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.

Identifying RNA editing sites using RNA sequencing data alone

Abstract

We show that RNA editing sites can be called with high confidence using RNA sequencing data from multiple samples across either individuals or species, without the need for matched genomic DNA sequence. We identified many previously unidentified editing sites in both humans and Drosophila; our results nearly double the known number of human protein recoding events. We also found that human genes harboring conserved editing sites within Alu repeats are enriched for neuronal functions.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Identification and validation of A-to-I RNA editing sites using RNA-seq data from human brain tissues.
Figure 2: Accurate identification of RNA editing sites in the primate lineage.
Figure 3: RNA editing site identification in Drosophila.

Accession codes

Primary accessions

Gene Expression Omnibus

References

  1. Nishikura, K. Annu. Rev. Biochem. 79, 321–349 (2010).

    Article  CAS  Google Scholar 

  2. Kim, U., Wang, Y., Sanford, T., Zeng, Y. & Nishikura, K. Proc. Natl. Acad. Sci. USA 91, 11457–11461 (1994).

    Article  CAS  Google Scholar 

  3. Levanon, E.Y. et al. Nat. Biotechnol. 22, 1001–1005 (2004).

    Article  CAS  Google Scholar 

  4. Eisenberg, E., Li, J.B. & Levanon, E.Y. RNA Biol. 7, 248–252 (2010).

    Article  CAS  Google Scholar 

  5. Rosenthal, J.J. & Seeburg, P.H. Neuron 74, 432–439 (2012).

    Article  CAS  Google Scholar 

  6. Bahn, J.H. et al. Genome Res. 22, 142–150 (2012).

    Article  CAS  Google Scholar 

  7. Peng, Z. et al. Nat. Biotechnol. 30, 253–260 (2012).

    Article  CAS  Google Scholar 

  8. Ramaswami, G. et al. Nat. Methods 9, 579–581 (2012).

    Article  CAS  Google Scholar 

  9. DePristo, M.A. et al. Nat. Genet. 43, 491–498 (2011).

    Article  CAS  Google Scholar 

  10. Li, M. et al. Science 333, 53–58 (2011).

    Article  CAS  Google Scholar 

  11. Kleinman, C.L., Adoue, V. & Majewski, J. RNA 18, 1586–1596 (2012).

    Article  CAS  Google Scholar 

  12. Kleinman, C.L. & Majewski, J. Science 335, 1302 (2012).

    Article  CAS  Google Scholar 

  13. Lin, W., Piskol, R., Tan, M.H. & Li, J.B. Science 335, 1302 (2012).

    Article  CAS  Google Scholar 

  14. Pickrell, J.K., Gilad, Y. & Pritchard, J.K. Science 335, 1302 (2012).

    Article  CAS  Google Scholar 

  15. Schrider, D.R., Gout, J.F. & Hahn, M.W. PLoS ONE 6, e25842 (2011).

    Article  CAS  Google Scholar 

  16. Piskol, R., Peng, Z., Wang, J. & Li, J.B. Nat. Biotechnol. 31, 19–20 (2013).

    Article  CAS  Google Scholar 

  17. Li, J.B. et al. Science 324, 1210–1213 (2009).

    Article  CAS  Google Scholar 

  18. Goodman, M. Am. J. Hum. Genet. 64, 31–39 (1999).

    Article  CAS  Google Scholar 

  19. Paz-Yaacov, N. et al. Proc. Natl. Acad. Sci. USA 107, 12174–12179 (2010).

    Article  CAS  Google Scholar 

  20. Tamura, K., Subramanian, S. & Kumar, S. Mol. Biol. Evol. 21, 36–44 (2004).

    Article  CAS  Google Scholar 

  21. Hoopengardner, B., Bhalla, T., Staber, C. & Reenan, R. Science 301, 832–836 (2003).

    Article  CAS  Google Scholar 

  22. Huang da, W. Nat. Protoc. 4, 44–57 (2009).

    Article  Google Scholar 

  23. Li, H. & Durbin, R. Bioinformatics 26, 589–595 (2010).

    Article  Google Scholar 

  24. Vacic, V., Iakoucheva, L.M. & Radivojac, P. Bioinformatics 22, 1536–1537 (2006).

    Article  CAS  Google Scholar 

  25. Kiran, A. & Baranov, P.V. Bioinformatics 26, 1772–1776 (2010).

    Article  CAS  Google Scholar 

  26. Palladino, M.J., Keegan, L.P., O'Connell, M.A. & Reenan, R.A. Cell 102, 437–449 (2000).

    Article  CAS  Google Scholar 

  27. Picardi, E. et al. Nucleic Acids Res. 38, 4755–4767 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank E. Levanon, A. Fire and members of the Li lab for constructive discussions, S. Blair for assistance with data set curation, and modENCODE Consortium for the use of Drosophila RNA-seq data sets. G.R. and P.D. were supported by the Stanford Genome Training Program funded by the US National Institutes of Health. R.Z. was partially supported by a Dean's fellowship from Stanford University School of Medicine. R.P. was supported by a fellowship from the German Academic Exchange Service. This work was supported by startup funds from Stanford University Department of Genetics and Ellison Medical Foundation (to J.B.L.) and Medical Research Council, UK (to M.A.O.).

Author information

Authors and Affiliations

Authors

Contributions

G.R. and R.Z. performed computational analyses with help from R.P., P.D. and J.B.L.; R.Z. and G.R. carried out the validation experiments; L.P.K. and M.A.O. generated RNA-seq data for wild-type and Adar5G1 flies; and G.R., R.Z. and J.B.L. wrote the paper with input from other authors.

Corresponding author

Correspondence to Jin Billy Li.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–19, Supplementary Tables 1–10, Supplementary Notes 1–5 (PDF 2289 kb)

Supplementary Data 1

A-to-G mismatches identified in lymphoblastoid cell lines (XLSX 23087 kb)

Supplementary Data 2

Non-A-to-G mismatches identified in lymphoblastoid cell lines (XLSX 8502 kb)

Supplementary Data 3

A-to-G mismatches identified in human brain tissues (XLSX 50144 kb)

Supplementary Data 4

Non-A-to-G mismatches identified in human brain tissues (XLSX 11477 kb)

Supplementary Data 5

A-to-G mismatches identified in other human tissues (XLSX 31524 kb)

Supplementary Data 6

Non-A-to-G mismatches identified in other human tissues (XLSX 9841 kb)

Supplementary Data 7

A-to-G mismatches identified in primate cross-species comparison (XLSX 1479 kb)

Supplementary Data 8

Non-A-to-G mismatches identified in primate cross-species comparison (XLSX 160 kb)

Supplementary Data 9

A-to-G mismatches identified in Drosophila cross-species comparison (XLSX 70 kb)

Supplementary Data 10

Non-A-to-G mismatches identified in Drosophila cross-species comparison (XLSX 35 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ramaswami, G., Zhang, R., Piskol, R. et al. Identifying RNA editing sites using RNA sequencing data alone. Nat Methods 10, 128–132 (2013). https://doi.org/10.1038/nmeth.2330

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nmeth.2330

This article is cited by

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