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Updated: Oct 11, 2025

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
Published on: August 3, 2018
The SEQC2 epigenomics quality control (EpiQC) study
Jonathan Foox1,2, Jessica Nordlund3,4, Claudia Lalancette5
1Department of Physiology and Biophysics, Weill Cornell Medicine, New York, New York, USA.
Background:
Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group.
Results:
Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms.
Conclusions:
The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.
Insights
This study benchmarks multiple DNA methylation sequencing methods, finding high concordance but also platform-specific differences. The results offer guidance for epigenetics research and best practices for experimental design using reference materials.
Area of Science:
- Epigenetics
- Genomics
- Molecular Biology
Background:
- DNA methylation, including 5-methylcytosine (5mC), is crucial for development, cell lineage, and disease stratification.
- Diverse interrogation methods necessitate harmonization and benchmarking for reliable genome-wide methylome sequencing.
- The FDA's Epigenomics Quality Control Group provides a cross-validated resource for epigenetics research.
Purpose of the Study:
- To conduct a multi-platform assessment of DNA methylation analysis techniques.
- To establish harmonized materials and methods for epigenetics research.
- To provide a benchmark for improving genome-wide methylome sequencing applications.
Main Methods:
- Evaluation of multiple whole-genome bisulfite sequencing (WGBS) protocols, oxidative bisulfite sequencing, enzymatic deamination, targeted methylation sequencing, nanopore sequencing, and methylation arrays.
- Rigorous quality assessment, cross-validation against Illumina EPIC microarrays, and testing of various analysis algorithms.
- Utilizing seven human cell lines as publicly available reference materials.
Main Results:
- High overall concordance was observed between different DNA methylation assays.
- Differences were noted in read mapping efficiency, CpG capture, coverage, and platform performance.
- Variable performance was found across 26 microarray normalization algorithms.
Conclusions:
- The presented data guide the use of DNA reference materials in epigenomics.
- Best practices for experimental design in future epigenetics studies are provided.
- The findings establish a baseline for advancing epigenomics research using standardized reference materials.

