A compendium of RNA-binding motifs for decoding gene regulation
Open accessAbstract
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.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 44 cited sources checked · 0 supported · 0 flagged
- Findingown data
Among the 207 RBPs initially analyzed, most yielded RNA-binding data distinct from all other proteins.
“Among the 207 RBPs we initially analysed, most yielded RNA-binding data distinct from that obtained from all other proteins”
Quote in the paperSubstantial claim - Findingown data
RNAcompete motifs are predictive of RNA sequences bound by the same proteins or their close homologues in vivo.
“However, RNAcompete motifs are predictive of RNA sequences bound by the same proteins (or their close homologues) in vivo”
Quote in the paperSubstantial claim - Findingnone given
The in vitro motifs identified correlate well with in vivo RNA-binding data.
“The motifs that we identify in vitro correlate well with in vivo RNA-binding data.”
Quote in the paperSubstantial claim - Findingown data
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.
“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”
Quote in the paperSubstantial claim - Findingown data
The authors systematically analyzed RNA motifs recognized by RBPs, covering 205 distinct genes from 24 diverse eukaryotes.
“Here we report a systematic analysis of the RNA motifs recognized by RNA-binding proteins, encompassing 205 distinct genes from 24 diverse eukaryotes.”
Quote in the paperSubstantial claim
- Findingown data
Proteins with closely related RBDs typically yield very similar RNA-binding data.
“The major exception is that proteins with closely related RBDs typically yield very similar data.”
Quote in the paperSubstantial claim - Findingown data
The sequence specificities of RBPs show deep evolutionary conservation.
“The sequence specificities of RNA-binding proteins display deep evolutionary conservation”
Quote in the paperSubstantial claim - Findingown data
All RBPs in the SUP12-RBM24-RBM38 cluster prefer similar (G1U)-rich sequences.
“all RBPs in the SUP12–RBM24–RBM38 cluster (Fig. 2, inset 2) prefer similar (G1U)-rich sequences.”
Quote in the paperNot a substantial claim - Findingnone given
The study uncovered an unexpected role for a splicing factor in controlling transcript abundance that is mis-regulated in autism.
“uncover an unexpected role for a splicing factor in the control of transcript abundance that is mis-regulated in autism.”
Quote in the paperSubstantial claim - Findingown data
For QKI, the RNAcompete motif had an AUROC of 93% versus 83% for the literature motif.
“for example, for QKI (quaking), the AUROC for the RNAcompete motif was 93% versus 83% for the literature motif.”
Quote in the paperNot a substantial claim - Findingnone given
Of the 193 unique RBPs, 52 have previously identified consensus RNA-binding sequences.
“Of the 193 unique RBPs, 52 have previously identified consensus RNA-binding sequences.”
Quote in the paperNot a substantial claim - Findingown data
The only instance where an RNAcompete motif did not have a significant positive AUROC to at least one corresponding in vivo data set was FUS, with AUROC <0.5 against in vivo crosslinking data for FUS and TAF15.
“We found only one instance in which the RNAcompete motif did not have a significant and positive AUROC to at least one corresponding in vivo data set: the RNAcompete motif for FUS produced an AUROC <0.5 when compared to in vivo crosslinking-based data for both FUS and its paralogue TAF15”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [14] Hoell, J. I. et al. RNA targets of wild-type and mutant FET family proteins. Nature Struct. Mol. Biol. 18, 1428–1431 (2011) source
Not checked in the free run.
- Findingown data
Groups of ancient families retain closely related sequence preferences.
“In numerous instances (shaded), groups of ancient families retain closely related sequence preferences.”
Quote in the paperSubstantial claim - Findingown data
RBFOX1 targets tend to have the most conserved RBFOX1 sites in their 3' UTRs (P < 10−4).
“These targets tend to have the most conserved RBFOX1 sites in their 3′ UTRs (P < 10−4; one-sided Mann–Whitney U-test of ranks”
Quote in the paperSubstantial claim - Findingcitation
In published RNA-seq data following RBFOX1 knockdown by RNAi, predicted RBFOX1 stability targets were collectively reduced in abundance (P < 10−15).
“we examined published RNA-seq data following RBFOX1 knockdown by RNA interference (RNAi)36 and found that the predicted RBFOX1 stability targets were collectively reduced in abundance (P < 10−15”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [36] Fogel, B. L. et al. RBFOX1 regulates both splicing and transcriptional networks in human neuronal development. Hum. Mol. Genet. 21, 4171–4186 (2012) source
Not checked in the free run.
- Findingown data
Quantification by three metrics shows that amino acid sequence identity higher than about 70% yields very similar motifs on average.
“Quantification of the relationship between RBD sequence identity and RNA-binding motifs by three different metrics shows that, on average, amino acid sequence identity higher than ~70% yields very similar motifs”
Quote in the paperSubstantial claim - Findingown data
Genes encoding transcripts with predicted 3' UTR binding sites for RBFOX1 that show decreases in mRNA levels in autism spectrum disorder are significantly enriched for voltage-gated ion channels, particularly potassium channels.
