Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Rapid and systematic analysis of the RNA recognition specificities of RNA-binding proteins

Nature Biotechnology volume 27, pages 667–670 (2009)Cite this article

Abstract

Metazoan genomes encode hundreds of RNA-binding proteins (RBPs) but RNA-binding preferences for relatively few RBPs have been well defined1. Current techniques for determining RNA targets, including in vitro selection and RNA co-immunoprecipitation2,3,4,5, require significant time and labor investment. Here we introduce RNAcompete, a method for the systematic analysis of RNA binding specificities that uses a single binding reaction to determine the relative preferences of RBPs for short RNAs that contain a complete range of k-mers in structured and unstructured RNA contexts. We tested RNAcompete by analyzing nine diverse RBPs (HuR, Vts1, FUSIP1, PTB, U1A, SF2/ASF, SLM2, RBM4 and YB1). RNAcompete identified expected and previously unknown RNA binding preferences. Using in vitro and in vivo binding data, we demonstrate that preferences for individual 7-mers identified by RNAcompete are a more accurate representation of binding activity than are conventional motif models. We anticipate that RNAcompete will be a valuable tool for the study of RNA-protein interactions.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The RNAcompete method and example data for HuR and Vts1.
Figure 2: RNAcompete analysis of nine different RBPs, representing four different classes of RNA binding domains.
Figure 3: ROC curves showing the ability of different representations of RNA-binding activity to predict bound versus unbound sequences in vivo.

Accession codes

Accessions

Gene Expression Omnibus

References

  1. Glisovic, T., Bachorik, J.L., Yong, J. & Dreyfuss, G. RNA-binding proteins and post-transcriptional gene regulation. FEBS Lett. 582, 1977–1986 (2008).

    Article  CAS  Google Scholar 

  2. Tenenbaum, S.A., Carson, C.C., Lager, P.J. & Keene, J.D. Identifying mRNA subsets in messenger ribonucleoprotein complexes by using cDNA arrays. Proc. Natl. Acad. Sci. USA 97, 14085–14090 (2000).

    Article  CAS  Google Scholar 

  3. Gerber, A.P., Herschlag, D. & Brown, P.O. Extensive association of functionally and cytotopically related mRNAs with Puf family RNA-binding proteins in yeast. PLoS Biol. 2, E79 (2004).

    Article  Google Scholar 

  4. Ule, J., Jensen, K., Mele, A. & Darnell, R.B. CLIP: a method for identifying protein-RNA interaction sites in living cells. Methods 37, 376–386 (2005).

    Article  CAS  Google Scholar 

  5. Tuerk, C. & Gold, L. Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 249, 505–510 (1990).

    Article  CAS  Google Scholar 

  6. 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).

    Article  CAS  Google Scholar 

  7. Berger, M.F. et al. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities. Nat. Biotechnol. 24, 1429–1435 (2006).

    Article  CAS  Google Scholar 

  8. Philippakis, A.A., Qureshi, A.M., Berger, M.F. & Bulyk, M.L. Design of compact, universal DNA microarrays for protein binding microarray experiments. J. Comput. Biol. 15, 655–665 (2008).

    Article  CAS  Google Scholar 

  9. 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).

    Article  CAS  Google Scholar 

  10. Levine, T.D., Gao, F., King, P.H., Andrews, L.G. & Keene, J.D. Hel-N1: an autoimmune RNA-binding protein with specificity for 3′ uridylate-rich untranslated regions of growth factor mRNAs. Mol. Cell. Biol. 13, 3494–3504 (1993).

    Article  CAS  Google Scholar 

  11. Aviv, T., Lin, Z., Ben-Ari, G., Smibert, C.A. & Sicheri, F. Sequence-specific recognition of RNA hairpins by the SAM domain of Vts1p. Nat. Struct. Mol. Biol. 13, 168–176 (2006).

    Article  CAS  Google Scholar 

  12. Sengupta, S. et al. The RNA-binding protein HuR regulates the expression of cyclooxygenase-2. J. Biol. Chem. 278, 25227–25233 (2003).

    Article  CAS  Google Scholar 

  13. Meisner, N.C. et al. mRNA openers and closers: modulating AU-rich element-controlled mRNA stability by a molecular switch in mRNA secondary structure. ChemBioChem 5, 1432–1447 (2004).

