The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Induced ncRNAs allosterically modify RNA-binding proteins in cis to inhibit transcription
Open accessAbstract
With the recent recognition of non-coding RNAs (ncRNAs) flanking many genes, a central issue is to obtain a full understanding of their potential roles in regulated gene transcription programmes, possibly through different mechanisms. Here we show that an RNA-binding protein, TLS (for translocated in liposarcoma), serves as a key transcriptional regulatory sensor of DNA damage signals that, on the basis of its allosteric modulation by RNA, specifically binds to and inhibits CREB-binding protein (CBP) and p300 histone acetyltransferase activities on a repressed gene target, cyclin D1 (CCND1) in human cell lines. Recruitment of TLS to the CCND1 promoter to cause gene-specific repression is directed by single-stranded, low-copy-number ncRNA transcripts tethered to the 5′ regulatory regions of CCND1 that are induced in response to DNA damage signals. Our data suggest that signal-induced ncRNAs localized to regulatory regions of transcription units can act cooperatively as selective ligands, recruiting and modulating the activities of distinct classes of RNA-binding co-regulators in response to specific signals, providing an unexpected ncRNA/RNA-binding protein-based strategy to integrate transcriptional programmes.
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
Rosenfeld, M. G., Lunyak, V. V., & Glass, C. K. (2006) · Genes & Development · doi:10.1101/gad.1424806 · Cited by 952
Feng, J., Bi, C., Clark, B. S., Mady, R., Shah, P., & Kohtz, J. D. (2006) · Genes & Development · doi:10.1101/gad.1416106 · Cited by 712
Hicks, G. G., Singh, N., Nashabi, A., Mai, S., Bozek, G., Klewes, L., Arapovic, D., White, E. K., Koury, M. J., Oltz, E. M., et al. (2000) · Nature Genetics · doi:10.1038/72842 · Cited by 299 · cited 1×
“S5b), while the N-terminus (1-211) interacted with CBP (Fig.”
Background
Cited by
Long non-coding RNAs: insights into functions
Mercer, T. R., Dinger, M. E., & Mattick, J. S. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2521 · Cited by 5,654
Evolution and Functions of Long Noncoding RNAs
Ponting, C. P., Oliver, P. L., & Reik, W. (2009) · Cell · doi:10.1016/j.cell.2009.02.006 · Cited by 4,208
Mechanisms underlying inflammation in neurodegeneration
Glass, C. K., Saijo, K., Winner, B., Marchetto, M. C., & Gage, F. H. (2010) · Cell · doi:10.1016/j.cell.2010.02.016 · Cited by 3,580
Self-citationLong non-coding RNAs: new players in cell differentiation and development
Fatica, A., & Bozzoni, I. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3606 · Cited by 2,980
Long Noncoding RNAs: Cellular Address Codes in Development and Disease
Batista, P. J., & Chang, H. Y. (2013) · Cell · doi:10.1016/j.cell.2013.02.012 · Cited by 2,531
Metadata
- Authors
- Wang, X., Arai, S., Song, X., Reichart, D., Du, K., Pascual, G., Tempst, P., Rosenfeld, M. G., Glass, C. K., & Kurokawa, R.
- Venue
- Nature
- Published
- 2008-05-28
- Volume
- 454
- Issue
- 7200
- Pages
- 126-130
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2088017477
- Cited by
- 988
- References
- 3
- FWCI
- 16.37
- Type
- journal article
- Language
- en
- Open access
- green
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: Induced ncRNAs allosterically modify RNA-binding proteins in cis to inhibit transcription. https://app.cochat.ai/papers/10.1038/nature06992
- The paper
- Wang, X., Arai, S., Song, X., Reichart, D., Du, K., Pascual, G., Tempst, P., Rosenfeld, M. G., Glass, C. K., & Kurokawa, R. (2008). Induced ncRNAs allosterically modify RNA-binding proteins in cis to inhibit transcription. Nature. https://doi.org/10.1038/nature06992
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.