Abstract
The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNAÂ structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.
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References
Hingerty, B., Brown, R. S. & Jack, A. Further refinement of the structure of yeast tRNAPhe. J. Mol. Biol. 124, 523â534 (1978).
Chen, Y. & Pollack, L. SAXS studies of RNA: structures, dynamics, and interactions with partners. Wiley Interdiscip. Rev. RNA 7, 512â526 (2016).
Dagenais, P., Desjardins, G. & Legault, P. An integrative NMRâSAXS approach for structural determination of large RNAs defines the substrate-free state of a trans-cleaving Neurospora Varkud Satellite ribozyme. Nucleic Acids Res. 49, 11959â11973 (2021).
Cheong, C. & Moore, P. B. Solution structure of an unusually stable RNA tetraplex containing G- and U-quartet structures. Biochemistry 31, 8406â8414 (1992).
Barnwal, R. P., Yang, F. & Varani, G. Applications of NMR to structure determination of RNAs large and small. Arch. Biochem. Biophys. 628, 42â56 (2017).
Gabashvili, I. S. et al. Solution structure of the E. coli 70S ribosome at 11.5âà resolution. Cell 100, 537â549 (2000).
Wrede, P., Wurst, R., Vournakis, J. & Rich, A. Conformational changes of yeast tRNAPhe and E. coli tRNA2Glu as indicated by different nuclease digestion patterns. J. Biol. Chem. 254, 9608â9616 (1979).
Wurst, R. M., Vournakis, J. N. & Maxam, A. M. Structure mapping of 5â²-32P-labeled RNA with S1 nuclease. Biochemistry 17, 4493â4499 (1978).
Lockard, R. E. & Kumar, A. Mapping tRNA structure in solution using double-strand-specific ribonuclease V1 from cobra venom. Nucleic Acids Res. 9, 5125â5140 (1981).
Lempereur, L. et al. Conformation of yeast 18S rRNA. Direct chemical probing of the 5â² domain in ribosomal subunits and in deproteinized RNA by reverse transcriptase mapping of dimethyl sulfate-accessible. Nucleic Acids Res. 13, 8339â8357 (1985).
Merino, E. J., Wilkinson, K. A., Coughlan, J. L. & Weeks, K. M. RNA structure analysis at single nucleotide resolution by selective 2â²-hydroxyl acylation and primer extension (SHAPE). J. Am. Chem. Soc. 127, 4223â4231 (2005).
Wan, Y., Kertesz, M., Spitale, R. C., Segal, E. & Chang, H. Y. Understanding the transcriptome through RNA structure. Nat. Rev. Genet. 12, 641â655 (2011).
Kertesz, M. et al. Genome-wide measurement of RNA secondary structure in yeast. Nature 467, 103â107 (2010).
Underwood, J. G. et al. FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing. Nat. Methods 7, 995â1001 (2010).
Rouskin, S., Zubradt, M., Washietl, S., Kellis, M. & Weissman, J. S. Genome-wide probing of RNA structure reveals active unfolding of mRNA structures in vivo. Nature 505, 701â705 (2014).
Ding, Y. et al. In vivo genome-wide profiling of RNA secondary structure reveals novel regulatory features. Nature 505, 696â700 (2014).
Wan, Y. et al. Landscape and variation of RNA secondary structure across the human transcriptome. Nature 505, 706â709 (2014).
Homan, P. J. et al. Single-molecule correlated chemical probing of RNA. Proc. Natl Acad. Sci. USA 111, 13858â13863 (2014).
Spitale, R. C. & Incarnato, D. Probing the dynamic RNA structurome and its functions. Nat. Rev. Genet. 24, 178â196 (2023).
Strobel, E. J., Yu, A. M. & Lucks, J. B. High-throughput determination of RNA structures. Nat. Rev. Genet. 19, 615â634 (2018).
Corley, M. et al. Footprinting SHAPE-eCLIP reveals transcriptome-wide hydrogen bonds at RNAâprotein interfaces. Mol. Cell 80, 903â914.e8 (2020).
Lee, B. et al. Comparison of SHAPE reagents for mapping RNA structures inside living cells. RNA 23, 169â174 (2017).
Spitale, R. C. et al. RNA SHAPE analysis in living cells. Nat. Chem. Biol. 9, 18â20 (2013).
Marinus, T., Fessler, A. B., Ogle, C. A. & Incarnato, D. A novel SHAPE reagent enables the analysis of RNA structure in living cells with unprecedented accuracy. Nucleic Acids Res. 49, e34 (2021).
Siegfried, N. A., Busan, S., Rice, G. M., Nelson, J. A. & Weeks, K. M. RNA motif discovery by SHAPE and mutational profiling (SHAPE-MaP). Nat. Methods 11, 959â965 (2014).
Zubradt, M. et al. DMS-MaPseq for genome-wide or targeted RNA structure probing in vivo. Nat. Methods 14, 75â82 (2017).
Aviran, S. & Incarnato, D. Computational approaches for RNA structure ensemble deconvolution from structure probing data. J. Mol. Biol. 434, 167635 (2022).
Busan, S., Weidmann, C. A., Sengupta, A. & Weeks, K. M. Guidelines for SHAPE reagent choice and detection strategy for RNA structure probing studies. Biochemistry 58, 2655â2664 (2019).
Guo, L. T. et al. Sequencing and structure probing of long RNAs using MarathonRT: a next-generation reverse transcriptase. J. Mol. Biol. 432, 3338â3352 (2020).
Mitchell, D., Cotter, J., Saleem, I. & Mustoe, A. M. Mutation signature filtering enables high-fidelity RNA structure probing at all four nucleobases with DMS. Nucleic Acids Res. 51, 8744â8757 (2023).
