1. Computational and Systems Biology
  2. Evolutionary Biology
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Mapping single-cell atlases throughout Metazoa unravels cell type evolution

  1. Alexander J Tarashansky
  2. Jacob M Musser
  3. Margarita Khariton
  4. Pengyang Li
  5. Detlev Arendt
  6. Stephen R Quake
  7. Bo Wang  Is a corresponding author
  1. Stanford University, United States
  2. European Molecular Biology Laboratory, Germany
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Cite this article as: eLife 2021;10:e66747 doi: 10.7554/eLife.66747
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Abstract

Comparing single-cell transcriptomic atlases from diverse organisms can elucidate the origins of cellular diversity and assist the annotation of new cell atlases. Yet, comparison between distant relatives is hindered by complex gene histories and diversifications in expression programs. Previously, we introduced the self-assembling manifold (SAM) algorithm to robustly reconstruct manifolds from single-cell data (Tarashansky et al., 2019). Here, we build on SAM to map cell atlas manifolds across species. This new method, SAMap, identifies homologous cell types with shared expression programs across distant species within phyla, even in complex examples where homologous tissues emerge from distinct germ layers. SAMap also finds many genes with more similar expression to their paralogs than their orthologs, suggesting paralog substitution may be more common in evolution than previously appreciated. Lastly, comparing species across animal phyla, spanning mouse to sponge, reveals ancient contractile and stem cell families, which may have arisen early in animal evolution.

Data availability

All data analyzed during this study are available through various sources as listed in Supplementary File 1.

The following previously published data sets were used

Article and author information

Author details

  1. Alexander J Tarashansky

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jacob M Musser

    Developmental Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Margarita Khariton

    Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Pengyang Li

    Department of Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Detlev Arendt

    Developmental Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7833-050X
  6. Stephen R Quake

    Bioengineering, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Bo Wang

    Bioengineering, Stanford University, Stanford, United States
    For correspondence
    wangbo@stanford.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8880-1432

Funding

Arnold and Mabel Beckman Foundation (Beckman Young Investigator Award)

  • Bo Wang

National Institutes of Health (1R35GM138061)

  • Bo Wang

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 experiments with and care of mice are performed in accordance with protocols approved by the Institutional Animal Care and Use Committees (IACUC) of Stanford University (protocol approval number 30366).

Reviewing Editor

  1. Alex K Shalek, Broad Institute of MIT and Harvard, United States

Publication history

  1. Received: January 26, 2021
  2. Accepted: April 30, 2021
  3. Accepted Manuscript published: May 4, 2021 (version 1)

Copyright

© 2021, Tarashansky 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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