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Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing

Nature Neuroscience volume 18, pages 145153 (2015) | Download Citation

Abstract

The primary sensory system requires the integrated function of multiple cell types, although its full complexity remains unclear. We used comprehensive transcriptome analysis of 622 single mouse neurons to classify them in an unbiased manner, independent of any a priori knowledge of sensory subtypes. Our results reveal eleven types: three distinct low-threshold mechanoreceptive neurons, two proprioceptive, and six principal types of thermosensitive, itch sensitive, type C low-threshold mechanosensitive and nociceptive neurons with markedly different molecular and operational properties. Confirming previously anticipated major neuronal types, our results also classify and provide markers for new, functionally distinct subtypes. For example, our results suggest that itching during inflammatory skin diseases such as atopic dermatitis is linked to a distinct itch-generating type. We demonstrate single-cell RNA-seq as an effective strategy for dissecting sensory responsive cells into distinct neuronal types. The resulting catalog illustrates the diversity of sensory types and the cellular complexity underlying somatic sensation.

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Acknowledgements

The authors thank the CLICK Imaging Facility, supported by the Wallenberg Foundation. This work was supported by the Swedish Research Council for Medicine and Health, the Swedish Foundation for Strategic Research and Linné grants (DBRM grants), the Swedish Brain Foundation, Hållsten Foundation, Torsten Söderberg Foundation, Wallenberg Scholar and European Research Council advanced grant (232675) to P.E.; and by European Research Council starting grant (261063) to S.L.

Author information

Author notes

    • Sten Linnarsson
    •  & Patrik Ernfors

    These authors jointly directed this work.

Affiliations

  1. Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.

    • Dmitry Usoskin
    • , Alessandro Furlan
    • , Saiful Islam
    • , Hind Abdo
    • , Peter Lönnerberg
    • , Daohua Lou
    • , Jens Hjerling-Leffler
    • , Olga Kharchenko
    • , Sten Linnarsson
    •  & Patrik Ernfors
  2. Division of Physiological Chemistry, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.

    • Jesper Haeggström
  3. Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.

    • Peter V Kharchenko
  4. Division of Hematology/Oncology, Children's Hospital, Boston, Massachusetts, USA.

    • Peter V Kharchenko

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Contributions

D.U., S.L. and P.E. designed the study. D.U., A.F., D.L., O.K., H.A., J.H.-L., J.H. and S.I. carried out experiments. D.U., P.V.K., P.L., P.E. and S.L. performed data analysis, including statistical analyses. D.U., S.L. and P.E. wrote the manuscript in consultation with all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Sten Linnarsson or Patrik Ernfors.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–3

  2. 2.

    Supplementary Methods Checklist

Excel files

  1. 1.

    Supplementary Table 1

    Full lists of genes showing differential expression (fold change and significance) for all eleven individual neuronal types analyzed using the SCDE method against all remaining neurons (pooled) See first worksheet (Tab1-INFO) for detailed legend.

  2. 2.

    Supplementary Table 2

    GO analysis of biological processes for eleven neuronal types To Fig. 2e. See first worksheet (Tab1-INFO) for detailed legend.

  3. 3.

    Supplementary Table 3

    Differential expression (fold change and significance) for neuronal versus non-neuronal populations and gene ontology analysis (biological process) distinguishing these two populations See first worksheet (Tab1-INFO) for detailed legend.

  4. 4.

    Supplementary Table 4

    Expression profile (fraction of positive cells, with color coding) for 452 genes (fused 11 lists with top 50 genes enriched in each of neuronal categories, by SCDE method, after redundancy removal; “top 50” list) and all neuronal types. To Fig. 2d. See first worksheet (Tab1-INFO) for detailed legend.

  5. 5.

    Supplementary Table 5

    Expression profile (fraction of positive cells, with color coding) of 18 genes (17 picked from “top 50” gene lists (Table S2) and Ntrk3 (TrkC) as extensively used sensory marker) used for in vivo immunohistochemical validation experiments. To Fig. 3. See first worksheet (Tab1-INFO) for detailed legend.

  6. 6.

    Supplementary Table 6

    Expression profile (fraction of positive cells, with color coding) for genes participating as operational components (shown in Figure 4a, in the same order) of sensory neurons in the different neuronal types. To Fig. 4a. See first worksheet (Tab1-INFO) for detailed legend.

  7. 7.

    Supplementary Table 7

    Expression profile (fraction of positive cells, with color coding) for itch-related and neuropeptide genes in unmyelinated neurons.  To Table 1. See first worksheet (Tab1-INFO) for detailed legend.

Videos

  1. 1.

    3D video for PCA plot of five clusters representing four neuronal and one non-neuronal cell populations shown in Figure 1a

  2. 2.

    3D video for PCA plot of four principal neuronal types shown in Figure 1b

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DOI

https://doi.org/10.1038/nn.3881

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