Smola, M. J., Rice, G. M., Busan, S., Siegfried, N. A. & Weeks, K. M. Selective 2â²-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP) for direct, versatile and accurate RNA structure analysis. Nat. Protoc. 10, 1643â1669 (2015).
Liu, Z. et al. In vivo nuclear RNA structurome reveals RNA-structure regulation of mRNA processing in plants. Genome Biol. 22, 11 (2021).
Sun, L. et al. RNA structure maps across mammalian cellular compartments. Nat. Struct. Mol. Biol. 26, 322â330 (2019).
Yamagami, R., Sieg, J. P., Assmann, S. M. & Bevilacqua, P. C. Genome-wide analysis of the in vivo tRNA structurome reveals RNA structural and modification dynamics under heat stress. Proc. Natl Acad. Sci. USA 119, e2201237119 (2022).
Yang, M. et al. Intact RNA structurome reveals mRNA structure-mediated regulation of miRNA cleavage in vivo. Nucleic Acids Res. 48, 8767â8781 (2020).
Watters, K. E., Strobel, E. J., Yu, A. M., Lis, J. T. & Lucks, J. B. Cotranscriptional folding of a riboswitch at nucleotide resolution. Nat. Struct. Mol. Biol. 23, 1124â1131 (2016).
Incarnato, D. et al. In vivo probing of nascent RNA structures reveals principles of cotranscriptional folding. Nucleic Acids Res. 45, 9716â9725 (2017).
Saldi, T., Riemondy, K., Erickson, B. & Bentley, D. L. Alternative RNA structures formed during transcription depend on elongation rate and modify RNA processing. Mol. Cell 81, 1789â1801.e5 (2021).
Yu, G. et al. Genome-wide probing of eukaryotic nascent RNA structure elucidates cotranscriptional folding and its antimutagenic effect. Nat. Commun. 14, 5853 (2023).
Yang, M. et al. In vivo single-molecule analysis reveals COOLAIR RNA structural diversity. Nature 609, 394â399 (2022).
Bohn, P., Gribling-Burrer, A. S., Ambi, U. B. & Smyth, R. P. Nano-DMS-MaP allows isoform-specific RNA structure determination. Nat. Methods 20, 849â859 (2023).
Aw, J. G. A. et al. Determination of isoform-specific RNA structure with nanopore long reads. Nat. Biotechnol. 39, 336â346 (2021).
Bevilacqua, P. C., Ritchey, L. E., Su, Z. & Assmann, S. M. Genome-wide analysis of RNA secondary structure. Annu. Rev. Genet. 50, 235â266 (2016).
Wan, Y., Qu, K., Ouyang, Z. & Chang, H. Y. Genome-wide mapping of RNA structure using nuclease digestion and high-throughput sequencing. Nat. Protoc. 8, 849â869 (2013).
Mortimer, S. A. & Weeks, K. M. Time-resolved RNA SHAPE chemistry: quantitative RNA structure analysis in one-second snapshots and at single-nucleotide resolution. Nat. Protoc. 4, 1413â1421 (2009).
Rabin, D. & Crothers, D. M. Analysis of RNA secondary structure by photochemical reversal of psoralen crosslinks. Nucleic Acids Res. 7, 689â703 (1979).
Cordero, P., Kladwang, W., VanLang, C. C. & Das, R. The mutate-and-map protocol for inferring base pairs in structured RNA. Methods Mol. Biol. 1086, 53â77 (2014).
Lu, Z. et al. RNA duplex map in living cells reveals higher-order transcriptome structure. Cell 165, 1267â1279 (2016).
Aw, J. G. A. et al. In vivo mapping of eukaryotic RNA interactomes reveals principles of higher-order organization and regulation. Mol. Cell 62, 603â617 (2016).
Sharma, E., Sterne-Weiler, T., OâHanlon, D. & Blencowe, B. J. Global mapping of human RNAâRNA interactions. Mol. Cell 62, 618â626 (2016).
Ziv, O. et al. COMRADES determines in vivo RNA structures and interactions. Nat. Methods 15, 785â788 (2018).
Kudla, G., Granneman, S., Hahn, D., Beggs, J. D. & Tollervey, D. Cross-linking, ligation, and sequencing of hybrids reveals RNAâRNA interactions in yeast. Proc. Natl Acad. Sci. USA 108, 10010â10015 (2011).
Sugimoto, Y. et al. hiCLIP reveals the in vivo atlas of mRNA secondary structures recognized by Staufen 1. Nature 519, 491â494 (2015).
Ye, R. et al. Capture RIC-seq reveals positional rules of PTBP1-associated RNA loops in splicing regulation. Mol. Cell 83, 1311â1327.e7 (2023).
Cao, C. et al. Global in situ profiling of RNAâRNA spatial interactions with RIC-seq. Nat. Protoc. 16, 2916â2946 (2021).
Christy, T. W. et al. Direct mapping of higher-order RNA interactions by SHAPE-JuMP. Biochemistry 60, 1971â1982 (2021).
Van Damme, R. et al. Chemical reversible crosslinking enables measurement of RNA 3D distances and alternative conformations in cells. Nat. Commun. 13, 911 (2022).
Xu, B. et al. Recent advances in RNA structurome. Sci. China Life Sci. 65, 1285â1324 (2022).
Gabryelska, M. M. et al. Global mapping of RNA homodimers in living cells. Genome Res. 32, 956â967 (2022).
Zhang, M. et al. Classification and clustering of RNA crosslink-ligation data reveal complex structures and homodimers. Genome Res. 32, 968â985 (2022).
