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3C-Seq (Chromosome Conformation Capture) Sequencing Service

Targeted chromatin interaction sequencing for promoter–enhancer loops, transcription-factor binding and regulatory network discovery.

  • Locus-specific quantitation for defined enhancer–promoter chromatin contacts.
  • Flexible formats for single-loop validation or panel-based loop screening.
  • Integrated CRO workflow from primer design to quantitative report delivery.
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3C-Seq chromatin interaction workflow showing enhancer

Why Targeted 3C-Seq Beats Genome-Wide Interaction Mapping

In targeted regulatory-genomics research, the ability to validate a single suspected loop between an enhancer and its gene promoter often determines the success of an entire project. Genome-wide methods such as Hi-C generate vast datasets but frequently leave researchers asking: Which of the thousands of interactions matter? In fact, a 2018 review noted that classic 3C techniques remain the gold standard for one-vs-one analysis of chromatin loops.

At the same time, many drug-development and functional-genomics teams face prohibitive costs, large sample input requirements and overly complex analysis workflows when opting for broad interaction mapping. Our 3C-Seq service addresses this gap by offering precise and cost-effective detection of chromatin contacts at the locus level—ideal for promoter–enhancer validation, pathway mapping, and regulatory-element discovery.

When to Choose 3C-Seq

  • You have a defined hypothesis about a specific enhancer–promoter interaction.
  • You want quantitative loop readouts for compound treatment, perturbation, or variant testing.
  • Your samples are limiting, making high-depth Hi-C impractical.
  • You need a focused, publication-ready assay rather than exploratory genome-wide mapping.

What is 3C-Seq?

3C-Seq (Chromosome Conformation Capture Sequencing) is a targeted genomics assay that quantifies physical contacts between predefined genomic loci — such as enhancer–promoter loops — by converting three-dimensional proximity into measurable DNA junctions.

The workflow begins with cross-linking chromatin in situ, digesting with a restriction enzyme, ligating spatially adjacent fragments and then performing targeted sequencing or amplification of ligation products.

Unlike genome-wide 3D methods (like Hi-C) that capture “all-vs-all” interactions, 3C-Seq focuses on “one-vs-one” or “one-vs-few” pairs with high sensitivity and lower sequencing depth.

By enabling locus-specific quantification of chromatin interactions, 3C-Seq supports downstream studies in gene regulation, functional genomics and targeted therapeutic development where validating specific loops is critical.

Service Highlights

Single-Locus Precision

Our 3C-Seq service zooms in on defined regulatory loops—such as enhancer–promoter pairs—instead of scanning the whole genome. You receive quantitative interaction frequencies for the specific contacts that drive your biology.

Flexible Assay Formats

Choose 3C-qPCR for single-loop validation or Multiplex 3C for panel analysis across many candidate loops. We align assay throughput with your research phase, from early discovery to targeted validation.

Low-Input Compatible

Our workflow is optimised for limited or precious samples—down to tens of thousands of cells or archival tissue—making 3C-Seq suitable for rare populations, primary cells and preclinical models.

Cost-Effective Validation Path

Compared with high-depth Hi-C sequencing, targeted 3C-Seq reduces data volume and cost while retaining locus specificity and clear, actionable output for decision-making.

End-to-End CRO Delivery

From primer design and digestion optimisation to ligation QC, amplification and bioinformatics, CD Genomics provides a single-vendor solution to minimise hand-offs and streamline your timelines.

Choosing the Right Technology: 3C-Seq vs Hi-C vs Capture-C

Technology Scope Resolution / Depth Input & Cost Consideration Best Use Case
3C-Seq Single or few locus interactions (one-vs-one) High precision at predefined loci Relatively low input and cost Validating specific enhancer–promoter loops and targeted regulatory studies
Capture-C Many predetermined loci pulled down (many-vs-many) Higher resolution in targeted regions Moderate input and cost Screening panels of candidate regulatory elements or networks
Hi-C Genome-wide interaction mapping (all-vs-all) Broad mapping; resolution depends on sequencing depth High input and high cost Unbiased discovery of chromatin architecture and large-scale interaction maps

Notes:

Workflow – Step-by-Step 3C-Seq Procedure

This workflow offers a focused alternative to genome-wide methods, delivering single-locus resolution, low input compatibility, and cost-efficient execution, making it ideal for loop validation in drug development, functional genomics, and breeding research.

