The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Cross-linking, ligation, and sequencing of hybrids reveals RNA–RNA interactions in yeast
Open accessAbstract
Many protein-protein and protein-nucleic acid interactions have been experimentally characterized, whereas RNA-RNA interactions have generally only been predicted computationally. Here, we describe a high-throughput method to identify intramolecular and intermolecular RNA-RNA interactions experimentally by cross-linking, ligation, and sequencing of hybrids (CLASH). As validation, we identified 39 known target sites for box C/D modification-guide small nucleolar RNAs (snoRNAs) on the yeast pre-rRNA. Novel snoRNA-rRNA hybrids were recovered between snR4-5S and U14-25S. These are supported by native electrophoresis and consistent with previously unexplained data. The U3 snoRNA was found to be associated with sequences close to the 3' side of the central pseudoknot in 18S rRNA, supporting a role in formation of this structure. Applying CLASH to the yeast U2 spliceosomal snRNA led to a revised predicted secondary structure, featuring alternative folding of the 3' domain and long-range contacts between the 3' and 5' domains. CLASH should allow transcriptome-wide analyses of RNA-RNA interactions in many organisms.
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.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“early CLASH publications showed the utility of the chimeric analysis approach in mapping snoRNA interactions in yeast (Kudla et al., 2011) and more recently was utilized to generate an extensive catalog of putative snoRNA interactions and reveal novel targets of orphan snoRNAs (Gumienny et al., 2017).”
From Scalable and deep profiling of mRNA targets for individual microRNAs with chimeric eCLIP (2022) · cites this paper as Kudla et al., 2011
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
Capturing Chromosome Conformation
Dekker, J., Rippe, K., Dekker, M., & Kleckner, N. (2002) · Science · doi:10.1126/science.1067799 · Cited by 3,652
DINAMelt web server for nucleic acid melting prediction
Markham, N. R., & Zuker, M. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki591 · Cited by 947
Site-Specific Ribose Methylation of Preribosomal RNA: A Novel Function for Small Nucleolar RNAs
Kiss-László, Z., Henry, Y. A. L., Bachellerie, J., Caizergues‐Ferrer, M., & Kiss, T. (1996) · Cell · doi:10.1016/s0092-8674(00)81308-2 · Cited by 855
Kiss (2002) · doi:10.1016/s0092-8674(02)00718-3 · Cited by 816
Merino, E. J., Wilkinson, K. A., Coughlan, J. L., & Weeks, K. M. (2005) · Journal of the American Chemical Society · doi:10.1021/ja043822v · Cited by 791
RNA processing and its regulation: global insights into biological networks
Licatalosi, D. D., & Darnell, R. B. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2673 · Cited by 777
Genome-wide measurement of RNA secondary structure in yeast
Kertesz, M., Wan, Y., Mazor, E., Rinn, J. L., Nutter, R. C., Chang, H. Y., & Segal, E. (2010) · Nature · doi:10.1038/nature09322 · Cited by 769
Parker, R., Siliciano, P. G., & Guthrie, C. (1987) · Cell · doi:10.1016/0092-8674(87)90564-2 · Cited by 513
Guthrie, C., & Patterson, B. (1988) · Annual Review of Genetics · doi:10.1146/annurev.ge.22.120188.002131 · Cited by 476
Function and synthesis of small nucleolar RNAs
Tollervey, D. W., & Kiss, T. (1997) · Current Opinion in Cell Biology · doi:10.1016/s0955-0674(97)80005-1 · Cited by 467
Self-citation
Cited by
Sorted by citations