    Article  CAS  Google Scholar 

  14. Tsai, D.E., Harper, D.S. & Keene, J.D. U1-snRNP-A protein selects a ten nucleotide consensus sequence from a degenerate RNA pool presented in various structural contexts. Nucleic Acids Res. 19, 4931–4936 (1991).

    Article  CAS  Google Scholar 

  15. Tacke, R. & Manley, J.L. The human splicing factors ASF/SF2 and SC35 possess distinct, functionally significant RNA binding specificities. EMBO J. 14, 3540–3551 (1995).

    Article  CAS  Google Scholar 

  16. Perez, I., McAfee, J.G. & Patton, J.G. Multiple RRMs contribute to RNA binding specificity and affinity for polypyrimidine tract binding protein. Biochemistry 36, 11881–11890 (1997).

    Article  CAS  Google Scholar 

  17. Gao, F.B., Carson, C.C., Levine, T. & Keene, J.D. Selection of a subset of mRNAs from combinatorial 3′ untranslated region libraries using neuronal RNA-binding protein Hel-N1. Proc. Natl. Acad. Sci. USA 91, 11207–11211 (1994).

    Article  CAS  Google Scholar 

  18. Aviv, T. et al. The RNA-binding SAM domain of Smaug defines a new family of post-transcriptional regulators. Nat. Struct. Biol. 10, 614–621 (2003).

    Article  CAS  Google Scholar 

  19. Shin, C. & Manley, J.L. The SR protein SRp38 represses splicing in M phase cells. Cell 111, 407–417 (2002).

    Article  CAS  Google Scholar 

  20. Lai, M.C., Kuo, H.W., Chang, W.C. & Tarn, W.Y. A novel splicing regulator shares a nuclear import pathway with SR proteins. EMBO J. 22, 1359–1369 (2003).

    Article  CAS  Google Scholar 

  21. Lin, Q., Taylor, S.J. & Shalloway, D. Specificity and determinants of Sam68 RNA binding. Implications for the biological function of K homology domains. J. Biol. Chem. 272, 27274–27280 (1997).

    Article  CAS  Google Scholar 

  22. Ohno, G., Hagiwara, M. & Kuroyanagi, H. STAR family RNA-binding protein ASD-2 regulates developmental switching of mutually exclusive alternative splicing in vivo. Genes Dev. 22, 360–374 (2008).

    Article  CAS  Google Scholar 

  23. Stickeler, E. et al. The RNA binding protein YB-1 binds A/C-rich exon enhancers and stimulates splicing of the CD44 alternative exon v4. EMBO J. 20, 3821–3830 (2001).

    Article  CAS  Google Scholar 

  24. Dong, J. et al. RNA-binding specificity of Y-box protein 1. RNA Biol. 6, 59–64 (2009).

    Article  CAS  Google Scholar 

  25. Skabkina, O.V., Lyabin, D.N., Skabkin, M.A. & Ovchinnikov, L.P. YB-1 autoregulates translation of its own mRNA at or prior to the step of 40S ribosomal subunit joining. Mol. Cell. Biol. 25, 3317–3323 (2005).

    Article  CAS  Google Scholar 

  26. Chen, X., Hughes, T.R. & Morris, Q. RankMotif.: a motif-search algorithm that accounts for relative ranks of K-mers in binding transcription factors. Bioinformatics 23, i72–i79 (2007).

    Article  CAS  Google Scholar 

  27. Sanford, J.R. Identification of nuclear and cytoplasmic mRNA targets for the shuttling protein SF2/ASF. PLoS One 3, e3369 (2008).

    Article  Google Scholar 

  28. Sanford, J.R. et al. Splicing factor SFRS1 recognizes a functionally diverse landscape of RNA transcripts. Genome Res. 19, 381–394 (2009).

    Article  CAS  Google Scholar 

  29. Oberstrass, F.C. et al. Structure of PTB bound to RNA: specific binding and implications for splicing regulation. Science 309, 2054–2057 (2005).

    Article  CAS  Google Scholar 

  30. Liu, H.X., Zhang, M. & Krainer, A.R. Identification of functional exonic splicing enhancer motifs recognized by individual SR proteins. Genes Dev. 12, 1998–2012 (1998).