Tants, J.-N. & Schlundt, A. Advances, applications, and perspectives in small-angle X-ray scattering of RNA. ChemBioChem 24, e202300110 (2023).
Zhang, K. et al. Cryo-EM structure of a 40âkDa SAM-IV riboswitch RNA at 3.7âà resolution. Nat. Commun. 10, 5511 (2019).
Kappel, K. et al. Accelerated cryo-EM-guided determination of three-dimensional RNA-only structures. Nat. Methods 17, 699â707 (2020).
Langeberg, C. J. & Kieft, J. S. A generalizable scaffold-based approach for structure determination of RNAs by cryo-EM. Nucleic Acids Res. 51, e100 (2023).
Reuter, J. S. & Mathews, D. H. RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinforma. 11, 129 (2010).
Lorenz, R. et al. ViennaRNA Package 2.0. Algorithms Mol. Biol. 6, 26 (2011).
Hofacker, I. L. et al. Fast folding and comparison of RNA secondary structures. Monatshefte fur Chem. 125, 167â188 (1994).
Hofacker, I. L., Fekete, M. & Stadler, P. F. Secondary structure prediction for aligned RNA sequences. J. Mol. Biol. 319, 1059â1066 (2002).
Washietl, S., Hofacker, I. L. & Stadler, P. F. Fast and reliable prediction of noncoding RNAs. Proc. Natl Acad. Sci. USA 102, 2454â2459 (2005).
Rivas, E., Clements, J. & Eddy, S. R. A statistical test for conserved RNA structure shows lack of evidence for structure in lncRNAs. Nat. Methods 14, 45â48 (2017).
Tavares, R. C. A., Pyle, A. M. & Somarowthu, S. Phylogenetic analysis with improved parameters reveals conservation in lncRNA structures. J. Mol. Biol. 431, 1592â1603 (2019).
Yu, H., Qi, Y. & Ding, Y. Deep learning in RNA structure studies. Front. Mol. Biosci. 9, 869601 (2022).
Sato, K. & Hamada, M. Recent trends in RNA informatics: a review of machine learning and deep learning for RNA secondary structure prediction and RNA drug discovery. Brief. Bioinform 24, bbad186 (2023).
Zhang, J., Fei, Y., Sun, L. & Zhang, Q. C. Advances and opportunities in RNA structure experimental determination and computational modeling. Nat. Methods 19, 1193â1207 (2022).
Aviran, S. et al. Modeling and automation of sequencing-based characterization of RNA structure. Proc. Natl Acad. Sci. USA 108, 11069â11074 (2011).
Selega, A., Sirocchi, C., Iosub, I., Granneman, S. & Sanguinetti, G. Robust statistical modeling improves sensitivity of high-throughput RNA structure probing experiments. Nat. Methods 14, 83â89 (2017).
Choudhary, K., Lai, Y. H., Tran, E. J. & Aviran, S. dStruct: identifying differentially reactive regions from RNA structurome profiling data. Genome Biol. 20, 40 (2019).
Marangio, P., Law, K. Y. T., Sanguinetti, G. & Granneman, S. diffBUM-HMM: a robust statistical modeling approach for detecting RNA flexibility changes in high-throughput structure probing data. Genome Biol. 22, 165 (2021).
Yu, B., Li, P., Zhang, Q. C. & Hou, L. Differential analysis of RNA structure probing experiments at nucleotide resolution: uncovering regulatory functions of RNA structure. Nat. Commun. 13, 4227 (2022).
Gong, J., Xu, K., Ma, Z., Lu, Z. J. & Zhang, Q. C. A deep learning method for recovering missing signals in transcriptome-wide RNA structure profiles from probing experiments. Nat. Mach. Intell. 3, 995â1006 (2021).
Low, J. T. & Weeks, K. M. SHAPE-directed RNA secondary structure prediction. Methods 52, 150â158 (2010).
Tomezsko, P. J. et al. Determination of RNA structural diversity and its role in HIV-1 RNA splicing. Nature 582, 438â442 (2020).
Olson, S. W. et al. Discovery of a large-scale, cell-state-responsive allosteric switch in the 7SK RNA using DANCE-MaP. Mol. Cell 82, 1708â1723.e10 (2022).
Morandi, E. et al. Genome-scale deconvolution of RNA structure ensembles. Nat. Methods 18, 249â252 (2021).
Goodarzi, H. et al. Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature 485, 264â268 (2012).
Fish, L. et al. A prometastatic splicing program regulated by SNRPA1 interactions with structured RNA elements. Science 372, eabc7531 (2021).
Morandi, E., van Hemert, M. J. & Incarnato, D. SHAPE-guided RNA structure homology search and motif discovery. Nat. Commun. 13, 1722 (2022).
Yang, Z., Zeng, X., Zhao, Y. & Chen, R. AlphaFold2 and its applications in the fields of biology and medicine. Signal. Transduct. Target. Ther. 8, 115 (2023).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583â589 (2021).
Westhof, E. & Leontis, N. B. An RNA-centric historical narrative around the Protein Data Bank. J. Biol. Chem. 296, 100555 (2021).
Singh, J., Hanson, J., Paliwal, K. & Zhou, Y. RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning. Nat. Commun. 10, 5407 (2019).
Danaee, P. et al. bpRNA: large-scale automated annotation and analysis of RNA secondary structure. Nucleic Acids Res. 46, 5381â5394 (2018).
Sato, K., Akiyama, M. & Sakakibara, Y. RNA secondary structure prediction using deep learning with thermodynamic integration. Nat. Commun. 12, 941 (2021).
Fu, L. et al. UFold: fast and accurate RNA secondary structure prediction with deep learning. Nucleic Acids Res. 50, e14 (2022).
