Evidence map›Paper›PMID 40855329›Full record

ArticleEpigenetics & chromatin2025

Comparison of current methods for genome-wide DNA methylation profiling.

Ana Regina de Abreu, Joe Ibrahim, Vasileios Lemonidis, Ligia Mateiu, Guy Van Camp, Ken Op de Beeck

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Epigenetics & chromatin, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ana Regina de Abreu *Center of Medical Genetics, University of Antwerp and Antwerp University Hospital, Prins Boudewijnlaan 43, 2650, Edegem, Belgium.
Joe Ibrahim *Center of Medical Genetics, University of Antwerp and Antwerp University Hospital, Prins Boudewijnlaan 43, 2650, Edegem, Belgium.
Vasileios LemonidisCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Prins Boudewijnlaan 43, 2650, Edegem, Belgium.
Ligia MateiuCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Prins Boudewijnlaan 43, 2650, Edegem, Belgium.
Guy Van CampCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Prins Boudewijnlaan 43, 2650, Edegem, Belgium.
Ken Op de BeeckCenter of Medical Genetics, University of Antwerp and Antwerp University Hospital, Prins Boudewijnlaan 43, 2650, Edegem, Belgium. ken.opdebeeck@uantwerpen.be.

Funding

Research Foundation Flanders 1SD3722NStichting Tegen Kanker C/2022/2056
6 · The paper itself

Abstract

backgroundDNA methylation is an epigenetic mechanism involved in gene regulation and cellular differentiation. Accurate and comprehensive assessment of DNA methylation patterns is thus essential for understanding their role in various biological processes and disease mechanisms. Bisulfite sequencing has long been the default method for analyzing methylation marks due to its single-base resolution, but the associated DNA degradation poses a concern. Although several methods have been proposed to circumvent this issue, there is no clear consensus on which method might be better suited for specific study designs.

resultsWe conducted a comparative evaluation of four DNA methylation detection approaches: whole-genome bisulfite sequencing (WGBS), Illumina methylation microarray (EPIC), enzymatic methyl-sequencing (EM-seq) and third-generation sequencing by Oxford Nanopore Technologies (ONT). DNA methylation profiles were assessed across three human genome samples derived from tissue, cell line, and whole blood. We systematically compared these methods in terms of resolution, genomic coverage, methylation calling accuracy, cost, time, and practical implementation. EM-seq showed the highest concordance with WGBS, indicating strong reliability due to their similar sequencing chemistry. ONT sequencing, while showing lower agreement with WGBS and EM-seq, captured certain loci uniquely and enabled methylation detection in challenging genomic regions. Despite a substantial overlap in CpG detection among methods, each method identified unique CpG sites, emphasizing their complementary nature.

conclusionsOur findings underscore the strengths and limitations of current DNA methylation detection methods. EM-seq and ONT emerge as robust alternatives to WGBS and EPIC, offering unique advantages: EM-seq delivers consistent and uniform coverage, while ONT excels in long-range methylation profiling and access to challenging genomic regions. These insights provide practical guidance for method selection based on specific experimental goals.

Indexed as

DNA MethylationHigh-Throughput Nucleotide SequencingSequence Analysis, DNAWhole Genome SequencingCpG IslandsGenome, HumanHumansCoverageCytosineDNA methylationEnzymatic methyl-sequencing (EM-seq)EpigenomicsIllumina EPIC arrayOxford Nanopore Technologies (ONT)Whole-genome bisulfite sequencing (WGBS)

Identifiers

PMID40855329
PMCPMC12376410

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Registered trials

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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.