RNA sequencing: the teenage years
Stark, R., Grzelak, M., & Hadfield, J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0150-2 · Cited by 2,041
Mapping the Human miRNA Interactome by CLASH Reveals Frequent Noncanonical Binding
Helwak, A., Kudla, G., Dudnakova, T., & Tollervey, D. (2013) · Cell · doi:10.1016/j.cell.2013.03.043 · Cited by 1,269
Self-citationHsu, S., Tseng, Y., Shrestha, S., Lin, Y., Khaleel, A., Chou, C., Chu, C.-F., Huang, H., Lin, C.-M., Ho, S.-Y., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1266 · Cited by 1,044
Ribosome Biogenesis in the Yeast Saccharomyces cerevisiae
Woolford, J. L., & Baserga, S. J. (2013) · Genetics · doi:10.1534/genetics.113.153197 · Cited by 780
Sloan, K. E., Warda, A. S., Sharma, S., Entian, K.-D., Lafontaine, D. L. J., & Bohnsack, M. T. (2017) · RNA Biology · doi:10.1080/15476286.2016.1259781 · Cited by 707
Revealing protein–lncRNA interaction
Ferrè, F., Colantoni, A., & Helmer‐Citterich, M. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv031 · Cited by 700
An overview of pre‐ribosomal RNA processing in eukaryotes
Henras, A. K., Plisson‐Chastang, C., O’Donohue, M.-F., Chakraborty, A., & Gleizes, P. (2014) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1269 · Cited by 644
Protein–RNA interactions: new genomic technologies and perspectives
König, J., Zarnack, K., Luscombe, N. M., & Ule, J. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3141 · Cited by 555
Advances and Trends in Omics Technology Development
Dai, X., & Shen, L. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2022.911861 · Cited by 604
Engreitz, J., Sirokman, K., McDonel, P. E., Shishkin, A. A., Surka, C., Russell, P. H., Grossman, S. R., Chow, A. Y., Guttman, M., & Lander, E. S. (2014) · Cell · doi:10.1016/j.cell.2014.08.018 · Cited by 514
Watkins, N. J., & Bohnsack, M. T. (2011) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.117 · Cited by 520
Non-coding RNA regulatory networks
Panni, S., Lovering, R. C., Porras, P., & Orchard, S. (2020) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2019.194417 · Cited by 479
Revealing lncRNA Structures and Interactions by Sequencing-Based Approaches
Qian, X., Zhao, J., Yeung, P. Y., Zhang, Q. C., & Kwok, C. K. (2018) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2018.09.012 · Cited by 436
How cells get the message: dynamic assembly and function of mRNA–protein complexes
Müller-McNicoll, M., & Neugebauer, K. M. (2013) · Nature Reviews Genetics · doi:10.1038/nrg3434 · Cited by 405
New frontiers in translational control of the cancer genome
Truitt, M. L., & Ruggero, D. (2016) · Nature Reviews Cancer · doi:10.1038/nrc.2016.27 · Cited by 378
Global Mapping of Human RNA-RNA Interactions
Sharma, E., Sterne‐Weiler, T., O’Hanlon, D., & Blencowe, B. J. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.04.030 · Cited by 394
Aw, J. G. A., Shen, Y., Wilm, A., Sun, M., Lim, X. N., Boon, K.-L., Tapşın, S., Chan, Y.-S., Tan, C.-P., Sim, A. Y. L., et al. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.04.028 · Cited by 356
Technological Developments in lncRNA Biology
Jathar, S., Kumar, V., Srivastava, J. P., & Tripathi, V. (2017) · Advances in experimental medicine and biology · doi:10.1007/978-981-10-5203-3_10 · Cited by 350
Bhattacharya, A., Ziebarth, J. D., & Cui, Y. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1028 · Cited by 347
Moore, M. J., Scheel, T. K. H., Luna, J. M., Park, C. Y., Fak, J. J., Nishiuchi, E., Rice, C. M., & Darnell, R. B. (2015) · Nature Communications · doi:10.1038/ncomms9864 · Cited by 326