Yang, E. et al. GCNfold: a novel lightweight model with valid extractors for RNA secondary structure prediction. Comput. Biol. Med. 164, 107246 (2023).
Li, Y. et al. Integrating end-to-end learning with deep geometrical potentials for ab initio RNA structure prediction. Nat. Commun. 14, 5745 (2023).
Wang, W. et al. trRosettaRNA: automated prediction of RNA 3D structure with transformer network. Nat. Commun. 14, 7266 (2023).
Das, R. & Baker, D. Automated de novo prediction of native-like RNA tertiary structures. Proc. Natl Acad. Sci. USA 104, 14664â14669 (2007).
Townshend, R. J. et al. Geometric deep learning of RNA structure. Science 373, 1047â1051 (2021).
Watkins, A. M., Rangan, R. & Das, R. FARFAR2: improved de novo rosetta prediction of complex global RNA folds. Structure 28, 963â976.e966 (2020).
Pan, X., Rijnbeek, P., Yan, J. & Shen, H.-B. Prediction of RNAâprotein sequence and structure binding preferences using deep convolutional and recurrent neural networks. BMC Genomics 19, 511 (2018).
Sun, L. et al. Predicting dynamic cellular proteinâRNA interactions by deep learning using in vivo RNA structures. Cell Res. 31, 495â516 (2021).
Xu, Y. et al. PrismNet: predicting proteinâRNA interaction using in vivo RNA structural information. Nucleic Acids Res. 51, W468âW477 (2023).
Baek, M. et al. Accurate prediction of proteinânucleic acid complexes using RoseTTAFoldNA. Nat. Methods 21, 117â121 (2024).
Sun, W., Ding, L. & Zhang, H. The potential role of RNA structure in crop molecular breeding. Front. Plant. Sci. 13, 868771 (2022).
Xiang, Y. et al. Pervasive downstream RNA hairpins dynamically dictate start-codon selection. Nature 621, 423â430 (2023).
Flamm, C. et al. Caveats to deep learning approaches to RNA secondary structure prediction. Front. Bioinform. 2, 835422 (2022).
Szikszai, M., Wise, M., Datta, A., Ward, M. & Mathews, D. H. Deep learning models for RNA secondary structure prediction (probably) do not generalize across families. Bioinformatics 38, 3892â3899 (2022).
Wayment-Steele, H. K. et al. RNA secondary structure packages evaluated and improved by high-throughput experiments. Nat. Methods 19, 1234â1242 (2022).
Gusarov, I. & Nudler, E. The mechanism of intrinsic transcription termination. Mol. Cell 3, 495â504 (1999).
Zhang, J. & Landick, R. A two-way street: regulatory interplay between RNA polymerase and nascent RNA structure. Trends Biochem. Sci. 41, 293â310 (2016).
Perdrizet, G. A. et al. Transcriptional pausing coordinates folding of the aptamer domain and the expression platform of a riboswitch. Proc. Natl Acad. Sci. USA 109, 3323â3328 (2012).
Steinert, H. et al. Pausing guides RNA folding to populate transiently stable RNA structures for riboswitch-based transcription regulation. eLife 6, e21297 (2017).
Turowski, T. W. et al. Nascent transcript folding plays a major role in determining RNA polymerase elongation rates. Mol. Cell 79, 488â503.e11 (2020).
Long, Y., Wang, X., Youmans, D. T. & Cech, T. R. How do lncRNAs regulate transcription? Sci. Adv. 3, eaao2110 (2017).
Yang, F. et al. Shape of promoter antisense RNAs regulates ligand-induced transcription activation. Nature 595, 444â449 (2021).
Liang, L. et al. Complementary Alu sequences mediate enhancerâpromoter selectivity. Nature 619, 868â875 (2023).
Peterlin, B. M., Brogie, J. E. & Price, D. H. 7SK snRNA: a noncoding RNA that plays a major role in regulating eukaryotic transcription. Wiley Interdiscip. Rev. RNA 3, 92â103 (2012).
AJ, C. Q., Bugai, A. & Barboric, M. Cracking the control of RNA polymerase II elongation by 7SK snRNP and P-TEFb. Nucleic Acids Res. 44, 7527â7539 (2016).
Whittaker, C. & Dean, C. The FLC locus: a platform for discoveries in epigenetics and adaptation. Annu. Rev. Cell Dev. Biol. 33, 555â575 (2017).
Roca, X., Krainer, A. R. & Eperon, I. C. Pick one, but be quick: 5â² splice sites and the problems of too many choices. Genes Dev. 27, 129â144 (2013).
Watakabe, A., Inoue, K., Sakamoto, H. & Shimura, Y. A secondary structure at the 3â² splice site affects the in vitro splicing reaction of mouse immunoglobulin mu chain pre-mRNAs. Nucleic Acids Res. 17, 8159â8169 (1989).
Varani, L. et al. Structure of tau exon 10 splicing regulatory element RNA and destabilization by mutations of frontotemporal dementia and parkinsonism linked to chromosome 17. Proc. Natl Acad. Sci. USA 96, 8229â8234 (1999).
Singh, N. N., Singh, R. N. & Androphy, E. J. Modulating role of RNA structure in alternative splicing of a critical exon in the spinal muscular atrophy genes. Nucleic Acids Res. 35, 371â389 (2007).
Warf, M. B. & Berglund, J. A. Role of RNA structure in regulating pre-mRNA splicing. Trends Biochem. Sci. 35, 169â178 (2010).
Rubtsov, P. Role of pre-mRNA secondary structures in the regulation of alternative splicing. Mol. Biol. 50, 823â830 (2016).
