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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

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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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Gene Expression Omnibus

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.

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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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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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