“genes encoding transcripts with predicted 3′ UTR binding sites for RBFOX1 that show decreases in mRNA levels in autism spectrum disorder are significantly enriched for voltage-gated ion channels, particularly potassium channels”
Quote in the paperSubstantial claim - Findingown data
In the same data, the average reduction in transcript abundance increased with the number of motif matches in the first 300 nucleotides of the 3' UTR for all mRNAs.
“In these same data, the average reduction in transcript abundance increased with the number of motif matches in the first 300 nucleotides of the 3′ UTR, for all mRNAs”
Quote in the paperSubstantial claim - Findingown data
The regulatory regions in which a motif is conserved are often consistent with the known function of the corresponding binding protein.
“Often the regulatory region(s) in which a motif is conserved are consistent with the known function of the corresponding binding protein(s).”
Quote in the paperSubstantial claim - Findingown data
In early Drosophila embryo data sets measuring translation, stability, and localization, the authors obtained dozens of significant associations between the presence of motif matches and specific regulatory outcomes.
“we have examined data sets measuring translation40, stability41 and localization42 of transcripts in the early Drosophila embryo, obtaining dozens of significant associations between the presence of motif matches and specific regulatory outcomes”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [40] Qin, X., Ahn, S., Speed, T. P. & Rubin, G. M. Global analyses of mRNA translational control during early Drosophila embryogenesis. Genome Biol. 8, R63 (2007) source
Not checked in the free run.
- cites [41] Tadros, W. et al. SMAUG is a major regulator of maternal mRNA destabilization in Drosophila and its translation is activated by the PAN GU kinase. Dev. Cell 12, 143–155 (2007) source
Not checked in the free run.
- cites [42] Lécuyer, E. et al. Global analysis of mRNA localization reveals a prominent role in organizing cellular architecture and function. Cell 131, 174–187 (2007) source
Not checked in the free run.
- Findingown data
Matches to motifs for 49 RBP families, representing almost two-thirds of human RBPs (104 of 165) with measured or inferred motifs, displayed a significant increase in conservation relative to immediate flanking sequences in at least one of the examined regions (FDR <0.01).
“Matches to motifs for 49 RBP families (defined on the basis of 70% identity in the RBDs), representing almost two-thirds of the human RBPs (104 of 165) with measured or inferred motifs (using 70% RBD identity), displayed a significant increase (false discovery rate (FDR) <0.01) in conservation relative to immediate flanking sequences, in at least one of the regions that we examined”
Quote in the paperSubstantial claim - Findingown data
Motifs remain similar at 50% identity.
“Motifs remain similar at 50% identity.”
Quote in the paperSubstantial claim - Findingown data
Known splicing regulators, including RBFOX and PTB family members, were associated with preferential exon inclusion or exclusion in a manner correlated with the expression and binding location of the RBP.
“known splicing regulators, including RBFOX and PTB family members4, were associated with preferential exon inclusion or exclusion in a manner that correlated with the expression and binding location of the RBP”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [34] Xue, Y. et al. Genome-wide analysis of PTB-RNA interactions reveals a strategy used by the general splicing repressor to modulate exon inclusion or skipping. Mol. Cell 36, 996–1006 (2009) source
Not checked in the free run.
- cites [35] Zhang, C. et al. Defining the regulatory network of the tissue-specific splicing factors Fox-1 and Fox-2. Genes Dev. 22, 2550–2563 (2008) source
Not checked in the free run.
- cites [4] Gabut, M., Chaudhry, S. & Blencowe, B. J. SnapShot: The splicing regulatory machinery. Cell 133, 192.e1 (2008) source
Not checked in the free run.
- Findingcitation
There is an inverse relationship between the degeneracy of columns within an RNAcompete motif and the evolutionary conservation of the matching bases within the predicted binding site in transcripts.
“there is an inverse relationship between the degeneracy of columns within an RNAcompete motif and the evolutionary conservation of the matching bases within the predicted binding site in transcripts”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [23] Moses, A. M., Chiang, D. Y., Pollard, D. A., Iyer, V. N. & Eisen, M. B. MONKEY: identifying conserved transcription-factor binding sites in multiple alignments using a binding site-specific evolutionary model. Genome Biol. 5, R98 (2004) source
Not checked in the free run.
- Findingcitation
The same RNA-seq data used in ref. 37 also support a role for RBFOX1 in stabilizing its predicted mRNA targets (P < 10−30).
“Notably, the same RNA-seq data used in ref. 37 also support a role for RBFOX1 in stabilizing its predicted mRNA targets (P < 10−30”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [37] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Findingcitation
The stabilizing/destabilizing roles predicted from the analysis were on average closely correlated with genome-wide measurements of RNA stability from a thio-U pulse-chase experiment.
“Nonetheless, the stabilizing/destabilizing roles predicted from this analysis were, on average, closely correlated with genome-wide measurements of RNA stability obtained previously from a thio-U pulse–chase experiment22”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [22] Goodarzi, H. et al. Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature 485, 264–268 (2012) source
Not checked in the free run.
