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Single-cell transcriptomic profiling of the aging mouse brain

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Author(s)
Ximerakis, Methodios
•
Lipnick, Scott L.
•
Innes, Brendan T.
•
Simmons, Sean Kenneth
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Adiconis, Xian
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Dionne, Danielle
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Mayweather, Brittany A.
•
Nguyen, Lan
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Niziolek, Zachary
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Ozek, Ceren
more
Date Issued
September 2019
Journal
Nature Neuroscience
Publisher
Springer Science and Business Media LLC
Citation
Ximerakis, Methodios et al. "Single-cell transcriptomic profiling of the aging mouse brain." Nature Neuroscience 22, 10 (September 2019): 1696–1708 © 2019 The Author(s)
Version
Author's final manuscript
Abstract
The mammalian brain is complex, with multiple cell types performing a variety of diverse functions, but exactly how each cell type is affected in aging remains largely unknown. Here we performed a single-cell transcriptomic analysis of young and old mouse brains. We provide comprehensive datasets 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. These data reveal that aging, rather than inducing a universal program, drives a distinct transcriptional course in each cell population, and they highlight key molecular processes, including ribosome biogenesis, underlying brain aging. Overall, these large-scale datasets (accessible online at https://portals.broadinstitute.org/single_cell/study/aging-mouse-brain) provide a resource for the neuroscience community that will facilitate additional discoveries directed towards understanding and modifying the aging process.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Broad Institute of MIT and Harvard
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
https://hdl.handle.net/1721.1/126746
DOI of Published Version
https://doi.org/10.1038/s41593-019-0491-3
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