Epigenetic Regulation of the DLK1-MEG3 MicroRNA Cluster in Human Type 2 Diabetic Islets
Kameswaran, V., Bramswig, N. C., McKenna, L. B., Penn, M. M. C., Schug, J., Hand, N. J., Chen, Y., Choi, I., Vourekas, A., Won, K., et al. (2014) · Cell Metabolism · doi:10.1016/j.cmet.2013.11.016 · Cited by 324
RIC-seq for global in situ profiling of RNA–RNA spatial interactions
Cai, Z., Cao, C., Ji, L., Ye, R., Wang, D., Xia, C., Wang, S., Du, Z., Hu, N., Yu, X., et al. (2020) · Nature · doi:10.1038/s41586-020-2249-1 · Cited by 310
Erratum: New frontiers in translational control of the cancer genome
Truitt, M., & Ruggero, D. (2017) · Nature reviews. Cancer · doi:10.1038/nrc.2017.30 · Cited by 306
Advances in CLIP Technologies for Studies of Protein-RNA Interactions
Lee, F. C. Y., & Ule, J. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.01.005 · Cited by 301
Functional diversity of small nucleolar RNAs
Bratkovič, T., Božič, J., & Rogelj, B. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkz1140 · Cited by 272
hiCLIP reveals the in vivo atlas of mRNA secondary structures recognized by Staufen 1
Sugimoto, Y., Vigilante, A., Darbo, É., Zirra, A., Militti, C., D’Ambrogio, A., Luscombe, N. M., & Ule, J. (2015) · Nature · doi:10.1038/nature14280 · Cited by 276
Competition between target sites of regulators shapes post-transcriptional gene regulation
Jens, M., & Rajewsky, N. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3853 · Cited by 267
Long Noncoding RNA Discovery in Cardiovascular Disease
Sallam, T., Sandhu, J., & Tontonoz, P. (2018) · Circulation Research · doi:10.1161/circresaha.117.311802 · Cited by 253
Cryo-EM structure of the spliceosome immediately after branching
Galej, W. P., Wilkinson, M. E., Fica, S. M., Oubridge, C., Newman, A. J., & Nagai, K. (2016) · Nature · doi:10.1038/nature19316 · Cited by 235
The miRNA–target interactions: An underestimated intricacy
Diener, C., Keller, A., & Meese, E. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkad1142 · Cited by 248
Architecture of the 90S Pre-ribosome: A Structural View on the Birth of the Eukaryotic Ribosome
Kornprobst, M., Turk, M., Kellner, N., Cheng, J., Flemming, D., Kos‐Braun, I. C., Koš, M., Thoms, M., Berninghausen, O., Beckmann, R., et al. (2016) · Cell · doi:10.1016/j.cell.2016.06.014 · Cited by 239
Kashi, K., Henderson, L., Bonetti, A., & Carninci, P. (2015) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2015.10.010 · Cited by 205
High-throughput determination of RNA structures
Strobel, E. J., Yu, A. M., & Lucks, J. B. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0034-x · Cited by 188
The Emerging Function and Mechanism of ceRNAs in Cancer
Wang, Y., Hou, J., He, D., Sun, M., Zhang, P., Yu, Y., & Chen, Y. (2016) · Trends in Genetics · doi:10.1016/j.tig.2016.02.001 · Cited by 187
Loganathan, T., & Doss, C. G. P. (2023) · Functional & Integrative Genomics · doi:10.1007/s10142-022-00947-4 · Cited by 196
RNA Binding Proteins in Intestinal Epithelial Biology and Colorectal Cancer
Chatterji, P., & Rustgi, A. K. (2018) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2018.03.008 · Cited by 166
Advances and challenges in the detection of transcriptome‐wide protein– RNA interactions
Wheeler, E. C., Nostrand, E. L. V., & Yeo, G. W.-M. (2017) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1436 · Cited by 164
Mapping RNA–RNA interactome and RNA structure in vivo by MARIO