    Article  CAS  Google Scholar 

  31. Gama-Carvalho, M., Barbosa-Morais, N.L., Brodsky, A.S., Silver, P.A. & Carmo-Fonseca, M. Genome-wide identification of functionally distinct subsets of cellular mRNAs associated with two nucleocytoplasmic-shuttling mammalian splicing factors. Genome Biol. 7, R113 (2006).

    Article  Google Scholar 

  32. Steffen, P., Voss, B., Rehmsmeier, M., Reeder, J. & Giegerich, R. RNAshapes: an integrated RNA analysis package based on abstract shapes. Bioinformatics 22, 500–503 (2006).

    Article  CAS  Google Scholar 

  33. Hofacker, I.L. et al. Fast folding and comparison of RNA secondary structures. Monatsh. Chem. 125, 167–188 (1994).

    Article  CAS  Google Scholar 

  34. Huber, W., von Heydebreck, A., Sultmann, H., Poustka, A. & Vingron, M. Variance stabilization applied to microarray data calibration and to the quantification of differential expression. Bioinformatics 18 Suppl 1, S96–S104 (2002).

    Article  Google Scholar 

  35. Hughes, J.D., Estep, P.W., Tavazoie, S. & Church, G.M. Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae. J. Mol. Biol. 296, 1205–1214 (2000).

    Article  CAS  Google Scholar 

  36. Bailey, T.L., Williams, N., Misleh, C. & Li, W.W. MEME: discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Res. 34, W369–373 (2006).

    Article  CAS  Google Scholar 

  37. Hiller, M., Pudimat, R., Busch, A. & Backofen, R. Using RNA secondary structures to guide sequence motif finding towards single-stranded regions. Nucleic Acids Res. 34, e117 (2006).

    Article  Google Scholar 

  38. Frey, B.J. & Dueck, D. Clustering by passing messages between data points. Science 315, 972–976 (2007).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We are grateful to C. Smibert, H. Lipshitz, F. Sicheri, M. Kekis and T. Babak for helpful commentary. Bacterial expression plasmids for the N-terminal arm of U1A, the Vts1 SAM domain, full-length PTB and YB1 were generously provided by C. Lutz (Univ. of Medicine and Dentistry of New Jersey), C. Smibert (Univ. of Toronto), M. Garcia-Blanco (Duke Univ.) and K. Kohno (Univ. of Occupational and Environmental Health, Kitakyushu, Japan). This work was supported by grants to T.R.H., B.J.B. and Q.M. from CIHR (MOP-49451, MOP-14609, MOP-93671), by Natural Sciences and Engineering Research Council operating and Canadian Foundation of Innovation grants to Q.M., Genome Canada through the Ontario Genomics Institute and the Ontario Research Fund. D.R. was supported in part by a National Science and Engineering Research Council of Canada (NSERC) postdoctoral fellowship.

Author information

Author notes

  1. Debashish Ray and Hilal Kazan: These authors have contributed equally to this work.

Authors and Affiliations

  1. Banting and Best Department of Medical Research, University of Toronto, Toronto, Ontario, Canada

    Debashish Ray, Lourdes Peña Castillo, Shaheynoor Talukder, Benjamin J Blencowe, Quaid Morris & Timothy R Hughes

  2. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

    Hilal Kazan & Quaid Morris

  3. Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada

    Esther T Chan, Sidharth Chaudhry, Benjamin J Blencowe, Quaid Morris & Timothy R Hughes

Authors
  1. Debashish Ray
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hilal Kazan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Esther T Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lourdes Peña Castillo
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sidharth Chaudhry
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Shaheynoor Talukder
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Benjamin J Blencowe
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Quaid Morris
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Timothy R Hughes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

D.R. developed the method and performed the experiments; D.R., H.K., Q.M. and T.R.H. designed the array, processed and analyzed the data, wrote the paper and made the figures; E.C. and L.P.C. contributed to the motif analyses and cross-validation; S.C. and S.T. assisted with cloning and protein production; B.J.B., Q.M. and T.R.H. conceived of the method and supported the project.

Corresponding authors

Correspondence to Quaid Morris or Timothy R Hughes.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5, Supplementary Table 1 (PDF 394 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Ray, D., Kazan, H., Chan, E. et al. Rapid and systematic analysis of the RNA recognition specificities of RNA-binding proteins. Nat Biotechnol 27, 667–670 (2009). https://doi.org/10.1038/nbt.1550

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nbt.1550

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing