A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing
- 1Queen Mary University of London
Abstract
DNA methylation is an important epigenetic mechanism involved in gene regulation. Most methods focus on analysing DNA methylation averaged from multiple reads, yet these average methylation profiles obscure heterogeneity between individual DNA molecules and coordinated methylation states across loci. Native Oxford Nanopore Technology (ONT) sequencing directly captures long, native DNA molecules together with their base modifications, allowing methylation to be studied at single-molecule resolution. Here, we present a scalable framework for genome-wide methylation analysis using ONT sequencing at single-molecule resolution, focused on two features that site-level summaries cannot recover. First, it quantifies molecule-to-molecule heterogeneity in DNA methylation by detecting Variable Methylated Domains (VMDs) and Variable Methylated Regions (VMRs). Second, it identifies coordinated methylation, as co-methylated positions (CMPs) and regions (CMRs), from the states observed on the same individual DNA molecules. Using data from human LCL cells, we demonstrate that substantial molecule-level methylation heterogeneity is masked by site-level summaries. Co-methylation analysis reveals coordinated patterns between CpG sites and genomic regions, including shared and sex-specific patterns, uncovering methylation organisation not apparent from average methylation levels. We also show that CMPs can be used to detect TF-pairs that are predicted to have coordinated binding. This framework is integrated within the DMRcaller R/Bioconductor package.
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BibTeX
@misc{kim2026framework,
title = {{A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing}},
author = {Y. J. Kim and N. R. Zabet},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.07.749820},
url = {https://www.biorxiv.org/content/10.64898/2026.09.07.749820v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing
AU - Y. J. Kim
AU - N. R. Zabet
PY - 2026
DA - 2026/09/07
PB - bioRxiv
DO - 10.64898/2026.09.07.749820
UR - https://www.biorxiv.org/content/10.64898/2026.09.07.749820v1
AB - DNA methylation is an important epigenetic mechanism involved in gene regulation. Most methods focus on analysing DNA methylation averaged from multiple reads, yet these average methylation profiles obscure heterogeneity between individual DNA molecules and coordinated methylation states across loci. Native Oxford Nanopore Technology (ONT) sequencing directly captures long, native DNA molecules together with their base modifications, allowing methylation to be studied at single-molecule resolution. Here, we present a scalable framework for genome-wide methylation analysis using ONT sequencing at single-molecule resolution, focused on two features that site-level summaries cannot recover. First, it quantifies molecule-to-molecule heterogeneity in DNA methylation by detecting Variable Methylated Domains (VMDs) and Variable Methylated Regions (VMRs). Second, it identifies coordinated methylation, as co-methylated positions (CMPs) and regions (CMRs), from the states observed on the same individual DNA molecules. Using data from human LCL cells, we demonstrate that substantial molecule-level methylation heterogeneity is masked by site-level summaries. Co-methylation analysis reveals coordinated patterns between CpG sites and genomic regions, including shared and sex-specific patterns, uncovering methylation organisation not apparent from average methylation levels. We also show that CMPs can be used to detect TF-pairs that are predicted to have coordinated binding. This framework is integrated within the DMRcaller R/Bioconductor package.
ER -