Whole-brain comparison of rodent and human brains using spatial transcriptomics
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/
Article and author information
Author details
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
- Alex Fornito, Monash University, Australia
Version history
- Preprint posted: March 18, 2022 (view preprint)
- Received: April 12, 2022
- Accepted: November 4, 2022
- Accepted Manuscript published: November 7, 2022 (version 1)
- 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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