Abstract

The hypothalamus contains the highest diversity of neurons in the brain. Many of these neurons can co-release neurotransmitters and neuropeptides in a use-dependent manner. Investigators have hitherto relied on candidate protein-based tools to correlate behavioral, endocrine and gender traits with hypothalamic neuron identity. Here we map neuronal identities in the hypothalamus by single-cell RNA sequencing. We distinguished 62 neuronal subtypes producing glutamatergic, dopaminergic or GABAergic markers for synaptic neurotransmission and harboring the ability to engage in task-dependent neurotransmitter switching. We identified dopamine neurons that uniquely coexpress the Onecut3 and Nmur2 genes, and placed these in the periventricular nucleus with many synaptic afferents arising from neuromedin S+ neurons of the suprachiasmatic nucleus. These neuroendocrine dopamine cells may contribute to the dopaminergic inhibition of prolactin secretion diurnally, as their neuromedin S+ inputs originate from neurons expressing Per2 and Per3 and their tyrosine hydroxylase phosphorylation is regulated in a circadian fashion. Overall, our catalog of neuronal subclasses provides new understanding of hypothalamic organization and function.

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Acknowledgements

The authors thank N.-G. Larsson and L. Olson for providing Dat1-Cre mice for the generation of reporter mice, H. Wong and M. Watanabe for antibodies and K. Meletis for his supervision of viral injections in Dat1-Cre mice. This work was supported by the Swedish Research Council (T. Harkany, T. Hökfelt, S.L., C. Broberger), Hjärnfonden (T. Harkany), the Petrus and Augusta Hedlunds Foundation (T. Harkany), the Novo Nordisk Foundation (T. Harkany, T. Hökfelt, C. Broberger), the National Brain Research Program of Hungary (MTA-SE NAP B, KTIA_NAP_13-2014-0013; A.A.), the European Commission (PAINCAGE grant, T. Harkany, T. Hökfelt), the European Research Council (BRAINCELL; S.L., ENDOSWITCH; C. Broberger and SECRET-CELLS; T. Harkany), intramural funds of the Medical University of Vienna (T. Harkany) and an NIH grant AG051459 (T.L.H.). R.A.R. is an EMBO long-term research fellow (ALTF 596-2014) cofunded by the European Commission FP7 (Marie Curie Actions, EMBOCOFUND2012, GA-2012-600394). A.Z. received support from the Human Frontier Science Program. F.C. is a Research Associate of the Fonds de la Recherche Scientifique-FNRS, Belgium. The single-cell sequencing infrastructure at CeMM was supported by a New Frontiers Research Infrastructure grant from the Austrian Academy of Sciences.

Author information

Author notes

    • Roman A Romanov
    •  & Amit Zeisel

    These authors contributed equally to this work.

    • Tamas L Horvath
    •  & Tibor Harkany

    These authors jointly directed this work.

Affiliations

  1. Department of Molecular Neurosciences, Center for Brain Research, Medical University of Vienna, Vienna, Austria.

    • Roman A Romanov
    • , Fatima Girach
    • , Erik Keimpema
    • , Daniela Calvigioni
    •  & Tibor Harkany
  2. Division of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.

    • Amit Zeisel
    •  & Sten Linnarsson
  3. Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.

    • Joanne Bakker
    • , Arash Hellysaz
    • , Daniela Calvigioni
    • , Ming-Dong Zhang
    • , Christian Broberger
    • , Tomas Hökfelt
    •  & Tibor Harkany
  4. Department of Bioengineering & CNC Program, Stanford University, Stanford, California, USA.

    • Raju Tomer
    • , Brian Hsueh
    • , Ailey K Crow
    •  & Karl Deisseroth
  5. MTA-SE NAP Research Group of Experimental Neuroanatomy and Developmental Biology, Hungarian Academy of Sciences, Budapest, Hungary.

    • Alán Alpár
  6. Department of Anatomy, Semmelweis University, Budapest, Hungary.

    • Alán Alpár
  7. Science for Life Laboratories, Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden.

    • Jan Mulder
  8. Laboratory of Neural Differentiation, Institute of Neuroscience, Université Catholique de Louvain, Brussels, Belgium.

    • Frédéric Clotman
  9. Synaptic Systems GmbH, Göttingen, Germany.

    • Henrik Martens
  10. Microscopy Labs Munich, Global Sales Support-Life Sciences, Carl Zeiss Microscopy GmbH, Munich, Germany.

    • Christian Schwindling
  11. The Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.

    • Jaideep S Bains
  12. Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary.