Nguyen, T. C., Cao, X., Yu, P., Shu Dong, X. I. A. O., Lu, J., Biase, F. H., Sridhar, B., Huang, N., Zhang, K., & Zhong, S. (2016) · Nature Communications · doi:10.1038/ncomms12023 · Cited by 164
Mapping the miRNA interactome by cross-linking ligation and sequencing of hybrids (CLASH)
Helwak, A., & Tollervey, D. W. (2014) · Nature Protocols · doi:10.1038/nprot.2014.043 · Cited by 160
Self-citationLncRNAs: From Basic Research to Medical Application
Wu, T., & Du, Y. (2017) · International Journal of Biological Sciences · doi:10.7150/ijbs.16968 · Cited by 140
General rules for functional microRNA targeting
Kim, D., Sung, Y. M., Park, J., Kim, S., Kim, J., Park, J., Ha, H., Bae, J. Y., Kim, S., & Baek, D. (2016) · Nature Genetics · doi:10.1038/ng.3694 · Cited by 139
Genetic variants in microRNA genes: impact on microRNA expression, function, and disease
Cammaerts, S., Stražišar, M., Rijk, P. D., & Del‐Favero, J. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00186 · Cited by 141
Technologies to probe functions and mechanisms of long noncoding RNAs
Chu, C., Spitale, R. C., & Chang, H. Y. (2015) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2921 · Cited by 141
SomamiR 2.0: a database of cancer somatic mutations altering microRNA–ceRNA interactions
Bhattacharya, A., & Cui, Y. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1220 · Cited by 133
Modifications in small nuclear RNAs and their roles in spliceosome assembly and function
Bohnsack, M. T., & Sloan, K. E. (2018) · Biological Chemistry · doi:10.1515/hsz-2018-0205 · Cited by 130
SIRT7-dependent deacetylation of the U3-55k protein controls pre-rRNA processing
Chen, S., Blank, M. F., Iyer-Bierhoff, A., Huang, B., Wang, L., Grummt, I., & Voit, R. (2016) · Nature Communications · doi:10.1038/ncomms10734 · Cited by 129
RNA structure probing uncovers RNA structure-dependent biological functions
Wang, X., Liu, C., Chen, L., & Zhang, Q. C. (2021) · Nature Chemical Biology · doi:10.1038/s41589-021-00805-7 · Cited by 124
Specialized box C/D snoRNPs act as antisense guides to target RNA base acetylation
Sharma, S., Yang, J., van Nues, R. W., Watzinger, P., Kötter, P., Lafontaine, D. L. J., Granneman, S., & Entian, K. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006804 · Cited by 132
Self-citationRAIN: RNA–protein Association and Interaction Networks
Junge, A., Refsgaard, J. C., Garde, C., Pan, X., Santos, A., Alkan, F., Anthon, C., von Mering, C., Workman, C. T., Jensen, L. J., et al. (2016) · Database · doi:10.1093/database/baw167 · Cited by 123
RISE: a database of RNA interactome from sequencing experiments
Gong, J., Shao, D., Xu, K., Lu, Z., Lu, Z. J., Yang, Y., & Zhang, Q. C. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx864 · Cited by 121
The panorama of miRNA-mediated mechanisms in mammalian cells
Stroynowska-Czerwińska, A., Fiszer, A., & Krzyżosiak, W. J. (2014) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-013-1551-6 · Cited by 122
Identification of RNA structures and their roles in RNA functions
Cao, X., Zhang, Y., Ding, Y., & Wan, Y. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00748-6 · Cited by 124
Chaker-Margot, M., Hunziker, M., Barandun, J., Dill, B. D., & Klinge, S. (2015) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3111 · Cited by 114
Accelerating Discovery and Functional Analysis of Small RNAs with New Technologies
Barquist, L., & Vogel, J. (2015) · Annual Review of Genetics · doi:10.1146/annurev-genet-112414-054804 · Cited by 115
Galamb, O., Barták, B. K., Kalmár, A., Nagy, Z. B., Szigeti, K. A., Tulassay, Z., Igaz, P., & Molnar, B. A. (2019) · World Journal of Gastroenterology · doi:10.3748/wjg.v25.i34.5026 · Cited by 113
Sun, Y., & Chen, Y.-Q. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00945-8 · Cited by 114
High-throughput determination of RNA structure by proximity ligation
Ramani, V., Qiu, R., & Shendure, J. (2015) · Nature Biotechnology · doi:10.1038/nbt.3289 · Cited by 108
Progress and challenges for chemical probing of RNA structure inside living cells
Kubota, M., Tran, C., & Spitale, R. C. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1958 · Cited by 106
Understanding the Functions of Long Non-Coding RNAs through Their Higher-Order Structures
Li, R., Zhu, H., & Luo, Y. (2016) · International Journal of Molecular Sciences · doi:10.3390/ijms17050702 · Cited by 100
Hfq CLASH uncovers sRNA-target interaction networks linked to nutrient availability adaptation
Iosub, I. A., van Nues, R. W., McKellar, S. W., Nieken, K. J., Marchioretto, M., Sy, B., Tree, J. J., Viero, G., & Granneman, S. (2020) · eLife · doi:10.7554/elife.54655 · Cited by 98
Self-citationTravis, A. J., Moody, J., Helwak, A., Tollervey, D. W., & Kudla, G. (2013) · Methods · doi:10.1016/j.ymeth.2013.10.015 · Cited by 98
Self-citationThe role of long non-coding RNAs in rheumatic diseases
Tang, Y., Zhou, T., Yu, X., Xue, Z., & Shen, N. (2017) · Nature Reviews Rheumatology · doi:10.1038/nrrheum.2017.162 · Cited by 90
Functions and properties of nuclear lncRNAs—from systematically mapping the interactomes of lncRNAs
Guh, C.-Y., Hsieh, Y.-H., & Chu, H.-P. C. (2020) · Journal of Biomedical Science · doi:10.1186/s12929-020-00640-3 · Cited by 90
Hunziker, M., Barandun, J., Petfalski, E., Tan, D., Delan‐Forino, C., Molloy, K. R., Kim, K. H., Dunn-Davies, H., Shi, Y., Chaker-Margot, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms12090 · Cited by 91
Self-citationThe centrality of RNA for engineering gene expression
Chappell, J., Takahashi, M. K., Meyer, S., Loughrey, D., Watters, K. E., & Lucks, J. B. (2013) · Biotechnology Journal · doi:10.1002/biot.201300018 · Cited by 86
State of the art technologies to explore long non‐coding RNAs in cancer
Salehi, S., Taheri, M. N., Azarpira, N., Zare, A., & Behzad‐Behbahani, A. (2017) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.13238 · Cited by 84
Schmitz, U., Lai, X., Winter, F., Wolkenhauer, O., Vera, J., & Gupta, S. K. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku465 · Cited by 83
Genome-Wide Analysis of miRNA-mRNA Interactions in Marrow Stromal Cells
Balakrishnan, I., Yang, X., Brown, J., Ramakrishnan, A., Torok‐Storb, B., Kabos, P., Hesselberth, J. R., & Pillai, M. M. (2013) · Stem Cells · doi:10.1002/stem.1531 · Cited by 78
Assembly and structure of the SSU processome — a nucleolar precursor of the small ribosomal subunit
Barandun, J., Hunziker, M., & Klinge, S. (2018) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2018.01.008 · Cited by 87
Ji, W., Ye, C., Xiong, H., Shen, Y., Lu, Y., Zhou, J., & Wang, L. (2016) · Oncotarget · doi:10.18632/oncotarget.12537 · Cited by 81
Identification of RNA Helicase Target Sites by UV Cross-Linking and Analysis of cDNA
Bohnsack, M. T., Tollervey, D. W., & Granneman, S. (2012) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/b978-0-12-396546-2.00013-9 · Cited by 83
Self-citationA comprehensive benchmark of RNA–RNA interaction prediction tools for all domains of life
Umu, S. U., & Gardner, P. P. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw728 · Cited by 79
Higher-Order Organization Principles of Pre-translational mRNPs
Metkar, M., Özadam, H., Lajoie, B. R., Imakaev, M., Mirny, L. A., Dekker, J., & Moore, M. J. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.09.012 · Cited by 75
Hahn, D., Kudla, G. R., Tollervey, D. W., & Beggs, J. D. (2012) · Genes & Development · doi:10.1101/gad.199307.112 · Cited by 77
Self-citationDesign and bioinformatics analysis of genome-wide CLIP experiments
Wang, T., Xiao, G., Chu, Y., Zhang, M. Q., Corey, D. R., & Xie, Y. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv439 · Cited by 77
Rrp5 Binding at Multiple Sites Coordinates Pre-rRNA Processing and Assembly
Lebaron, S., Segerstolpe, Å., French, S. L., Dudnakova, T., Alves, F. D. L., Granneman, S., Rappsilber, J., Beyer, A. L., Wieslander, L., & Tollervey, D. W. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.10.017 · Cited by 74
Self-citationHigh-throughput identification of C/D box snoRNA targets with CLIP and RiboMeth-seq
Gumienny, R., Jedlinski, D., Schmidt, A., Gypas, F., Martin, G., Viña‐Vilaseca, A., & Zavolan, M. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1321 · Cited by 73
Enhancer RNA: Biogenesis, function, and regulation
Ye, R., Cao, C., & Xue, Y. (2020) · Essays in Biochemistry · doi:10.1042/ebc20200014 · Cited by 71
Beyond CLIP: advances and opportunities to measure RBP–RNA and RNA–RNA interactions
Lin, C., & Miles, W. O. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz295 · Cited by 72
Lu, Z., & Chang, H. Y. (2016) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2016.01.007 · Cited by 69
Wong, N. K., Huang, C., Islam, R., & Yip, S. P. (2018) · Journal of Hematology & Oncology · doi:10.1186/s13045-018-0673-6 · Cited by 70
Yeast and human RNA helicases involved in ribosome biogenesis: Current status and perspectives
Rodríguez‐Galán, O., García-Gómez, J. J., & de la Cruz, J. (2013) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2013.01.007 · Cited by 73
Recent advances in RNA structurome
Xu, B., Zhu, Y., Cao, C., Chen, H., Jin, Q., Li, G., Ma, J., Yang, S. L., Zhao, J., Zhu, J., et al. (2022) · Science China Life Sciences · doi:10.1007/s11427-021-2116-2 · Cited by 63
RNA: interactions drive functionalities
Dai, X., Zhang, S., & Zaleta-Rivera, K. (2019) · Molecular Biology Reports · doi:10.1007/s11033-019-05230-7 · Cited by 65
In vivo structure and dynamics of the SARS-CoV-2 RNA genome
Zhang, Y., Huang, K. L., Xie, D., Lau, J. Y., Shen, W., Li, P., Wang, D., Zou, Z., Shu, S., Ren, H., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25999-1 · Cited by 64
Self-citationTiny giants of gene regulation: experimental strategies for microRNA functional studies
Steinkraus, B. R., Tögel, M., & Fulga, T. A. (2016) · Wiley Interdisciplinary Reviews Developmental Biology · doi:10.1002/wdev.223 · Cited by 64
The Future of Cross-Linking and Immunoprecipitation (CLIP)Preprint
Ule, J., Hwang, H., & Darnell, R. B. (2018) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a032243 · Cited by 65
Weiss, C. N., & Ito, K. (2017) · International review of cytology · doi:10.1016/bs.ircmb.2017.03.007 · Cited by 63
piRTarBase: a database of piRNA targeting sites and their roles in gene regulation
Wu, W.-S., Brown, J. S., Chen, T.-T., Chu, Y.-H., Huang, W.-C., Tu, S., & Lee, H.-C. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky956 · Cited by 59
