The DOI matches its Crossref record; 47 of the 47 references it cites were found in a registry or an index; none of the 44 sources its claims cite is checked for support yet.
A compendium of RNA-binding motifs for decoding gene regulation
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RNA-binding proteins are key regulators of gene expression, yet only a small fraction have been functionally characterized. Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes. The sequence specificities of RNA-binding proteins display deep evolutionary conservation, and the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence. The motifs that we identify in vitro correlate well with in vivo RNA-binding data. Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation, enabling new insights into the functions of RNA-binding proteins both in normal physiology and in human disease. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.
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“Among the 207 RBPs we initially analysed, most yielded RNA-binding data distinct from that obtained from all other proteins”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
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“However, RNAcompete motifs are predictive of RNA sequences bound by the same proteins (or their close homologues) in vivo”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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“The motifs that we identify in vitro correlate well with in vivo RNA-binding data.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
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“In almost all cases, E scores for 7-mers from the two halves of the RNAcompete pool for a given protein are more similar to each other than to those of other assayed proteins”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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“Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
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“The major exception is that proteins with closely related RBDs typically yield very similar data.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
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In the paper
“The sequence specificities of RNA-binding proteins display deep evolutionary conservation”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
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“all RBPs in the SUP12–RBM24–RBM38 cluster (Fig. 2, inset 2) prefer similar (G1U)-rich sequences.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
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“uncover an unexpected role for a splicing factor in the control of transcript abundance that is mis-regulated in autism.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
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“for example, for QKI (quaking), the AUROC for the RNAcompete motif was 93% versus 83% for the literature motif.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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In the paper
“We initially determined the sequence preferences for 207 different RBPs, corresponding to seven different structural classes and representing the products of 193 unique RBP-encoding genes”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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“The vast majority of RBPs appear to bind target sequences in ssRNA, and none absolutely requires a specific RNA secondary structure, although 22 RBPs display a significant preference for (n = 7) or against (n = 15) predicted hairpin loops”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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“The analysed RBPs included 85 from human, 61 from Drosophila and an additional 61 from 18 other eukaryotes selected to be dissimilar to already profiled RBPs.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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In the paper
“Most of these have obvious similarity to our RNAcompete-derived motifs (Supplementary Data 5; 35 very similar, six partial matches, and 11 discrepancies).”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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In the paper
“motifs for the alternative splicing factorsRBFOX1, RBFOX2 and RBFOX3 (ref. 4) are conserved in introns downstream of alternative exons, whereas sites for the stability/translation factors PUM1 and PUM2 are most highly conserved in 3′ UTRs24,25”
§ A compendium of RNA-binding motifs for decoding gene regulation > Sequence conservation of motif matches
What the sources say
- Not checked yetcites [4] Gabut, M., Chaudhry, S. & Blencowe, B. J. SnapShot: The splicing regulatory machinery. Cell 133, 192.e1 (2008) source
- Not checked yetcites [24] Yeo, G. W. et al. An RNA code for the FOX2 splicing regulator revealed by mapping RNA-protein interactions in stem cells. Nature Struct. Mol. Biol. 16, 130–137 (2009) source
- Not checked yetcites [25] Morris, A. R., Mukherjee, N. & Keene, J. D. Ribonomic analysis of human Pum1 reveals cis-trans conservation across species despite evolution of diverse mRNA target sets. Mol. Cell. Biol. 28, 4093–4103 (2008) source
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In the paper
“This analysis identified several known regulators of mRNA stability, including RBM4 and ELAVL1 (refs 31, 32), and correctly predicted the direction of their effect (destabilizing for RBM4 and stabilizing for ELAVL1”
§ A compendium of RNA-binding motifs for decoding gene regulation > Insights into RBP multi-functionality
What the sources say
- Not checked yetcites [31] Markus, M. A. & Morris, B. J. RBM4: a multifunctional RNA-binding protein. Int. J. Biochem. Cell Biol. 41, 740–743 (2009) source
- Not checked yetcites [32] Myer, V. E., Fan, X. C. & Steitz, J. A. Identification of HuR as a protein implicated in AUUUA-mediated mRNA decay. EMBO J. 16, 2130–2139 (1997) source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“very different motifs have been previously described for different HNRNPA family members from human and Drosophila19–22, whereas the RNAcompete motifs for the same proteins are closely related”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
What the sources say
- Not checked yetcites [19] Huelga, S. C. et al. Integrative genome-wide analysis reveals cooperative regulation of alternative splicing by hnRNP proteins. Cell Rep. 1, 167–178 (2012) source
- Not checked yetcites [20] Burd, C. G. & Dreyfuss, G. RNA binding specificity of hnRNP A1: significance of hnRNP A1 high-affinity binding sites in pre-mRNA splicing. EMBO J. 13, 1197–1204 (1994) source
- Not checked yetcites [21] Blanchette, M. et al. Genome-wide analysis of alternative pre-mRNA splicing and RNA-binding specificities of the Drosophila hnRNP A/B family members. Mol. Cell 33, 438–449 (2009) source
- Not checked yetcites [22] Goodarzi, H. et al. Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature 485, 264–268 (2012) source
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In the paper
“family members from fungi, protists and algae have all maintained the presumed ancestral CAC core-recognition specificity17, but differ in their preference for flanking nucleotides”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
What the sources say
- Not checked yetcites [17] Stefl, R., Skrisovska, L. & Allain, F. H. RNA sequence- and shape-dependent recognition by proteins in the ribonucleoprotein particle. EMBO Rep. 6, 33–38 (2005) source
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In the paper
“These fragments succeed more often than full-length proteins or individual RBDs in trial experiments (Supplementary Table 1) and yield data that are consistent with previously known motifs”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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In the paper
“in some cases motifs can even be predicted on the basis of specific interactions between DNA-contacting amino acid residues and DNA bases9,10”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
What the sources say
- Not checked yetcites [9] Christensen, R. G. et al. Recognition models to predict DNA-binding specificities of homeodomain proteins. Bioinformatics 28, i84–i89 (2012) source
- Not checked yetcites [10] Liu, J. & Stormo, G. D. Context-dependent DNA recognition code for C2H2 zinc-finger transcription factors. Bioinformatics 24, 1850–1857 (2008) source
plainconditional- Asserted: passes — The authors put it forward as true.
