DNA Hydroxymethylation Analysis Service: Genome-Wide 5hmC Profiling

5-Hydroxymethylcytosine (5hmC) is a distinct epigenetic mark generated through TET-mediated oxidation of 5-methylcytosine (5mC), playing a pivotal role in active DNA demethylation, gene regulation, and cellular differentiation. Unlike 5mC, which is predominantly associated with gene repression, 5hmC is enriched in gene bodies and regulatory regions of actively transcribed genes, particularly in embryonic stem cells and neuronal tissues. At CD Genomics, we offer five complementary 5hmC detection platforms — hMeDIP-seq, 5hmC-SEAL-seq, oxBS-seq, ACE-seq, and ONT long-read sequencing — plus targeted oxTBS for locus-specific validation. This multi-platform capability allows us to recommend the optimal method for your specific biological question based on your sample type, resolution needs, and research goals.

Key Highlights of Our DNA Hydroxymethylation Analysis Service:

Five Complementary Detection Strategies: Choose from hMeDIP-seq, 5hmC-SEAL-seq, oxBS-seq, ACE-seq, or ONT long-read sequencing — plus targeted oxTBS — to match your resolution, input, and phasing requirements.
Single-Base Resolution Options: oxBS-seq and ACE-seq provide quantitative, single-base 5hmC detection; ONT long-read sequencing adds single-molecule phasing capability.
Low-Input Compatibility: Chemical labeling and enzymatic methods work with limited sample material, including FFPE and cfDNA — ACE-seq requires only 10-100 ng input.
Integrated Bioinformatics: Comprehensive analysis pipeline including differential hydroxymethylation, functional annotation, multi-omics integration, and haplotype-phased modification analysis for long-read data.

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DNA hydroxymethylation analysis overview showing TET-mediated 5hmC generation and multiple detection approaches

Overview

What Is 5-Hydroxymethylcytosine and How Is It Detected?

5-Hydroxymethylcytosine (5hmC) is generated by the Ten-Eleven Translocation (TET) family of dioxygenases (TET1/2/3), which oxidize 5mC to 5hmC in a Fe²⁺- and α-ketoglutarate-dependent manner. Unlike 5mC, which constitutes ~4-6% of cytosines in mammalian genomes, 5hmC is present at much lower levels (~0.1-1% of cytosines), with highest enrichment in the brain (~0.4-0.8% of all cytosines), embryonic stem cells, and certain cancer tissues.

Detecting 5hmC specifically—without interference from the abundant 5mC background—requires methods that can distinguish the hydroxylated form. We offer five complementary approaches, each optimized for specific research needs:

hMeDIP-seq — Antibody-based immunoprecipitation of 5hmC-enriched DNA fragments. Region-based resolution, suitable for genome-wide 5hmC screening. Cost-effective for large-cohort studies.
5hmC-SEAL-seq — Chemical labeling via β-glucosyltransferase-mediated glucose conjugation, followed by biotin click chemistry and streptavidin enrichment. Higher specificity than antibody-based methods; compatible with low-input cfDNA and FFPE samples.
oxBS-seq — Oxidative bisulfite sequencing. KRuO₄ chemical oxidation of 5hmC to 5fC, followed by bisulfite conversion. Single-base 5hmC quantification by subtraction (oxBS vs standard BS). The benchmark for per-CpG 5hmC accuracy.
ACE-seq — APOBEC-coupled epigenetic sequencing. Enzymatic deamination of 5hmC to 5hmU without bisulfite treatment. Single-base resolution with the gentlest chemistry — the preferred choice for FFPE and cfDNA samples with limited input (10-100 ng).
ONT Long-Read 5hmC Sequencing — Oxford Nanopore Technologies direct detection of 5hmC (and 5mC simultaneously) from native DNA without chemical or enzymatic conversion. Ionic current signal analysis via Dorado/Megalodon basecallers resolves 5hmC at single-base, single-molecule resolution on ultra-long reads (10-100 kb+), enabling haplotype-phased modification analysis. Ideal for studies requiring simultaneous 5mC/5hmC profiling, structural variant integration, or phasing of epigenetic marks across alleles.

Expert Recommendation: For most discovery-phase projects, we recommend a tiered strategy: start with hMeDIP-seq or 5hmC-SEAL-seq for cost-effective genome-wide screening, then validate key loci with ACE-seq or oxBS-seq for single-base quantitative confirmation. For projects that also require 5mC data or haplotype-level phasing, ONT long-read sequencing provides both modifications from a single run.