RNA structures in alternative splicing and back‐splicing
Xu, B., Meng, Y., & Jin, Y. (2020) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1626 · Cited by 63
Transcriptome-wide analysis of protein–RNA interactions using high-throughput sequencing
Milek, M., Wyler, E., & Landthaler, M. (2011) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2011.12.001 · Cited by 64
KARR-seq reveals cellular higher-order RNA structures and RNA–RNA interactions
Wu, T., Cheng, A. Y., Zhang, Y., Xu, J., Wu, J., Wen, L., Li, X., Liu, B., Dou, X., Wang, P., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-02109-8 · Cited by 57
The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis
Pinkney, H. R., Wright, B. M., & Diermeier, S. D. (2020) · Non-Coding RNA · doi:10.3390/ncrna6040049 · Cited by 56
ncPred: ncRNA-Disease Association Prediction through Tripartite Network-Based Inference
Alaimo, S., Giugno, R., & Pulvirenti, A. (2014) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2014.00071 · Cited by 56
irCLASH reveals RNA substrates recognized by human ADARs
Song, Y., Yang, W., Fu, Q., Wu, L. L., Zhao, X., Zhang, Y., & Zhang, R. (2020) · Nature Structural & Molecular Biology · doi:10.1038/s41594-020-0398-4 · Cited by 56
A pre-ribosomal RNA interaction network involving snoRNAs and the Rok1 helicase
Martin, R., Hackert, P., Ruprecht, M., Simm, S., Brüning, L., Mirus, O., Sloan, K. E., Kudla, G. R., Schleiff, E., & Bohnsack, M. T. (2014) · RNA · doi:10.1261/rna.044669.114 · Cited by 54
Self-citationGlobal in situ profiling of RNA-RNA spatial interactions with RIC-seq
Cao, C., Cai, Z., Ye, R., Su, R., Hu, N., Zhao, H., & Xue, Y. (2021) · Nature Protocols · doi:10.1038/s41596-021-00524-2 · Cited by 51
Decoding protein–RNA interactions using CLIP-based methodologies
Xiang, J. S., Schafer, D. M., Rothamel, K. L., & Yeo, G. W.-M. (2024) · Nature Reviews Genetics · doi:10.1038/s41576-024-00749-3 · Cited by 50
Yoon, J., & Gorospe, M. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-3378-5_2 · Cited by 48
The evolution of RNA structural probing methods: From gels to next‐generation sequencing
Mailler, É., Paillart, J., Marquet, R., Smyth, R. P., & Vivet‐Boudou, V. (2018) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1518 · Cited by 52
Metadata
- Authors
- Kudla, G., Granneman, S., Hahn, D., Beggs, J. D., & Tollervey, D.
- Affiliations
- Wellcome Centre for Cell Biology (GB)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2011-05-24
- Volume
- 108
- Issue
- 24
- Pages
- 10010-10015
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC3116431
- OpenAlex
- W2117165052
- Cited by
- 308
- References
- 39
- Citations by year
- 2026: 12 · 2025: 16 · 2024: 17 · 2023: 23 · 2022: 22 · 2021: 22 · 2020: 25 · 2019: 16 · 2018: 37 · 2017: 25 · 2016: 32 · 2015: 22 · 2014: 12 · 2013: 16 · 2012: 9
- FWCI
- 5.07
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Funders
- Wellcome Trust
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
- Keywords
- RNA-RNA interactions, CLASH, box C/D snoRNA, small nucleolar RNA, pre-rRNA, U3 snoRNA, U2 snRNA, spliceosome, RNA secondary structure, Saccharomyces cerevisiae
- MeSH terms
- Base Sequence, Models, Molecular, Molecular Sequence Data, Nucleic Acid Conformation, RNA, Fungal, RNA, Ribosomal, RNA, Ribosomal, 18S, RNA, Small Nuclear, Saccharomyces cerevisiae, Blotting, Northern, Spliceosomes, Sequence Analysis, DNA, DNA, Complementary, RNA, Small Nucleolar
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
