Sex, strain and lateral differences in brain cytoarchitecture across a large mouse population

  1. David Elkind
  2. Hannah Hochgerner
  3. Etay Aloni
  4. Noam Shental  Is a corresponding author
  5. Amit Zeisel  Is a corresponding author
  1. Open University of Israel, Israel
  2. Technion - Israel Institute of Technology, Israel

Abstract

The mouse brain is by far the most intensively studied among mammalian brains, yet basic measures of its cytoarchitecture remain obscure. For example, quantifying cell numbers, and the interplay of sex-, strain-, and individual variability in cell density and volume is out of reach for many regions. The Allen Mouse Brain Connectivity project produces high-resolution full brain images of hundreds of brains. Although these were created for a different purpose, they reveal details of neuroanatomy and cytoarchitecture. Here, we used this population to systematically characterize cell density and volume for each anatomical unit in the mouse brain. We developed a deep neural network-based segmentation pipeline that uses the auto-fluorescence intensities of images to segment cell nuclei even within the densest regions, such as the dentate gyrus. We applied our pipeline to 507 brains of males and females from C57BL/6J and FVB.CD1 strains. Globally, we found that increased overall brain volume does not result in uniform expansion across all regions. Moreover, region-specific density changes are often negatively correlated with the volume of the region, therefore cell count does not scale linearly with volume. Many regions, including layer 2/3 across several cortical areas, showed distinct lateral bias. We identified strain-specific or sex-specific differences. For example, males tended to have more cells in extended amygdala and hypothalamic regions (MEA, BST, BLA, BMA, and LPO, AHN) while females had more cells in the orbital cortex (ORB). Yet, inter-individual variability was always greater than the effect size of a single qualifier. We provide the results of this analysis as an accessible resource for the community.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting file; Tables related to values of data appear in the figures can be found in excel file.

The following previously published data sets were used

Article and author information

Author details

  1. David Elkind

    Department of Computer Science, Open University of Israel, Raanana, Israel
    Competing interests
    The authors declare that no competing interests exist.
  2. Hannah Hochgerner

    Faculty of Biotechnology and Food Engineering, Technion - Israel Institute of Technology, Haifa, Israel
    Competing interests
    The authors declare that no competing interests exist.
  3. Etay Aloni

    Faculty of Biotechnology and Food Engineering, Technion - Israel Institute of Technology, Haifa, Israel
    Competing interests
    The authors declare that no competing interests exist.
  4. Noam Shental

    Department of Computer Science, Open University of Israel, Raanana, Israel
    For correspondence
    shental@openu.ac.il
    Competing interests
    The authors declare that no competing interests exist.
  5. Amit Zeisel

    Faculty of Biotechnology and Food Engineering, Technion - Israel Institute of Technology, Haifa, Israel
    For correspondence
    amit.zeisel@technion.ac.il
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2424-9279

Funding

European Research Council (TYPEWIRE-852786)

  • Hannah Hochgerner
  • Etay Aloni
  • Amit Zeisel

Human Frontier Science Program (CDA-0039/2019-C)

  • Hannah Hochgerner
  • Amit Zeisel

Israel Science Foundation (2028912)

  • Hannah Hochgerner
  • Amit Zeisel

Swedish Brain Foundation

  • Hannah Hochgerner

Israel ministry of science, technology & space (3-16033)

  • Noam Shental

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

Copyright

© 2023, Elkind 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. David Elkind
  2. Hannah Hochgerner
  3. Etay Aloni
  4. Noam Shental
  5. Amit Zeisel
(2023)
Sex, strain and lateral differences in brain cytoarchitecture across a large mouse population
eLife 12:e82376.
https://doi.org/10.7554/eLife.82376

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https://doi.org/10.7554/eLife.82376