Characterization of universal features of partially methylated domains across tissues and species
Knott, Simon R. V.
Hannon, Gregory J.
Smith, Andrew D.
Epigenetics & Chromatin
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Decato, B. E., Qu, J., Ji, X., Wagenblast, E., Knott, S. R. V., Hannon, G. J., & Smith, A. D. (2020). Characterization of universal features of partially methylated domains across tissues and species. Epigenetics & Chromatin, 13 (1)https://doi.org/10.1186/s13072-020-00363-7
Abstract: Background: Partially methylated domains (PMDs) are a hallmark of epigenomes in reproducible and specific biological contexts, including cancer cells, the placenta, and cultured cell lines. Existing methods for deciding whether PMDs exist in a sample, as well as their identification, are few, often tailored to specific biological questions, and require high coverage samples for accurate identification. Results: In this study, we outline a set of axioms that take a step towards a functional definition for PMDs, describe an improved method for comparable PMD detection across samples with substantially differing sequencing depths, and refine the decision criteria for whether a sample contains PMDs using a data-driven approach. Applying our method to 267 methylomes from 7 species, we corroborated recent results regarding the general association between replication timing and PMD state, and report identification of several reproducibly “escapee” genes within late-replicating domains that escape the reduced expression and hypomethylation of their immediate genomic neighborhood. We also explored the discordant PMD state of orthologous genes between human and mouse, and observed a directional association of PMD state with gene expression and local gene density. Conclusions: Our improved method makes low sequencing depth, population-level studies of PMD variation possible and our results further refine the model of PMD formation as one where sequence context and regional epigenomic features both play a role in gradual genome-wide hypomethylation.
Research, Partially methylated domains, DNA methylation, Cancer, Hidden Markov models
National Institutes of Health (HG005238)
External DOI: https://doi.org/10.1186/s13072-020-00363-7
This record's URL: https://www.repository.cam.ac.uk/handle/1810/311007