: No

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    AtFusionDB: A comprehensive database of fusion transcripts in model plant Arabidopsis thaliana
    (Springer Nature Publishing AG, 2026) Shree, Tanu; Kumar, Shailesh
    Fusion 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.
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    Validation of plant fusion peptides using proteomics data
    (Springer Nature Publishing AG, 2026) Hamid, Fiza; Aftab, Sahrish; Shree, Tanu; Kumar, Shailesh
    Fusion 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.
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    The intersection of AI and genomics in health and disease: Advancements and applications
    (Elsevier B.V., 2026) Kaushik, Love; Vivek, A T; Arora, Simran; Hamid, Fiza; Mukherjee, Kanka; Bisht, Niyati; Chaudhary, Sakshi; Shukla, Jagriti; Nawani, Sakshi; Kumar, Shailesh
    AI and genomics are revolutionizing precision medicine by using machine learning (ML) to analyze large-scale next-generation sequencing (NGS) data, identifying genetic mutations and biomarkers for personalized therapies. In practice, this accelerates drug discovery and enhances variant detection, while in cancer genomics, AI enables early detection via liquid biopsies and refines treatment by integrating multi-omics data to improve therapeutic precision. However, challenges such as data biases in underrepresented populations, limited model interpretability, and ethical concerns regarding privacy and algorithmic inequity hinder clinical adoption and demand robust governance. Efforts to diversify datasets also face standardization hurdles, although explainable AI and federated learning provide promising solutions for improving transparency and privacy. In this chapter, we discuss the role of AI in advancing genomics from diagnostics to novel therapies and emphasize the need for equitable frameworks to ensure responsible implementation, thereby paving the way for breakthroughs in personalized medicine.
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    Identification of tRNA-derived fragments in legumes
    (Springer Nature Publishing AG, 2026) Arora, Simran; Aftab, Sahrish; Shree, Tanu; Kumar, Shailesh
    The tRNA-derived noncoding RNAs (tncRNAs) belong to the novel class of noncoding RNAs, acting as important components of genome regulatory circuits. In planta, the mechanism of generation and function of tncRNAs is not fully elucidated. Production of important leguminous plants like chickpea, Medicago and soybean is majorly hampered due to different biotic and abiotic stresses. Identification and characterization of tncRNAs in legumes may open a new paradigm for molecular biologists to make novel tools for the improved varieties of legumes for sustainable agriculture. The first step in the study of tncRNAs is to identify and annotate them in small RNA sequencing datasets. Here, we have demonstrated the tncRNA Toolkit for the identification and annotation of tncRNAs in a small RNA sequencing dataset of the important legume crop chickpea.
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    A protocol for the detection of fusion transcripts using RNA-sequencing data
    (Springer Nature Publishing AG, 2024) Hamid, Fiza; Arora, Simran; Chitkara, Pragya; Kumar, Shailesh
    Fusion transcripts are formed when two genes or their mRNAs fuse to produce a novel gene or chimeric transcript. Fusion genes are well-known cancer biomarkers used for cancer diagnosis and as therapeutic targets. Gene fusions are also found in normal physiology and lead to the evolution of novel genes that contribute to better survival and adaptation for an organism. Various in vitro approaches, such as FISH, PCR, RT-PCR, and chromosome banding techniques, have been used to detect gene fusion. However, all these approaches have low resolution and throughput. Due to the development of high-throughput next-generation sequencing technologies, the detection of fusion transcript becomes feasible using whole genome sequencing, RNA-Seq data, and bioinformatics tools. This chapter will overview the general computational protocol for fusion transcript detection from RNA-sequencing datasets.
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    Identification of virus-derived small interfering RNAs (vsiRNAs) from infected sRNA-Seq samples
    (Springer Nature Publishing AG, 2024) Vivek, A. T.; Kumar, Shailesh
    Plants have developed sophisticated defense mechanisms to combat viral infections, prominently utilizing Dicer-like enzymes (DCL) for generating virus-derived small interfering RNAs (vsiRNAs) through RNA interference (RNAi). This intrinsic mechanism effectively impedes virus replication. Exploiting their potential, vsiRNAs have become a major focus area for comprehensive viral investigations in plants, integrating both bioinformatics and experimental strategies. This chapter introduces an up-to-date computational workflow optimized for identifying and comprehensively annotating vsiRNAs with the utilization of small RNA sequencing (sRNA-seq) data collected from virus-infected plants. The workflow detailed in this chapter centers on known plant-targeting viruses, providing step-by-step guidance to enhance vsiRNA analysis, ultimately advancing the comprehension of plant-virus interactions.
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    In silico identification of tRNA fragments, novel candidates for cancer biomarkers, and therapeutic targets
    (Springer Nature Publishing AG, 2024) Singh, Ankita; Zahra, Shafaque; Arora, Simran; Hamid, Fiza; Kumar, Shailesh
    The identification of a wide variety of RNA molecules using high-throughput sequencing techniques in the transcriptome pool of living organisms has revealed hidden regulatory insights in the cell. The class of non-coding RNA fragments produced from transfer RNA, or tRFs, is one such example. They are heterogeneously sized molecules with lengths ranging between 15 and 50 nt. They have a history of being dysregulated in human malignancies and other illnesses. The detection of these molecules has been made easier by a variety of bioinformatics techniques. The various types of tRFs and how they relate to cancer are covered in this chapter. It also provides a summary of the biological significance of tRFs reported in human cancer. Additionally, it emphasizes the utilities of databases and computational tools that have been created by different research teams for the investigation of tRFs. This will further aid the exploration and analysis of tRFs in cancer research and will support future advancement and a better comprehension of these molecules.
