Brief Communication | Published:

irCLIP platform for efficient characterization of protein–RNA interactions

Nature Methods volume 13, pages 489492 (2016) | Download Citation

Abstract

The complexity of transcriptome-wide protein–RNA interaction networks is incompletely understood. While emerging studies are greatly expanding the known universe of RNA-binding proteins, methods for the discovery and characterization of protein–RNA interactions remain resource intensive and technically challenging. Here we introduce a UV-C crosslinking and immunoprecipitation platform, irCLIP, which provides an ultraefficient, fast, and nonisotopic method for the detection of protein–RNA interactions using far less material than standard protocols.

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References

  1. 1.

    , , & Methods Enzymol. 164, 287–309 (1988).

  2. 2.

    , , & Methods 37, 376–386 (2005).

  3. 3.

    et al. Nature 456, 464–469 (2008).

  4. 4.

    , , & Nature 460, 479–486 (2009).

  5. 5.

    et al. Mol. Cell 36, 996–1006 (2009).

  6. 6.

    et al. Cell 141, 129–141 (2010).

  7. 7.

    et al. Mol. Cell 43, 340–352 (2011).

  8. 8.

    et al. Nat. Struct. Mol. Biol. 17, 909–915 (2010).

  9. 9.

    et al. Cell 152, 453–466 (2013).

  10. 10.

    et al. Cell Rep. 6, 1139–1152 (2014).

  11. 11.

    et al. RNA 21, 135–143 (2015).

  12. 12.

    et al. Cell 149, 1393–1406 (2012).

  13. 13.

    et al. Mol. Cell 46, 674–690 (2012).

  14. 14.

    et al. Nat. Struct. Mol. Biol. 20, 1122–1130 (2013).

  15. 15.

    et al. Nat. Protoc. 9, 263–293 (2014).

  16. 16.

    et al. Methods 65, 274–287 (2014).

  17. 17.

    , , , & Nat. Methods 11, 319–324 (2014).

  18. 18.

    , & Methods 26, 170–181 (2002).

  19. 19.

    & Biotechnol. Prog. 17, 1107–1113 (2001).

  20. 20.

    et al. RNA 19, 958–970 (2013).

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Acknowledgements

We thank A. Fire, P. Sarnow, and M. Kay for presubmission review. We thank L. Morcom and P. Bernstein for expert administrative assistance and members of the Khavari lab for helpful discussions. This work was supported by the US VA Office of Research and Development, NIH AR49737 and NIH CA142635 (P.A.K.), P50-HG007735 and R01-ES023168 (H.Y.C.), and the Stanford Medical Scientist Program and NIH 1F30CA189514-01 (R.A.F.).

Author information

Affiliations

  1. Program in Epithelial Biology, Stanford University School of Medicine, Stanford, California, USA.

    • Brian J Zarnegar
    • , Ryan A Flynn
    • , Ying Shen
    • , Brian T Do
    • , Howard Y Chang
    •  & Paul A Khavari
  2. Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA.

    • Ryan A Flynn
    • , Brian T Do
    •  & Howard Y Chang
  3. Veterans Affairs, Palo Alto Healthcare System, Palo Alto, California, USA.

    • Paul A Khavari

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Contributions

B.J.Z. designed and executed experiments, analyzed the data, and wrote the manuscript with input from the coauthor R.A.F. R.A.F. and B.T.D. designed the FAST-iCLIP pipeline for analysis of ir/iCLIP data. Y.S. executed statistical analysis of ir/iCLIP data replicates. P.A.K. and H.Y.C. designed experiments and wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Paul A Khavari.

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DOI

https://doi.org/10.1038/nmeth.3840

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