ArticleScientific reports2025
Reliable investigation of DNA methylation using Oxford nanopore technologies.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Chemical Exposures, DNA Methylation and Whole Blood DNA Damage in Pet Golden Retrievers.Veterinary and comparative oncology · 2026Article
- Implementation of a medical genomics program for rare diseases in Uruguay.Orphanet journal of rare diseases · 2026Article
- The potential of methylation signal detection in eDNA toward functional ecological monitoring.Communications biology · 2026Review
- Population-scale detection of methylation outliers from long-read genome sequencing.medRxiv : the preprint server for health sciences · 2026Article
- Long-read sequencing technologies and bioinformatics: a new perspective for decoding DNA methylation modifications.Journal of translational medicine · 2026Review
- NanoLoop: A Deep Learning Framework Leveraging Nanopore Sequencing for Chromatin Loop Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- LEMONmethyl-seq: Targeted long-read DNA methylation profiling reveals dynamics of CRISPR epigenome editing and endogenous DNA methylation patterns.bioRxiv : the preprint server for biology · 2026Article
- Epigenetic regulation and antimicrobial resistance: functional roles of DNA methylation.FEMS microbiology reviews · 2026Review
- Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Oxford Nanopore Technologies (ONT) offers an efficient and effective solution for studying DNA methylation. Both R9.4.1 and R10.4.1 ONT chemistries have been widely used to generate numerous DNA methylation data, making it inevitable to conduct cross-ONT-chemistry methylation analysis. However, the two ONT chemistries have unique designs and may cause potential bias in methylation detection, complicating cross-chemistry methylation investigation. In this study, we sequenced two pairs of wild-type and their knockout samples using R9.4.1 and R10.4.1 chemistries and investigated the concordance and bias of the two pairs of ONT methylation data. Although we confirmed high concordances of methylation data generated by the two ONT chemistries and the improvement of R10 chemistry in repeat regions, we found that both chemistries possess detection bias for methylation. Thus, cross-ONT-chemistry methylation studies identified hundreds of thousands of differential methylation sites caused by chemistry variabilities. We also explored different methods to calculate coverage and methylation percentages. Our evaluations provide valuable recommendations for cross-ONT-chemistry methylation analysis and suggest better practices for robust methylation investigation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.