- Findingown data
In vivo reporter experiments showed that mRNA abundance of a reporter with a single RBFOX1 site in the 3' UTR increased relative to an identical reporter with a mutant RBFOX1 site upon induction of RBFOX1 expression.
“This prediction is further supported by in vivo experiments in which the mRNA abundance of a reporter construct harbouring a single RBFOX1 site in the 3′ UTR increased, relative to an identical reporter containing a mutant RBFOX1 site, upon induction of RBFOX1 expression”
Quote in the paperSubstantial claim - Findingown data
Using a 70% sequence identity cutoff between RBDs, the authors systematically mapped motifs across 288 sequenced eukaryotes.
“Using a cutoff of 70%sequence identity between RBDs, we have systematically mapped motifs across 288 sequenced eukaryotes.”
Quote in the paperSubstantial claim - Findingown data
Similar analyses identified associations between RBP motifs and alternative splicing patterns.
“We used similar analyses to identify associations between RBP motifs and alternative splicing patterns.”
Quote in the paperSubstantial claim - Findingown data
RNAcompete analysis of 12 additional proteins from diverse species that are 61-96% identical to proteins with novel motifs among the 207 RBPs yielded new motifs highly similar to the original motifs.
“We tested the accuracy of these heurisitics by performing RNAcompete analysis of 12 additional proteins from diverse species that are 61–96%identical to proteins with novel motifs that were among the 207 RBPs. These new motifs were highly similar”
Quote in the paperSubstantial claim - Interpretationown data
The motifs can be linked to distinct functional roles in various types of post-transcriptional regulation.
“Moreover, we can associate them with distinct functional roles in diverse types of post-transcriptional regulation”
Quote in the paperSubstantial claim - Interpretationreasoning
The recognition preferences of a large fraction of metazoan RBPs can be inferred from their RNA-binding domain sequence.
“the recognition preferences for a large fraction of metazoan RNA-binding proteins can thus be inferred from their RNA-binding domain sequence.”
Quote in the paperSubstantial claim - Premisecitation
Sequence-specific binding between RBPs and their RNA targets is usually mediated by one or more RNA-binding domains, including RRM and KH domains.
“Sequence-specific associations between RBPs and their RNA targets are typically mediated by one or more RNA-binding domains (RBDs), such as the RNA recognition motif (RRM) and hnRNPK-homology (KH)domains.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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 in the free run.
- Premisereasoning
The absence of motifs for most RBPs across eukaryotes impedes analysis of post-transcriptional regulation.
“Altogether, the lack of motifs for the vast majority of RBPs across all branches of eukaryotes hinders analysis of post-transcriptional regulation.”
Quote in the paperSubstantial claim - Premisecitation
There are almost no data on the sequence preferences of RBPs in most organisms.
“There are virtually no data on the sequence preferences of RBPs in most organisms”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [6] De Gaudenzi, J. G., Noe, G., Campo, V. A., Frasch, A. C. & Cassola, A. Gene expression regulation in trypanosomatids. Essays Biochem. 51, 31–46 (2011) source
Not checked in the free run.
- Interpretationown data
The analysis predicts that RBFOX1 positively regulates mRNA stability.
“This analysis predicts that RBFOX1 positively regulates mRNA stability”
Quote in the paperSubstantial claim - Interpretationown data
Two proteins whose RBDs are more than 70% identical are likely to have similar, if not identical, RNA sequence specificity.
“Thus, two proteins for which their RBDs are >70% identical are likely to have a similar, if not identical, RNA sequence specificity.”
Quote in the paperSubstantial claim - Interpretationnone given
Motif inference based on RBD identity alone is only a first approximation.
“We caution that motif inference based on RBD identity alone is only a first approximation.”
Quote in the paperSubstantial claim - Interpretationown data
These proteins play a role in the regulation of mRNA turnover.
“supporting a role for these proteins in the regulation of mRNA turnover.”
Quote in the paperSubstantial claim - Premisecitation
Dual functions for splicing regulators in 3'-end poly-A site selection and mRNA transport have been described.
“Indeed, dual functions for splicing regulators in 3′-end poly-A site selection and mRNA transport have been described26,27”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [26] Licatalosi, D. D. et al. HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature 456, 464–469 (2008) source
Not checked in the free run.
- cites [27] Wang, E. T. et al. Transcriptome-wide regulation of pre-mRNA splicing and mRNA localization by muscleblind proteins. Cell 150, 710–724 (2012) source
Not checked in the free run.
- Interpretationown data
Assuming a closely related RNA motif will be bound by any protein with >70% RBD sequence identity to one of the 207 analyzed proteins, the RNAcompete data capture observed or inferred motifs for 57% of all human and 30% of all metazoan RBPs that contain multiple RBDs.
“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, then the RNAcompete data collectively capture observed or inferred motifs for 57% of all human and 30% of all metazoan RBPs that contain multiple RBDs”
Quote in the paperSubstantial claim- 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.
- Interpretationown data
A significant fraction of potential RBP binding sites in regulatory regions are under purifying selection.
