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INTERPIN: A repository for intrinsic transcription termination hairpins in bacteria

Gupta, S and Padmashali, N and Pal, D (2023) INTERPIN: A repository for intrinsic transcription termination hairpins in bacteria. In: Biochimie .

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Official URL: https://doi.org/10.1016/j.biochi.2023.07.018

Abstract

The large-scale detection of putative intrinsic transcription terminators is limited to only a few bacteria currently. We discovered a group of hairpins, called cluster hairpins, present within 15 nucleotides from each other. These are expected to work in tandem to cause intrinsic transcription termination (ITT), while the single hairpin can do the same alone. Therefore, exploring these ITT sites and the hairpins across bacterial genomes becomes highly desirable. INTERPIN is the largest archived collection of in silico inferred ITT hairpins in bacteria, covering 12745 bacterial genomes and encompassing ten bacterial phyla for �25 million hairpins. Users can obtain details on operons, individual cluster, and single ITT hairpins that were screened therein. Integrated Genome Viewer (IGV) software interactively visualizes hairpin secondary and tertiary structures in the genomic context. We also discuss statistics for the occurrence of cluster or single hairpins and other termination alternatives while showing the validation of predicted hairpins against in vivo detected hairpins. The database is freely available at http://pallab.cds.iisc.ac.in/INTERPIN/. INTERPIN (database and software) can make predictions for both AT and GC-rich genomes, which has not been achieved by any other program so far. It can also be used to improve genome annotation as well as to get predictions to improve the understanding of the ITT pathway by further analysis. © 2023 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM)

Item Type: Journal Article
Publication: Biochimie
Publisher: Elsevier B.V.
Additional Information: The copyright for this article belongs to the Elsevier B.V.
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 28 Oct 2023 05:26
Last Modified: 28 Oct 2023 05:26
URI: https://eprints.iisc.ac.in/id/eprint/83172

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