Kubodera, T. et al. Thiamineâregulated gene expression of Aspergillus oryzae thiA requires splicing of the intron containing a riboswitchâlike domain in the 5â²âUTR. FEBS Lett. 555, 516â520 (2003).
Cheah, M. T., Wachter, A., Sudarsan, N. & Breaker, R. R. Control of alternative RNA splicing and gene expression by eukaryotic riboswitches. Nature 447, 497â500 (2007).
Wachter, A. et al. Riboswitch control of gene expression in plants by splicing and alternative 3â² end processing of mRNAs. Plant. Cell 19, 3437â3450 (2007).
Warf, M. B., Diegel, J. V., von Hippel, P. H. & Berglund, J. A. The protein factors MBNL1 and U2AF65 bind alternative RNA structures to regulate splicing. Proc. Natl Acad. Sci. USA 106, 9203â9208 (2009).
Muro, A. F. et al. Regulation of fibronectin EDA exon alternative splicing: possible role of RNA secondary structure for enhancer display. Mol. Cell. Biol. 19, 2657â2671 (1999).
Buratti, E. et al. RNA folding affects the recruitment of SR proteins by mouse and human polypurinic enhancer elements in the fibronectin EDA exon. Mol. Cell. Biol. 24, 1387â1400 (2004).
McManus, C. J. & Graveley, B. R. RNA structure and the mechanisms of alternative splicing. Curr. Opin. Genet. Dev. 21, 373â379 (2011).
Lin, C. L., Taggart, A. J. & Fairbrother, W. G. RNA structure in splicing: an evolutionary perspective. RNA Biol. 13, 766â771 (2016).
Graveley, B. R. Mutually exclusive splicing of the insect Dscam pre-mRNA directed by competing intronic RNA secondary structures. Cell 123, 65â73 (2005).
Anastassiou, D., Liu, H. & Varadan, V. Variable window binding for mutually exclusive alternative splicing. Genome Biol. 7, 1â12 (2006).
Xu, B., Meng, Y. & Jin, Y. RNA structures in alternative splicing and back-splicing. Wiley Interdiscip. Rev. RNA 12, e1626 (2021).
Lovci, M. T. et al. Rbfox proteins regulate alternative mRNA splicing through evolutionarily conserved RNA bridges. Nat. Struct. Mol. Biol. 20, 1434â1442 (2013).
Woodson, S. A., Panja, S. & Santiago-Frangos, A. Proteins that chaperone RNA regulation. Microbiol. Spectr. 6 https://doi.org/10.1128/microbiolspec.RWR-0026-2018 (2018).
Wu, J. Y. & Maniatis, T. Specific interactions between proteins implicated in splice site selection and regulated alternative splicing. Cell 75, 1061â1070 (1993).
Kalmykova, S. et al. Conserved long-range base pairings are associated with pre-mRNA processing of human genes. Nat. Commun. 12, 2300 (2021).
Zhang, Y. et al. The biogenesis of nascent circular RNAs. Cell Rep. 15, 611â624 (2016).
Zhang, X. O. et al. Complementary sequence-mediated exon circularization. Cell 159, 134â147 (2014).
Johansson, J. et al. An RNA thermosensor controls expression of virulence genes in Listeria monocytogenes. Cell 110, 551â561 (2002).
Brito Querido, J., Diaz-Lopez, I. & Ramakrishnan, V. The molecular basis of translation initiation and its regulation in eukaryotes. Nat. Rev. Mol. Cell Biol. 25, 168â186 (2024).
Leppek, K., Das, R. & Barna, M. Functional 5â² UTR mRNA structures in eukaryotic translation regulation and how to find them. Nat. Rev. Mol. Cell Biol. 19, 158â174 (2018).
Spitale, R. C. et al. Structural imprints in vivo decode RNA regulatory mechanisms. Nature 519, 486â490 (2015).
Waldron, J. A. et al. mRNA structural elements immediately upstream of the start codon dictate dependence upon eIF4A helicase activity. Genome Biol. 20, 300 (2019).
Wang, J. et al. Rapid 40S scanning and its regulation by mRNA structure during eukaryotic translation initiation. Cell 185, 4474â4487.e17 (2022).
Zhang, H., Wang, Y. & Lu, J. Function and evolution of upstream ORFs in eukaryotes. Trends Biochem. Sci. 44, 782â794 (2019).
Corley, M. et al. An RNA structure-mediated, posttranscriptional model of human É-1-antitrypsin expression. Proc. Natl Acad. Sci. USA 114, E10244âE10253 (2017).
Jankowsky, E. & Guenther, U. P. A helicase links upstream ORFs and RNA structure. Curr. Genet. 65, 453â456 (2019).
Lyu, K. et al. An RNA G-quadruplex structure within the ADAR 5â²UTR interacts with DHX36 helicase to regulate translation. Angew. Chem. Int. Ed. Engl. 61, e202203553 (2022).
Kwok, C. K., Ding, Y., Shahid, S., Assmann, S. M. & Bevilacqua, P. C. A stable RNA G-quadruplex within the 5â²-UTR of Arabidopsis thaliana ATR mRNA inhibits translation. Biochem. J. 467, 91â102 (2015).
Cho, H. et al. Translational control of phloem development by RNA G-quadruplex-JULGI determines plant sink strength. Nat. Plants 4, 376â390 (2018).
Kikinis, Z., Eisenstein, R. S., Bettany, A. J. & Munro, H. N. Role of RNA secondary structure of the iron-responsive element in translational regulation of ferritin synthesis. Nucleic Acids Res. 23, 4190â4195 (1995).
Zhou, Z. D. & Tan, E. K. Iron regulatory protein (IRP)âiron responsive element (IRE) signaling pathway in human neurodegenerative diseases. Mol. Neurodegener. 12, 75 (2017).