“We conclude that a significant fraction of potential RBP binding sites in regulatory regions are under purifying selection.”
Quote in the paperSubstantial claim - Interpretationreasoning
Reduction of the stability of RBFOX1 targets may affect nervous-system-specific processes.
“indicating that reduction of the stability of RBFOX1 targets may affect nervous-system-specific processes.”
Quote in the paperSubstantial claim - Premisecitation
Dual roles for RBPs in the control of splicing and stability are emerging.
“dual roles for RBPs in the control of splicing and stability are emerging28–30.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [28] Sawicka, K., Bushell, M., Spriggs, K. A. & Willis, A. E. Polypyrimidine-tract-binding protein: a multifunctional RNA-binding protein. Biochem. Soc. Trans. 36, 641–647 (2008) source
Not checked in the free run.
- cites [29] Biedermann, B., Hotz, H. R. & Ciosk, R. The Quaking family of RNA-binding proteins: coordinators of the cell cycle and differentiation. Cell Cycle 9, 1929–1933 (2010) source
Not checked in the free run.
- cites [30] Izquierdo, J. M. Hu antigen R (HuR) functions as an alternative pre-mRNA splicing regulator of Fas apoptosis-promoting receptor on exon definition. J. Biol. Chem. 283, 19077–19084 (2008) source
Not checked in the free run.
- Interpretationown data
The sequence conservation of RBP motif matches in transcripts indicates potential new regulatory associations, particularly those associated with the 3' UTR.
“The sequence conservation of RBP motif matches in transcripts indicates potential new regulatory associations, particularly those associated with the 3′ UTR”
Quote in the paperSubstantial claim - Interpretationown data
This observation provides a simple heuristic by which RNA sequence preferences of previously uncharacterized RBPs can be reliably inferred.
“This observation is of tremendous practical value, because it provides a simple heuristic by which the RNA sequence preferences of previously uncharacterized RBPs can be reliably inferred.”
Quote in the paperSubstantial claim - Interpretationcitation
Inference by simple protein identity is particularly valuable for RBPs for which it may not be possible to derive recognition codes.
“Nonetheless, inference by simple protein identity is particularly valuable for those RBPs for which it may not be possible to derive recognition codes5.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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
Not checked in the free run.
- Interpretationown data
Many proteins with well-defined roles in splicing also have conserved motif matches in 3' UTRs, suggesting more diverse regulatory roles for these factors.
“many proteins with well-defined roles in splicing (those with an asterisk in Fig. 4a) also have conserved motif matches in 3′ UTRs, suggesting more diverse regulatory roles for these factors.”
Quote in the paperSubstantial claim - Premisecitation
Reduced levels of RBFOX1 in the brains of individuals with autism spectrum disorder have been associated with widespread changes in alternative splicing of exons associated with proximal RBFOX1 binding sites.
“Reduced levels of RBFOX1 in the brains of individuals with autism spectrum disorder have been associated with widespread changes in alternative splicing of exons associated with proximal RBFOX1 binding sites37.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [37] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011) source
Not checked in the free run.
- Interpretationown data
By profiling a relatively small number of RBPs, it should be possible to broadly assess RBP sequence preferences across all eukaryotes.
“Our observations suggest that by profiling a relatively small number of RBPs it should be possible to broadly assess RBP sequence preferences across all eukaryotes.”
Quote in the paperSubstantial claim
- May combine two claims. 20
- Classified as probably not a substantial claim. 6
May combine two claims.
Findingown dataThe authors initially determined sequence preferences for 207 RBPs, representing seven structural classes and 193 unique RBP-encoding genes.
“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”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe vast majority of RBPs appear to bind target sequences in single-stranded RNA, and none absolutely requires a specific RNA secondary structure, although 22 RBPs show significant preference for (n=7) or against (n=15) predicted hairpin loops.
“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”
Quote in the paperSubstantial claimMay combine two claims.
Findingown dataThe analyzed RBPs included 85 human, 61 Drosophila, and 61 from 18 other eukaryotes chosen to be dissimilar to already profiled RBPs.
“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.”
Quote in the paperNot a substantial claimMay combine two claims.
Findingown dataMost of these 52 RBPs have obvious similarity to RNAcompete-derived motifs, with 35 very similar, six partial matches, and 11 discrepancies.
“Most of these have obvious similarity to our RNAcompete-derived motifs (Supplementary Data 5; 35 very similar, six partial matches, and 11 discrepancies).”
Quote in the paperSubstantial claimMay combine two claims.
FindingcitationRBFOX1, RBFOX2, and RBFOX3 motifs are conserved in introns downstream of alternative exons, whereas PUM1 and PUM2 sites are most highly conserved in 3' UTRs.
“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”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [4] Gabut, M., Chaudhry, S. & Blencowe, B. J. SnapShot: The splicing regulatory machinery. Cell 133, 192.e1 (2008) source
Not checked in the free run.
- cites [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 in the free run.
- cites [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
Not checked in the free run.
May combine two claims.