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In the paper
“The motifs for DNA-binding proteins can be highly similar for closely related proteins, allowing accurate inference of motifs7,8”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
What the sources say
- Not checked yetcites [7] Noyes, M. B. et al. Analysis of homeodomain specificities allows the family-wide prediction of preferred recognition sites. Cell 133, 1277–1289 (2008) source
- Not checked yetcites [8] Berger, M. F. et al. Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences. Cell 133, 1266–1276 (2008) source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Collectively, these analyses demonstrate that the RNAcompete motifs are generally both accurate and functionally relevant.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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In the paper
“These nematode, mouse and human proteins are regulators of muscle development15,16, indicating both biochemical and functional conservation.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
What the sources say
- Not checked yetcites [15] Miyamoto, S., Hidaka, K., Jin, D. & Morisaki, T. RNA-binding proteins Rbm38 and Rbm24 regulate myogenic differentiation via p21-dependent and -independent regulatory pathways. Genes Cells 14, 1241–1252 (2009) source
- Not checked yetcites [16] Anyanful, A. et al. The RNA-binding protein SUP-12 controls muscle-specific splicing of the ADF/cofilin pre-mRNA in C. elegans . J. Cell Biol. 167, 639–647 (2004) source
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In the paper
“RNA-binding proteins (RBPs) regulate numerous aspects of co- and post-transcriptional gene expression, including RNA splicing, polyadenylation, capping, modification, export, localization, translation and turnover1,2.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
What the sources say
- Not checked yetcites [1] Glisovic, T., Bachorik, J. L., Yong, J. & Dreyfuss, G. RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 582, 1977–1986 (2008) source
- Not checked yetcites [2] Keene, J. D. RNA regulons: coordination of post-transcriptional events. Nature Rev. Genet. 8, 533–543 (2007) source
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In the paper
“Canonical RBDs typically bind short, single-stranded (ss)RNA sequences3,4, but some also recognize structured RNAs5.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
What the sources say
- Not checked yetcites [3] 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) source
- Not checked yetcites [4] Gabut, M., Chaudhry, S. & Blencowe, B. J. SnapShot: The splicing regulatory machinery. Cell 133, 192.e1 (2008) source
- Not checked yetcites [5] Auweter, S. D., Oberstrass, F. C. & Allain, F. H. Sequence-specific binding of single-stranded RNA: is there a code for recognition? Nucleic Acids Res. 34, 4943–4959 (2006) source
plaincorrelational- Asserted: passes — The authors put it forward as true.
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In the paper
“A minority of the thousands of RBD-containing proteins in eukaryotic genomes have been studied in detail, and the assays used to generate the motifs are heterogeneous.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
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In the paper
“For internal cross-validation, the pool was divided into two halves, each of which contained at least eight copies of all possible 9-mers, 33 copies of each 8-mer, and 155 copies of each 7-mer.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Large-scale analysis of RBPs
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In the paper
“The human genome, for example, encodes 239 proteins with RRM domains and 38 with KH domains, among a total of 424 known and predicted RBPs3.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
What the sources say
- Not checked yetcites [3] 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) source
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“For example, 15% of human, 8% of Drosophila and 3% of Caenorhabditis elegans RBD-containing proteins have known RNA-binding motifs3”
§ A compendium of RNA-binding motifs for decoding gene regulation > Abstract
What the sources say
- Not checked yetcites [3] 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) source
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Collectively, these analyses indicated previously unanticipated roles in alternative splicing and/or mRNA stability for known RBPs with well-defined sequence preferences as well as for uncharacterized RBPs.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Insights into RBP multi-functionality
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In the paper
“The marked change in the central ‘UCAC’ in the unusual consensus in Trypanosoma brucei (HUUCACR) seems to correspond to the unusual T. brucei U1 loop sequence (CAUCAC versus AUUGCAC in most other species).”
§ A compendium of RNA-binding motifs for decoding gene regulation > Conservation of ancient motifs
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In the paper
“In other cases (for example, PUM1 and PUM2), the direction of the effect was counter to expectation33, indicating that correlation may reflect possible additional functional roles for these proteins and/or their binding motifs.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Insights into RBP multi-functionality
What the sources say
- Not checked yetcites [33] Van Etten, J. et al. Human Pumilio proteins recruit multiple deadenylases to efficiently repress messenger RNAs. J. Biol. Chem. 287, 36370–36383 (2012) source
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In the paper
“The analyses above show that RBP motifs can be readily used to infer human post-transcriptional regulation mechanisms, and can explain evolutionary constraints found within both coding and non-coding regions of transcripts.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Discussion
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In the paper
“This analysis suggests that RBP multi-functionality may be more widespread than previously appreciated; motifs for most (38 out of 49) RBP families shown in Fig. 4a display significant conservation in more than one of the three regions examined.”
§ A compendium of RNA-binding motifs for decoding gene regulation > Sequence conservation of motif matches
hedgedconditional- Asserted: passes — The authors put it forward as true.
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The authors state this as an assumption.
A closely related RNA motif will be bound by any protein that has more than 70% sequence identity in its RBDs to those in one of the 207 proteins analyzed.
“If we assume that a closely related RNA motif will be bound by any protein that has >70% sequence identity in its RBDs to those in one of the 207 proteins that we analysed”
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 check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Computational analysis suggested that the miR-140-5p-G seed in the Ago2 complex and the RBP, Ybx1 (also known as YB-1), potentially compete for the same RNA binding sites”
From Gain-of-function mutation of microRNA-140 in human skeletal dysplasia (2019) · cites this paper as [30]
Experimental — accuracy not yet measuredThe check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“Next, Ybx1 seCLIP analysis identified a binding motif similar to the Ybx1 binding motif reported previously30–32”
From Gain-of-function mutation of microRNA-140 in human skeletal dysplasia (2019) · cites this paper as [30]
Experimental — accuracy not yet measuredIn the citing paper
“Several recent findingspropose that Rbfox can also regulate alternative polyadenylation (Wang et al., 2008) and mRNA stability (Ray et al., 2013), based on analysis of Rbfox motif sites in 3′ UTRs that are correlated with transcript abundance in different tissues.”
