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A biophysical miRNA-mRNA interaction model infers canonical and noncanonical targets

Nature Methods volume 10, pages 253–255 (2013)Cite this article

Abstract

We introduce a biophysical model of miRNA-target interaction and infer its parameters from Argonaute 2 cross-linking and immunoprecipitation data. We show that a substantial fraction of human miRNA target sites are noncanonical and that predicted target-site affinity correlates well with the extent of target destabilization. Our model provides a rigorous biophysical approach to miRNA target identification beyond ad hoc miRNA seed–based methods.

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Figure 1: A biophysical model of miRNA-target interaction.
Figure 2: Assessment of functionality of MIRZA-identified miRNA targets.

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References

  1. Bartel, D.P. Cell 136, 215–233 (2009).

    CAS PubMed PubMed Central Google Scholar

  2. Friedman, R.C., Farh, K.K.H., Burge, C.B. & Bartel, D.P. Genome Res. 19, 92–105 (2009).

    Article CAS PubMed PubMed Central Google Scholar

  3. Gaidatzis, D., van Nimwegen, E., Hausser, J. & Zavolan, M. BMC Bioinformatics 8, 69 (2007).

    Article PubMed PubMed Central Google Scholar

  4. Vella, M.C., Choi, E.Y., Lin, S.Y., Reinert, K. & Slack, F.J. Genes Dev. 18, 132–137 (2004).

    Article CAS PubMed PubMed Central Google Scholar

  5. Lal, A. et al. Mol. Cell 35, 610–625 (2009).

    Article CAS PubMed PubMed Central Google Scholar

  6. Chi, S.W., Zang, J.B., Mele, A. & Darnell, R.B. Nature 460, 479–486 (2009).

    Article CAS PubMed PubMed Central Google Scholar

  7. Brennecke, J., Stark, A., Russell, R.B. & Cohen, S.M. PLoS Biol. 3, e85 (2005).

    Article PubMed PubMed Central Google Scholar

  8. Kishore, S. et al. Nat. Methods 8, 559–564 (2011).

    Article CAS PubMed Google Scholar

  9. Chi, S.W., Hannon, G.J. & Darnell, R.B. Nat. Struct. Mol. Biol. 19, 321–327 (2012).

    Article CAS PubMed PubMed Central Google Scholar

  10. Linsley, P.S. et al. Mol. Cell. Biol. 27, 2240–2252 (2007).

    Article CAS PubMed PubMed Central Google Scholar

  11. Grimson, A. et al. Mol. Cell 27, 91–105 (2007).

    Article CAS PubMed PubMed Central Google Scholar

  12. Leivonen, S.K. et al. Oncogene 28, 3926–3936 (2009).

    Article CAS PubMed Google Scholar

  13. Selbach, M. et al. Nature 455, 58–63 (2008).

    Article CAS PubMed Google Scholar

  14. Gennarino, V.A. et al. Genome Res. 19, 481–490 (2009).

    Article CAS PubMed PubMed Central Google Scholar

  15. Grün, D., Wang, Y.L., Langenberger, D., Gunsalus, K.C. & Rajewsky, N. PLoS Comput. Biol. 1, e13 (2005).

    Article PubMed PubMed Central Google Scholar

  16. Garcia, D.M. et al. Nat. Struct. Mol. Biol. 18, 1139–1146 (2011).

    Article CAS PubMed PubMed Central Google Scholar

  17. Kertesz, M., Iovino, N., Unnerstall, U., Gaul, U. & Segal, E. Nat. Genet. 39, 1278–1284 (2007).

    Article CAS PubMed Google Scholar

  18. Betel, D., Koppal, A., Agius, P., Sander, C. & Leslie, C. Genome Biol. 11, R90 (2010).

    Article PubMed PubMed Central Google Scholar

  19. Miranda, K.C. et al. Cell 126, 1203–1217 (2006).

    Article CAS PubMed Google Scholar

  20. Rehmsmeier, M., Steffen, P., Hochsmann, M. & Giegerich, R. RNA 10, 1507–1517 (2004).

    Article CAS PubMed PubMed Central Google Scholar

  21. Lorenz, R. et al. Algorithms Mol. Biol. 6, 26 (2011).

    Article PubMed PubMed Central Google Scholar

  22. Yang, J.H. et al. Nucleic Acids Res. 39, D202–D209 (2011).

    Article CAS PubMed Google Scholar

  23. Gentleman, R.C. Genome Biol. 5, R80 (2004).

    Article PubMed PubMed Central Google Scholar

  24. Wu, Z., Irizarry, R.A., Gentleman, R., Martinez-Murillo, F. & Spencer, F. J. Am. Stat. Assoc. 99, 909–917 (2004).

    Article Google Scholar

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Acknowledgements

We are grateful to N. Beerenwinkel and S. Bergmann for comments in the initial stages of this work. We are also thankful to A.R. Gruber and the other members of the Zavolan group for providing input and feedback on the algorithm and the manuscript, A. Crippa for help with the code distribution and P.J. Balwierz for help converting the LaTeX manuscript to Word. M.K. was supported by Swiss National Science Foundation ProDoc grant PDFMP3_123123 to M.Z. and E.v.N. The work was additionally supported by Swiss National Science Foundation grant 31003A_127307 to M.Z.

Author information

Authors and Affiliations

  1. Biozentrum, University of Basel, Basel, Switzerland

    Mohsen Khorshid, Jean Hausser, Mihaela Zavolan & Erik van Nimwegen

  2. Swiss Institute of Bioinformatics, Basel, Switzerland

    Mohsen Khorshid, Jean Hausser, Mihaela Zavolan & Erik van Nimwegen

Authors
  1. Mohsen Khorshid

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  2. Jean Hausser

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  3. Mihaela Zavolan

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  4. Erik van Nimwegen

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Contributions

Conceived of and designed the experiments: E.v.N. and M.Z. Performed the experiments: M.K. and J.H. Analyzed the data: J.H., M.K., E.v.N. and M.Z. Wrote the paper: J.H., M.K., M.Z. and E.v.N.

Corresponding authors

Correspondence to Mihaela Zavolan or Erik van Nimwegen.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Table 2 and Supplementary Note (PDF 7288 kb)

Supplementary Table 1

Ago2-CLIP cross-link–centered sites used to train the MIRZA model (XLSX 217 kb)

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Khorshid, M., Hausser, J., Zavolan, M. et al. A biophysical miRNA-mRNA interaction model infers canonical and noncanonical targets. Nat Methods 10, 253–255 (2013). https://doi.org/10.1038/nmeth.2341

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