Findingown dataThe analysis identified known regulators of mRNA stability, including RBM4 and ELAVL1, and correctly predicted the direction of their effect (destabilizing for RBM4 and stabilizing for ELAVL1).
“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”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [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
Not checked in the free run.
May combine two claims.
FindingcitationVery different motifs have been previously described for different HNRNPA family members from human and Drosophila, whereas RNAcompete motifs for the same proteins are closely related.
“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”
Quote in the paperNot a substantial claim0 of 4 sources checked- cites [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 in the free run.
- cites [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 in the free run.
- cites [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 in the free run.
- cites [22] Goodarzi, H. et al. Systematic discovery of structural elements governing stability of mammalian messenger RNAs. Nature 485, 264–268 (2012) source
Not checked in the free run.
May combine two claims.
FindingcitationFamily members of SNRPA/SNF from fungi, protists, and algae have maintained the presumed ancestral CAC core-recognition specificity but differ in flanking nucleotide preference.
“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”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [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
Not checked in the free run.
May combine two claims.
Study design and conductown dataThese fragments succeeded more often than full-length proteins or individual RBDs in trial experiments and produced data consistent with previously known motifs.
“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”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationIn some cases, DNA-binding motifs can be predicted from specific interactions between DNA-contacting amino acid residues and DNA bases.
“in some cases motifs can even be predicted on the basis of specific interactions between DNA-contacting amino acid residues and DNA bases9,10”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [9] Christensen, R. G. et al. Recognition models to predict DNA-binding specificities of homeodomain proteins. Bioinformatics 28, i84–i89 (2012) source
Not checked in the free run.
- cites [10] Liu, J. & Stormo, G. D. Context-dependent DNA recognition code for C2H2 zinc-finger transcription factors. Bioinformatics 24, 1850–1857 (2008) source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationMotifs for DNA-binding proteins can be highly similar among closely related proteins, allowing accurate inference of motifs.
“The motifs for DNA-binding proteins can be highly similar for closely related proteins, allowing accurate inference of motifs7,8”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [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
Not checked in the free run.
May combine two claims.
Interpretationown dataCollectively, RNAcompete motifs are generally both accurate and functionally relevant.
“Collectively, these analyses demonstrate that the RNAcompete motifs are generally both accurate and functionally relevant.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationcitationThe SUP12, RBM24, and RBM38 proteins are regulators of muscle development in nematode, mouse, and human, indicating biochemical and functional conservation.
“These nematode, mouse and human proteins are regulators of muscle development15,16, indicating both biochemical and functional conservation.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [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
Not checked in the free run.
Classified as probably not a substantial claim.
PremisecitationRNA-binding proteins control many steps of co- and post-transcriptional gene expression, such as splicing, polyadenylation, capping, modification, export, localization, translation, and turnover.
“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.”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [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 in the free run.
- cites [2] Keene, J. D. RNA regulons: coordination of post-transcriptional events. Nature Rev. Genet. 8, 533–543 (2007) source
Not checked in the free run.
May combine two claims.
PremisecitationCanonical RBDs typically bind short single-stranded RNA sequences, but some also recognize structured RNAs.
“Canonical RBDs typically bind short, single-stranded (ss)RNA sequences3,4, but some also recognize structured RNAs5.”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [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 in the free run.
- cites [4] Gabut, M., Chaudhry, S. & Blencowe, B. J. SnapShot: The splicing regulatory machinery. Cell 133, 192.e1 (2008) source
Not checked in the free run.
- cites [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
Not checked in the free run.
May combine two claims.
Premiseown dataOnly a minority of RBD-containing proteins in eukaryotic genomes have been studied in detail, and the assays used to generate their motifs are heterogeneous.
“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.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Study design and conductown dataThe RNA pool was split into two halves for internal cross-validation, with each half containing at least eight copies of every 9-mer, 33 copies of each 8-mer, and 155 copies of each 7-mer.
“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.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe human genome encodes 239 RRM-domain proteins and 38 KH-domain proteins among 424 known and predicted RBPs.
“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.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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 in the free run.
May combine two claims.
PremisecitationKnown RNA-binding motifs exist for 15% of human, 8% of Drosophila, and 3% of Caenorhabditis elegans RBD-containing proteins.
“For example, 15% of human, 8% of Drosophila and 3% of Caenorhabditis elegans RBD-containing proteins have known RNA-binding motifs3”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [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 in the free run.
May combine two claims.
Interpretationown dataThe 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.
“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.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Interpretationnone givenThe marked change in the central UCAC in the T. brucei consensus (HUUCACR) seems to correspond to the unusual T. brucei U1 loop sequence (CAUCAC versus AUUGCAC in most other species).
“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).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationFor PUM1 and PUM2, the predicted direction of effect was counter to expectation, indicating that correlation may reflect possible additional functional roles for these proteins and/or their binding motifs.
“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.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [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
Not checked in the free run.
May combine two claims.
Interpretationown dataThe analyses 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.
“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.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationown dataRBP multi-functionality may be more widespread than previously appreciated; motifs for most (38 out of 49) RBP families shown display significant conservation in more than one of the three regions examined.