From HITS-CLIP and integrative modeling define the Rbfox splicing-regulatory network linked to brain development and autism (2014) · cites this paper as Ray et al., 2013
Citations
Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625
Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega
Sievers, F., Wilm, A., Dineen, D., Gibson, T., Karplus, K., Li, W.-Z., Lopez, R., McWilliam, H., Remmert, M., Söding, J., et al. (2011) · Molecular Systems Biology · doi:10.1038/msb.2011.75 · Cited by 15,576
Self-citationInsights 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
Transcriptomic Analysis of Autistic Brain Reveals Convergent Molecular Pathology
Voineagu, I., Wang, X., Johnston, P., Lowe, J. K., Tian, Y., Horvath, S., Mill, J., Cantor, R. M., Blencowe, B. J., & Geschwind, D. H. (2011) · Nature · doi:10.1038/nature10110 · Cited by 1,874
Self-citationRNA‐binding proteins and post‐transcriptional gene regulation
Glisovic, T., Bachorik, J. L., Yong, J., & Dreyfuss, G. (2008) · FEBS Letters · doi:10.1016/j.febslet.2008.03.004 · Cited by 1,398
HITS-CLIP yields genome-wide insights into brain alternative RNA processing
Licatalosi, D. D., Mele, A., Fak, J. J., Ule, J., Kayikci, M., Chi, S. W., Clark, T. A., Schweitzer, A. C., Blume, J. E., Wang, X., et al. (2008) · Nature · doi:10.1038/nature07488 · Cited by 1,352
RNA regulons: coordination of post-transcriptional events
Keene, J. D. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2111 · Cited by 1,321 · cited 1×
“To systematically seek possible roles for RBPs in mRNA stability, we identified cases in which there is a relationship between (1) the appearance of one or more strong motifs for an RBP in the 39 UTR, and (2) (anti-)correlation of the abundance of the transcript and the mRNA expression level of the RBP, over a diverse…”
Lécuyer, E., Yoshida, H., Parthasarathy, N., Alm, C., Babak, T., Cerovina, T., Hughes, T. R., Tomancak, P., & Krause, H. M. (2007) · Cell · doi:10.1016/j.cell.2007.08.003 · Cited by 967
Barash, Y., Calarco, J. A., Gao, W., Pan, Q., Wang, X., Shai, O., Blencowe, B. J., & Frey, B. J. (2010) · Nature · doi:10.1038/nature09000 · Cited by 925
RBPDB: a database of RNA-binding specificities
Cook, K. B., Kazan, H., Zuberi, K., Morris, Q., & Hughes, T. R. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1069 · Cited by 638
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Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
Alipanahi, B., Delong, A., Weirauch, M. T., & Frey, B. J. (2015) · Nature Biotechnology · doi:10.1038/nbt.3300 · Cited by 2,873
“We also applied models trained on in vitro RNAcompete data to in vivo CLIP-seq (crosslinking and immunoprecipitation followed by high-throughput sequencing) and RIP-seq (RNA-immunoprecipitation sequencing) data 22 .”
BackgroundMethodSelf-citationA census of human RNA-binding proteins
Gerstberger, S., Hafner, M., & Tuschl, T. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3813 · Cited by 2,032
“sites (Ascano et al., 2012a; Ray et al., 2013; Spencer et al., 2006; Todd et al., 2001), and the evolution of paralogs represent an alternative to facilitating regulation across cell types.”
BackgroundDetermination and Inference of Eukaryotic Transcription Factor Sequence Specificity
Weirauch, M. T., Yang, A. W. H., Albu, M., Coté, A. G., Montenegro‐Montero, A., Drewe, P., Najafabadi, H. S., Lambert, S. A., Mann, I. K., Cook, K. B., et al. (2014) · Cell · doi:10.1016/j.cell.2014.08.009 · Cited by 1,749
Self-citationN6-methyladenosine-dependent RNA structural switches regulate RNA–protein interactions
Liu, N., Dai, Q., Zheng, G., He, C., Parisien, M., & Pan, T. (2015) · Nature · doi:10.1038/nature14234 · Cited by 1,988
A brave new world of RNA-binding proteins
Hentze, M. W., Castello, A., Schwarzl, T., & Preiss, T. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.130 · Cited by 1,821
Mechanisms and Regulation of Alternative Pre-mRNA Splicing
Lee, Y., & Rio, D. C. (2015) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060614-034316 · Cited by 1,291
The human splicing code reveals new insights into the genetic determinants of disease
Xiong, H. Y., Alipanahi, B., Lee, L. J., Bretschneider, H., Merico, D., Yuen, R. K. C., Hua, Y., Gueroussov, S., Najafabadi, H. S., Hughes, T., et al. (2014) · Science · doi:10.1126/science.1254806 · Cited by 1,243
“Because the model was built using the reference genome only, its performance was first validated using held-out data, including additional RNA-seq (54), RT-PCR, RBP binding (14), and MBNL knockdown (15) data sets.”
BackgroundMethodSelf-citationSotillo, E., Barrett, D. M., Black, K. L., Bagashev, A., Oldridge, D. A., Wu, G. S., Sussman, R. T., Lanauze, C. B., Ruella, M., Gazzara, M. R., et al. (2015) · Cancer Discovery · doi:10.1158/2159-8290.cd-15-1020 · Cited by 1,279
“However, the Drosophila homolog of SRSF3, RBP-1, is known to bind to the [A/T] CAAC[A/G] hexamer (23).”
BackgroundSystematic Discovery of Xist RNA Binding Proteins
Chu, C., Zhang, Q. C., da Rocha, S. T., Flynn, R. A., Bharadwaj, M. C., Calabrese, J. M., Magnuson, T., Heard, É., & Chang, H. Y. (2015) · Cell · doi:10.1016/j.cell.2015.03.025 · Cited by 1,100
Context-dependent control of alternative splicing by RNA-binding proteins
Fu, X.-D., & Ares, M. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3778 · Cited by 1,044
Functional 5′ UTR mRNA structures in eukaryotic translation regulation and how to find them
Leppek, K., Das, R., & Barna, M. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.103 · Cited by 949
The BioGRID interaction database: 2015 update
Chatr‐aryamontri, A., Breitkreutz, B., Oughtred, R., Boucher, L., Heinicke, S., Chen, D., Stark, C., Breitkreutz, A., Kolas, N. K., O’Donnell, L., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1204 · Cited by 911
“At the same time, sequencing-based meth-ods have uncovered many intricacies of gene regulation at a genomic scale, including expression patterns, alternative splicing, non-coding transcription and the myriad of regulatory factors that bind DNA and RNA (7–11).”
BackgroundApplications of deep learning and reinforcement learning to biological data
Mahmud, M., Kaiser, M. S., Hussain, A., & Vassanelli, S. (2018) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2018.2790388 · Cited by 765
“data, and classifying and detecting cancers from them (D); and predicting DNA- and RNA-sequence specificity (E), RNA binding proteins (F), and micro RNA precursors (G). Ray et al.: method proposed in [148]. 12/32 DUD-E dataset (reported in [187]), the RF based method outperforms the CNN based method. This may be attri…”
MethodStructural imprints in vivo decode RNA regulatory mechanisms
Spitale, R. C., Flynn, R. A., Zhang, Q. C., Crisalli, P., Lee, B., Jung, J., Kuchelmeister, H. Y., Batista, P. J., Torre, E. A., Kool, E. T., et al. (2015) · Nature · doi:10.1038/nature14263 · Cited by 760
Revealing protein–lncRNA interaction
Ferrè, F., Colantoni, A., & Helmer‐Citterich, M. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv031 · Cited by 700
Imamura, K., Imamachi, N., Akizuki, G., Kumakura, M., Kawaguchi, A., Nagata, K., Kato, A., Kawaguchi, Y., Sato, H., Yoneda, M., et al. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.01.009 · Cited by 688
STREME: accurate and versatile sequence motif discovery
Bailey, T. L. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab203 · Cited by 631
RBPmap: a web server for mapping binding sites of RNA-binding proteins
Paz, I., Kosti, I., Ares, M., Cline, M., & Mandel‐Gutfreund, Y. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku406 · Cited by 581
“Recently, Ray et al. have used thousands of short designed RNA oligos to determine the binding preferences of 207 different RBPs, mainly from human and Drosophila melanogaster (3).”