Pestova, T. V., Shatsky, I. N., Fletcher, S. P., Jackson, R. J. & Hellen, C. U. A prokaryotic-like mode of cytoplasmic eukaryotic ribosome binding to the initiation codon during internal translation initiation of hepatitis C and classical swine fever virus RNAs. Genes Dev. 12, 67â83 (1998).
Kieft, J. S., Zhou, K., Jubin, R. & Doudna, J. A. Mechanism of ribosome recruitment by hepatitis C IRES RNA. RNA 7, 194â206 (2001).
Otto, G. A. & Puglisi, J. D. The pathway of HCV IRES-mediated translation initiation. Cell 119, 369â380 (2004).
Weingarten-Gabbay, S. et al. Comparative genetics. Systematic discovery of cap-independent translation sequences in human and viral genomes. Science 351, aad4939 (2016).
Beaudoin, J. D. et al. Analyses of mRNA structure dynamics identify embryonic gene regulatory programs. Nat. Struct. Mol. Biol. 25, 677â686 (2018).
Mustoe, A. M. et al. Pervasive regulatory functions of mRNA structure revealed by high-resolution SHAPE probing. Cell 173, 181â195.e18 (2018).
Farabaugh, P. J. Programmed translational frameshifting. Microbiol. Rev. 60, 103â134 (1996).
Kudla, G., Murray, A. W., Tollervey, D. & Plotkin, J. B. Coding-sequence determinants of gene expression in Escherichia coli. Science 324, 255â258 (2009).
Goodman, D. B., Church, G. M. & Kosuri, S. Causes and effects of N-terminal codon bias in bacterial genes. Science 342, 475â479 (2013).
Caliskan, N., Katunin, V. I., Belardinelli, R., Peske, F. & Rodnina, M. V. Programmed â1 frameshifting by kinetic partitioning during impeded translocation. Cell 157, 1619â1631 (2014).
Caliskan, N., Peske, F. & Rodnina, M. V. Changed in translation: mRNA recoding by â1 programmed ribosomal frameshifting. Trends Biochem. Sci. 40, 265â274 (2015).
Jungfleisch, J. et al. A novel translational control mechanism involving RNA structures within coding sequences. Genome Res. 27, 95â106 (2017).
Mao, Y. et al. m6A in mRNA coding regions promotes translation via the RNA helicase-containing YTHDC2. Nat. Commun. 10, 5332 (2019).
Yang, X. et al. RNA G-quadruplex structures exist and function in vivo in plants. Genome Biol. 21, 226 (2020).
Arif, A. et al. The GAIT translational control system. WIREs RNA 9, e1441 (2018).
Chaudhury, A. et al. TGF-β-mediated phosphorylation of hnRNP E1 induces EMT via transcript-selective translational induction of Dab2 and ILEI. Nat. Cell Biol. 12, 286â293 (2010).
Hussey, GeorgeS. et al. Identification of an mRNP complex regulating tumorigenesis at the translational elongation step. Mol. Cell 41, 419â431 (2011).
Brown, J. A. et al. Structural insights into the stabilization of MALAT1 noncoding RNA by a bipartite triple helix. Nat. Struct. Mol. Biol. 21, 633â640 (2014).
Brown, J. A. Unraveling the structure and biological functions of RNA triple helices. Wiley Interdiscip. Rev. RNA 11, e1598 (2020).
Wan, Y. et al. Genome-wide measurement of RNA folding energies. Mol. Cell 48, 169â181 (2012).
Yang, X. et al. RNA G-quadruplex structure contributes to cold adaptation in plants. Nat. Commun. 13, 6224 (2022).
Kharel, P. et al. Stress promotes RNA G-quadruplex folding in human cells. Nat. Commun. 14, 205 (2023).
Marzluff, W. F., Wagner, E. J. & Duronio, R. J. Metabolism and regulation of canonical histone mRNAs: life without a poly(A) tail. Nat. Rev. Genet. 9, 843â854 (2008).
Fischer, J. W., Busa, V. F., Shao, Y. & Leung, A. K. L. Structure-mediated RNA decay by UPF1 and G3BP1. Mol. Cell 78, 70â84.e6 (2020).
Meisner, N.-C. et al. mRNA openers and closers: modulating AU-rich element-controlled mRNA stability by a molecular switch in mRNA secondary structure. ChemBioChem 5, 1432â1447 (2004).
Carthew, R. W. & Sontheimer, E. J. Origins and mechanisms of miRNAs and siRNAs. Cell 136, 642â655 (2009).
Yadav, D. K. et al. Staufen1 reads out structure and sequence features in ARF1 dsRNA for target recognition. Nucleic Acids Res. 48, 2091â2106 (2019).
Mino, T. et al. Regnase-1 and roquin regulate a common element in inflammatory mRNAs by spatiotemporally distinct mechanisms. Cell 161, 1058â1073 (2015).
Leppek, K. et al. Roquin promotes constitutive mRNA decay via a conserved class of stem-loop recognition motifs. Cell 153, 869â881 (2013).
Binas, O. et al. Structural basis for the recognition of transiently structured AU-rich elements by Roquin. Nucleic Acids Res. 48, 7385â7403 (2020).
Shi, B. et al. RNA structural dynamics regulate early embryogenesis through controlling transcriptome fate and function. Genome Biol. 21, 120 (2020).
Mauger, D. M. et al. mRNA structure regulates protein expression through changes in functional half-life. Proc. Natl Acad. Sci. USA 116, 24075â24083 (2019).