“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.”
Quote in the paperSubstantial claim
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?
Computational analysis suggested that the miR-140-5p-G seed in the Ago2 complex and the RBP Ybx1 potentially compete for the same RNA binding sites.
“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]
The Large-scale analysis of RBPs section describes computational analysis of RBP binding motifs, but does not address competition between Ybx1 and an Ago2-bound microRNA. Searches for YBX1, miR-140-5p, and overlapping Ago2/RBP binding sites found no passage supporting the specific claim. (LLM, conf=0.76)
Experimental — accuracy not yet measuredYbx1 seCLIP analysis identified a binding motif similar to the Ybx1 binding motif reported previously.
“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]
The Large-scale analysis of RBPs section describes how the paper derived RNA-binding motifs, but the passages found do not identify a YBX1 motif. Searches for “YBX1,” “YB-1,” and “Y-box binding protein 1” found no passage establishing the specific motif comparison attributed to this source. (LLM, conf=0.72)
Experimental — accuracy not yet measuredRecent findings propose that Rbfox can also regulate alternative polyadenylation and mRNA stability, based on analysis of Rbfox motif sites in 3′ UTRs correlated with transcript abundance in different tissues.
“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
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
RNA regulons: coordination of post-transcriptional events
Keene, J. D. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2111 · Cited by 1,321 · cited 1× · see citing works
“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 · see citing works
Barash, Y., Calarco, J. A., Gao, W., Pan, Q., Wang, X., Ofer Shai, A., Blencowe, B. J., & Frey, B. J. (2010) · Nature · doi:10.1038/nature09000 · Cited by 891 · see citing works
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 · see citing works
Self-citationHogan, D. J., Riordan, D. P., Gerber, A. P., Herschlag, D., & Brown, P. O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060255 · Cited by 609 · see citing works
Variation in Homeodomain DNA Binding Revealed by High-Resolution Analysis of Sequence Preferences
Berger, M. F., Badis, G., Gehrke, A. R., Talukder, S., Philippakis, A. A., Peña-Castillo, L., Alleyne, T. M., Mnaimneh, S., Botvinnik, O. B., Chan, E. T., et al. (2008) · Cell · doi:10.1016/j.cell.2008.05.024 · Cited by 606 · see citing works
Yeo, G. W., Coufal, N. G., Liang, T. Y., Peng, G. E., Fu, X.-D., & Gage, F. H. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1545 · Cited by 572 · see citing works
Transcriptome-wide Regulation of Pre-mRNA Splicing and mRNA Localization by Muscleblind Proteins
Wang, E. T., Cody, N. A. L., Jog, S., Biancolella, M., Wang, T. T., Treacy, D. J., Luo, S., Schroth, G. P., Housman, D. E., Reddy, S., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.041 · Cited by 490 · see citing works
Burd, C. G., & Dreyfuss, G. (1994) · The EMBO Journal · doi:10.1002/j.1460-2075.1994.tb06369.x · Cited by 488 · see citing works
Rapid and systematic analysis of the RNA recognition specificities of RNA-binding proteins
Ray, D., Kazan, H., Chan, E. T., Peña‐Castillo, L., Chaudhry, S., Talukder, S., Blencowe, B. J., Morris, Q., & Hughes, T. R. (2009) · Nature Biotechnology · doi:10.1038/nbt.1550 · Cited by 479 · see citing works
Self-citationHuelga, S. C., Vu, A. Q., Arnold, J. D., Liang, T. Y., Liu, P. P., Yan, B. Y., Donohue, J. P., Shiue, L., Hoon, S., Brenner, S., et al. (2012) · Cell Reports · doi:10.1016/j.celrep.2012.02.001 · Cited by 470 · see citing works
Xue, Y., Zhou, Y., Wu, T., Zhu, T., Ji, X., Kwon, Y.-S., Zhang, C., Yeo, G., Black, D. L., Sun, H., et al. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.12.003 · Cited by 469 · see citing works
STAMP: a web tool for exploring DNA-binding motif similarities
Mahony, S., & Benos, P. V. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm272 · Cited by 469 · see citing works
Noyes, M. B., Christensen, R. G., Wakabayashi, A., Stormo, G. D., Brodsky, M. H., & Wolfe, S. A. (2008) · Cell · doi:10.1016/j.cell.2008.05.023 · Cited by 452 · see citing works
Berger, M. F., & Bulyk, M. L. (2009) · Nature Protocols · doi:10.1038/nprot.2008.195 · Cited by 398 · see citing works
RNA targets of wild-type and mutant FET family proteins
Hoell, J. I., Larsson, E., Runge, S., Nusbaum, J. D., Duggimpudi, S., Farazi, T. A., Hafner, M., Borkhardt, A., Sander, C., & Tuschl, T. (2011) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.2163 · Cited by 350 · see citing works
Polypyrimidine-tract-binding protein: a multifunctional RNA-binding protein
Sawicka, K., Bushell, M., Spriggs, K. A., & Willis, A. E. (2008) · Biochemical Society Transactions · doi:10.1042/bst0360641 · Cited by 332 · see citing works
Tadros, W., Goldman, A. L., Babak, T., Menzies, F., Vardy, L., Orr-Weaver, T., Hughes, T. R., Westwood, J. T., Smibert, C. A., & Lipshitz, H. D. (2007) · Developmental Cell · doi:10.1016/j.devcel.2006.10.005 · Cited by 330 · see citing works
Self-citationSequence-specific binding of single-stranded RNA: is there a code for recognition?
Auweter, S. D., Oberstrass, F. C., & Allain, F. H.-T. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl620 · Cited by 314 · see citing works
Identification of HuR as a protein implicated in AUUUA‐mediated mRNA decay
Myer, V. E., Fan, X. C., & Steitz, J. A. (1997) · The EMBO Journal · doi:10.1093/emboj/16.8.2130 · Cited by 302 · see citing works
Defining the regulatory network of the tissue-specific splicing factors Fox-1 and Fox-2
Zhang, C., Zhang, Z., Castle, J., Sun, S., Johnson, J., Krainer, A. R., & Zhang, M. Q. (2008) · Genes & Development · doi:10.1101/gad.1703108 · Cited by 300 · see citing works
Different gene regulation strategies revealed by analysis of binding motifs
Wunderlich, Z., & Mirny, L. A. (2009) · Trends in Genetics · doi:10.1016/j.tig.2009.08.003 · Cited by 282 · see citing works
Conservation of an RNA regulatory map between Drosophila and mammalsPreprint
Brooks, A. N., Yang, L. C., Duff, M. O., Hansen, K. D., Park, J. W., Dudoit, S., Brenner, S. E., & Graveley, B. R. (2010) · Genome Research · doi:10.1101/gr.108662.110 · Cited by 236 · see citing works
RBFOX1 regulates both splicing and transcriptional networks in human neuronal development
Fogel, B. L., Wexler, E., Wahnich, A., Friedrich, T., Vijayendran, C., Gao, F., Parikshak, N., Konopka, G., & Geschwind, D. H. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds240 · Cited by 216 · see citing works
Human Pumilio Proteins Recruit Multiple Deadenylases to Efficiently Repress Messenger RNAs
Van Etten, J., Schagat, T. L., Hrit, J., Weidmann, C. A., Brumbaugh, J., Coon, J. J., & Goldstrohm, A. C. (2012) · Journal of Biological Chemistry · doi:10.1074/jbc.m112.373522 · Cited by 205 · see citing works
Systematic discovery of structural elements governing stability of mammalian messenger RNAs
Goodarzi, H., Najafabadi, H. S., Oikonomou, P., Greco, T. M., Fish, L., Salavati, R., Cristea, I. M., & Tavazoie, S. (2012) · Nature · doi:10.1038/nature11013 · Cited by 187 · see citing works
Self-citationRNA sequence‐ and shape‐dependent recognition by proteins in the ribonucleoprotein particle
Stefl, R., Skrisovska, L., & Allain, F. H. ‐. (2005) · The EMBO Reports · doi:10.1038/sj.embor.7400325 · Cited by 175 · see citing works
Predicting in vivo binding sites of RNA-binding proteins using mRNA secondary structure
Li, X., Quon, G., Lipshitz, H. D., & Morris, Q. (2010) · RNA · doi:10.1261/rna.2017210 · Cited by 174 · see citing works
Self-citationIzquierdo, J. M. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m800017200 · Cited by 156 · see citing works
Morris, A. R., Mukherjee, N., & Keene, J. D. (2008) · Molecular and Cellular Biology · doi:10.1128/mcb.00155-08 · Cited by 155 · see citing works
Moses, A. M., Chiang, D. Y., Pollard, D. A., Iyer, V. N., & Eisen, M. B. (2004) · Genome Biology · doi:10.1186/gb-2004-5-12-r98 · Cited by 153 · see citing works
Gene expression regulation in trypanosomatids
De Gaudenzi, J. G., Noé, G., Campo, V. A., Frasch, A. C., & Cassola, A. (2011) · Essays in Biochemistry · doi:10.1042/bse0510031 · Cited by 116 · see citing works
Blanchette, M., Green, R. E., MacArthur, S., Brooks, A. N., Brenner, S. E., Eisen, M. B., & Rio, D. C. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.01.022 · Cited by 86 · see citing works
Global analyses of mRNA translational control during early Drosophila embryogenesis
Qin, X., Ahn, S., Speed, T. P., & Rubin, G. M. (2007) · Genome Biology · doi:10.1186/gb-2007-8-4-r63 · Cited by 86 · see citing works
SnapShot: The Splicing Regulatory Machinery
Gabut, M., Chaudhry, S., & Blencowe, B. J. (2008) · Cell · doi:10.1016/j.cell.2008.03.010 · Cited by 66 · see citing works
Self-citationMiyamoto, S., Hidaka, K., Jin, D., & Morisaki, T. (2009) · Genes to Cells · doi:10.1111/j.1365-2443.2009.01347.x · Cited by 64 · see citing works
Anyanful, A., Ono, K., Johnsen, R. C., Ly, H., Jensen, V., Baillie, D. L., & Ono, S. (2004) · The Journal of Cell Biology · doi:10.1083/jcb.200407085 · Cited by 58 · see citing works
RBM4: A multifunctional RNA-binding protein
Markus, M. A., & Morris, B. J. (2009) · The International Journal of Biochemistry & Cell Biology · doi:10.1016/j.biocel.2008.05.027 · Cited by 50 · see citing works
Context-dependent DNA recognition code for C2H2 zinc-finger transcription factors
Liu, J., & Stormo, G. D. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn331 · Cited by 48 · see citing works
Recognition models to predict DNA-binding specificities of homeodomain proteins
Christensen, R. G., Enuameh, M. S., Noyes, M. B., Brodsky, M. H., Wolfe, S. A., & Stormo, G. D. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts202 · Cited by 42 · see citing works
The Quaking family of RNA-binding proteins: Coordinators of the cell cycle and differentiation
Biedermann, B., Hotz, H.-R., & Ciosk, R. (2010) · Cell Cycle · doi:10.4161/cc.9.10.11533 · Cited by 37 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
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 · see citing works
“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 · see citing works
“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 1,705 · see citing works
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 · see citing works
A brave new world of RNA-binding proteins
Hentze, M. W., Castelló, A., Schwarzl, T., & Preiß, T. (2018) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm.2017.130 · Cited by 1,727 · see citing works
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 · see citing works
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 1,225 · see citing works
“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 1,251 · see citing works
“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 1,103 · see citing works
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 · see citing works
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 · see citing works
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 884 · see citing works
“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 852 · see citing works
“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 745 · see citing works
Revealing protein–lncRNA interaction
Ferrè, F., Colantoni, A., & Helmer‐Citterich, M. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv031 · Cited by 702 · see citing works
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 680 · see citing works
STREME: accurate and versatile sequence motif discovery
Bailey, T. L. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab203 · Cited by 631 · see citing works
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 572 · see citing works
“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 · see citing works
“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 · see citing works
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 549 · see citing works
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 553 · see citing works
“The shown SF2/ASF motif is from Smith et al. (2006) and the hnRNP H2 motif is from Ray et al. (2013).”
InfluentialMayr, C. (2019) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a034728 · Cited by 519 · see citing works
“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.”
BackgroundInfluentialTDP-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 524 · see citing works
“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 · see citing works
Zou, Q., Xing, P., Wei, L., & Liu, B. (2019) · RNA · doi:10.1261/rna.069112.118 · Cited by 525 · see citing works
“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 502 · see citing works
Self-citationCytoplasmic 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 428 · see citing works
“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 423 · see citing works
“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 · see citing works
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 389 · see citing works
“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 407 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 381 · see citing works
“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 · see citing works
“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 389 · see citing works
“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 · see citing works
“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 382 · see citing works
“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 383 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 329 · see citing works
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 · see citing works
“, 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 · see citing works
<i>cat</i>RAPID <i>omics</i>: 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 · see citing works
“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 · see citing works
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 339 · see citing works
“(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 · see citing works
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 290 · see citing works
“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 296 · see citing works
“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., Costa, F., & Backofen, R. (2014) · Genome Biology · doi:10.1186/gb-2014-15-1-r17 · Cited by 283 · see citing works
“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 · see citing works
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 296 · see citing works
“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 · see citing works
“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 309 · see citing works
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 · see citing works
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 271 · see citing works
“…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 295 · see citing works
“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 277 · see citing works
SR Proteins: Binders, Regulators, and Connectors of RNA
Jeong-Yu, S. (2017) · Molecules and Cells · doi:10.14348/molcells.2017.2319 · Cited by 270 · see citing works
“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 276 · see citing works
“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 277 · see citing works
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 254 · see citing works
“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 234 · see citing works
“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 248 · see citing works
“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 kmer content
Kirk, J. M., Kim, S. O., Inoue, K., Smola, M. J., Lee, D. M., Schertzer, M. D., Wooten, J., Baker, A., Sprague, D., Collins, D. W., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0207-8 · Cited by 204 · see citing works
“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 270 · see citing works
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 243 · see citing works
“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 240 · see citing works
“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 255 · see citing works
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 238 · see citing works
“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 252 · see citing works
“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 · see citing works
“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 216 · see citing works
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 237 · see citing works
“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 · see citing works
“…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 · see citing works
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 232 · see citing works
“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 231 · see citing works
“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 · see citing works
“…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 · see citing works
“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 217 · see citing works
“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 230 · see citing works
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 229 · see citing works
“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 · see citing works
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 209 · see citing works
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 210 · see citing works
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 214 · see citing works
“, 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 · see citing works
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 228 · see citing works
“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 199 · see citing works
Pan, X., & Shen, H. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1561-8 · Cited by 203 · see citing works
“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 217 · see citing works
“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 194 · see citing works
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 202 · see citing works
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 198 · see citing works
- 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.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-06.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-06.
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