Diagram illustrating TET-mediated 5mC to 5hmC oxidation and the four detection approaches: hMeDIP, SEAL, oxBS, and ACE

Decision Guide

Technology Decision Guide: Selecting the Right 5hmC Detection Method

Choosing the optimal 5hmC profiling method depends on your research goals—whether you need genome-wide screening, single-base resolution, quantitative accuracy, or compatibility with limited or damaged DNA samples.

Technology	Detection Principle	Resolution	DNA Input	Bisulfite-Free	Quantitative
hMeDIP-seq	Anti-5hmC antibody enrichment	Region-based (~150-300 bp)	1-2 μg	Yes	Semi-quantitative
5hmC-SEAL-seq	β-GT chemical labeling + biotin	Region-based (~150-300 bp)	100 ng-1 μg	Yes	Quantitative
oxBS-seq	Chemical oxidation + bisulfite	Single-base	200 ng-1 μg	No	Quantitative
ACE-seq	APOBEC enzymatic deamination	Single-base	10-100 ng	Yes	Quantitative
ONT Long-Read	Direct ionic current signal detection of modified bases	Single-base, single-molecule	1-3 μg (native DNA)	Yes	Semi-quantitative
Targeted oxTBS	PCR-based targeted oxidative BS	Single-base	10-100 ng	No	Quantitative

Selection Strategy: For unbiased genome-wide 5hmC screening and discovery, hMeDIP-seq or 5hmC-SEAL-seq provide cost-effective regional profiles. When single-base resolution and quantitative accuracy are essential—such as for comparing 5hmC levels at specific loci across conditions—choose oxBS-seq or ACE-seq. For projects with extremely limited or degraded DNA (FFPE, cfDNA), ACE-seq offers the gentlest chemistry and lowest input requirement. For studies requiring simultaneous 5mC and 5hmC detection, haplotype-phased modification analysis, or integration with structural variant calling, ONT long-read sequencing provides a single-platform solution with unique phasing capabilities.

Advantages

Core Technical Advantages

Our DNA hydroxymethylation analysis platform is designed to address the key technical challenges in 5hmC detection—specificity, sensitivity, and reproducibility across diverse sample types.

Discrimination from Abundant 5mC: Standard bisulfite sequencing cannot distinguish 5hmC from 5mC — both read as "methylated." Our oxBS-seq and ACE-seq methods provide true 5hmC-specific signals, enabling accurate quantification even in genomes where 5mC is 10- to 100-fold more abundant. ONT long-read sequencing further distinguishes 5mC and 5hmC at single-molecule resolution without any chemical or enzymatic conversion.
Method Flexibility for Any Project Scale: From single-gene targeted analysis (targeted oxTBS) to whole-genome single-base profiling (ACE-seq, oxBS-seq), cohort-scale screening (hMeDIP, SEAL), and haplotype-resolved long-read analysis (ONT), we match the technology to your sample size, budget, and resolution needs. Our multi-platform capability means recommendations are driven by your research question — not by which instrument we own.
Low-Input and Damaged DNA Compatibility: ACE-seq uses enzymatic deamination without bisulfite treatment or harsh chemical oxidation, preserving DNA integrity and enabling 5hmC profiling from as little as 10 ng of FFPE-derived or circulating cell-free DNA — samples that typically fail in bisulfite-based workflows. 5hmC-SEAL-seq also avoids bisulfite, offering FFPE-compatible enrichment from 100 ng input.

Applications

Applications in Epigenetics Research

5hmC profiling has emerged as a critical tool across multiple biomedical fields, providing insights that go beyond conventional DNA methylation analysis.

Cancer Epigenetics & Biomarker Discovery

Global 5hmC loss is a hallmark of many cancers, while locus-specific 5hmC gains occur at oncogenic regulatory elements. 5hmC profiling in cfDNA from liquid biopsies has emerged as a promising approach for early cancer detection, tumor typing, and treatment monitoring, particularly in brain, breast, and colorectal cancers. For studies comparing 5hmC with conventional WGBS or MeDIP-seq methylation profiles, our integrated analysis pipelines reveal active demethylation dynamics invisible to 5mC-only approaches. cfDNA epigenetics applications are fully supported with low-input methods.