    • Zoltán Máté
    •  & Gábor Szabó
  13. Department of Genetic and Behavioral Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan.

    • Yuchio Yanagawa
  14. CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria.

    • Andre Rendeiro
    • , Matthias Farlik
    •  & Christoph Bock
  15. Science for Life Laboratory, Albanova University Center, Royal Institute of Technology, Stockholm, Sweden.

    • Mathias Uhlén
  16. Institute of Physiology, Christian Albrechts University, Kiel, Germany.

    • Peer Wulff
  17. Program in Integrative Cell Signaling and Neurobiology of Metabolism, Section of Comparative Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.

    • Tamas L Horvath

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Contributions

T. Harkany and R.A.R. conceived the general framework of this study. T. Harkany, T.L.H., S.L., R.A.R., A.Z., T. Hökfelt, C. Broberger, K.D. designed experiments, T. Harkany, T.L.H., S.L., T. Hökfelt, C. Broberger, K.D., A.A., J.M. and C. Bock senior authors, sponsored research. R.A.R., A.Z., A.H., J.B., F.G., A.A., E.K., R.T., B.H., A.K.C., D.C., M.-D.Z., A.R. and M.F. performed research and analyzed data. H.M., C.S., D.C., Z.M., G.S., F.C., Y.Y., M.U., J.S.B. and P.W. provided unique reagents. R.A.R., A.Z., T.L.H. and T. Harkany wrote the paper. All authors reviewed the manuscript and approved its submission.

Competing interests

T. Harkany declares support from GW Pharmaceuticals on projects unrelated to the focus of this report.

Corresponding authors

Correspondence to Tamas L Horvath or Tibor Harkany.

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Supplementary information

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  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–8 and Supplementary Table 1

  2. 2.

    Supplementary Methods Checklist

Excel files

  1. 1.

    Supplementary Table 2

    Gene expression in neurons in hypothalamic clusters #1-#62

  2. 2.

    Supplementary Table 3: Marker sets used to define junction points during dendrogram construction

    This table shows the top markers that separate each junction of the dendrogram in Figure 2a. For each junction, we searched for genes that best separate the two sides of the junction. The average of the log2(x+1) expression (left) and the fraction of positive cells in each group (expression > 0; right) were calculated, and genes were ranked by their difference. The table shows the top 50 genes found to be specific for each side of particular junctions (left and right) as mentioned above each sub-table. In addition to the score, the p value was calculated using binomial distribution against the null hypothesis that the positive cells are distributed randomly between the groups. q values correspond to p values corrected for multiple testing since each gene was tested for all 61 junctions.

  3. 3.

    Supplementary Table 4: Expression of neuropeptide-coding genes in hypothalamic clusters #1-#62

    Increasing color depth from white toward red was used to visualize genes expressed by individual clusters at distinct levels of statistical significance (q values are shown).

  4. 4.

    Supplementary Table 5: P values for neuron-specific genes (Wilcoxon rank-sum test) expressed by hypothalamic neuronal clusters #1-#62

    Increasing color depth from white toward red was used to visualize genes at distinct levels of statistical significance.

  5. 5.

    Supplementary Table 6: Q values for neuron-specific genes (Wilcoxon rank-sum test corrected for multiple testing using horizontal correction) expressed by hypothalamic neuronal clusters #1-#62

    Increasing color depth from white toward red was used to visualize genes at distinct levels of statistical significance.

Videos

  1. 1.

    Three-dimensional reconstruction of the suprachiasmatic nucleus-paraventricular hypothalamic nucleus region by light-sheet microscopy.

    Red and green colors correspond to phospho-Ser40-TH and onecut-3 immunosignals respectively. Data in rendered form are shown in Fig. 5f. Imaging was performed on a Zeiss Lightsheet Z.1 microscope at 5x primary magnification.

  2. 2.

    Three-dimensional reconstruction of the retrochiasmatic-arcuate nucleus rostral-caudal extent by light-sheet microscopy.

    Red and green colors correspond to phospho-Ser40-TH and onecut-3 immunosignals respectively. Data in rendered form are shown in Fig. 5f. Imaging was performed on a Zeiss Lightsheet Z.1 microscope at 5x primary magnification.

  3. 3.

    Three-dimensional reconstruction of TH+ neurons of the hypothalamus in the intact adult mouse forebrain by CLARITY.

    TH+ cells were visualized using TH immunostaining (see Expanded Methods for details). The size of the bounding box in the movie (i.e. zoomed in volume) is 4.624 mm × 1.910 mm.

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https://doi.org/10.1038/nn.4462

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