1. Neuroscience
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The landscape of regulatory genes in brain-wide neuronal phenotypes of a vertebrate brain

  1. Hui Zhang
  2. Haifang Wang Haifang
  3. Xiaoyu Shen
  4. Xinling Jia
  5. Shuguang Yu
  6. Xiaoying Qiu
  7. Yufan Wang
  8. Jiulin Du  Is a corresponding author
  9. Jun Yan  Is a corresponding author
  10. Jie He  Is a corresponding author
  1. Chinese Academy of Sciences, China
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Cite this article as: eLife 2021;10:e68224 doi: 10.7554/eLife.68224

Abstract

Multidimensional landscapes of regulatory genes in neuronal phenotypes at whole-brain levels in the vertebrate remain elusive. We generated single-cell transcriptomes of ~67,000 region- and glutamatergic/neuromodulator-identifiable cells from larval zebrafish brains. Hierarchical clustering based on effector gene profiles ('terminal features') distinguished major brain cell types. Sister clusters at hierarchical termini displayed similar terminal features. It was further verified by a population-level statistical method. Intriguingly, glutamatergic/GABAergic sister clusters mostly expressed distinct transcriptional factor (TF) profiles ('convergent pattern'), whereas neuromodulator-type sister clusters predominantly expressed the same TF profiles ('matched pattern'). Interestingly, glutamatergic/GABAergic clusters with similar TF profiles could also display different terminal features ('divergent pattern'). It led us to identify a library of RNA-binding proteins that differentially marked divergent pair clusters, suggesting the post-transcriptional regulation of neuron diversification. Thus, our findings reveal multidimensional landscapes of transcriptional and post-transcriptional regulators in whole-brain neuronal phenotypes in the zebrafish brain.

Data availability

Single cell RNA-seq data has been deposited on BIG (Genome Sequence Archive - CRA002361), which will be available upon the publication

The following data sets were generated
The following previously published data sets were used

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Author details

  1. Hui Zhang

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5300-5310

  2. Haifang Wang Haifang

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.

  3. Xiaoyu Shen

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8868-7035

  4. Xinling Jia

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.

  5. Shuguang Yu

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6640-5420

  6. Xiaoying Qiu

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.

  7. Yufan Wang

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    Competing interests
    The authors declare that no competing interests exist.

  8. Jiulin Du

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    For correspondence
    forestdu@ion.ac.cn
    Competing interests
    The authors declare that no competing interests exist.

  9. Jun Yan

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    For correspondence
    junyan@ion.ac.cn
    Competing interests
    The authors declare that no competing interests exist.

  10. Jie He

    Institutes for Biological Sciences, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shangjai, China
    For correspondence
    jiehe@ion.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2539-2616

Funding

Shanghai Science and Technology Development Foundation (2018SHZDZX05)

  • Jiulin Du
  • Jun Yan
  • Jie He

Chinese Academy of Sciences (XDB32000000)

  • Jiulin Du
  • Jun Yan
  • Jie He

Shanghai Science and Technology Development Foundation (18JC1410100)

  • Jiulin Du
  • Jun Yan
  • Jie He

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

Reviewing Editor

  1. Koichi Kawakami, National Institute of Genetics, Japan

Publication history

  1. Received: March 10, 2021
  2. Accepted: December 5, 2021
  3. Accepted Manuscript published: December 13, 2021 (version 1)
  4. Version of Record published: January 19, 2022 (version 2)

Copyright

© 2021, Zhang 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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