Dissecting Murine Muscle Stem Cell Aging through Regeneration Using Integrative Genomic Analysis
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During aging, there is a progressive loss of volume and function in skeletal muscle that impacts mobility and quality of life. The repair of skeletal muscle is regulated by tissue-resident stem cells called satellite cells (or muscle stem cells [MuSCs]), but in aging, MuSCs decrease in numbers and regenerative capacity. The transcriptional networks and epigenetic changes that confer diminished regenerative function in MuSCs as a result of natural aging are only partially understood. Herein, we use an integrative genomics approach to profile MuSCs from young and aged animals before and after injury. Integration of these datasets reveals aging impacts multiple regulatory changes through significant differences in gene expression, metabolic flux, chromatin accessibility, and patterns of transcription factor (TF) binding activities. Collectively, these datasets facilitate a deeper understanding of the regulation tissue-resident stem cells use during aging and healing.
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Other stem cell subpopulations lose quiescence and become abnormally activated, particularly in blood and muscle.
“Other stem cell subpopulations lose quiescence and become abnormally activated, particularly in blood and muscle12,35,44.”
From Ageing and rejuvenation of tissue stem cells and their niches (2023) · cites this paper as [12]
Transcriptional changes in old MuSCs involve metabolic pathways and genes that regulate chromatin accessibility.
“Transcriptional changes in old MuSCs involve metabolic pathways and genes that regulate chromatin accessibility12,34,65.”
From Ageing and rejuvenation of tissue stem cells and their niches (2023) · cites this paper as [12]
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Shaping Gene Expression by Landscaping Chromatin Architecture: Lessons from a Master
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Transcriptional and Chromatin Dynamics of Muscle Regeneration after Severe Trauma
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Flagged first, then by citations
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Sorted by citations
Ageing and rejuvenation of tissue stem cells and their niches
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- Authors
- Shcherbina, A., Larouche, J., Fraczek, P., Yang, B. A., Brown, L. A., Markworth, J. F., Chung, C. H., Khaliq, M., de Silva, K., Choi, J. J., Fallahi-Sichani, M., Chandrasekaran, S., Jang, Y. C., Brooks, S. V., & Aguilar, C. A.
- Affiliations
- Stanford University (US)
- University of Michigan (US)
- Georgia Institute of Technology (US)
- Corresponding author
- Aguilar, Carlos A.
- ORCID
- Venue
- Cell Reports
- Publisher
- Elsevier BV
- Published
- 2020-07
- Volume
- 32
- Issue
- 4
- Pages
- 107964
- ISSN
- 2211-1247 (ISSN-L)
- PMC
- PMC8025697
- OpenAlex
- W3045623544
- Cited by
- 76
- References
- 96
- Citations by year
- 2026: 7 · 2025: 15 · 2024: 13 · 2023: 18 · 2022: 10 · 2021: 10 · 2020: 2
- FWCI
- 3.24
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cell Reports (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Defense
- 3M Foundation
- National Institutes of Health
- American Federation for Aging Research
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Muscle Physiology and Disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Congenital heart defects research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- muscle stem cells, satellite cells, skeletal muscle aging, muscle regeneration, muscle damage, transcriptional regulatory networks, epigenetic modifications, chromatin accessibility, transcription factor binding, metabolic flux, gene expression profiling, integrative genomics
- MeSH terms
- Aging, Animals, Cell Line, Female, Mice, Inbred C57BL, Regeneration, Stem Cells, Cellular Senescence, Muscle, Skeletal, Genomics, Muscle Cells, Myoblasts, Satellite Cells, Skeletal Muscle, Mice
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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