Epigenetic inheritance of circadian period in clonal cells
Abstract
Circadian oscillations are generated via transcriptional-translational negative feedback loops. However, individual cells from fibroblast cell lines have heterogeneous rhythms, oscillating independently and with different period lengths. Here we showed that heterogeneity in circadian period is heritable and used a multi-omics approach to investigate underlying mechanisms. By examining large-scale phenotype-associated gene expression profiles in hundreds of mouse clonal cell lines, we identified and validated multiple novel candidate genes involved in circadian period determination in the absence of significant genomic variants. We also discovered differentially co-expressed gene networks that were functionally associated with period length. We further demonstrated that global differential DNA methylation bidirectionally regulated these same gene networks. Interestingly, we found that depletion of DNMT1 and DNMT3A had opposite effects on circadian period, suggesting non-redundant roles in circadian gene regulation. Together, our findings identify novel gene candidates involved in periodicity, and reveal DNA methylation as an important regulator of circadian periodicity.
Data availability
RNA Sequencing data have been deposited in GEO under accession codes: GSE132663 and GSE132665. Exome sequencing data have been deposited in SRA under accession number: PRJNA548837. All data generated or analyzed during this study are included in the manuscript and supporting files. Source data have been provided for Figures 2 and 4.
-
Transcriptional Profiling of Clonal Cell Lines with Different Circadian PeriodNCBI Gene Expression Omnibus, GSE132663.
-
RRBS Profiling of Clonal Cell Lines with Different Circadian PeriodNCBI Gene Expression Omnibus, GSE132665.
Article and author information
Author details
Funding
Howard Hughes Medical Institute
- Joseph S Takahashi
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Li et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 3,138
- views
-
- 510
- downloads
-
- 15
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Citations by DOI
-
- 15
- citations for umbrella DOI https://doi.org/10.7554/eLife.54186