Gonzalez, I., Buonomo, S. B., Nasmyth, K. & von Ahsen, U. ASH1 mRNA localization in yeast involves multiple secondary structural elements and Ash1 protein translation. Curr. Biol. 9, 337â340 (1999).
Macdonald, P. M., Kerr, K., Smith, J. L. & Leask, A. RNA regulatory element BLE1 directs the early steps of bicoid mRNA localization. Development 118, 1233â1243 (1993).
St Johnston, D., Beuchle, D. & Nusslein-Volhard, C. Staufen, a gene required to localize maternal RNAs in the Drosophila egg. Cell 66, 51â63 (1991).
Ferrandon, D., Elphick, L., Nusslein-Volhard, C. & St Johnston, D. Staufen protein associates with the 3â²UTR of bicoid mRNA to form particles that move in a microtubule-dependent manner. Cell 79, 1221â1232 (1994).
Bergsten, S. E., Huang, T., Chatterjee, S. & Gavis, E. R. Recognition and long-range interactions of a minimal nanos RNA localization signal element. Development 128, 427â435 (2001).
Kim-Ha, J., Webster, P. J., Smith, J. L. & Macdonald, P. M. Multiple RNA regulatory elements mediate distinct steps in localization of oskar mRNA. Development 119, 169â178 (1993).
Van De Bor, V., Hartswood, E., Jones, C., Finnegan, D. & Davis, I. gurken and the I factor retrotransposon RNAs share common localization signals and machinery. Dev. Cell 9, 51â62 (2005).
Bullock, S. L., Ringel, I., Ish-Horowicz, D. & Lukavsky, P. J. Aâ²-form RNA helices are required for cytoplasmic mRNA transport in Drosophila. Nat. Struct. Mol. Biol. 17, 703â709 (2010).
Chao, J. A. et al. ZBP1 recognition of β-actin zipcode induces RNA looping. Genes Dev. 24, 148â158 (2010).
Patel, V. L. et al. Spatial arrangement of an RNA zipcode identifies mRNAs under post-transcriptional control. Genes Dev. 26, 43â53 (2012).
Fernandez-Moya, S. M. et al. RGS4 RNA secondary structure mediates Staufen2 RNP assembly in neurons. Int. J. Mol. Sci. 22, 13021 (2021).
Wang, T. et al. RNA motifs and modification involve in RNA long-distance transport in plants. Front. Cell Dev. Biol. 9, 651278 (2021).
Zhang, W. et al. tRNA-related sequences trigger systemic mRNA transport in plants. Plant Cell 28, 1237â1249 (2016).
Fernandes, J., Jayaraman, B. & Frankel, A. The HIV-1 Rev response element: an RNA scaffold that directs the cooperative assembly of a homo-oligomeric ribonucleoprotein complex. RNA Biol. 9, 6â11 (2012).
Malim, M. H., Hauber, J., Le, S. Y., Maizel, J. V. & Cullen, B. R. The HIV-1 rev trans-activator acts through a structured target sequence to activate nuclear export of unspliced viral mRNA. Nature 338, 254â257 (1989).
Pasquinelli, A. E. et al. The constitutive transport element (CTE) of MasonâPfizer monkey virus (MPMV) accesses a cellular mRNA export pathway. EMBO J. 16, 7500â7510 (1997).
Gruter, P. et al. TAP, the human homolog of Mex67p, mediates CTE-dependent RNA export from the nucleus. Mol. Cell 1, 649â659 (1998).
Aibara, S., Katahira, J., Valkov, E. & Stewart, M. The principal mRNA nuclear export factor NXF1:NXT1 forms a symmetric binding platform that facilitates export of retroviral CTE-RNA. Nucleic Acids Res. 43, 1883â1893 (2015).
Van Treeck, B. et al. RNA self-assembly contributes to stress granule formation and defining the stress granule transcriptome. Proc. Natl Acad. Sci. USA 115, 2734â2739 (2018).
Poudyal, R. R., Sieg, J. P., Portz, B., Keating, C. D. & Bevilacqua, P. C. RNA sequence and structure control assembly and function of RNA condensates. RNA 27, 1589â1601 (2021).
Jain, A. & Vale, R. D. RNA phase transitions in repeat expansion disorders. Nature 546, 243â247 (2017).
Zhang, Y. et al. G-quadruplex structures trigger RNA phase separation. Nucleic Acids Res. 47, 11746â11754 (2019).
Langdon, E. M. & Gladfelter, A. S. A new lens for RNA localization: liquidâliquid phase separation. Annu. Rev. Microbiol. 72, 255â271 (2018).
Roden, ChristineA. et al. Double-stranded RNA drives SARS-CoV-2 nucleocapsid protein to undergo phase separation at specific temperatures. Nucleic Acids Res. 50, 8168â8192 (2022).
Clemson, C. M. et al. An architectural role for a nuclear noncoding RNA: NEAT1 RNA is essential for the structure of paraspeckles. Mol. Cell 33, 717â726 (2009).
Yamazaki, T. et al. Functional domains of NEAT1 architectural lncRNA induce paraspeckle assembly through phase separation. Mol. Cell 70, 1038â1053.e7 (2018).
Asamitsu, S. et al. RNA G-quadruplex organizes stress granule assembly through DNAPTP6 in neurons. Sci. Adv. 9, eade2035 (2023).
Mimura, M. et al. Quadruplex folding promotes the condensation of linker histones and DNAs via liquidâliquid phase separation. J. Am. Chem. Soc. 143, 9849â9857 (2021).
Warner, K. D., Hajdin, C. E. & Weeks, K. M. Principles for targeting RNA with drug-like small molecules. Nat. Rev. Drug Discov. 17, 547â558 (2018).
