Whole-brain comparison of rodent and human brains using spatial transcriptomics

  1. Antoine Beauchamp  Is a corresponding author
  2. Yohan Yee
  3. Benjamin C Darwin
  4. Armin Raznahan
  5. Rogier B Mars  Is a corresponding author
  6. Jason P Lerch  Is a corresponding author
  1. University of Toronto, Canada
  2. Mouse Imaging Centre, Canada
  3. Hospital for Sick Children, Canada
  4. National Institute of Mental Health, United States
  5. Radboud University Nijmegen, Netherlands
  6. University of Oxford, United Kingdom

Abstract

The ever-increasing use of mouse models in preclinical neuroscience research calls for an improvement in the methods used to translate findings between mouse and human brains. Previously we showed that the brains of primates can be compared in a direct quantitative manner using a common reference space built from white matter tractography data (Rogier B. Mars et al., 2018b). Here we extend the common space approach to evaluate the similarity of mouse and human brain regions using openly accessible brain-wide transcriptomic data sets. We show that mouse-human homologous genes capture broad patterns of neuroanatomical organization, but that the resolution of cross-species correspondences can be improved using a novel supervised machine learning approach. Using this method, we demonstrate that sensorimotor subdivisions of the neocortex exhibit greater similarity between species, compared with supramodal subdivisions, and that mouse isocortical regions separate into sensorimotor and supramodal clusters based on their similarity to human cortical regions. We also find that mouse and human striatal regions are strongly conserved, with the mouse caudoputamen exhibiting an equal degree of similarity to both the human caudate and putamen.

Data availability

The Allen Mouse Brain Atlas and Allen Human Brain Atlas data sets are openly accessible and can be downloaded from the Allen Institute's API (http://api.brain-map.org). All of the code and additional data needed to generate this analysis, including figures and manuscript, is accessible at https://github.com/abeaucha/MouseHumanTranscriptomicSimilarity/

The following previously published data sets were used

Article and author information

Author details

  1. Antoine Beauchamp

    Department of Medical Biophysics, University of Toronto, Toronto, Canada
    For correspondence
    antoine.beauchamp@mail.utoronto.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0008-7471
  2. Yohan Yee

    Mouse Imaging Centre, Montréal, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7083-1932
  3. Benjamin C Darwin

    Hospital for Sick Children, Toronto, Canada
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8689-046X
  4. Armin Raznahan

    Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5622-1190
  5. Rogier B Mars

    Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
    For correspondence
    rogier.mars@ndcn.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
  6. Jason P Lerch

    Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
    For correspondence
    jason.lerch@ndcn.ox.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

Funding

Canadian Institutes of Health Research (Doctoral Award - Frederick Banting and Charles Best Canada Graduate Scholarships (GSD-165737))

  • Antoine Beauchamp

Wellcome Trust (203139/Z/16/Z)

  • Rogier B Mars
  • Jason P Lerch

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

Reviewing Editor

  1. Alex Fornito, Monash University, Australia

Version history

  1. Preprint posted: March 18, 2022 (view preprint)
  2. Received: April 12, 2022
  3. Accepted: November 4, 2022
  4. Accepted Manuscript published: November 7, 2022 (version 1)
  5. Version of Record published: November 29, 2022 (version 2)

Copyright

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

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  1. Antoine Beauchamp
  2. Yohan Yee
  3. Benjamin C Darwin
  4. Armin Raznahan
  5. Rogier B Mars
  6. Jason P Lerch
(2022)
Whole-brain comparison of rodent and human brains using spatial transcriptomics
eLife 11:e79418.
https://doi.org/10.7554/eLife.79418

Share this article

https://doi.org/10.7554/eLife.79418

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