BackgroundRegulation by 3′-Untranslated Regions
Mayr, C. (2017) · Annual Review of Genetics · doi:10.1146/annurev-genet-120116-024704 · Cited by 588
“functional screens with newly developed in vitro methods that identify high-affinity motifs of RBPs (14, 74, 104) will help to shed light on the multilayered regulation accomplished by 3′-UTRs.”
BackgroundSequence, Structure, and Context Preferences of Human RNA Binding Proteins
Dominguez, D., Freese, P., Alexis, M. S., Su, A., Hochman, M., Palden, T., Bazile, C., Lambert, N. J., Van Nostrand, E. L., Pratt, G. A., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.05.001 · Cited by 562
The rules and impact of nonsense-mediated mRNA decay in human cancers
Lindeboom, R. G. H., Supek, F., & Lehner, B. (2016) · Nature Genetics · doi:10.1038/ng.3664 · Cited by 563
Synonymous Mutations Frequently Act as Driver Mutations in Human Cancers
Supek, F., Miñana, B., Valcárcel, J., Gabaldón, T., & Lehner, B. (2014) · Cell · doi:10.1016/j.cell.2014.01.051 · Cited by 575
“The shown SF2/ASF motif is from Smith et al. (2006) and the hnRNP H2 motif is from Ray et al. (2013).”
InfluentialTDP-43 loss and ALS-risk SNPs drive mis-splicing and depletion of UNC13A
Brown, A., Wilkins, O. G., Keuss, M. J., Kargbo-Hill, S. E., Zanovello, M., Lee, W. C., Bampton, A., Lee, F. C. Y., Masino, L., Qi, Y. A., et al. (2022) · Nature · doi:10.1038/s41586-022-04436-3 · Cited by 545
“SNPs are mainly associated with increased ALS risk (van Es et al., 2009; Nicolas et al., 2018) but also shown to contribute to FTD in sporadic ALS (Placek et al., 2019).”
The Central Dogma Decentralized: New Perspectives on RNA Function and Local Translation in Neurons
Holt, C. E., & Schuman, E. M. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.036 · Cited by 525
Zou, Q., Xing, P., Wei, L., & Liu, B. (2019) · RNA · doi:10.1261/rna.069112.118 · Cited by 525
“We picked out several representative examples of similar known motifs found in previous research (Ray et al. 2013) with convolution kernels help researchers to study the relationship between them in biological experiments.”
BackgroundEnhancer RNAs and regulated transcriptional programs
Lam, M. T. Y., Li, W., Rosenfeld, M. G., & Glass, C. K. (2014) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2014.02.007 · Cited by 522
Self-citationMayr, C. (2019) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a034728 · Cited by 519
“In addition to AU-rich elements, many other cis-regulatory motifs are known (Ray et al. 2013; Dominguez et al. 2018), including those bound by IGF2BP1, Pumilio, PTB, and MBNL.”
BackgroundInfluentialCytoplasmic functions of long noncoding RNAs
Noh, J. H., Kim, K. M., McClusky, W. G., Abdelmohsen, K., & Gorospe, M. (2018) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1471 · Cited by 445
“To identify lncRNPs computationally, many databases have been developed to provide information on RBP target RNAs and RNA-binding motifs using validated protein-RNA interactions (Cook, Kazan, Zuberi, Morris, & Hughes, 2011; Giulietti et al., 2013; Giudice, Sanchez-Cabo, Torroja, & Lara-Pezzi, 2016; Park, Yu, Choi, Kim…”
MethodRMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data
Xuan, J., Sun, W., Lin, P.-H., Zhou, K., Liu, S., Zheng, L., Qu, L., & Yang, J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx934 · Cited by 426
“Interestingly, consistent with a recent report about FMR1 as a sequence-context-dependent m6A reader (47,48), we also discovered FMR1 bound to 74,460 m6A modification sites (Supplementary Figure S2).”
BackgroundA Long Noncoding RNA lincRNA-EPS Acts as a Transcriptional Brake to Restrain Inflammation
Atianand, M., Hu, W., Satpathy, A. T., Shen, Y., Ricci, E. P., Alvarez‐Dominguez, J. R., Bhatta, A., Schattgen, S., McGowan, J. D., Blin, J., et al. (2016) · Cell · doi:10.1016/j.cell.2016.05.075 · Cited by 446
Lambert, N. J., Robertson, A. D., Jangi, M., McGeary, S. E., Sharp, P. A., & Burge, C. B. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.04.016 · Cited by 407
“analysis, enabling high-throughput identification of RNA binding motifs (Ray et al., 2009; Ray et al., 2013).”
BackgroundMethodThe structure, function and evolution of proteins that bind DNA and RNA
Hudson, W. H., & Ortlund, E. A. (2014) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3884 · Cited by 418
Human 5′ UTR design and variant effect prediction from a massively parallel translation assay
Sample, P. J., Wang, B., Reid, D. W., Presnyak, V., McFadyen, I. J., Morris, D. R., & Seelig, G. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0164-5 · Cited by 442
The Role of m6A/m-RNA Methylation in Stress Response Regulation
Engel, M., Eggert, C., Kaplick, P. M., Eder, M., Röh, S., Tietze, L., Namendorf, C., Arloth, J., Weber, P., Rex-Haffner, M., et al. (2018) · Neuron · doi:10.1016/j.neuron.2018.07.009 · Cited by 411
Distinct brain transcriptome profiles in C9orf72-associated and sporadic ALS
Prudencio, M., Belzil, V., Batra, R., Ross, C. A., Gendron, T. F., Pregent, L., Murray, M. E., Overstreet, K., Johnston, A., Desaro, P., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4065 · Cited by 396
“The identified motifs were then cross-referenced with the known binding motifs of RNA-binding proteins (RBP) and literature 36, 66 (RBP database: http:// rbpdb.ccbr.utoronto.ca/), to identify RBPs that may be responsible for AS cassette exon events significantly represented in our dataset.”