Neuroepigenetics & Brain Disorders

The brain exhibits the highest 5hmC levels of any mammalian tissue (~0.4-0.8% of cytosines), with 5hmC enrichment at synaptic genes and neuronal activity-regulated loci. 5hmC profiling in neurological disorders—including Alzheimer's disease, Huntington's disease, and autism spectrum disorders—has revealed disease-specific hydroxymethylation signatures. ONT long-read sequencing is particularly advantageous for brain samples, as ultra-long reads enable phasing of neuron-specific 5hmC patterns across large genomic regions.

Developmental & Stem Cell Biology

TET-mediated 5hmC dynamics are central to embryonic development, cellular reprogramming, and lineage specification. 5hmC maps during these processes reveal how active DNA demethylation shapes the regulatory landscape of pluripotency and differentiation.

Environmental Epigenomics

5hmC patterns respond to environmental exposures, dietary factors, and oxidative stress. Profiling 5hmC changes in response to toxicants, hypoxia, or inflammatory stimuli provides a dynamic readout of active epigenetic reprogramming in disease pathogenesis.

Bioinformatics

Comprehensive 5hmC Bioinformatics Pipeline

Our bioinformatics pipeline is specifically designed for the unique challenges of 5hmC data analysis—including subtraction-based quantification (oxBS vs BS), enrichment-based peak calling, and direct signal-level modification detection for ONT long-read data.

Standard Analysis Modules:

Raw Data QC & Alignment: Quality filtering, adapter trimming, and reference genome alignment using optimized aligners. For oxBS-seq, bisulfite-aware alignment (Bismark, BWA-meth). For ONT data, read quality assessment and alignment via minimap2 or NGMLR.
5hmC Quantification: For oxBS-seq and ACE-seq, per-base 5hmC level estimation by comparing oxidized/non-oxidized or deaminated/non-deaminated signal ratios. For enrichment-based methods (hMeDIP, SEAL), normalized 5hmC enrichment scores across genomic intervals. For ONT data, base-level 5hmC probability calls via Dorado, Megalodon, or Remora modification-aware basecallers.
Differential Hydroxymethylation Analysis: Identification of differentially hydroxymethylated regions (DhMRs) between sample groups using DESeq2, edgeR, or methylKit with appropriate statistical models.
Genomic Annotation: DhMR annotation to promoters, gene bodies, enhancers, and repeat elements. Integration with publicly available ChIP-seq, ATAC-seq, and RNA-seq data for regulatory context. For ONT data, phased modification analysis across haplotype blocks.

Advanced Analysis Options:

Multi-Omics Integration: Correlate 5hmC changes with gene expression (RNA-seq), chromatin accessibility (ATAC-seq), and histone modification profiles to build mechanistic models of epigenetic regulation. For ONT projects, simultaneous 5mC/5hmC co-analysis with structural variant calls from the same data.
Motif & Transcription Factor Analysis: Identify transcription factor binding motifs enriched within DhMRs to predict upstream regulators of observed 5hmC changes using HOMER and MEME Suite.
Functional Enrichment: GO and KEGG pathway analysis of genes associated with differentially hydroxymethylated regions to identify biological processes affected by 5hmC reprogramming.
Custom Visualization: Publication-ready figures including 5hmC browser tracks, heatmaps, violin plots, correlation analyses, and haplotype-phased modification tracks for long-read data.

Demo

Publication-Ready Demo Results

Our 5hmC data deliverables include comprehensive visualizations designed for direct use in manuscripts and presentations.

5hmC Genome Browser Tracks: Visual comparison of 5hmC enrichment across sample groups at specific gene loci, with or without concurrent 5mC tracks for direct comparison.
Differential DhMR Heatmap: Hierarchical clustering of significantly differentially hydroxymethylated regions across all samples, revealing group-specific 5hmC patterns.
Genomic Feature Distribution: Quantitative breakdown of 5hmC-enriched regions across promoters, gene bodies, intergenic regions, and repetitive elements.
5hmC vs 5mC Scatter Plot: Direct comparison showing loci where 5hmC and 5mC levels diverge, highlighting regions of active demethylation.
Functional Enrichment Summary: GO and KEGG pathway enrichment showing biological processes associated with differentially hydroxymethylated genes.
Multi-Sample MDS/PCA Plot: Dimensionality reduction plot demonstrating sample clustering based on genome-wide 5hmC profiles.

Workflow

End-to-End Workflow & QC Checkpoints

We maintain stringent quality control at every step, from sample receipt through final data delivery.

