Abstract

Seeking new insights into the homeostasis, modulation and plasticity of cortical synaptic networks, we have analyzed results from a single-cell RNA-seq study of 22,439 mouse neocortical neurons. Our analysis exposes transcriptomic evidence for dozens of molecularly distinct neuropeptidergic modulatory networks that directly interconnect all cortical neurons. This evidence begins with a discovery that transcripts of one or more neuropeptide precursor (NPP) and one or more neuropeptide-selective G-protein-coupled receptor (NP-GPCR) genes are highly abundant in all, or very nearly all, cortical neurons. Individual neurons express diverse subsets of NP signaling genes from palettes encoding 18 NPPs and 29 NP-GPCRs. These 47 genes comprise 37 cognate NPP/NP-GPCR pairs, implying the likelihood of local neuropeptide signaling. Here we use neuron-type-specific patterns of NP gene expression to offer specific, testable predictions regarding 37 peptidergic neuromodulatory networks that may play prominent roles in cortical homeostasis and plasticity.

Data availability

The present study is an analysis of a large transcriptomic dataset that is now freely available for download in its entirety athttp://celltypes.brain-map.org/rnaseq/ and is described fully in a rigorously peer-reviewed publication (Tasic, et al., Nature 563:72-78, 2018). All code and intermediate data products involved in preparing this manuscript are freely available from a well-documented GitHub repository: https://github.com/AllenInstitute/PeptidergicNetworks

The following previously published data sets were used

Article and author information

Author details

  1. Stephen J Smith

    Allen Institute for Brain Science, Seattle, United States
    For correspondence
    stephens@alleninstitute.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2290-8701
  2. Uygar Sümbül

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7134-8897
  3. Lucas T Graybuck

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8814-6818
  4. Forrest Collman

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Shamishtaa Seshamani

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Rohan Gala

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Olga Gliko

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Leila Elabbady

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Jeremy A Miller

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4549-588X
  10. Trygve E Bakken

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3373-7386
  11. Jean Rossier

    Neuroscience Paris Seine, Sorbonne Université, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  12. Zizhen Yao

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Ed Lein

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9012-6552
  14. Hongkui Zeng

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0326-5878
  15. Bosiljka Tasic

    Allen Institute for Brain Science, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6861-4506
  16. Michael Hawrylycz

    Allen Institute for Brain Science, Seattle, United States
    For correspondence
    MikeH@alleninstitute.org
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institutes of Health (R01NS092474)

  • Stephen J Smith

National Institutes of Health (R01MH104227)

  • Stephen J Smith

National Institutes of Health (1U24NS109113)

  • Stephen J Smith

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. David D Ginty, Harvard Medical School, United States

Version history

  1. Received: April 23, 2019
  2. Accepted: November 10, 2019
  3. Accepted Manuscript published: November 11, 2019 (version 1)
  4. Version of Record published: November 27, 2019 (version 2)

Copyright

© 2019, Smith et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Stephen J Smith
  2. Uygar Sümbül
  3. Lucas T Graybuck
  4. Forrest Collman
  5. Shamishtaa Seshamani
  6. Rohan Gala
  7. Olga Gliko
  8. Leila Elabbady
  9. Jeremy A Miller
  10. Trygve E Bakken
  11. Jean Rossier
  12. Zizhen Yao
  13. Ed Lein
  14. Hongkui Zeng
  15. Bosiljka Tasic
  16. Michael Hawrylycz
(2019)
Single-cell transcriptomic evidence for dense intracortical neuropeptide networks
eLife 8:e47889.
https://doi.org/10.7554/eLife.47889

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https://doi.org/10.7554/eLife.47889

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