Liu, S. et al. Classification and function of RNA-protein interactions. Wiley Interdiscip. Rev. RNA 11, e1601 (2020).
Li, W. et al. Functional roles of enhancer RNAs for oestrogen-dependent transcriptional activation. Nature 498, 516–520 (2013).
Yang, F. et al. The lncRNA Firre anchors the inactive X chromosome to the nucleolus by binding CTCF and maintains H3K27me3 methylation. Genome Biol. 16, 52 (2015).
Yin, Y. et al. U1 snRNP regulates chromatin retention of noncoding RNAs. Nature 580, 147–150 (2020).
Hentze, M. W., Castello, A., Schwarzl, T. & Preiss, T. A brave new world of RNA-binding proteins. Nat. Rev. Mol. Cell Biol. 19, 327–341 (2018).
Thelen, M. P. & Kye, M. J. The role of RNA binding proteins for local mRNA translation: implications in neurological disorders. Front. Mol. Biosci. 6, 161 (2019).
Li, W., Deng, X. & Chen, J. RNA-binding proteins in regulating mRNA stability and translation: roles and mechanisms in cancer. Semin. Cancer Biol. 86, 664–677 (2022).
Pederson, T. A layperson encounter, on the ‘modified’ RNA world. Proc. Natl Acad. Sci. USA 118, e2110706118 (2021).
Chen, L. L. Towards higher-resolution and in vivo understanding of lncRNA biogenesis and function. Nat Methods 19, 1152–1155 (2022).
García-Mauriño, S. M. et al. RNA binding protein regulation and cross-talk in the control of AU-rich mRNA fate. Front. Mol. Biosci. 4, 71 (2017).
Sanchez de Groot, N. et al. RNA structure drives interaction with proteins. Nat. Commun. 10, 3246 (2019).
Russell, R. RNA misfolding and the action of chaperones. Front. Biosci. 13, 1–20 (2008).
Witten, J. T. & Ule, J. Understanding splicing regulation through RNA splicing maps. Trends Genet. 27, 89–97 (2011).
Quinones-Valdez, G. et al. Regulation of RNA editing by RNA-binding proteins in human cells. Commun. Biol. 2, 19 (2019).
Maziuk, B., Ballance, H. I. & Wolozin, B. Dysregulation of RNA binding protein aggregation in neurodegenerative disorders. Front. Mol. Neurosci. 10, 89 (2017).
Stanley, R. F. & Abdel-Wahab, O. Dysregulation and therapeutic targeting of RNA splicing in cancer. Nat. Cancer 3, 536–546 (2022).
Enguita, F. J. et al. The interplay between lncRNAs, RNA-binding proteins and viral genome during SARS-CoV-2 infection reveals strong connections with regulatory events involved in RNA metabolism and immune response. Theranostics 12, 3946–3962 (2022).
Ramanathan, M., Porter, D. F. & Khavari, P. A. Methods to study RNA-protein interactions. Nat. Methods 16, 225–234 (2019).
Gräwe, C., Stelloo, S., van Hout, F. A. H. & Vermeulen, M. RNA-centric methods: toward the interactome of specific RNA transcripts. Trends Biotechnol. 39, 890–900 (2021).
Garcia-Moreno, M. et al. System-wide profiling of RNA-binding proteins uncovers key regulators of virus infection. Mol. Cell 74, 196–211 (2019).
Huang, R., Han, M., Meng, L. & Chen, X. Transcriptome-wide discovery of coding and noncoding RNA-binding proteins. Proc. Natl Acad. Sci. USA 115, E3879–E3887 (2018).
Bao, X. et al. Capturing the interactome of newly transcribed RNA. Nat. Methods 15, 213–220 (2018).
McHugh, C. A. & Guttman, M. RAP-MS: a method to identify proteins that interact directly with a specific RNA molecule in cells. Methods Mol. Biol. 1649, 473–488 (2018).
Matia-González, A. M., Iadevaia, V. & Gerber, A. P. A versatile tandem RNA isolation procedure to capture in vivo formed mRNA-protein complexes. Methods 118–119, 93–100 (2017).
Zeng, F. et al. A protocol for PAIR: PNA-assisted identification of RNA binding proteins in living cells. Nat. Protoc. 1, 920–927 (2006).
Tsai, B. P., Wang, X., Huang, L. & Waterman, M. L. Quantitative profiling of in vivo-assembled RNA-protein complexes using a novel integrated proteomic approach. Mol. Cell Proteomics 10, M110.007385 (2011).
Ramanathan, M. et al. RNA-protein interaction detection in living cells. Nat. Methods 15, 207–212 (2018).
Tsue, A. F. et al. Oligonucleotide-mediated proximity-interactome mapping (O-MAP): a unified method for RNA-targeted microenvironment-mapping in situ. Nat. Methods 21, 2058–2071 (2024).
Qin, W., Cho, K. F., Cavanagh, P. E. & Ting, A. Y. Deciphering molecular interactions by proximity labeling. Nat. Methods 18, 133–143 (2021).
