Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures

View ORCID ProfileMartin Jinye Zhang, Angela Oliveira Pisco, Spyros Darmanis, James Zou
doi: https://doi.org/10.1101/2019.12.23.887604
Martin Jinye Zhang
1Department of Electrical Engineering, Stanford University, Palo Alto, 94304 USA
2Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, 02120 USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Martin Jinye Zhang
  • For correspondence: martinjzhang@gmail.com angela.pisco@czbiohub.org jamesz@stanford.edu
Angela Oliveira Pisco
3Chan-Zuckerberg Biohub, San Francisco, 94158 USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: martinjzhang@gmail.com angela.pisco@czbiohub.org jamesz@stanford.edu
Spyros Darmanis
3Chan-Zuckerberg Biohub, San Francisco, 94158 USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
James Zou
1Department of Electrical Engineering, Stanford University, Palo Alto, 94304 USA
3Chan-Zuckerberg Biohub, San Francisco, 94158 USA
4Department of Biomedical Data Science, Stanford University, Palo Alto, 94304 USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: martinjzhang@gmail.com angela.pisco@czbiohub.org jamesz@stanford.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Data/Code
  • Preview PDF
Loading

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 dataset35 to systematically characterize gene expression changes during aging across diverse cell types in 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 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. We integrated the aging-related genes to construct a cell-wise aging score that allowed us to investigate the aging status of different cell types from a transcriptomic perspective. Overall, our analysis provides one of the most comprehensive and systematic characterization of the molecular signatures of aging across diverse tissue-cell types in a mammalian system.

Footnotes

  • https://figshare.com/articles/tms_gene_data/11413869

  • https://github.com/czbiohub/tabula-muris-senis/tree/master/2_aging_signature

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
Back to top
PreviousNext
Posted December 27, 2019.
Download PDF

Supplementary Material

Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures
Martin Jinye Zhang, Angela Oliveira Pisco, Spyros Darmanis, James Zou
bioRxiv 2019.12.23.887604; doi: https://doi.org/10.1101/2019.12.23.887604
Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
Citation Tools
Mouse Aging Cell Atlas Analysis Reveals Global and Cell Type Specific Aging Signatures
Martin Jinye Zhang, Angela Oliveira Pisco, Spyros Darmanis, James Zou
bioRxiv 2019.12.23.887604; doi: https://doi.org/10.1101/2019.12.23.887604

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (2543)
  • Biochemistry (4994)
  • Bioengineering (3497)
  • Bioinformatics (15279)
  • Biophysics (6926)
  • Cancer Biology (5427)
  • Cell Biology (7771)
  • Clinical Trials (138)
  • Developmental Biology (4558)
  • Ecology (7180)
  • Epidemiology (2059)
  • Evolutionary Biology (10261)
  • Genetics (7532)
  • Genomics (9826)
  • Immunology (4899)
  • Microbiology (13304)
  • Molecular Biology (5165)
  • Neuroscience (29569)
  • Paleontology (203)
  • Pathology (842)
  • Pharmacology and Toxicology (1470)
  • Physiology (2153)
  • Plant Biology (4780)
  • Scientific Communication and Education (1015)
  • Synthetic Biology (1343)
  • Systems Biology (4022)
  • Zoology (771)