Single-cell transcriptomics of the aged mouse brain reveals convergent, divergent and unique aging signatures
Scott L. Lipnick,
Sean K. Simmons,
Brendan T. Innes,
Brittany A. Mayweather,
Vincent L. Butty,
Sean M. Buchanan,
Stuart R. Levine,
Gary D. Bader,
Joshua Z. Levin,
Lee L. Rubin
Posted 11 Oct 2018
bioRxiv DOI: 10.1101/440032 (published DOI: 10.1038/s41593-019-0491-3)
Posted 11 Oct 2018
The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how the brain is affected with aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide a comprehensive dataset of aging-related genes, pathways and ligand-receptor interactions in nearly all brain cell types. Our analysis identified gene signatures that vary in a coordinated manner across cell types and gene sets that are regulated in a cell type specific manner, even at times in opposite directions. Thus, our data reveals that aging, rather than inducing a universal program drives a distinct transcriptional course in each cell population. These data provide an important resource for the aging community and highlight key molecular processes, including ribosomal biogenesis, underlying aging. We believe that this large-scale dataset, which is publicly accessible online (aging-mouse-brain), will facilitate additional discoveries directed towards understanding and modifying the aging process.
- Downloaded 3,583 times
- Download rankings, all-time:
- Site-wide: 1,069 out of 78,016
- In neuroscience: 136 out of 13,968
- Year to date:
- Site-wide: 3,394 out of 78,016
- Since beginning of last month:
- Site-wide: 2,963 out of 78,016
Downloads over time
Distribution of downloads per paper, site-wide
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!