Mouse aging cell atlas analysis reveals global and cell type specific aging signatures

  1. Martin Jinye Zhang  Is a corresponding author
  2. Angela O Pisco  Is a corresponding author
  3. Spyros Darmanis
  4. James Zou  Is a corresponding author
  1. Harvard University, United States
  2. Chan-Zuckerberg Biohub, United States
  3. Stanford University, United States

Abstract

Aging is associated with complex molecular and cellular processes that are poorly understood. Here we leveraged the Tabula Muris Senis single-cell RNA-seq dataset to systematically characterize gene expression changes during aging across diverse cell types in the mouse. We identified aging-dependent genes in 76 tissue-cell types from 23 tissues and characterized both shared and tissue-cell-specific aging behaviors. We found that the aging-related genes shared by multiple tissue-cell types also change their expression congruently in the same direction during aging in most tissue-cell types, suggesting a coordinated global aging behavior at the organismal level. Scoring cells based on these shared aging genes allowed us to contrast the aging status of different tissues and cell types from a transcriptomic perspective. In addition, we identified genes that exhibit age-related expression changes specific to each functional category of tissue-cell types. Altogether, our analyses provide one of the most comprehensive and systematic characterizations of the molecular signatures of aging across diverse tissue-cell types in a mammalian system.

Data availability

All data can be downloaded at https://figshare.com/articles/dataset/tms_gene_data_rv1/12827615.

The following previously published data sets were used

Article and author information

Author details

  1. Martin Jinye Zhang

    Epidemiology, Harvard University, Boston, United States
    For correspondence
    jinyezhang@hsph.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0006-2466
  2. Angela O Pisco

    Data Science, Chan-Zuckerberg Biohub, San Francisco, United States
    For correspondence
    angela.pisco@czbiohub.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0142-2355
  3. Spyros Darmanis

    Data Science, Chan-Zuckerberg Biohub, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. James Zou

    Biomedical Data Science, Stanford University, Stanford, United States
    For correspondence
    jamesyzou@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8880-4764

Funding

Chan-Zuckberg Biohub

  • James Zou

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

Reviewing Editor

  1. Jing-Dong Jackie Han, Chinese Academy of Sciences, China

Version history

  1. Received: August 20, 2020
  2. Accepted: March 29, 2021
  3. Accepted Manuscript published: April 13, 2021 (version 1)
  4. Version of Record published: April 14, 2021 (version 2)

Copyright

© 2021, Zhang 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. Martin Jinye Zhang
  2. Angela O Pisco
  3. Spyros Darmanis
  4. James Zou
(2021)
Mouse aging cell atlas analysis reveals global and cell type specific aging signatures
eLife 10:e62293.
https://doi.org/10.7554/eLife.62293

Share this article

https://doi.org/10.7554/eLife.62293

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