SRSF1-Regulated Alternative Splicing in Breast Cancer
Anczuków, O., Akerman, M., Cléry, A., Wu, J., Shen, C., Shirole, N. H., Raimer, A. C., Sun, S., Jensen, M. A., Hua, Y., et al. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.09.005 · Cited by 362
“The published SRSF1 motifs do agree in many respects, such as the general preference for purines or the occurrence of AGGA in the consensus (Pandit et al., 2013; Ray et al., 2013; Sanford et al., 2009; Smith et al., 2006; Tacke and Manley, 1995).”
InfluentialWu, B., Su, S., Patil, D. P., Liu, H., Gan, J., Jaffrey, S. R., & Ma, J. (2018) · Nature Communications · doi:10.1038/s41467-017-02770-z · Cited by 401
“10 support to previous binding site predictions based on analysis of diverse deep sequencing results (Huelga et al., 2012; Ray et al., 2013) (Table 3).”
ResultBechara, E., Sebestyén, E., Bernardis, I., Eyras, E., & Valcárcel, J. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.11.010 · Cited by 374
“recently reported preferred sequence motifs for RBM5 and 6 (Ray et al., 2013).”
BackgroundRNA-binding proteins in tumor progression
Qin, H., Ni, H., Liu, Y., Yuan, Y., Xi, T., Li, X., & Zheng, L. (2020) · Journal of Hematology & Oncology · doi:10.1186/s13045-020-00927-w · Cited by 387
“The RNA recognition motif domain of the Rbfox family protein binds to the 3′UTR region of the target mRNA related to cancer development, which contributes to the stability of the mRNA and thus promotes the progression of cancer [99, 100].”
BackgroundSelf-citationCLIP and complementary methods
Hafner, M., Katsantoni, M., Köster, T., Marks, J., Mukherjee, J., Staiger, D., Ule, J., & Zavolan, M. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00018-1 · Cited by 406
C2H2 zinc finger proteins greatly expand the human regulatory lexicon
Najafabadi, H. S., Mnaimneh, S., Schmitges, F. W., Garton, M., Lam, K. N., Yang, A., Albu, M., Weirauch, M. T., Radovani, E., Kim, P. M., et al. (2015) · Nature Biotechnology · doi:10.1038/nbt.3128 · Cited by 346
Self-citationNew 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
Variant interpretation: functional assays to the rescue
Starita, L. M., Ahituv, N., Dunham, M. J., Kitzman, J. O., Roth, F. P., Seelig, G., Shendure, J., & Fowler, D. M. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.07.014 · Cited by 381
The neurogenetics of alternative splicing
Vuong, C. K., Black, D. L., & Zheng, S. (2016) · Nature Reviews Neuroscience · doi:10.1038/nrn.2016.27 · Cited by 340
Tushev, G., Glock, C., Heumüller, M., Biever, A., Jovanovic, M., & Schuman, E. M. (2018) · Neuron · doi:10.1016/j.neuron.2018.03.030 · Cited by 377
Di, C., Yuan, J., Wu, Y., Li, J., Lin, H., Hu, L., Zhang, T., Qi, Y., Gerstein, M., Guo, Y., et al. (2014) · The Plant Journal · doi:10.1111/tpj.12679 · Cited by 334
Weyn-Vanhentenryck, S. M., Mele, A., Yan, Q., Sun, S., Farny, N., Zhang, Z., Xue, C., Herre, M., Silver, P. A., Zhang, M. Q., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.02.005 · Cited by 333
“, 2008) and mRNA stability (Ray et al., 2013), based on analysis of Rbfox motif sites in 30 UTRs that are correlated with transcript abundance in different tissues.”
InfluentialAlternative mRNA transcription, processing, and translation: insights from RNA sequencing
de Klerk, E., & ‘t Hoen, P. A. C. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.01.001 · Cited by 350
cat RAPID omics: a web server for large-scale prediction of protein–RNA interactions
Agostini, F., Zanzoni, A., Klus, P., Marchese, D., Cirillo, D., & Tartaglia, G. G. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt495 · Cited by 313
“Here we introduce catRAPID omics to perform high-throughput predictions of protein–RNA interactions using the information on protein and RNA domains involved in macromolecular recognition.”
MethodRIC-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
Swarm Intelligence-Enhanced Detection of Non-Small-Cell Lung Cancer Using Tumor-Educated Platelets
Best, M. G., Sol, N., Veld, S. G. J. G. I. ‘., Vancura, A., Muller, M., Niemeijer, A.-L. N., Fejes, A. V., Tjon‐Kon‐Fat, L., Veld, A. E. H. I. ‘., Leurs, C. E., et al. (2017) · Cancer Cell · doi:10.1016/j.ccell.2017.07.004 · Cited by 341
“(ii) All characterized motif sequences extracted from literature (102 in total, Table S3 of Ray et al. (Ray et al., 2013), filtered for Homo Sapiens) are reduced to 547 non-redunant (‘A’, ‘G’, ‘C’, and ‘T’-sequence) annotations according to the IUPAC motif annotation.”
InfluentialRNA Seeds Higher-Order Assembly of FUS Protein
Schwartz, J. C., Wang, X., Podell, E. R., & Cech, T. R. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.11.017 · Cited by 313
Interaction between N6-methyladenosine (m6A) modification and noncoding RNAs in cancer
Chen, Y., Yu, L., Shu, Y., He, J., & Gao, W. (2020) · Molecular Cancer · doi:10.1186/s12943-020-01207-4 · Cited by 288
“m(6)A methylation acts as an RNA structural switch RNA-binding proteins regulate the biological functions of their target RNAs by recognizing and binding to singlestranded RNA-binding motifs (RBMs), but these RBMs are often buried in local RNA structure, thus, avoiding interactions with RNA-binding proteins [48, 49].”
BackgroundA Compendium of RNA-Binding Proteins that Regulate MicroRNA Biogenesis
Treiber, T., Treiber, N., Plessmann, U., Harlander, S., Daiß, J. L., Eichner, N., Lehmann, G. J., Schall, K., Urlaub, H., & Meister, G. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.03.014 · Cited by 309
“For example, mutation of the AUCUU motif (Ray et al., 2013) in miR-29b-2 completely abolishes recognition by MATR3 (Figure 4C).”
BackgroundGraphProt: modeling binding preferences of RNA-binding proteins
Maticzka, D., Lange, S. J., Costa, F., & Backofen, R. (2014) · Genome biology · doi:10.1186/gb-2014-15-1-r17 · Cited by 294
“Both the CLIP-seq and RNAcompete sets (from Figures 3 and 4, respectively) were used to compare models with and without structure information, as shown in Figure 6 (prediction comparisons were performed analo-gously to previous benchmarking analyses).”
