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Methyl-Hi-C Sequencing Service: Simultaneous 3D Genome & Methylation Profiling

In the complex world of gene regulation, the "shape" of the genome (3D architecture) and the chemical markers on the DNA (methylation) are intimately linked. Traditionally, studying these two layers required two separate experiments: Hi-C for structure and Whole Genome Bisulfite Sequencing (WGBS) for methylation. This approach doubles the cost, doubles the sample requirement, and introduces data integration challenges because you are comparing two different populations of cells.

  • Dual Output: High-resolution 3D chromatin maps + whole-genome methylation profiles.
  • Sample Efficiency: Generate two "omics" datasets from a single input source.
  • Direct Linkage: Correlate loop formation directly with the methylation status of the anchoring sequences.
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3D illustration of a DNA loop with methylation markers in Methyl-Hi-C.

Overview: One Sample, Two Layers of Epigenetic Data

Our Methyl-Hi-C Sequencing Service solves the challenge of integrating multi-omics data by combining high-throughput chromosome conformation capture (Hi-C) with bisulfite sequencing in a single, streamlined workflow. By performing bisulfite conversion on proximity-ligated DNA, we enable you to simultaneously map the 3D chromatin loops and the DNA methylation status of the exact same DNA molecules.

This powerful multi-omics approach is a game-changer for researchers working with limited biological material, such as clinical biopsies or rare cell populations. It provides a direct, unambiguous link between chromatin folding and epigenetic regulation, giving you a complete picture of genome function without the guesswork of integrating separate datasets.

Why Choose Methyl-Hi-C?

  • Direct Linkage: Tells you definitively if specific DNA loops are anchored by methylated alleles.
  • Sample Efficiency: Maximize data recovery from finite inputs like FACS-sorted cells.
  • No Batch Effects: Structural and methylation data come from the same library prep event.

Advantages of Methyl-Hi-C

Direct Linkage of Structure and Function

When you run Hi-C and WGBS separately, you are looking at population averages. Methyl-Hi-C preserves the physical linkage. It tells you definitively whether a specific DNA loop is anchored by methylated or unmethylated DNA. This is critical for studying allele-specific phenomena like genomic imprinting or deciphering complex heterogeneity in tumor samples.

Sample Efficiency (Multi-Omics)

Biological samples are often precious and finite. Whether you are working with rare FACS-sorted immune cells, early embryonic tissue, or longitudinal patient biopsies, splitting your sample for multiple assays may not be an option. Methyl-Hi-C maximizes your data recovery, providing a comprehensive epigenetic and structural profile from a single input.

Eliminating Batch Effects

Integrating data from separate experiments always introduces technical noise—or "batch effects"—caused by slight differences in sample handling. Because Methyl-Hi-C generates both structural and methylation data from the same library preparation event, these technical variations are eliminated. The correlation you observe is biological, not artifactual.

Technical Comparison: Methyl-Hi-C vs. Separate Assays

Feature Methyl-Hi-C (Our Service) Hi-C + WGBS (Separate)
Data Output 3D Structure + Methylome (Simultaneous) Structure (Hi-C) + Methylome (WGBS)
Input Requirement Low (Single input needed) High (Requires splitting sample 2x)
Data Linkage Direct (Same Molecule) Indirect (Population Average)
Batch Effect None (Unified workflow) Potential variation between assays
Cost Efficiency High (One library prep) Moderate (Two separate preps)
Best For Mechanistic studies, Rare samples Large-scale screening where only one modality matters

Our Methyl-Hi-C Workflow: From Crosslinking to Bisulfite Sequencing

Our optimized workflow integrates two complex protocols into a robust, high-yield service. We handle the critical "handshake" between chromatin fixation and chemical conversion to ensure high-quality data.

  1. In Situ Hi-C Module: Cells are crosslinked to freeze 3D structures. Chromatin is digested (DpnII) and filled with biotin before ligation to capture proximity.
  2. Bisulfite Conversion: Ligated DNA is purified and treated with bisulfite to convert unmethylated Cytosines to Uracils, encoding epigenetic information.
  3. Library Construction: Specialized adapters and amplification protocols are used for the fragile, bisulfite-converted DNA.
  4. Sequencing: Deep PE150 sequencing on Illumina platforms.
  5. Dual-Pipeline Analysis: Bioinformatics processing maps interactions (Hi-C matrix) and calls methylation states (linear tracks) simultaneously.

Step-by-step workflow diagram of the Methyl-Hi-C sequencing service.

Sample Requirements

Sample Type Recommended Input Minimum Input Storage/Transport
Cell Lines 1 Million cells 50,000 cells Flash Frozen Pellet or Cryopreserved
Primary Cells 1 Million cells 100,000 cells Fresh or Cryopreserved
Tissue 20-50 mg 10 mg Flash Frozen (Liquid Nitrogen)
Blood 2-5 mL 1 mL EDTA Tubes (Fresh)

*Note: For ultra-low input projects (<50,000 cells), please consult with our technical team to discuss feasibility.

Key Deliverables & Demo Results

We deliver comprehensive, integrated data visualization packages that allow you to see the genome in multiple dimensions at once.

Integrated Heatmaps

Standard Hi-C heatmaps (TADs/loops) aligned with parallel "Methylation Heatmaps" to visualize the epigenetic status of interacting loci.

Linear Tracks

High-resolution tracks showing DNA methylation levels (CG, CHG, CHH contexts) aligned with structural domains.

Interaction Matrices

Data files listing specific loop anchors along with their methylation percentage, ready for statistical analysis.

Integrated heatmap showing Hi-C contacts and methylation levels.Integrated Heatmap

Case Study: Tet-Mediated Demethylation & Chromatin Folding

DNA methylation is known to repress gene expression, but its direct role in shaping the physical structure of chromosomes has been debated. In a 2024 study, researchers investigated how the removal of methylation—mediated by Tet enzymes—affects the 3D genome.

The research team utilized Methyl-Hi-C to profile mouse embryonic stem cells. They compared wild-type cells with "Triple Knockout" (TKO) cells lacking Tet1, Tet2, and Tet3 enzymes. This setup created a system where methylation levels were drastically altered, allowing the team to observe the structural consequences.

The simultaneous profiling capability of Methyl-Hi-C was crucial. It revealed that in the absence of Tet enzymes, the genome became hypermethylated. This global increase in methylation directly correlated with a strengthening of "compartment" segregation—essentially, the "active" and "inactive" parts of the genome separated more rigidly.

Data showing the link between DNA methylation and chromatin compartments in Methyl-Hi-C.

By using Methyl-Hi-C, the study provided direct, molecule-level evidence that DNA methylation dynamics are a driver of chromatin organization, rather than just a passive bystander. The method allowed them to link specific methylation changes to specific structural shifts in the same cells.

(Source: Tet-mediated DNA methylation dynamics affect chromosome organization, Nucleic Acids Research, 2024.)

Frequently Asked Questions

References

  1. Tet-mediated DNA methylation dynamics affect chromosome organization. Nucleic Acids Research. 2024.
  2. Joint profiling of DNA methylation and chromatin architecture in single cells. Nature Methods. 2019.
  3. NOMe-HiC: joint profiling of genetic variant, DNA methylation, chromatin accessibility, and 3D genome in the same DNA molecule. Genome Biology. 2023.
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