The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Pervasive Chromatin-RNA Binding Protein Interactions Enable RNA-Based Regulation of Transcription
Open accessAbstract
SUMMARY Increasing evidence suggests that transcriptional control and chromatin activities at large involve regulatory RNAs, which likely enlist specific RNA-binding proteins (RBPs). Although multiple RBPs have been implicated in transcription control, it has remained unclear how extensively RBPs directly act on chromatin. We embarked on a large-scale RBP ChIP-seq analysis, revealing widespread RBP presence in active chromatin regions in the human genome. Like transcription factors (TFs), RBPs also show strong preference for hotspots in the genome, particularly gene promoters, where their association is frequently linked to transcriptional output. Unsupervised clustering reveals extensive co-association between TFs and RBPs, as exemplified by YY1, a known RNA-dependent TF, and RBM25, an RBP involved in splicing regulation. Remarkably, RBM25 depletion attenuates all YY1-dependent activities, including chromatin binding, DNA looping, and transcription. We propose that various RBPs may enhance network interaction through harnessing regulatory RNAs to control transcription.
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Self-citationBEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Landscape of transcription in human cells
Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012) · Nature · doi:10.1038/nature11233 · Cited by 5,187
HiC-Pro: an optimized and flexible pipeline for Hi-C data processing.
Servant, N., Varoquaux, N., Lajoie, B. R., Viara, E., Chen, C.-J., Vert, J.-P., Heard, E., Dekker, J., & Barillot, E. (2015) · Genome Biology · doi:10.1186/s13059-015-0831-x · Cited by 2,565 · cited 1×
“” PCA analysis is then applied to 40-kb resolution interaction matrix generated by HiC-Pro (Servant et al., 2015), and regions of continuous positive or negative PC1 values were used for the identification of A or B compartments (Heinz et al.”
MethodWidespread transcription at neuronal activity-regulated enhancers
Kim, T.-K., Hemberg, M., Gray, J. M., Costa, A. M., Bear, D. M., Wu, J., Harmin, D. A., Laptewicz, M., Barbara-Haley, K., Kuersten, S., et al. (2010) · Nature · doi:10.1038/nature09033 · Cited by 2,450
Insights into RNA Biology from an Atlas of Mammalian mRNA-Binding Proteins
Castello, A., Fischer, B., Eichelbaum, K., Horos, R., Beckmann, B. M., Strein, C., Davey, N. E., Humphreys, D. T., Preiss, T., Steinmetz, L. M., et al. (2012) · Cell · doi:10.1016/j.cell.2012.04.031 · Cited by 2,132
A census of human RNA-binding proteins
Gerstberger, S., Hafner, M., & Tuschl, T. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3813 · Cited by 2,032
A large-scale binding and functional map of human RNA-binding proteins
Van Nostrand, E. L., Freese, P., Pratt, G. A., Wang, X., Wei, X., Xiao, R., Blue, S. M., Chen, J.-Y., Cody, N. A. L., Dominguez, D., et al. (2020) · Nature · doi:10.1038/s41586-020-2077-3 · Cited by 1,317
Self-citationCoupling mRNA processing with transcription in time and space
Bentley, D. L. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3662 · Cited by 828
Cohesin and CTCF differentially affect chromatin architecture and gene expression in human cells
Zuin, J., Dixon, J. R., van der Reijden, M. I. J. A., Ye, Z., Kolovos, P., Brouwer, R. W. W., van de Corput, M. P. C., van de Werken, H. J. G., Knoch, T. A., van IJcken, W. F. J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1317788111 · Cited by 779
Transcription factor trapping by RNA in gene regulatory elements
Sigova, A. A., Abraham, B. J., Ji, X., Molinie, B., Hannett, N. M., Guo, Y. E., Jangi, M., Giallourakis, C. C., Sharp, P. A., & Young, R. A. (2015) · Science · doi:10.1126/science.aad3346 · Cited by 492
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Structural basis for inactivation of PRC2 by G-quadruplex RNA
Song, J., Gooding, A. R., Hemphill, W. O., Love, B. D., Robertson, A., Yao, L., Zon, L. I., North, T. E., Kasinath, V., & Cech, T. R. (2023) · Science · doi:10.1126/science.adh0059 · Cited by 73
Enhancers regulate 3′ end processing activity to control expression of alternative 3′UTR isoforms
Kwon, B., Fansler, M. M., Patel, N. D., Lee, J., Ma, W., & Mayr, C. (2022) · Nature Communications · doi:10.1038/s41467-022-30525-y · Cited by 47
Sequential verification of transcription by Integrator and Restrictor
Estell, C., Łazowski, K., Eaton, J. D., & West, S. (2025) · Molecular Cell · doi:10.1016/j.molcel.2025.09.025 · Cited by 16
Korn, S. M., Von Ehr, J., Dhamotharan, K., Tants, J.-N., Abele, R., & Schlundt, A. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24043286 · Cited by 4
Metadata
- Authors
- Xiao, R., Chen, J.-Y., Liang, Z., Luo, D., Chen, G., Lu, Z. J., Chen, Y., Zhou, B., Li, H., Du, X., Yang, Y., San, M., Wei, X., Liu, W., Lécuyer, E., Graveley, B. R., Yeo, G. W., Burge, C. B., Zhang, M. Q., Zhou, Y., & Fu, X.-D.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2019-06
- Volume
- 178
- Issue
- 1
- Pages
- 107-121.e18
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2954785163
- Cited by
- 395
- References
- 13
- FWCI
- 12.75
- Type
- journal article
- Language
- en
- Open access
- bronze
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