BackgroundMethodInfluentialTranslation affects mRNA stability in a codon-dependent manner in human cells
Wu, Q., Medina, S. G., Kushawah, G., DeVore, M. L., Castellano, L. A., Hand, J. M., Wright, M., & Bazzini, A. A. (2019) · eLife · doi:10.7554/elife.45396 · Cited by 283
Transcriptional diversity during lineage commitment of human blood progenitors
Chen, L., Kostadima, M. A., Martens, J. H. A., Canu, G., Garcia, S. P., Turro, E., Downes, K., Macaulay, I. C., Bielczyk-Maczyńska, E., Coe, S., et al. (2014) · Science · doi:10.1126/science.1251033 · Cited by 311
“We used 102 recently described RNA-binding motifs of 80 human RNA-binding proteins (41) to identify sets of motifs significantly enriched or depleted in the regions surrounding DSU junctions (table S13).”
ATtRACT—a database of RNA-binding proteins and associated motifs
Giudice, G., Sánchez‐Cabo, F., Torroja, C., & Lara‐Pezzi, E. (2016) · Database · doi:10.1093/database/baw035 · Cited by 270
“Three are the major available sources of data compiling information on RBPs and their binding sites: (i) RBPDB (3) is a repository of experimentally validated RBPs extracted from literature, (ii) CISBP-RNA (4) contains RBPs and binding sites extracted from in vitro RNAcompete experiments and a portion of the experimen…”
BackgroundInfluentialNeighboring Gene Regulation by Antisense Long Non-Coding RNAs
Villegas, V. E., & Zaphiropoulos, P. G. (2015) · International Journal of Molecular Sciences · doi:10.3390/ijms16023251 · Cited by 320
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
Precise temporal regulation of alternative splicing during neural development
Weyn‐Vanhentenryck, S. M., Feng, H., Ustianenko, D., Duffié, R., Yan, Q., Jacko, M., Martinez, J. C., Goodwin, M., Zhang, X., Hengst, U., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04559-0 · Cited by 272
“…et al. 2013a) or motif enrichment or conservation score, or MECS (Weyn-Vanhentenryck et al. 2014) for the four RBPs we focused on and RNAcompete (Ray et al. 2013) for many additional RBPs), mono-, di-, and tri-mer counts, splice site strength, exon and intron regulatory element counts, and exon…”
BackgroundThe recruitment of chromatin modifiers by long noncoding RNAs: lessons from PRC2
Davidovich, C., & Cech, T. R. (2015) · RNA · doi:10.1261/rna.053918.115 · Cited by 308
“Sequence specificities of RNA-binding proteins often display deep evolutionary conservation, andmotifs identified in vitro often correlate well with in vivo RNA-binding data (Ray et al. 2013).”
BackgroundSpecificity and nonspecificity in RNA–protein interactions
Jankowsky, E., & Harris, M. E. (2015) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm4032 · Cited by 286
SR Proteins: Binders, Regulators, and Connectors of RNA
Jeong-Yu, S. (2017) · Molecules and Cells · doi:10.14348/molcells.2017.2319 · Cited by 286
“Thus, SR-regulated splicing is likely to be modulated by many other RBPs. Recent proteomic analyses have indicated a large number of proteins that may be directly or indirectly linked to mRNA isoform production (Castello et al., 2016; Ray et al., 2013).”
Machine Learning in Genomic Medicine: A Review of Computational Problems and Data Sets
Leung, M. K. K., Delong, A., Alipanahi, B., & Frey, B. J. (2015) · Proceedings of the IEEE · doi:10.1109/jproc.2015.2494198 · Cited by 284
“7 (left) shows a published PFM for modeling the human RBFOX1 protein [35].”
BackgroundMethodInfluentialAdvanced Applications of RNA Sequencing and Challenges
Han, Y., Gao, S., Muegge, K., Zhang, W., & Zhou, B. (2015) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s28991 · Cited by 303
Widespread RNA binding by chromatin-associated proteins
Hendrickson, D. G., Kelley, D. R., Tenen, D. E., Bernstein, B., & Rinn, J. L. (2016) · Genome biology · doi:10.1186/s13059-016-0878-3 · Cited by 258
“In fact, the highest relative lncRNA/mRNA enrichment was observed primarily among the traditional RBPs (HUR, HNRNPU, HNRNPH1 and ADAR, but not IMP1 and PABP).”
MethodInfluentialcat RAPID omics v2.0 : going deeper and wider in the prediction of protein–RNA interactions
Armaos, A., Colantoni, A., Proietti, G., Rupert, J., & Tartaglia, G. G. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab393 · Cited by 235
“RNA-binding proteins with no motifs in the above mentioned resources were assigned those of the most similar RBPs with which they share at least 70% sequence identity, if any (RBPs with this level of sequence identity have been shown to bind similar motifs (22)).”
Systematic Characterization of Stress-Induced RNA Granulation
Namkoong, S., Ho, A., Woo, Y. M., Kwak, H., & Lee, J. H. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.02.025 · Cited by 242
“Sequence motifs for known mouse RNA binding protein (RBP) were acquired from the CISBP-RNA database (Ray et al., 2013).”
BackgroundFunctional classification of long non-coding RNAs by k-mer content
Kirk, J. M., Kim, S. O., Inoue, K., Smola, M. J., Lee, D. M., Schertzer, M. D., Wooten, J. S., Baker, A. R., Sprague, D., Collins, D. W., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0207-8 · Cited by 261
“23 .”
BackgroundMethodInfluentialFTO controls reversible m6Am RNA methylation during snRNA biogenesis
Mauer, J., Sindelar, M., Despic, V., Guez, T., Hawley, B. R., Vasseur, J., Rentmeister, A., Gross, S. S., Pellizzoni, L., Debart, F., et al. (2019) · Nature Chemical Biology · doi:10.1038/s41589-019-0231-8 · Cited by 274
Pathogenic variants that alter protein code often disrupt splicing
Soemedi, R., Cygan, K. J., Rhine, C. L., Wang, J., Bulacan, C., Yang, J. J., Bayrak‐Toydemir, P., McDonald, J., & Fairbrother, W. G. (2017) · Nature Genetics · doi:10.1038/ng.3837 · Cited by 245
“Clustering the functional profiles of human RBP motifs in the 5K panel (see Online Methods) resulted in 19 clusters, with the two largest clusters matching the profile of exonic splicing enhancers and repressors (Fig.”
InfluentialEmerging Roles of Disordered Sequences in RNA-Binding Proteins
Calabretta, S., & Richard, S. (2015) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2015.08.012 · Cited by 246
“Bioinformatics focusing on the specific RNA sequences bound by RBPs have revealed many new RBP–RNA interactions [24].”