Sample QC & DNA Extraction: Assessing DNA quantity, purity (OD260/280), and integrity. For FFPE samples, DV200 assessment. QC: DNA quality meets method-specific thresholds. Expert Tip: For FFPE samples, DV₂₀₀ >30% is the critical QC threshold. If DV₂₀₀ falls below this, ACE-seq is strongly preferred — its enzymatic chemistry tolerates fragmented DNA far better than bisulfite-based methods. We have successfully processed FFPE blocks archived for up to 8 years using ACE-seq.
5hmC Detection Library Preparation: Method-specific steps—antibody enrichment (hMeDIP), chemical labeling (SEAL), chemical oxidation (oxBS), or enzymatic deamination (ACE). QC: Oxidation efficiency ≥95% (oxBS), enrichment efficiency verified by qPCR (hMeDIP). Expert Tip: For oxBS-seq, oxidation efficiency is the most important QC metric. We validate ≥95% conversion using spike-in controls in every batch. Incomplete oxidation — often from aged KRuO₄ solution — is the most common source of inflated 5hmC estimates in subtraction-based methods.
Library Amplification & Indexing: PCR amplification with unique dual indexes, library purification, and size selection. QC: Library yield and fragment size distribution. Expert Tip: For ACE-seq libraries, we use fewer PCR cycles (8-10) than bisulfite-based libraries because the APOBEC reaction preserves more amplifiable template. Over-amplification generates duplicate reads that reduce effective sequencing depth and inflate apparent coverage.
High-Throughput Sequencing: Illumina NovaSeq 6000/NovaSeq X. QC: Q30 ≥ 85%, alignment rate, conversion rate (spike-in controls). Expert Tip: For oxBS-seq, matched BS and oxBS libraries from the same sample must be sequenced together in the same lane. This minimizes lane-to-lane technical variation, which directly improves the accuracy of subtraction-based 5hmC quantification at each CpG.
Bioinformatics Analysis: 5hmC quantification, differential analysis, functional annotation, and generation of publication-ready reports and figures. QC: Sample correlation, bisulfite conversion rate (where applicable). Expert Tip: For enrichment-based data (hMeDIP/SEAL), input or IgG control sequencing is essential for accurate peak calling. Without proper controls, GC bias and copy number variations can mimic differential 5hmC signals, particularly in cancer samples with genomic instability.

Sample

Sample Requirements

Optimal 5hmC profiling depends on sample quality and method selection. Below are general guidelines for each approach.

Method	Sample Type	Minimum DNA Input	Quality Requirements	Notes
hMeDIP-seq	gDNA (tissue, cells)	1-2 μg	OD260/280: 1.8-2.0; High integrity	Not suitable for FFPE or cfDNA
5hmC-SEAL-seq	gDNA, cfDNA	100 ng-1 μg	OD260/280: 1.8-2.0	Gentler chemistry; compatible with FFPE
oxBS-seq	gDNA (tissue, cells)	200 ng-1 μg	OD260/280: 1.8-2.0; High integrity	Harsh chemical oxidation may degrade FFPE DNA
ACE-seq	gDNA, cfDNA, FFPE	10-100 ng	DV200 >30% for FFPE	Best choice for low-input and damaged DNA
ONT Long-Read	gDNA (tissue, cells, blood)	1-3 μg (high molecular weight)	OD260/280: 1.8-2.0; DNA length >10 kb preferred	Simultaneous 5mC+5hmC; requires intact HMW DNA; FFPE not compatible

Deliverables

Deliverables and Turnaround

Upon completion of your 5hmC project, you will receive a comprehensive data package organized for immediate use in downstream analyses and publication preparation.

Deliverable	Description
Raw sequencing data	Demultiplexed paired-end FASTQ files with quality scores
Quality control report	Comprehensive QC metrics: read quality (FastQC), alignment statistics, bisulfite conversion rate (oxBS), enrichment efficiency (hMeDIP/SEAL), spike-in recovery
5hmC quantification	Per-region enrichment scores (BED/bigWig for hMeDIP, SEAL) or per-base 5hmC levels (BED/bigWig for oxBS, ACE)
Differential DhMR list	Annotated table of significantly differentially hydroxymethylated regions with genomic coordinates, statistical metrics (p-value, FDR, fold change), and nearest gene annotations
Genomic annotation report	Distribution of DhMRs across genomic features with summary statistics and figures
Functional enrichment results	GO and KEGG pathway enrichment tables with significance metrics
Publication-ready figures	All figures generated during analysis in high-resolution formats (PDF, PNG, TIFF) suitable for manuscript submission
Methods section draft	Detailed description of experimental and analytical methods for inclusion in your manuscript

Optional Deliverables: Multi-omics integration report (5hmC + RNA-seq/ATAC-seq/ChIP-seq), custom figure generation, interactive data browser for exploring your 5hmC data, and long-term raw data archival (beyond standard retention). All files are delivered via secure cloud transfer or hard drive (for large datasets). A project scientist will schedule a data review call to walk you through the results and answer questions. Project timelines depend on sample type, sequencing depth, and analysis complexity — contact us for a project-specific timeline estimate.

