The Concurrence of DNA Methylation and Demethylation Is Associated With Transcription Regulation

Authors

Jiejun Shi
Jianfeng Xu
Yiling Elaine Chen
Jason Sheng Li
Ya Cui
Lanlan Shen
Jingyi Jessica Li
Wei Li

Publication Date

9-6-2021

Journal

Nature Communications

DOI

10.1038/s41467-021-25521-7

PMID

34489442

PMCID

PMC8421433

PubMedCentral® Posted Date

9-6-2021

PubMedCentral® Full Text Version

Post-print

Published Open-Access

no

Keywords

Animals, Chromatin, CpG Islands, DNA, DNA Methylation, DNA Modification Methylases, DNA-Binding Proteins, Epigenesis, Genetic, Gene Ontology, Genome, Histones, Humans, Isoenzymes, Mice, Molecular Sequence Annotation, Mouse Embryonic Stem Cells, Neoplasms, Proto-Oncogene Proteins, T-Lymphocytes, Transcription, Genetic

Abstract

The mammalian DNA methylome is formed by two antagonizing processes, methylation by DNA methyltransferases (DNMT) and demethylation by ten-eleven translocation (TET) dioxygenases. Although the dynamics of either methylation or demethylation have been intensively studied in the past decade, the direct effects of their interaction on gene expression remain elusive. Here, we quantify the concurrence of DNA methylation and demethylation by the percentage of unmethylated CpGs within a partially methylated read from bisulfite sequencing. After verifying 'methylation concurrence' by its strong association with the co-localization of DNMT and TET enzymes, we observe that methylation concurrence is strongly correlated with gene expression. Notably, elevated methylation concurrence in tumors is associated with the repression of 40~60% of tumor suppressor genes, which cannot be explained by promoter hypermethylation alone. Furthermore, methylation concurrence can be used to stratify large undermethylated regions with negligible differences in average methylation into two subgroups with distinct chromatin accessibility and gene regulation patterns. Together, methylation concurrence represents a unique methylation metric important for transcription regulation and is distinct from conventional metrics, such as average methylation and methylation variation.