Publications of NIPGR Scientists

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Author: search.filters.author.Singh, AjeetSubject: search.filters.subject.Non-coding RNAs

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    Long non-coding RNA and microRNA landscape of two major domesticated cotton species
    (Elsevier B.V., 2023) Singh, Ajeet; AT, Vivek; Gupta, Kanika; Sharma, Shruti; Kumar, Shailesh
    Allotetraploid cotton plants Gossypium hirsutum and Gossypium barbadense have been widely cultivated for their natural, renewable textile fibres. Even though ncRNAs in domesticated cotton species have been extensively studied, systematic identification and annotation of lncRNAs and miRNAs expressed in various tissues and developmental stages under various biological contexts are limited. This influences the comprehension of their functions and future research on these cotton species. Here, we report high confidence lncRNAs and miRNA collection from G. hirsutum accession and G. barbadense accession using large-scale RNA-seq and small RNA-seq datasets incorporated into a user-friendly database, CoNCRAtlas. This database provides a wide range and depth of lncRNA and miRNA annotation based on the systematic integration of extensive annotations such as expression patterns derived from transcriptome data analysis in thousands of samples, as well as multi-omics annotations. We assume this comprehensive resource will accelerate evolutionary and functional studies in ncRNAs and inform future breeding programs for cotton improvement. CoNCRAtlas is accessible at http://www.nipgr.ac.in/CoNCRAtlas/.
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    tncRNA Toolkit: A pipeline for convenient identification of RNA (tRNA)-derived non-coding RNAs
    (Elsevier B.V., 2023) Zahra, Shafaque; Singh, Ajeet; Kumar, Shailesh
    Insights into the eukaryotic gene regulation networks have improved due to the advent of diverse classes of non-coding RNAs. The transfer RNA (tRNA)-derived non-coding RNAs or tncRNAs is a novel class of non-coding RNAs, shown to regulate gene expression at transcription and translation levels. Here, we present a pipeline 'tncRNA Toolkit' for accurately identifying tncRNAs using small RNA sequencing (sRNA-seq) data. Previously, we identified tncRNA in six major angiosperms by utilizing our pipeline and highlighted the significant points regarding their generation and functions. The 'tncRNA Toolkit' is available at the URL: http://www.nipgr.ac.in/tncRNA. The scripts are written in bash and Python3 programming languages. The program can be efficiently run as a standalone command-line tool and installed in any Linux-based Operating System (OS). The user can run this program by providing the input of sRNA-seq data and genome file.The various features of the 'tncRNA Toolkit' are as follows:•Major tncRNA classes identified by this tool include tRF-5, tRF-3, tRF-1, 5'tRH, 3'tRH, and leader tRF. Also, it categorizes miscellaneous tncRNAs as other tRF.•It provides the following information for each identified tncRNA viz. tncRNA class, raw and normalized read count (RPM), read length, progenitor tRNA information (amino acid, anticodon, locus, strand), tncRNA sequence, and tRNA modification sites.•We hope to facilitate quick and reliable tncRNA identification, which will boost the exploration of this novel class of non-coding RNAs and their relevance in the living world, including plants.
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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/