Case

Case Study: Plasma cfDNA 5hmC Sequencing for Multi-Cancer Detection

nano-5hmC-Seal Pan-Cancer Detection with 96.6% Specificity Across Six Cancer Types

Source: Shao J, Bernicker EH, He C, Li Z, Clinical and Translational Discovery, 2022. https://doi.org/10.1002/ctd2.136

Background. Noninvasive multi-cancer early detection remains a major unmet need in oncology. While individual cancer types have established screening modalities (mammography, colonoscopy, low-dose CT), a single blood-based test capable of detecting multiple cancer types with high specificity would transform cancer screening. 5-hydroxymethylcytosine (5hmC) profiling of plasma cell-free DNA (cfDNA) offers a genome-wide epigenetic readout that reflects the tissue of origin, but robust multi-cancer validation across diverse tumor types was lacking.

Methods. The study applied nano-5hmC-Seal (a low-input chemical labeling-based 5hmC enrichment method using β-glucosyltransferase and biotin click chemistry) to plasma cfDNA from 384 patients spanning six cancer types — bladder, breast, colorectal, kidney, lung, and prostate cancer — and 221 healthy controls. Genome-wide 5hmC profiles were generated, and machine learning classifiers were developed for pan-cancer detection and tissue-of-origin determination. Performance was validated in an independent cohort with different ethnic backgrounds.

Figure 1: Genome-wide 5hmC profiles in plasma cfDNA from cancer patients vs. healthy controls, demonstrating differential hydroxymethylation patterns and multi-cancer detection performance (Shao et al., Clin Transl Disc, 2022).

Results. The nano-5hmC-Seal protocol generated highly reproducible genome-wide 5hmC profiles from plasma cfDNA. The pan-cancer 5hmC classifier distinguished cancer patients from healthy controls with 68.6% sensitivity at 96.6% specificity across all six cancer types. Cancer-type-specific signatures achieved substantially higher performance: 80.0% sensitivity for breast cancer, 88.9% for kidney cancer, 94.1% for lung cancer, and 96.4% for prostate cancer — all at approximately 100% specificity. Critically, early-stage cancers (stage I–II) were detected with 89.3%–100% sensitivity across cancer types. In an independent validation cohort of lung cancer patients from a different ethnic background, the lung cancer-specific signature achieved 98.0% sensitivity and 82.3% specificity. A separate 5hmC-based classifier accurately determined the tissue of origin, demonstrating the potential for simultaneous detection and localization.

Conclusion. This study demonstrates that plasma cfDNA 5hmC profiling via nano-5hmC-Seal enables robust multi-cancer detection with high specificity and accurate tissue-of-origin determination. The strong performance across six major cancer types and in independent cross-ethnic validation supports the clinical feasibility of 5hmC-based liquid biopsy for pan-cancer screening. For researchers developing cfDNA epigenetic biomarkers, this work establishes a benchmark for multi-cancer 5hmC signatures and validates the nano-5hmC-Seal platform as a scalable approach for large-cohort cancer detection studies.

FAQ

Frequently Asked Questions (FAQ)

Q: What is the difference between 5mC and 5hmC, and why does it matter?

A: 5-Methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC) are distinct epigenetic marks with different biological functions. 5mC is primarily associated with gene repression and is the most abundant DNA modification. 5hmC is generated by TET-mediated oxidation of 5mC and is enriched in gene bodies and active regulatory regions. Standard bisulfite sequencing cannot distinguish them — both read as "methylated." Our specialized methods (oxBS-seq, ACE-seq, hMeDIP-seq, 5hmC-SEAL-seq, ONT long-read) are specifically designed to detect 5hmC without interference from the much more abundant 5mC background.

Q: Which 5hmC detection method should I choose for my project?

A: This depends on your research question and sample material. For unbiased genome-wide screening, choose hMeDIP-seq or 5hmC-SEAL-seq. For single-base quantitative accuracy, choose oxBS-seq or ACE-seq. For limited or damaged DNA (FFPE, cfDNA), ACE-seq is best (10-100 ng). For projects needing simultaneous 5mC+5hmC with haplotype phasing, ONT long-read sequencing provides a single-platform solution. We offer free consultation to help match the method to your project.