BackgroundCompetition 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
CLIPdb: a CLIP-seq database for protein-RNA interactions
Yang, Y., Di, C., Hu, B., Zhou, M., Liu, Y., Song, N., Li, Y., Umetsu, J., & Lu, Z. J. (2015) · BMC Genomics · doi:10.1186/s12864-015-1273-2 · Cited by 240
“The RBPs corresponding to these CLIP-seq data were further annotated with detailed information that was manually curated from other databases, such as NCBI [25], CISBP-RNA [26] and RBPDB [27].”
MethodPan, X., Rijnbeek, P. R., Yan, J., & Shen, H. (2018) · BMC Genomics · doi:10.1186/s12864-018-4889-1 · Cited by 249
“As proposed by DeepBind, the the filter_length (motif width) should be 1.5 times the verified motif width, which is 7 in CISBP-RNA database [48].”
MethodInfluentialSebestyén, E., Singh, B., Miñana, B., Pagès, A., Mateo, F., Pujana, M. A., Valcárcel, J., & Eyras, E. (2016) · Genome Research · doi:10.1101/gr.199935.115 · Cited by 276
“RNA binding motif enrichment RNAcompete motifs (Ray et al. 2013) were used for analysis.”
MethodInfluentialAlternative splicing during mammalian organ development
Mazin, P., Khaitovich, P., Cardoso-Moreira, M., & Kaessmann, H. (2021) · Nature Genetics · doi:10.1038/s41588-021-00851-w · Cited by 219
Motif-based analysis of large nucleotide data sets using MEME-ChIP
Ma, W., Noble, W. S., & Bailey, T. L. (2014) · Nature Protocols · doi:10.1038/nprot.2014.083 · Cited by 244
“MEME-ChIP’s motif databases include DNA and RNA motifs assayed by using in vitro approaches (e.g., SELEX 33 , protein binding microarray 18 , competitive RNA binding 21 ) and in vivo motifs (e.g. JASPAR 17 ).”
MethodCytoplasmic Rbfox1 Regulates the Expression of Synaptic and Autism-Related Genes
Lee, J.-A., Damianov, A., Lin, C.-H., Fontes, M., Parikshak, N. N., Anderson, E. S., Geschwind, D. H., Black, D. L., & Martin, K. C. (2016) · Neuron · doi:10.1016/j.neuron.2015.11.025 · Cited by 232
“…distance from GCAUG motif (Figure S7D), indicating that the miRNA sites e autism genes, SFARI ASD (Basu et al., 2009), ASD-associated co-expression rnell et al., 2011), Rbox1 3ʹ UTR stability targets (Ray et al., 2013), and coment values for overrepresenting sets with odds ratio >1.5 are shown.”
BackgroundInfluentialGeorgilis, A., Klotz, S., Hanley, C. J., Herranz, N., Weirich, B., Morancho, B., Leote, A. C., D'Artista, L., Gallage, S., Seehawer, M., et al. (2018) · Cancer Cell · doi:10.1016/j.ccell.2018.06.007 · Cited by 237
Intrinsically disordered RGG/RG domains mediate degenerate specificity in RNA binding
Akdogan‐Ozdilek, B., Thompson, V. F., Ahmed, N. S., White, C. I., Batey, R., & Schwartz, J. C. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx460 · Cited by 228
“These results agree well with three prior structural studies of the FUS RRM (49–51).”
BackgroundRBFOX and PTBP1 proteins regulate the alternative splicing of micro-exons in human brain transcriptsPreprint
Li, Y., Sánchez‐Pulido, L., Haerty, W., & Ponting, C. P. (2014) · Genome Research · doi:10.1101/gr.181990.114 · Cited by 242
“Because higher thymine and cytosine content can strengthen polypyrimidine tracts and enhance splicing, we searched for thymine-rich motifs within a compendium of RNA-binding motifs (Ray et al. 2013) that are more strongly enriched upstream of CS micro-exons compared to other classes of exons.”
BackgroundMethodBuenrostro, J. D., Araya, C. L., Chircus, L. M., Layton, C. J., Chang, H. Y., Snyder, M. P., & Greenleaf, W. J. (2014) · Nature Biotechnology · doi:10.1038/nbt.2880 · Cited by 220
“…dependence of RNA-protein interactions include medium-throughput microfluidic methods 18 and high-throughput methods coupling affinity-based selection with high-throughput DNA sequencing or array hybridization 19 , which recently have been used to generate a catalog of RNA binding motifs 20 .”
MethodA Deep Neural Network for Predicting and Engineering Alternative Polyadenylation
Bogard, N., Linder, J., Rosenberg, A. B., & Seelig, G. (2019) · Cell · doi:10.1016/j.cell.2019.04.046 · Cited by 215
“We cross-referenced the PWMs with published binding data, as well as the Compendium of RNA Binding Protein motifs (Ray et al., 2013) using the Tomtom comparison tool (Gupta et al., 2007), and surveyed the top-scoring results for APA mediators.”
MethodShort linear motifs – ex nihilo evolution of protein regulation
Davey, N. E., Cyert, M., & Moses, A. M. (2015) · Cell Communication and Signaling · doi:10.1186/s12964-015-0120-z · Cited by 228
“binding site (4 nucleotides) [124]; a single Zinc Finger recognition site (3 nucleotides) [125]; and an miRNA seed regions (6–8 nucleotides) [126].”
BackgroundBiochemical Properties and Biological Functions of FET Proteins
Schwartz, J. C., Cech, T. R., & Parker, R. (2014) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060614-034325 · Cited by 236
Guo, R., Zheng, L., Park, J. W., Lyu, R., Chen, H., Jiao, F., Xu, W., Mu, S.-R., Wen, H., Qiu, J., et al. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.08.022 · Cited by 237
“In contrast, we did not observe any other unique features at the 30 splice sites or any significant reported motifs for RNA-binding proteins and splicing factors in the first 250 bp and the last 250 bp of the introns (Anderson et al., 2012; Ray et al., 2013).”
Cuperus, J. T., Groves, B., Kuchina, A., Rosenberg, A. B., Jojic, N., Fields, S., & Seelig, G. (2017) · Genome Research · doi:10.1101/gr.224964.117 · Cited by 205
RNA localization is a key determinant of neurite-enriched proteome
Zappulo, A., van den Bruck, D., Mattioli, C. C., Franke, V., Imami, K., McShane, E., Moreno‐Estellés, M., Calviello, L., Filipchyk, A., Peguero-Sánchez, E., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00690-6 · Cited by 217
Gruber, A. J., Schmidt, R., Gruber, A. J., Martin, G., Ghosh, S., Belmadani, M., Keller, W., & Zavolan, M. (2016) · Genome Research · doi:10.1101/gr.202432.115 · Cited by 213
Loughlin, F. E., Lukavsky, P. J., Kazeeva, T., Reber, S., Hock, E., Colombo, M., von Schroetter, C., Pauli, P., Cléry, A., Mühlemann, O., et al. (2018) · Molecular Cell · doi:10.1016/j.molcel.2018.11.012 · Cited by 207
“, 2011); CG-rich (Ray et al., 2013), AUU-rich (Hoell et al.”
