ArticleRNA biology2021
PresRAT: a server for identification of bacterial small-RNA sequences and their targets with probable binding region.
Article in RNA biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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9 citing papers in PubMed.
- The long 5' UTR of nrdAB modulates mRNA levels, stability, and virulence in Pseudomonas aeruginosa PAO1.Scientific reports · 2025Article
- sRNAdeep: a novel tool for bacterial sRNA prediction based on DistilBERT encoding mode and deep learning algorithms.BMC genomics · 2024Article
- Characterisation of sRNAs enriched in outer membrane vesicles of pathogenicJournal of extracellular biology · 2024Article
- Investigating the impact of insertion sequences and transposons in the genomes of the most significant phytopathogenic bacteria.Microbial genomics · 2024Article
- Genomic basis of environmental adaptation in the widespread poly-extremophilic Exiguobacterium group.The ISME journal · 2024Article
- Methods for Bioinformatic Prediction of Genuine sRNAs from Outer Membrane Vesicles.Methods in molecular biology (Clifton, N.J.) · 2024Article
- The Fate and Functionality of Alien tRNA Fragments in Culturing Medium and Cells ofInternational journal of molecular sciences · 2023Article
- Intestinal GCN2 controlseLife · 2023Article
- Regulation of biofilm formation by non-coding RNA in prokaryotes.Current research in pharmacology and drug discovery · 2023Review
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3 authors.
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Abstract
Bacterial small-RNA (sRNA) sequences are functional RNAs, which play an important role in regulating the expression of a diverse class of genes. It is thus critical to identify such sRNA sequences and their probable mRNA targets. Here, we discuss new procedures to identify and characterize sRNA and their targets via the introduction of an integrated online platform 'PresRAT'. PresRAT uses the primary and secondary structural attributes of sRNA sequences to predict sRNA from a given sequence or bacterial genome. PresRAT also finds probable target mRNAs of sRNA sequences from a given bacterial chromosome and further concentrates on the identification of the probable sRNA-mRNA binding regions. Using PresRAT, we have identified a total of 66,209 potential sRNA sequences from 292 bacterial genomes and 2247 potential targets from 13 bacterial genomes. We have also implemented a protocol to build and refine 3D models of sRNA and sRNA-mRNA duplex regions and generated 3D models of 50 known sRNAs and 81 sRNA-mRNA duplexes using this platform. Along with the server part, PresRAT also contains a database section, which enlists the predicted sRNA sequences, sRNA targets, and their corresponding 3D models with structural dynamics information.
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