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    Musashi-2 causes cardiac hypertrophy and heart failure by inducing mitochondrial dysfunction through destabilizing Cluh and Smyd1 mRNA
    (Springer Nature Publishing AG, 2023) Singh, Sandhya; Gaur, Aakash; Sharma, Rakesh Kumar; Kumari, Renu; Prakash, Shakti; Kumari, Sunaina; Chaudhary, Ayushi Devendrasingh; Prasun, Pankaj; Pant, Priyanka; Hunkler, Hannah; Thum, Thomas; Jagavelu, Kumaravelu; Bharati, Pragya; Hanif, Kashif; Chitkara, Pragya; Kumar, Shailesh; Mitra, Kalyan; Gupta, Shashi Kumar
    Regulation of RNA stability and translation by RNA-binding proteins (RBPs) is a crucial process altering gene expression. Musashi family of RBPs comprising Msi1 and Msi2 is known to control RNA stability and translation. However, despite the presence of MSI2 in the heart, its function remains largely unknown. Here, we aim to explore the cardiac functions of MSI2. We confirmed the presence of MSI2 in the adult mouse, rat heart, and neonatal rat cardiomyocytes. Furthermore, Msi2 was significantly enriched in the heart cardiomyocyte fraction. Next, using RNA-seq data and isoform-specific PCR primers, we identified Msi2 isoforms 1, 4, and 5, and two novel putative isoforms labeled as Msi2 6 and 7 to be expressed in the heart. Overexpression of Msi2 isoforms led to cardiac hypertrophy in cultured cardiomyocytes. Additionally, Msi2 exhibited a significant increase in a pressure-overload model of cardiac hypertrophy. We selected isoforms 4 and 7 to validate the hypertrophic effects due to their unique alternative splicing patterns. AAV9-mediated overexpression of Msi2 isoforms 4 and 7 in murine hearts led to cardiac hypertrophy, dilation, heart failure, and eventually early death, confirming a pathological function for Msi2. Using global proteomics, gene ontology, transmission electron microscopy, seahorse, and transmembrane potential measurement assays, increased MSI2 was found to cause mitochondrial dysfunction in the heart. Mechanistically, we identified Cluh and Smyd1 as direct downstream targets of Msi2. Overexpression of Cluh and Smyd1 inhibited Msi2-induced cardiac malfunction and mitochondrial dysfunction. Collectively, we show that Msi2 induces hypertrophy, mitochondrial dysfunction, and heart failure.
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    PtRNAdb: a web resource of plant tRNA genes from a wide range of plant species
    (Springer Nature Publishing AG, 2022) Singh, Ajeet; Zahra, Shafaque; Das, Durdam; Kumar, Shailesh
    tRNA, as well as their derived products such as short interspersed nuclear elements (SINEs), pseudogenes, and transfer RNA (tRNA)-derived fragments (tRFs), have now been shown to be vital for cellular life, functioning, and adaptation during different stress conditions in all diverse life forms. In this study, we have developed PtRNAdb (www.nipgr.ac.in/PtRNAdb), a plant-exclusive tRNA database containing 113,849 tRNA gene sequences from phylogenetically diverse plant species. We have analyzed a total of 106 nuclear, 89 plastidial, and 38 mitochondrial genomes of plants by the tRNAscan-SE software package, and after careful curation of the output data, we integrated the data and developed this database. The information about the tRNA gene sequences obtained was further enriched with a consensus sequence-based study of tRNA genes based on their isoacceptors and isodecoders. We have also built covariance models based on the isoacceptors and isodecoders of all the tRNA sequences using the infernal tool. The user can also perform BLAST not only against PtRNAdb entries but also against all the tRNA sequences stored in the PlantRNA database and annotated tRNA genes across the plant kingdom available at NCBI. This resource is believed to be of high utility for plant researchers as well as molecular biologists to carry out further exploration of the plant tRNAome on a wider spectrum, as well as for performing comparative and evolutionary studies related to tRNAs, and their derivatives across all domains of life. Database URL: http://www.nipgr.ac.in/PtRNAdb/
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    In silico methods for the identification of viral-derived small interfering RNAs (vsiRNAs) and their application in plant genomics
    (Springer Nature Publishing AG, 2022) Narayan, Aditya; Zahra, Shafaque; Singh, Ajeet; Kumar, Shailesh
    The current era of high-throughput sequencing (HTS) technology has expedited the detection and diagnosis of viruses and viroids in the living system including plants. HTS data has become vital to study the etiology of the infection caused by both known as well as novel viral elements in planta, and their impact on overall crop health and productivity. Viral-derived small interfering RNAs are generated as a result of defence response by the host via RNAi machinery. They are immensely exploited for performing exhaustive viral investigations in plants using bioinformatics as well as experimental approaches. This chapter briefly presents the basics of virus-derived small interfering RNAs (vsiRNAs) biology in plants and their applications in plant genomics and highlights in silico strategies exploited for virus/viroid detection. It gives a systematic pipeline for vsiRNAs identification using currently available bioinformatics tools and databases. This will surely work as a quick beginner’s recipe for the in silico revelation of plant vsiRNAs as well as virus/viroid diagnosis using high-throughput sequencing data.