BackgroundSong, Y., Botvinnik, O. B., Lovci, M. T., Kakaradov, B., Liu, P., Xu, J. L., & Yeo, G. W. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.06.003 · Cited by 204
Li, L., Chen, H., Gao, Y., Wang, Y., Zhang, G., Pan, S., Ji, L., Kong, R., Wang, G., Jia, Y.-H., et al. (2016) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-16-0008 · Cited by 231
“TIA-1 functioned as ancient DNA/RNA trans-acting regulator to broaden the transcriptome and proteome diversity (45, 46).”
BackgroundPost-transcriptional Regulatory Functions of Mammalian Pumilio Proteins
Goldstrohm, A. C., Hall, T. M. T., & McKenney, K. M. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.09.006 · Cited by 198
Pan, X., & Shen, H. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1561-8 · Cited by 200
“For example, there are 5 known motifs (M031, M108, M112, M127, M232) in study [34] for protein ELAVL1-2, and all of them have been correctly discovered by iDeep.”
BackgroundMethodInfluentialRPI-Pred: predicting ncRNA-protein interaction using sequence and structural information
Venkateswaran, S., Liu, L., Adjeroh, D., & Zhou, X. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv020 · Cited by 222
“In despite of the increasing amount (∼400) of successfully identified RNA binding proteins (RBP) in the human genome (25,26), we still lack a complete understanding of RPI complexes and their roles in post-transcriptional regulatory networks (7,27).”
BackgroundBCLAF1 and its splicing regulator SRSF10 regulate the tumorigenic potential of colon cancer cells
Zhou, X., Li, X., Cheng, Y., Wu, W., Xie, Z., Xi, Q., Han, J. S., Wu, G., Fang, J. S., & Feng, Y. (2014) · Nature Communications · doi:10.1038/ncomms5581 · Cited by 192
Self-citationRecurrent chimeric fusion RNAs in non-cancer tissues and cells
Babiceanu, M., Qin, F., Xie, Z., Jia, Y., Lopez, K., Janus, N., Facemire, L., Kumar, S., Pang, Y., Qi, Y., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw032 · Cited by 208
LARP1 functions as a molecular switch for mTORC1-mediated translation of an essential class of mRNAs
Hong, S., Freeberg, M., Han, T., Kamath, A., Yao, Y., Fukuda, T., Suzuki, T., Kim, J. K., & Inoki, K. (2017) · eLife · doi:10.7554/elife.25237 · Cited by 208
Metadata
- Authors
- Ray, D., Kazan, H., Cook, K. B., Weirauch, M. T., Najafabadi, H. S., Li, X., Gueroussov, S., Albu, M., Zheng, H., Yang, A., Na, H., Irimia, M., Matzat, L. H., Dale, R. K., Smith, S. A., Yarosh, C. A., Kelly, S. M., Nabet, B., Mecenas, D., Li, W., Laishram, R. S., Qiao, M., Lipshitz, H. D., Piano, F., Corbett, A. H., Carstens, R. P., Frey, B. J., Anderson, R. A., Lynch, K. W., Penalva, L. O. F., Lei, E. P., Fraser, A. G., Blencowe, B. J., Morris, Q. D., & Hughes, T. R.
- Affiliations
- University of Toronto (CA)
- National Institutes of Health (US)
- University of Pennsylvania (US)
- Emory University (US)
- New York University (US)
- University of Wisconsin–Madison (US)
- The University of Texas at San Antonio Health Science Center (US)
- Corresponding author
- Morris, Quaid D.
- Hughes, Timothy R.
- ORCID
- Ray, Debashish
- Kazan, Hilal
- Cook, Kate B.
- Weirauch, Matthew T.
- Najafabadi, Hamed S.
- Li, Xiao
- Gueroussov, Serge
- Albu, Mihai
- Zheng, Hong
- Yang, Ally
- Irimia, Manuel
- Dale, Ryan K.
- Smith, Sarah A.
- Kelly, Seth M.
- Nabet, Behnam
- Mecenas, Desirea
- Li, Weimin
- Laishram, Rakesh S.
- Lipshitz, Howard D.
- Piano, Fabio
- Corbett, Anita H.
- Carstens, Russ P.
- Anderson, Richard A.
- Lynch, Kristen W.
- Penalva, Luiz O. F.
- Lei, Elissa P.
- Fraser, Andrew G.
- Blencowe, Benjamin J.
- Morris, Quaid D.
- Hughes, Timothy R.
- Venue
- Nature
- Published
- 2013-07
- Volume
- 499
- Issue
- 7457
- Pages
- 172-177
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3929597
- OpenAlex
- W2105694586
- Semantic Scholar
- 6943c053b8d7b29e384c45d180d2da4bac8434cc
- Cited by
- 1,480
- References
- 47
- Citations by year
- 2026: 71 · 2025: 85 · 2024: 130 · 2023: 98 · 2022: 118 · 2021: 135 · 2020: 118 · 2019: 129 · 2018: 131 · 2017: 119 · 2016: 108 · 2015: 106 · 2014: 106 · 2013: 24
- FWCI
- 51.40
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institutes of Health
- Canadian Institutes of Health Research (125894_1, 93671_1, MOP-49451, MOP-14409, MOP-67011)
- National Human Genome Research Institute (1R01HG00570, R01HG005700)
- National Cancer Institute (R01CA104708, P30CA014520)
- National Institute of General Medical Sciences (R01GM084034, R01GM058728, R01GM051968, R01GM114386, T32GM008061)
- National Institute of Diabetes and Digestive and Kidney Diseases (Z01DK015602, DK015602-05)
- 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 regulation and disease
- Keywords
- RNA-binding proteins, RNA-binding motif, post-transcriptional regulation, RNA-binding domain, sequence specificity, evolutionary conservation, interaction site prediction, eukaryotic gene regulation
- MeSH terms
- RNA Splicing Factors, Autistic Disorder, Base Sequence, Binding Sites, Eukaryotic Cells, Gene Expression Regulation, Humans, Molecular Sequence Data, RNA-Binding Proteins, Conserved Sequence, Protein Structure, Tertiary, RNA Stability, Nucleotide Motifs
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.
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