Skip to main content

Thank you for visiting 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.

Visualizing SNVs to quantify allele-specific expression in single cells

This article has been updated


We present a FISH-based method for detecting single-nucleotide variants (SNVs) in exons and introns on individual RNA transcripts with high efficiency. We used this method to quantify allelic expression in cell populations and in single cells, and also to distinguish maternal from paternal chromosomes in single cells.

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

Prices vary by article type



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

Figure 1: Toehold probes enable SNV detection on individual RNA molecules in situ.
Figure 2: Allele-specific expression in GM12878 single cells and populations.

Change history

  • 14 August 2013

    In the version of this article initially published online, a bar in panel d of Figure 1 was left blank. It should have been filled with the appropriate colors to indicate the number of transcripts derived from wild-type (blue) or mutant (orange) RNA and the number of unclassified transcripts (colorless). The error has been corrected for the print, PDF and HTML versions of the article.


  1. Femino, A.M., Fay, F.S., Fogarty, K. & Singer, R.H. Science 280, 585–590 (1998).

    Article  CAS  Google Scholar 

  2. Raj, A., van den Bogaard, P., Rifkin, S.A., van Oudenaarden, A. & Tyagi, S. Nat. Methods 5, 877–879 (2008).

    Article  CAS  Google Scholar 

  3. Levesque, M.J. & Raj, A. Nat. Methods 10, 246–248 (2013).

    Article  CAS  Google Scholar 

  4. Larsson, C., Grundberg, I., Söderberg, O. & Nilsson, M. Nat. Methods 7, 395–397 (2010).

    Article  CAS  Google Scholar 

  5. Gimelbrant, A., Hutchinson, J.N., Thompson, B.R. & Chess, A. Science 318, 1136–1140 (2007).

    Article  CAS  Google Scholar 

  6. Gregg, C. et al. Science 329, 643–648 (2010).

    Article  CAS  Google Scholar 

  7. Ferguson-Smith, A.C. Nat. Rev. Genet. 12, 565–575 (2011).

    Article  CAS  Google Scholar 

  8. Zhang, D.Y. & Winfree, E. J. Am. Chem. Soc. 131, 17303–17314 (2009).

    Article  CAS  Google Scholar 

  9. Zhang, D.Y., Chen, S.X. & Yin, P. Nat. Chem. 4, 208–214 (2012).

    Article  CAS  Google Scholar 

  10. Li, Q., Luan, G., Guo, Q. & Liang, J. Nucleic Acids Res. 30, E5 (2002).

    Article  Google Scholar 

  11. Raj, A. & Tyagi, S. Methods Enzymol. 472, 365–386 (2010).

    Article  CAS  Google Scholar 

  12. Lubeck, E. & Cai, L. Nat. Methods 9, 743–748 (2012).

    Article  CAS  Google Scholar 

  13. 1000 Genomes Project Consortium. et al. Nature 467, 1061–1073 (2010).

  14. Gertz, J. et al. PLoS Genet. 7, e1002228 (2011).

    Article  CAS  Google Scholar 

  15. Rozowsky, J. et al. Mol. Syst. Biol. 7, 522 (2011).

    Article  Google Scholar 

  16. Raj, A., Peskin, C.S., Tranchina, D., Vargas, D.Y. & Tyagi, S. PLoS Biol. 4, e309 (2006).

    Article  Google Scholar 

  17. Chubb, J.R. et al. Dev. Biol. 292, 519–532 (2006).

    Article  CAS  Google Scholar 

  18. Golding, I., Paulsson, J., Zawilski, S.M. & Cox, E.C. Cell 123, 1025–1036 (2005).

    Article  CAS  Google Scholar 

  19. Raj, A. & van Oudenaarden, A. Cell 135, 216–226 (2008).

    Article  CAS  Google Scholar 

  20. Abramowitz, L.K. & Bartolomei, M.S. Curr. Opin. Genet. Dev. 22, 72–78 (2012).

    Article  CAS  Google Scholar 

Download references


We thank Biosearch technologies for providing many of the reagents used in our assays and G. Nair for many discussions about statistics. We acknowledge the US National Institutes of Health Director's New Innovator Award (1DP2OD008514; M.J.L., P.G., Y.W. and A.R.) and a Burroughs-Wellcome Fund Career Award at the Scientific Interface (A.R.) for supporting our work.

Author information

Authors and Affiliations



M.J.L. conceived of the method with guidance from A.R. M.J.L. performed the image analysis and P.G. performed the statistical analysis. M.J.L., Y.W. and P.G. performed the experiments. M.J.L., P.G. and A.R. wrote the paper.

Corresponding authors

Correspondence to Marshall J Levesque or Arjun Raj.

Ethics declarations

Competing interests

A.R. and M.J.L. are inventors on a US provisional patent 61/785,498 on the method described in this paper, and receive royalties related to this and other related patents.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8, Supplementary Tables 1 and 2, and Supplementary Note 1 (PDF 1655 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Levesque, M., Ginart, P., Wei, Y. et al. Visualizing SNVs to quantify allele-specific expression in single cells. Nat Methods 10, 865–867 (2013).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


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