Brain–muscle tissue communication prevents muscle aging by maintaining daily physiology
Cite this dataset
Sassone-Corsi, Paolo et al. (2024). Brain–muscle tissue communication prevents muscle aging by maintaining daily physiology [Dataset]. Dryad. https://doi.org/10.5061/dryad.8931zcrxp
Abstract
A network of molecular clocks is crucial for coordinating daily physiology and maintaining organismal health. However, the mechanisms underlying the interactions between these clocks and the significance of intra-tissue clock networks in muscle tissue maintenance have remained elusive. To uncover this network structure, we established a minimal clock module with the central clock (suprachiasmatic nucleus/brain) and/or a peripheral clock (muscle) in arrhythmic mice with premature aging. We find that reconstituting the brain-muscle clock network alone is sufficient to preserve fundamental daily homeostatic functions and prevent premature muscle aging. However, achieving whole muscle daily physiology requires the contribution of other peripheral clocks. Mechanistically, the muscle peripheral clock acts as a gatekeeper, selectively suppressing signals from the central clock that could be detrimental to muscle function if left uncontrolled while also integrating important muscle homeostatic functions. Our findings unveil the reciprocal interactions between central and peripheral clocks crucial for daily muscle function and highlight the significant influence of eating patterns on these interactions. These insights have implications for promoting healthier aging and reversing age-related muscle pathologies.
README: Brain–muscle tissue communication prevents muscle aging by maintaining daily physiology
https://doi.org/10.5061/dryad.8931zcrxp
Data
Each Excel file contains a sheet with a list of relevant variables and their definitions.
Supplementary tables S1 to S4 legends:
Table S1. Rhythmic transcriptome output by JTK_CYCLE in defined mice genotypes, with 12:12 hour light/dark (LD) cycles.
Table S2. Rhythmic transcriptome output by RAIN in defined mice genotypes, with 12:12 hour LD cycles.
Table S3. Differential rhythmicity analysis dryR in defined mice genotypes, with 12:12 hour LD cycles.
Table S4. Transcription factor motif enrichment analysis using g:Profiler, with 12:12 hour LD cycles.
Funding
Institute for Research in Biomedicine, Award: SEV-2015-0505
Institute for Research in Biomedicine, Award: NIH F32 F
Fundación Bancaria Caixa d’Estalvis i Pensions de Barcelona, Award: ID 100010434
Horizon 2020 Framework Programme, Award: 749869
Ministerio de Ciencia e Innovación, Award: RTI2018-096068
Ministerio de Ciencia e Innovación, Award: ERC-2016-AdG-741966
European Research Council, Award: ERC-787041
European Research Council, Award: RYC2019-026661-I