ArticleNature communications2023
TRS: a method for determining transcript termini from RNAtag-seq sequencing data.
Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- TerminatorNet: comprehensive identification of intrinsic transcription terminators in bacteria.Bioinformatics (Oxford, England) · 2026Article
- From environmental signals to adaptive phenotypes: signal-responsive regulation and network logic of bacterial small RNAs.FEMS microbiology reviews · 2026Review
- Analysis of 3'-seq data from multiplebioRxiv : the preprint server for biology · 2025Article
- BacTermFinder: a comprehensive and general bacterial terminator finder using a CNN ensemble.NAR genomics and bioinformatics · 2025Article
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Authors and funding
4 authors.
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Abstract
In bacteria, determination of the 3' termini of transcripts plays an essential role in regulation of gene expression, affecting the functionality and stability of the transcript. Several experimental approaches were developed to identify the 3' termini of transcripts, however, these were applied only to a limited number of bacteria and growth conditions. Here we present a straightforward approach to identify 3' termini from widely available RNA-seq data without the need for additional experiments. Our approach relies on the observation that the RNAtag-seq sequencing protocol results in overabundance of reads mapped to transcript 3' termini. We present TRS (Termini by Read Starts), a computational pipeline exploiting this property to identify 3' termini in RNAtag-seq data, and show that the identified 3' termini are highly reliable. Since RNAtag-seq data are widely available for many bacteria and growth conditions, our approach paves the way for studying bacterial transcription termination in an unprecedented scope.
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