Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain

  1. David M Young
  2. Siavash Fazel Darbandi
  3. Grace Schwartz
  4. Zachary Bonzell
  5. Deniz Yuruk
  6. Mai Nojima
  7. Laurent C Gole
  8. John LR Rubenstein
  9. Weimiao Yu
  10. Stephan J Sanders  Is a corresponding author
  1. University of California, San Francisco, United States
  2. Agency for Science, Technology and Research, Singapore

Abstract

3D imaging data necessitate 3D reference atlases for accurate quantitative interpretation. Existing computational methods to generate 3D atlases from 2D-derived atlases result in extensive artifacts, while manual curation approaches are labor-intensive. We present a computational approach for 3D atlas construction that substantially reduces artifacts by identifying anatomical boundaries in the underlying imaging data and using these to guide 3D transformation. Anatomical boundaries also allow extension of atlases to complete edge regions. Applying these methods to the eight developmental stages in the Allen Developing Mouse Brain Atlas (ADMBA) led to more comprehensive and accurate atlases. We generated imaging data from fifteen whole mouse brains to validate atlas performance and observed qualitative and quantitative improvement (37% greater alignment between atlas and anatomical boundaries). We provide the pipeline as the MagellanMapper software and the eight 3D reconstructed ADMBA atlases. These resources facilitate whole-organ quantitative analysis between samples and across development.

Data availability

The full 3D generated atlases and wild-type brain images are being deposited with the Human Brain Project EBRAINS data platform. All data analyses are included in the manuscript and supporting files.

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

Article and author information

Author details

  1. David M Young

    Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Siavash Fazel Darbandi

    Psychiatry, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Grace Schwartz

    Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Zachary Bonzell

    Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Deniz Yuruk

    Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Mai Nojima

    Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Laurent C Gole

    Institute of Molecular and Cellular Biology, Agency for Science, Technology and Research, Singapore, Singapore
    Competing interests
    The authors declare that no competing interests exist.
  8. John LR Rubenstein

    Department of Psychiatry, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4414-7667
  9. Weimiao Yu

    Institute of Molecular and Cellular Biology, Agency for Science, Technology and Research, Singapore, Singapore
    Competing interests
    The authors declare that no competing interests exist.
  10. Stephan J Sanders

    Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, United States
    For correspondence
    stephan.sanders@ucsf.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9112-5148

Funding

Brain and Behavior Research Foundation (NARSAD Young Investigator Grant)

  • Stephan J Sanders

National Institute of Mental Health (U01 MH122681)

  • Stephan J Sanders

National Institute of Mental Health (R01 MH109901)

  • Stephan J Sanders

National Institute of Neurological Disorders and Stroke (R01 NS099099)

  • John LR Rubenstein

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

Ethics

Animal experimentation: All procedures and animal care were approved and performed in accordance with institutional guidelines from the University of California San Francisco Laboratory Animal Research Center (LARC). All animal handling complied with the approved Institutional Animal Care and Use Committee (IACUC) protocol (AN180174-02) at the University of California San Francisco.

Reviewing Editor

  1. Joseph G Gleeson, Howard Hughes Medical Institute, The Rockefeller University, United States

Publication history

  1. Received: July 24, 2020
  2. Accepted: February 10, 2021
  3. Accepted Manuscript published: February 11, 2021 (version 1)
  4. Version of Record published: March 25, 2021 (version 2)

Copyright

© 2021, Young 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 M Young
  2. Siavash Fazel Darbandi
  3. Grace Schwartz
  4. Zachary Bonzell
  5. Deniz Yuruk
  6. Mai Nojima
  7. Laurent C Gole
  8. John LR Rubenstein
  9. Weimiao Yu
  10. Stephan J Sanders
(2021)
Constructing and optimizing 3D atlases from 2D data with application to the developing mouse brain
eLife 10:e61408.
https://doi.org/10.7554/eLife.61408

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