Childs-Disney, J. L. et al. Targeting RNA structures with small molecules. Nat. Rev. Drug Discov. 21, 736â762 (2022).
Abulwerdi, F. A. et al. Development of small molecules with a noncanonical binding mode to HIV-1 trans activation response (TAR) RNA. J. Med. Chem. 59, 11148â11160 (2016).
Prado, S. et al. A small-molecule inhibitor of HIV-1 Rev function detected by a diversity screen based on RREâRev interference. Biochem. Pharmacol. 156, 68â77 (2018).
Howe, J. A. et al. Selective small-molecule inhibition of an RNA structural element. Nature 526, 672â677 (2015).
Blount Kenneth, F. et al. Novel riboswitch-binding flavin analog that protects mice against Clostridium difficile infection without inhibiting cecal flora. Antimicrob. Agents Chemother. 59, 5736â5746 (2015).
Balaratnam, S. et al. Investigating the NRAS 5â² UTR as a target for small molecules. Cell Chem. Biol. 30, 643â657.e8 (2023).
Aguilar, R. et al. Targeting Xist with compounds that disrupt RNA structure and X inactivation. Nature 604, 160â166 (2022).
Dhillon, S. Risdiplam: first approval. Drugs 80, 1853â1858 (2020).
Naryshkin, N. A. et al. SMN2 splicing modifiers improve motor function and longevity in mice with spinal muscular atrophy. Science 345, 688â693 (2014).
Ratni, H. et al. Discovery of risdiplam, a selective survival of motor neuron-2 (SMN2) gene splicing modifier for the treatment of spinal muscular atrophy (SMA). J. Med. Chem. 61, 6501â6517 (2018).
Sivaramakrishnan, M. et al. Binding to SMN2 pre-mRNAâprotein complex elicits specificity for small molecule splicing modifiers. Nat. Commun. 8, 1476 (2017).
Campagne, S. et al. Structural basis of a small molecule targeting RNA for a specific splicing correction. Nat. Chem. Biol. 15, 1191â1198 (2019).
Wang, J., Schultz, P. G. & Johnson, K. A. Mechanistic studies of a small-molecule modulator of SMN2 splicing. Proc. Natl Acad. Sci. USA 115, E4604âE4612 (2018).
Velagapudi, S. P., Gallo, S. M. & Disney, M. D. Sequence-based design of bioactive small molecules that target precursor microRNAs. Nat. Chem. Biol. 10, 291â297 (2014).
Costales, M. G. et al. A designed small molecule inhibitor of a non-coding RNA sensitizes HER2 negative cancers to herceptin. J. Am. Chem. Soc. 141, 2960â2974 (2019).
Fang, L. et al. Pervasive transcriptome interactions of protein-targeted drugs. Nat. Chem. 15, 1374â1383 (2023).
Costales, M. G., Matsumoto, Y., Velagapudi, S. P. & Disney, M. D. Small molecule targeted recruitment of a nuclease to RNA. J. Am. Chem. Soc. 140, 6741â6744 (2018).
Costales, M. G. et al. Small-molecule targeted recruitment of a nuclease to cleave an oncogenic RNA in a mouse model of metastatic cancer. Proc. Natl Acad. Sci. USA 117, 2406â2411 (2020).
Tong, Y. et al. Programming inactive RNA-binding small molecules into bioactive degraders. Nature 618, 169â179 (2023).
McCown, P. J., Corbino, K. A., Stav, S., Sherlock, M. E. & Breaker, R. R. Riboswitch diversity and distribution. RNA 23, 995â1011 (2017).
Acknowledgements
This work was supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC) (BB/X01102X/1) and European Research Council (ERC) (selected by the ERC, funded by BBSRC Horizon Europe Guarantee (EP/Y009886/1)) (Y.D. and Y.Z.). Y.W. and X.C. are supported by funding from A*STAR, the National Research Foundation of Singapore, the EMBO Young Investigator Programme and a CIFAR Azrieli global scholar fellowship.
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Glossary
- Aptamer domain
-
An RNA structure in a riboswitch that binds to small molecules.
- Enzymatic structure probing
-
Refers to the use of nucleases that cleave RNA selectively at single-stranded or double-stranded regions (for example, RNase T1 and RNase V1, respectively); the resulting digestion footprints of the RNA can chart its structure.
- i-Motifs
-
Cytosine-rich DNAs that form quadruplex structures; also known as intercalated-motif DNAs.
- Riboswitches
-
Highly folded segments of (mostly bacterial) mRNAs that, when bound by environmental small molecules, induce structure changes that regulate the transcription or translation of the mRNA.
- R-loop structure
-
A three-stranded nucleic acid structure composed of a DNAâRNA hybrid and a displaced single strand of DNA.
- Small nucleolar RNAs
-
A class of small non-coding RNAs (ncRNAs) that mostly reside in nucleoli, which guide chemical modifications of other RNA species such as ribosomal RNAs.
- Stress granules
-
Dynamic cytoplasmic bodies formed in response to cellular stress, comprising RNA molecules and various proteins; they have a role in RNA metabolism and are associated with responses to environmental stresses.
- Upstream open reading frames
-
(uORFs). Open reading frames (ORFs) located upstream of a main open reading frame, that is, within the 5â² untranslated region (UTR) of the mRNA. uORFs can encode small peptides, and can regulate the translation of the main ORF by competing for the translation machinery.
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Cao, X., Zhang, Y., Ding, Y. et al. Identification of RNA structures and their roles in RNA functions. Nat Rev Mol Cell Biol 25, 784â801 (2024). https://doi.org/10.1038/s41580-024-00748-6
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DOI: https://doi.org/10.1038/s41580-024-00748-6