Q: Can you detect 5hmC in FFPE samples?

Q: How do you differentiate true 5hmC signal from background in oxBS-seq?

A: oxBS-seq uses a two-step subtraction approach. One aliquot of DNA undergoes standard bisulfite sequencing (BS-seq, which reads both 5mC and 5hmC as "methylated"), while a second aliquot undergoes oxidative bisulfite sequencing (oxBS-seq, where 5hmC is oxidized to 5fC and then reads as "unmethylated" after bisulfite). True 5hmC is calculated as the difference between BS and oxBS signals at each cytosine position. We include spike-in controls and oxidation efficiency assays to validate the accuracy of this subtraction.

Q: What bioinformatics support do you provide for 5hmC data analysis?

Q: Can Oxford Nanopore long-read sequencing detect 5hmC, and when should I choose it?

A: Yes. Oxford Nanopore Technologies (ONT) long-read sequencing directly detects 5hmC (and 5mC simultaneously) from native DNA by analyzing the ionic current signal as DNA passes through the nanopore — no bisulfite conversion, PCR, or enzymatic modification needed. Tools like Dorado, Megalodon, and Remora provide single-base, single-molecule 5hmC calls. ONT is the best choice when you need: (1) simultaneous 5mC + 5hmC from the same data, (2) haplotype-phased modification analysis (which allele carries the mark), (3) integration with structural variant detection, or (4) ultra-long reads (10-100 kb+) spanning repetitive regions intractable to short-read methods. Limitations include higher DNA input (1-3 μg of high-molecular-weight DNA), lower quantitative precision at individual CpGs compared to oxBS-seq, and incompatibility with FFPE samples. For most quantitative 5hmC applications, we recommend oxBS-seq or ACE-seq; ONT is complementary for phasing, SV integration, and simultaneous 5mC/5hmC profiling.

Q: What is the typical sequencing depth required for 5hmC profiling?

A: Required depth depends on the method and research question. For enrichment-based methods (hMeDIP-seq, 5hmC-SEAL-seq), 30-50 million reads per sample are typically sufficient for genome-wide coverage. For single-base resolution methods (oxBS-seq, ACE-seq), 100-200 million reads per sample are recommended — noting that oxBS-seq requires matched BS and oxBS libraries, effectively doubling the sequencing. For ONT long-read sequencing, 15-30× genome coverage (typically 50-100 Gb for a human genome) is recommended for robust 5hmC calling, with higher coverage needed for rare cell populations or low-abundance modifications.

References

Tahiliani M, Koh KP, Shen Y, et al. Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science, 2009, 324(5929):930-935. https://doi.org/10.1126/science.1170116
Booth MJ, Branco MR, Ficz G, et al. Quantitative sequencing of 5-methylcytosine and 5-hydroxymethylcytosine at single-base resolution. Science, 2012, 336(6083):934-937. https://doi.org/10.1126/science.1220671
Song CX, Szulwach KE, Fu Y, et al. Selective chemical labeling reveals the genome-wide distribution of 5-hydroxymethylcytosine. Nature Biotechnology, 2011, 29(1):68-72. https://doi.org/10.1038/nbt.1732
Schutsky EK, DeNizio JE, Hu P, et al. Nondestructive, base-resolution sequencing of 5-hydroxymethylcytosine using a DNA deaminase. Nature Biotechnology, 2018, 36(11):1083-1090. https://doi.org/10.1038/nbt.4204
Yu M, Hon GC, Szulwach KE, et al. Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell, 2012, 149(6):1368-1380. https://doi.org/10.1016/j.cell.2012.04.027
Pastor WA, Pape UJ, Huang Y, et al. Genome-wide mapping of 5-hydroxymethylcytosine in embryonic stem cells. Nature, 2011, 473(7347):394-397. https://doi.org/10.1038/nature10102
Liu Y, Rosikiewicz W, Pan Z, et al. DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation. Genome Biology, 2021, 22:295. https://doi.org/10.1186/s13059-021-02510-z

! For research use only. Not intended for clinical diagnosis, treatment, or individual health assessments. The case study presented is from published, peer-reviewed literature and is provided for informational purposes to illustrate the application of 5hmC detection technology. It does not represent work performed by CD Genomics unless explicitly stated.

! For research purposes only. Not intended for clinical diagnosis, treatment, or individual health assessments.