Weissinger, R., Heinold, L., Akram, S., Jansen, R. P. & Hermesh, O. RNA proximity labeling: a new detection tool for RNA-protein interactions. Molecules 26, 2270 (2021).
Zhang, Z. et al. Capturing RNA-protein interaction via CRUIS. Nucleic Acids Res. 48, e52 (2020).
Li, Y. et al. CBRPP: a new RNA-centric method to study RNA-protein interactions. RNA Biol. 18, 1608–1621 (2021).
Gilbert, C. & Svejstrup, J. Q. RNA immunoprecipitation for determining RNA-protein associations in vivo. Curr. Protoc. Mol. Biol. Chapter 27, Unit 27.4 (2006).
Hafner, M. et al. CLIP and complementary methods. Nat. Rev. Methods Primers 1, 20 (2021).
Hafner, M. et al. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 141, 129–141 (2010).
König, J. et al. iCLIP reveals the function of hnRNP particles in splicing at individual nucleotide resolution. Nat. Struct. Mol. Biol. 17, 909–915 (2010).
Licatalosi, D. D. et al. HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature 456, 464–469 (2008).
Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat. Methods. 13, 508–514 (2016).
Nawaz, A. et al. Serine 970 of RNA helicase MOV10 is phosphorylated and controls unfolding activity and fate of mRNAs targeted for AGO2-mediated. silencing. J. Biol. Chem. 299, 104577 (2023).
Weyn-Vanhentenryck, S. M. et al. HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism. Cell Rep. 6, 1139–1152 (2014).
Zarnegar, B. J. et al. irCLIP platform for efficient characterization of protein-RNA interactions. Nat. Methods 13, 489–492 (2016).
Hinze, F. et al. Expanding the map of protein-RNA interaction sites via cell fusion followed by PAR-CLIP. RNA Biol. 15, 359–368 (2018).
Gu, J. et al. GoldCLIP: gel-omitted ligation-dependent CLIP. Genomics Proteomics Bioinformatics 16, 136–143 (2018).
Porter, D. F. et al. easyCLIP analysis of RNA-protein interactions incorporating absolute quantification. Nat. Commun. 12, 1569 (2021).
McMahon, A. C. et al. TRIBE: hijacking an RNA-editing enzyme to identify cell-specific targets of RNA-binding proteins. Cell 165, 742–753 (2016).
Rahman, R., Xu, W., Jin, H. & Rosbash, M. Identification of RNA-binding protein targets with HyperTRIBE. Nat. Protoc. 13, 1829–1849 (2018).
Seo, K. W. & Kleiner, R. E. Profiling dynamic RNA-protein interactions using small-molecule-induced RNA editing. Nat. Chem. Biol. 19, 1361–1371 (2023).
Johnson, K. L. et al. Revealing protein-protein interactions at the transcriptome scale by sequencing. Mol. Cell. 81, 4091–4103.e9 (2021).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat. Soc. Series B Stat. Methodol. 57, 289–300 (1995).
Gene Ontology Consortium & Aleksander, S. A. et al. The Gene Ontology knowledgebase in 2023. Genetics. 224, iyad031 (2023).
Protter, D. S. W. & Parker, R. Principles and properties of stress granules. Trends Cell Biol. 26, 668–679 (2016).
Caudron-Herger, M., Jansen, R. E., Wassmer, E. & Diederichs, S. RBP2GO: a comprehensive pan-species database on RNA-binding proteins, their interactions and functions. Nucleic Acids Res. 49, D425–D436 (2021).
Cook, K. B., Kazan, H., Zuberi, K., Morris, Q. & Hughes, T. R. RBPDB: a database of RNA-binding specificities. Nucleic Acids Res. 39, D301–D308 (2011).
Giudice, G., Sánchez-Cabo, F., Torroja, C. & Lara-Pezzi, E. ATtRACT-a database of RNA-binding proteins and associated motifs. Database 2016, baw035 (2016).
Ghosh P., Murugavel P. & Sowdhamini R. hRBPome: a central repository of all known human RNA-binding proteins. Preprint at bioRxiv http://biorxiv.org/lookup/doi/10.1101/269043 (2018).
Perez-Perri, J. I. et al. Discovery of RNA-binding proteins and characterization of their dynamic responses by enhanced RNA interactome capture. Nat. Commun. 9, 4408 (2018).
Li, J. H., Liu, S., Zhou, H., Qu, L. H. & Yang, J. H. starBase v2.0: decoding miRNA-ceRNA, miRNA-ncRNA and protein-RNA interaction networks from large-scale CLIP-Seq data. Nucleic Acids Res. 42, D92–D97 (2014).
Mullari, M., Lyon, D., Jensen, L. J. & Nielsen, M. L. Specifying RNA-binding regions in proteins by peptide cross-linking and affinity purification. J. Proteome Res. 16, 2762–2772 (2017).
Castello, A. et al. Comprehensive identification of RNA-binding domains in human cells. Mol. Cell. 63, 696–710 (2016).
