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

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

Article and author information

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

Version 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)
  5. Version of Record updated: February 20, 2023 (version 3)

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.

Metrics

  • 3,135
    views
  • 502
    downloads
  • 7
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  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
  9. Jun Yan
  10. Jie He
(2021)
The landscape of regulatory genes in brain-wide neuronal phenotypes of a vertebrate brain
eLife 10:e68224.
https://doi.org/10.7554/eLife.68224

Share this article

https://doi.org/10.7554/eLife.68224

Further reading

    1. Neuroscience
    Alexandra L Jellinger, Rebecca L Suthard ... Steve Ramirez
    Research Article

    Negative memories engage a brain and body-wide stress response in humans that can alter cognition and behavior. Prolonged stress responses induce maladaptive cellular, circuit, and systems-level changes that can lead to pathological brain states and corresponding disorders in which mood and memory are affected. However, it is unclear if repeated activation of cells processing negative memories induces similar phenotypes in mice. In this study, we used an activity-dependent tagging method to access neuronal ensembles and assess their molecular characteristics. Sequencing memory engrams in mice revealed that positive (male-to-female exposure) and negative (foot shock) cells upregulated genes linked to anti- and pro-inflammatory responses, respectively. To investigate the impact of persistent activation of negative engrams, we chemogenetically activated them in the ventral hippocampus over 3 months and conducted anxiety and memory-related tests. Negative engram activation increased anxiety behaviors in both 6- and 14-month-old mice, reduced spatial working memory in older mice, impaired fear extinction in younger mice, and heightened fear generalization in both age groups. Immunohistochemistry revealed changes in microglial and astrocytic structure and number in the hippocampus. In summary, repeated activation of negative memories induces lasting cellular and behavioral abnormalities in mice, offering insights into the negative effects of chronic negative thinking-like behaviors on human health.

    1. Neuroscience
    Alexandra H Leighton, Juliette E Cheyne, Christian Lohmann
    Research Article

    Synaptic inputs to cortical neurons are highly structured in adult sensory systems, such that neighboring synapses along dendrites are activated by similar stimuli. This organization of synaptic inputs, called synaptic clustering, is required for high-fidelity signal processing, and clustered synapses can already be observed before eye opening. However, how clustered inputs emerge during development is unknown. Here, we employed concurrent in vivo whole-cell patch-clamp and dendritic calcium imaging to map spontaneous synaptic inputs to dendrites of layer 2/3 neurons in the mouse primary visual cortex during the second postnatal week until eye opening. We found that the number of functional synapses and the frequency of transmission events increase several fold during this developmental period. At the beginning of the second postnatal week, synapses assemble specifically in confined dendritic segments, whereas other segments are devoid of synapses. By the end of the second postnatal week, just before eye opening, dendrites are almost entirely covered by domains of co-active synapses. Finally, co-activity with their neighbor synapses correlates with synaptic stabilization and potentiation. Thus, clustered synapses form in distinct functional domains presumably to equip dendrites with computational modules for high-capacity sensory processing when the eyes open.