ArticleRNA biology2017
Genome-wide identification and characterization of small RNAs in Rhodobacter capsulatus and identification of small RNAs affected by loss of the response regulator CtrA.
Article in RNA biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 16 citations in OpenAlex.
- An antisense RNA regulates production of DnaA and affects sporulation in Bacillus subtilis.PLoS genetics · 2025Article
- BacTermFinder: a comprehensive and general bacterial terminator finder using a CNN ensemble.NAR genomics and bioinformatics · 2025Article
- Selective extracellular secretion of small double-stranded RNA by Tetragenococcus halophilus.Functional & integrative genomics · 2022Article
- Prediction of Bacterial sRNAs Using Sequence-Derived Features and Machine Learning.Bioinformatics and biology insights · 2022Article
- sRNARFTarget: a fast machine-learning-based approach for transcriptome-wide sRNA target prediction.RNA biology · 2022Article
- Small regulatory RNAs of oral streptococci and periodontal bacteria.The Japanese dental science review · 2021Review
- Article
- An sRNA and Cold Shock Protein Homolog-Based Feedforward Loop Post-transcriptionally Controls Cell Cycle Master Regulator CtrA.Frontiers in microbiology · 2018Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small non-coding RNAs (sRNAs) are involved in the control of numerous cellular processes through various regulatory mechanisms, and in the past decade many studies have identified sRNAs in a multitude of bacterial species using RNA sequencing (RNA-seq). Here, we present the first genome-wide analysis of sRNA sequencing data in Rhodobacter capsulatus, a purple nonsulfur photosynthetic alphaproteobacterium. Using a recently developed bioinformatics approach, sRNA-Detect, we detected 422 putative sRNAs from R. capsulatus RNA-seq data. Based on their sequence similarity to sRNAs in a sRNA collection, consisting of published putative sRNAs from 23 additional bacterial species, and RNA databases, the sequences of 124 putative sRNAs were conserved in at least one other bacterial species; and, 19 putative sRNAs were assigned a predicted function. We bioinformatically characterized all putative sRNAs and applied machine learning approaches to calculate the probability of a nucleotide sequence to be a bona fide sRNA. The resulting quantitative model was able to correctly classify 95.2% of sequences in a validation set. We found that putative cis-targets for antisense and partially overlapping sRNAs were enriched with protein-coding genes involved in primary metabolic processes, photosynthesis, compound binding, and with genes forming part of macromolecular complexes. We performed differential expression analysis to compare the wild type strain to a mutant lacking the response regulator CtrA, an important regulator of gene expression in R. capsulatus, and identified 18 putative sRNAs with differing levels in the two strains. Finally, we validated the existence and expression patterns of four novel sRNAs by Northern blot analysis.
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