Kang, J. et al. RNAInter v4.0: RNA interactome repository with redefined confidence scoring system and improved accessibility. Nucleic Acids Res. 50, D326–D332 (2022).
Masuda, A. et al. CUGBP1 and MBNL1 preferentially bind to 3′ UTRs and facilitate mRNA decay. Sci. Rep. 2, 209 (2012).
Oberstrass, F. C. et al. Structure of PTB bound to RNA: specific binding and implications for splicing regulation. Science. 309, 2054–2057 (2005).
Barabási, A. L. Scale-free networks: a decade and beyond. Science 325, 412–413 (2009).
Van Nostrand, E. L. et al. Author correction: a large-scale binding and functional map of human RNA-binding proteins. Nature 589, E5 (2021).
Ye, H. et al. The SP1-induced long noncoding RNA, LINC00339, promotes tumorigenesis in colorectal cancer via the miR-378a-3p/MED19 axis. Onco. Targets Ther. 13, 11711–11724 (2020).
Yuan, Y., Haiying, G., Zhuo, L., Ying, L. & Xin, H. Long non-coding RNA LINC00339 facilitates the tumorigenesis of non-small cell lung cancer by sponging miR-145 through targeting FOXM1. Biomed. Pharmacother. 105, 707–713 (2018).
Stelzer, G. et al. The GeneCards Suite: from gene data mining to disease genome sequence analyses. Curr. Protoc. Bioinformatics 54, 1.30.1–1.30.33 (2016).
Zhang, W., Xie, M., Shu, M. D., Steitz, J. A. & DiMaio, D. A proximity-dependent assay for specific RNA-protein interactions in intact cells. RNA 22, 1785–1792 (2016).
Kattah, N. H., Kattah, M. G. & Utz, P. J. The U1-snRNP complex: structural properties relating to autoimmune pathogenesis in rheumatic diseases. Immunol. Rev. 233, 126–145 (2010).
Reid, M. A., Dai, Z. & Locasale, J. W. The impact of cellular metabolism on chromatin dynamics and epigenetics. Nat. Cell Biol. 19, 1298–1306 (2017).
Chen, X. et al. PHGDH expression increases with progression of Alzheimer’s disease pathology and symptoms. Cell Metab. 34, 651–653 (2022).
Liang, X. H. et al. Induction of autophagy and inhibition of tumorigenesis by beclin 1. Nature 402, 672–676 (1999).
Tran, S., Fairlie, W. D. & Lee, E. F. BECLIN1: protein structure, function and regulation. Cells 10, 1522 (2021).
Wortel, I. M. N., van der Meer, L. T., Kilberg, M. S. & van Leeuwen, F. N. Surviving stress: modulation of ATF4-mediated stress responses in normal and malignant cells. Trends Endocrinol. Metab. 28, 794–806 (2017).
Danzi, M. C. et al. The effect of Jun dimerization on neurite outgrowth and motif binding. Mol Cell Neurosci. 92, 114–127 (2018).
Zhu, H., Yu, H., Zhou, H., Zhu, W. & Wang, X. Elevated nuclear PHGDH synergistically functions with cMyc to reshape the immune microenvironment of liver cancer. Adv Sci. 10, e2205818 (2023).
Calandrelli, R. et al. Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells. Nat Commun. 14, 6519 (2023).
Soloviev, Z. et al. Structural mass spectrometry decodes domain interaction and dynamics of the full-length Human Histone Deacetylase 2. Biochim Biophys Acta Proteins Proteom. 1870, 140759 (2022).
Jankowsky, E. & Harris, M. E. Specificity and nonspecificity in RNA-protein interactions. Nat. Rev. Mol. Cell Biol. 16, 533–544 (2015).
Xiao, R. et al. Pervasive chromatin-RNA binding protein interactions enable RNA-based regulation of transcription. Cell 178, 107–121 (2019).
Dethoff, E. A. & Weeks, K. M. Effects of refolding on large-scale RNA structure. Biochemistry 58, 3069–3077 (2019).
Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17, 10–12 (2011).
Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics 34, i884–i890 (2018).
O’Leary, N. A. et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 44, D733–D745 (2016).
Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000).
Thomas, P. D. et al. PANTHER: making genome-scale phylogenetics accessible to all. Protein Sci. 31, 8–22 (2022).
Bastian, M., Heymann, S. & Jacomy, M. Gephi: an open source software for exploring and manipulating networks. ICWSM 3, 361–362 (2009).
Shannon, P. et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504 (2003).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell. 38, 576–589 (2010).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2013).
Zhijie Q., Shuanghong, X. & Kara J. Genome-wide mapping of RNA-protein associations via sequencing. Datasets. Gene Expression Omnibus https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE270010 (2025).
Chen, J., Zhao, W., Qi, Z. & Wen, X. Identification of PHGDH protein-assocaited RNAs and their overlap with PRIM-seq derived RNAs through RIP-seq. Datasets. Gene Expression Omnibus https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE270009 (2025).
Qi, Z. PRIMseqTools. Source code. GitHub https://github.com/Zhong-Lab-UCSD/PRIMseqTools.git (2025).