1. Sample reception and quality control

We receive tissues, cells or nuclei and assess viability, integrity and suitability for cross-linking. Poor quality or over-fixed samples may reduce ligation efficiency and sensitivity.

2. Formaldehyde cross-linking

Intact chromatin is treated with formaldehyde alone or in combination with additional cross-linkers to fix DNA–protein and protein–protein interactions, preserving chromatin loops in situ.

3. Restriction enzyme digestion

Chromatin is fragmented with selected restriction enzymes (e.g. HindIII, BglII, DpnII or DdeI) under optimised conditions to generate ligatable fragments while maintaining proximity information.

4. Proximity ligation

Under highly diluted conditions, DNA fragments that are spatially close within the nucleus are preferentially ligated, forming new junctions that represent chromatin contacts.

5. Reverse cross-linking and DNA purification

Cross-links are reversed and DNA is purified to yield a library of ligated fragments ready for targeted amplification.

6. Quantification: 3C-qPCR or Multiplex 3C

Depending on the selected format, we design primers for single-loop qPCR or multiplex panels. Carefully chosen controls and normalisation strategies ensure reproducible, quantitative loop readouts.

7. Data analysis and reporting

We normalise interaction frequencies, filter background ligation events, calculate enrichment metrics and deliver a structured report with raw data and publication-ready figures.

3C-Seq assay 8-step workflow for chromatin interaction analysis

3C Variants – Choosing the Right Format for Your Project

Format Throughput Sensitivity Ideal Sample Input Key Output Metrics
3C-qPCR Low (single target) Medium ~1 × 105 cells or more ΔCt fold-change of loop vs control, relative interaction frequency
Multiplex 3C Medium (multiple loci) Medium ~5 × 104–105 cells Relative enrichment across multiple loop pairs in a panel format

Technical Specifications for 3C-Seq

Assay Chemistry

  • Cross-linking: formaldehyde alone or FA + DSG for high-confidence loop detection.
  • Restriction enzymes: HindIII, BglII, DpnII, DdeI (selected based on locus and design).
  • Ligation: dilution-based proximity ligation using T4 DNA ligase.
  • Detection: qPCR or multiplex PCR with high-sensitivity quantification options.

Performance Metrics

Resolution Loop-level (fragment-level, enzyme dependent)
Quantification type Relative (qPCR, multiplex) and high-sensitivity digital modes
Dynamic range Typically 10²–10⁴ fold change, depending on format and design
Reproducibility CV < 10–15% across biological replicates under optimised conditions
Assay noise Controlled by enzyme QC, ligation efficiency and internal controls
Sample throughput Single locus up to > 50 loci per multiplex panel

Recommended Applications of 3C-Seq

Our 3C-Seq service is ideally positioned to support research programmes across biology, drug development and breeding pipelines where precise chromatin interaction data adds actionable insight.

Promoter–Enhancer Validation for Target Discovery

Use 3C-Seq to confirm whether distal enhancers physically interact with target gene promoters, helping prioritise regulatory elements for CRISPR perturbation or reporter assays.

Drug Mechanism of Action & Biomarker Research

Quantify loop frequency changes after compound treatment or genetic perturbation and correlate loop modulation with gene expression, signalling pathways and phenotypic outcomes.

Rare Cell Populations and Precious Samples

Apply 3C-Seq to low-input samples such as primary cells, sorted populations or archival biopsies, where traditional genome-wide 3D assays are limited by material requirements.

Crop Genomics & Breeding Research

Validate candidate enhancer–gene connections in complex crop genomes and integrate loop information into marker-assisted breeding programmes and trait-discovery pipelines.

Diagnostic Research & Variant Interpretation

Link non-coding variants in regulatory elements to their target genes by measuring physical contacts between variant-harbouring regions and promoters in patient-derived or model-system samples.

