A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing

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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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-09-13
DOI
https://doi.org/10.64898/2026.09.07.749820
Primary Topic
Epigenetics and DNA Methylation
Type
preprint
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preprint

A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing

Nicolae Radu Zabet, Young Jun Kim
bioRxiv (Cold Spring Harbor Laboratory)
Epigenetics and DNA Methylation
preprint

A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing

Nicolae Radu Zabet, Young Jun Kim
preprint en

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.

bioRxiv (Cold Spring Harbor Laboratory)
Queen Mary University of London (GB)
Epigenetics and DNA Methylation
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A Framework for Quantifying DNA Methylation Heterogeneity and Detecting Co-methylated loci from Native Nanopore Sequencing — Nicolae Radu Zabet, Young Jun Kim · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS