The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
Rho and NusG suppress pervasive antisense transcription in Escherichia coli
Open accessAbstract
Despite the prevalence of antisense transcripts in bacterial transcriptomes, little is known about how their synthesis is controlled. We report that a major function of the Escherichia coli termination factor Rho and its cofactor, NusG, is suppression of ubiquitous antisense transcription genome-wide. Rho binds C-rich unstructured nascent RNA (high C/G ratio) prior to its ATP-dependent dissociation of transcription complexes. NusG is required for efficient termination at minority subsets (∼20%) of both antisense and sense Rho-dependent terminators with lower C/G ratio sequences. In contrast, a widely studied nusA deletion proposed to compromise Rho-dependent termination had no effect on antisense or sense Rho-dependent terminators in vivo. Global colocalization of the histone-like nucleoid-structuring protein (H-NS) with Rho-dependent terminators and genetic interactions between hns and rho suggest that H-NS aids Rho in suppression of antisense transcription. The combined actions of Rho, NusG, and H-NS appear to be analogous to the Sen1–Nrd1–Nab3 and nucleosome systems that suppress antisense transcription in eukaryotes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364
Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources
Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890
Cluster analysis and display of genome-wide expression patterns
Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14863 · Cited by 16,184
Construction of Escherichia coli K‐12 in‐frame, single‐gene knockout mutants: the Keio collection
Baba, T., Ara, T., Hasegawa, M., Takai, Y., Okumura, Y., Baba, M., Datsenko, K. A., Tomita, M., Wanner, B. L., & Mori, H. (2006) · Molecular Systems Biology · doi:10.1038/msb4100050 · Cited by 7,858
affy—analysis of Affymetrix GeneChip data at the probe level
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg405 · Cited by 5,218
Fitting a mixture model by expectation maximization to discover motifs in biopolymers.
Bailey, T. L., & Elkan, C. (1994) · PubMed · Cited by 4,982
SOAP: Short oligonucleotide alignment program
Li, R., Li, Y., Kristiansen, K., & Wang, J. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn025 · Cited by 3,597
Culture Medium for Enterobacteria
Neidhardt, F. C., Bloch, P. L., & Smith, D. F. (1974) · Journal of Bacteriology · doi:10.1128/jb.119.3.736-747.1974 · Cited by 2,958
Carrozza, M. J., Li, B., Florens, L., Suganuma, T., Swanson, S. K., Lee, K. K., Shia, W.-J., Anderson, S., Yates, J., Washburn, M. P., et al. (2005) · Cell · doi:10.1016/j.cell.2005.10.023 · Cited by 1,294
Transcriptome analysis by strand-specific sequencing of complementary DNA
Parkhomchuk, D., Borodina, T., Amstislavskiy, V., Banaru, M., Hallen, L., Krobitsch, S., Lehrach, H., & Soldatov, A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp596 · Cited by 938
Cited by
Thomason, M. K., Bischler, T., Eisenbart, S. K., Förstner, K. U., Zhang, A., Herbig, A., Nieselt, K., Sharma, C. M., & Storz, G. (2015) · Journal of Bacteriology · doi:10.1128/jb.02096-14 · Cited by 335
Universal Molecular Triggers of Stress Responses in Cyanobacterium Synechocystis
Mironov, K., Sinetova, M., Shumskaya, M., & Los, D. (2019) · Life · doi:10.3390/life9030067 · Cited by 56
Sinetova, M. A., & Los, D. A. (2016) · Molecular BioSystems · doi:10.1039/c6mb00551a · Cited by 33
Shen, B. A., Hustmyer, C. M., Roston, D., Wolfe, M. B., & Landick, R. (2022) · iScience · doi:10.1016/j.isci.2022.104429 · Cited by 20
Self-citation
Metadata
- Authors
- Peters, J. M., Mooney, R. A., Grass, J. A., Jessen, E. D., Tran, F., & Landick, R.
- Venue
- Genes & Development
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2012-12-01
- Volume
- 26
- Issue
- 23
- Pages
- 2621-2633
- ISSN
- 0890-9369 (ISSN-L)
- 1549-5477
- OpenAlex
- W2136067498
- Cited by
- 264
- References
- 71
- Type
- posted content
- Language
- en
- Open access
- diamond
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Rho and NusG suppress pervasive antisense transcription in Escherichia coli. https://app.cochat.ai/papers/10.1101/gad.196741.112
- The paper
- Peters, J. M., Mooney, R. A., Grass, J. A., Jessen, E. D., Tran, F., & Landick, R. (2012). Rho and NusG suppress pervasive antisense transcription in Escherichia coli. Genes & Development. https://doi.org/10.1101/gad.196741.112
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
