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Transcriptional profiling of cells sorted by RNA abundance

Nature Methods volume 11, pages 549–551 (2014)Cite this article

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Abstract

We have developed a quantitative technique for sorting cells on the basis of endogenous RNA abundance, with a molecular resolution of 10–20 transcripts. We demonstrate efficient and unbiased RNA extraction from transcriptionally sorted cells and report a high-fidelity transcriptome measurement of mouse induced pluripotent stem cells (iPSCs) isolated from a heterogeneous reprogramming culture. This method is broadly applicable to profiling transcriptionally distinct cellular states without requiring antibodies or transgenic fluorescent proteins.

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Figure 1: Quantitative single-cell measurement of transcription.
Figure 2: RNA extraction and transcriptional sorting.
Figure 3: Isolation and transcriptional profiling of iPSCs.

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Gene Expression Omnibus

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Acknowledgements

We thank M. Lou for performing the microarray experiments and M. Bienko, N. Crosetto and N. Slavov for critical reading of the manuscript. This work was supported by the US National Institutes of Health (NIH) National Cancer Institute Physical Sciences Oncology Center at Massachusetts Institute of Technology (U54CA143874), an NIH Pioneer award (8 DP1 CA174420-05), a Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) Vici award to A.v.O. and an NWO Rubicon award to S.S. R.J. was supported by NIH grants HD 045022 and R37CA084198. D.A.F. was supported by a Vertex Scholarship, a US National Science Foundation Graduate Research Fellowship and Jerome and Florence Brill Graduate Student Fellowship. Support for S.K. was provided by the Koch Institute for Integrative Cancer Research Graduate Fellowship.

Author information

Author notes

  1. Sandy Klemm, Stefan Semrau and Kay Wiebrands: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Sandy Klemm

  2. Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Stefan Semrau & Alexander van Oudenaarden

  3. Hubrecht Institute – Royal Netherlands Academy of Arts and Sciences, Utrecht, The Netherlands

    Kay Wiebrands, Dylan Mooijman & Alexander van Oudenaarden

  4. University Medical Center Utrecht, Utrecht, The Netherlands

    Kay Wiebrands, Dylan Mooijman & Alexander van Oudenaarden

  5. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Dina A Faddah, Rudolf Jaenisch & Alexander van Oudenaarden

  6. Whitehead Institute for Biomedical Research, Cambridge, Massachusetts, USA

    Dina A Faddah & Rudolf Jaenisch

  7. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Alexander van Oudenaarden

Authors
  1. Sandy Klemm
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  7. Alexander van Oudenaarden
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Contributions

A.v.O., S.K. and S.S. developed the idea of transcriptionally profiling RNA-sorted cells. S.S. and S.K. demonstrated the compatibility of smFISH with flow cytometry. S.K. performed all of the experiments; K.W. collaborated on the RNA integrity measurements in Supplementary Figure 4 and the reverse cross-linking controls in Figure 2. S.K., S.S., K.W. and A.v.O. developed the reverse cross-linking protocol. S.K. and D.M. optimized the RNA flow sorting procedure. S.K. conceived and experimentally validated the RNA-preserving hybridization buffer (RPHB). D.A.F. and R.J. produced the 2° reprogrammable MEFs. S.K. analyzed the data, developed the analytic estimate of the molecular resolution, prepared the figures, and wrote the manuscript in collaboration with A.v.O., who guided the project. All authors read and commented on the manuscript.

Corresponding authors

Correspondence to Sandy Klemm or Alexander van Oudenaarden.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7 and Supplementary Note (PDF 8051 kb)

Supplementary Data

Probe sequences of smFISH libraries (XLS 35 kb)

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Klemm, S., Semrau, S., Wiebrands, K. et al. Transcriptional profiling of cells sorted by RNA abundance. Nat Methods 11, 549–551 (2014). https://doi.org/10.1038/nmeth.2910

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