The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index.
Comprehensive identification of RNA–protein interactions in any organism using orthogonal organic phase separation (OOPS)
Open accessAbstract
Existing high-throughput methods to identify RNA-binding proteins (RBPs) are based on capture of polyadenylated RNAs and cannot recover proteins that interact with nonadenylated RNAs, including long noncoding RNA, pre-mRNAs and bacterial RNAs. We present orthogonal organic phase separation (OOPS), which does not require molecular tagging or capture of polyadenylated RNA, and apply it to recover cross-linked protein–RNA and free protein, or protein-bound RNA and free RNA, in an unbiased way. We validated OOPS in HEK293, U2OS and MCF10A human cell lines, and show that 96% of proteins recovered were bound to RNA. We show that all long RNAs can be cross-linked to proteins, and recovered 1,838 RBPs, including 926 putative novel RBPs. OOPS is approximately 100-fold more efficient than existing methods and can enable analyses of dynamic RNA–protein interactions. We also characterize dynamic changes in RNA–protein interactions in mammalian cells following nocodazole arrest, and present a bacterial RNA-interactome for Escherichia coli. OOPS is compatible with downstream proteomics and RNA sequencing, and can be applied in any organism. RNA-binding proteins can be identified and quantified in any organism using a simple method that combines UV cross-linking and phase separation.
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
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
VMD: visual molecular dynamics
Humphrey, W., Dalke, A., & Schulten, K. (1996) · Journal of Molecular Graphics · doi:10.1016/0263-7855(96)00018-5 · Cited by 66,952
Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction
Chomczynski, P., & Sacchi, N. (1987) · Analytical Biochemistry · doi:10.1016/0003-2697(87)90021-2 · Cited by 46,426
HISAT: a fast spliced aligner with low memory requirements
Kim, D., Langmead, B., & Salzberg, S. L. (2015) · Nature Methods · doi:10.1038/nmeth.3317 · Cited by 24,112
ggplot2: Elegant Graphics for Data Analysis
Wickham, H. (2009) · doi:10.1007/978-0-387-98141-3 · Cited by 14,447
Salmon provides fast and bias-aware quantification of transcript expression
Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017) · Nature Methods · doi:10.1038/nmeth.4197 · Cited by 12,700
KEGG: new perspectives on genomes, pathways, diseases and drugs
Kanehisa, M., Furumichi, M., Tanabe, M., Sato, Y., & Morishima, K. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1092 · Cited by 8,865
UniProt: the Universal Protein knowledgebase
Apweiler, R. (2004) · Nucleic Acids Research · doi:10.1093/nar/gkh131 · Cited by 7,498
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
2016 update of the PRIDE database and its related tools
Vizcaíno, J. A., Csordas, A., del-Toro, N., Dianes, J. A., Griss, J., Lavidas, I., Mayer, G., Perez-Riverol, Y., Reisinger, F., Ternent, T., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1145 · Cited by 3,451
Cited by
Spatial proteomics: a powerful discovery tool for cell biology
Lundberg, E., & Borner, G. H. H. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0094-y · Cited by 591
Properties of Stress Granule and P-Body Proteomes
Youn, J.-Y., Dyakov, B. J. A., Zhang, J., Knight, J. D. R., Vernon, R. M., Forman-Kay, J. D., & Gingras, A.-C. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.09.014 · Cited by 445
Transcription factors interact with RNA to regulate genes
Oksuz, O., Henninger, J. E., Warneford-Thomson, R., Zheng, M. M., Erb, H., Vancura, A., Overholt, K. J., Hawken, S. W., Banani, S. F., Lauman, R., et al. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.06.012 · Cited by 275
Qin, W., Myers, S. A., Carey, D. K., Carr, S. A., & Ting, A. Y. (2021) · Nature Communications · doi:10.1038/s41467-021-25259-2 · Cited by 84
Jin, W., Brannan, K. W., Kapeli, K., Park, S. S., Tan, H. Q., Gosztyla, M. L., Mujumdar, M., Ahdout, J., Henroid, B., Rothamel, K., et al. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.06.019 · Cited by 52
Metadata
- Authors
- Queiroz, R. M. L., Smith, T., Villanueva, E., Marti-Solano, M., Monti, M., Pizzinga, M., Mirea, D.-M., Ramakrishna, M., Harvey, R. F., Dezi, V., Thomas, G. H., Willis, A. E., & Lilley, K. S.
- Venue
- Nature Biotechnology
- Published
- 2019-01-03
- Volume
- 37
- Issue
- 2
- Pages
- 169-178
- ISSN
- 0733-222X (ISSN-L)
- 1087-0156
- 1546-1696
- OpenAlex
- W2907992023
- Cited by
- 365
- References
- 89
- FWCI
- 12.25
- 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: Comprehensive identification of RNA–protein interactions in any organism using orthogonal organic phase separation (OOPS). https://app.cochat.ai/papers/10.1038/s41587-018-0001-2
- The paper
- Queiroz, R. M. L., Smith, T., Villanueva, E., Marti-Solano, M., Monti, M., Pizzinga, M., Mirea, D.-M., Ramakrishna, M., Harvey, R. F., Dezi, V., Thomas, G. H., Willis, A. E., & Lilley, K. S. (2019). Comprehensive identification of RNA–protein interactions in any organism using orthogonal organic phase separation (OOPS). Nature Biotechnology. https://doi.org/10.1038/s41587-018-0001-2
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.