Multiplex 3C vs Capture-C vs HiChIP

Method Throughput Target Scope Sample Input Requirement Primary Output / Application Key Advantage
Multiplex 3C Medium (many loci) Multiple specific enhancer–promoter pairs ~104–105 cells Relative quantification of multiple loops via qPCR or digital readouts High throughput among targeted assays; cost-efficient for focused panels
Capture-C High (hundreds of loci) Many predetermined fragments enriched using probes ~105–106 cells Sequencing-based interaction profiles with finer mapping in selected regions Broader locus panels and higher resolution than basic 3C
HiChIP High to very high Protein-mediated chromatin contacts (e.g. TF-bound enhancers) ~105–106 cells Genome-wide or large-scale loops anchored by a protein of interest Combines ChIP and interaction capture to provide rich biological context

Why CD Genomics

Our 3C-Seq service is ideally positioned to support research programmes across biology, drug development and breeding pipelines where precise chromatin interaction data adds actionable insight.

End-to-End 3C-Seq Workflow Under One Roof

We manage every step—primer design, digestion optimisation, ligation efficiency control and quantitative readouts—to reduce variability and shorten project timelines.

Validated Protocols for Diverse Sample Types

Our team has established cross-linking and digestion conditions for suspension and adherent cells, primary tissue, blood-derived cells and low-input samples, each with tailored QC thresholds.

High-Precision Quantification

We match assay format and analysis strategy to your goals—from single-loop validation to multi-locus screening—and provide normalised interaction frequencies with appropriate controls.

Expert Bioinformatics & Reporting

You receive structured reports, QC metrics and figures that are ready to integrate into manuscripts, internal decision-making or regulatory documentation.

RUO Service with Quality Governance

All work is performed under RUO conditions with version-controlled SOPs, secure data handling and optional NDAs to protect your programme.

Sample Requirements for 3C-Seq

Sample Type Minimum Input Preferred Input Notes
Cultured cells 1 × 105 cells 5 × 105–1 × 106 cells Fresh cells recommended; avoid over-fixation and prolonged storage.
Primary cells 5 × 104 cells 1–5 × 105 cells Suitable for sorted or rare populations; contact us for project-specific advice.
Tissues 10–20 mg 30–50 mg Provide tissue in cold PBS; avoid necrotic regions where possible.
Cryopreserved pellets 1 × 105 cells 5 × 105 cells Thaw rapidly with minimal handling to preserve chromatin integrity.
Nuclei preparations Equivalent to 1 × 105 cells 2–5 × 105 nuclei Provide nuclei in an appropriate buffer; avoid harsh detergents.
Low-input projects Case-by-case Case-by-case Consultation required for < 5 × 104 cells.

Key Deliverables

Our 3C-Seq service is ideally positioned to support research programmes across biology, drug development and breeding pipelines where precise chromatin interaction data adds actionable insight.

Raw Data Files
Raw qPCR Ct tables, panel readouts and optional FASTQ files for sequencing-based formats.

Normalised Interaction Matrices
Tabulated results showing loop frequencies at defined loci (e.g., enhancer–promoter pairs).

QC Summary
Comprehensive metrics covering digestion efficiency, ligation rates and primer performance.

Publication-Ready Report
A formatted PDF describing background, methods, results and loop enrichment.

Optional Design Files
Primer design files for extended panels or follow-up experiments.

Case Study: Systematic Evaluation of 3C-Based Chromatin Interaction Assays

Chromosome conformation capture derivatives—including Hi-C, Micro-C, 3C-Seq and targeted 3C approaches— are widely used to quantify chromatin interactions and reveal enhancer–promoter communication. However, fragment size, cross-linking conditions and enzyme selection can dramatically affect signal-to-noise ratios, loop detection sensitivity and compartment quantification.

Chromosome conformation capture derivatives—including Hi-C, Micro-C, 3C-Seq and targeted 3C approaches— are widely used to quantify chromatin interactions and reveal enhancer–promoter communication. However, fragment size, cross-linking conditions and enzyme selection can dramatically affect signal-to-noise ratios, loop detection sensitivity and compartment quantification.

Akgol Oksuz et al. systematically evaluated 12 protocol variants across three cross-linking chemistries (FA, FA+DSG, FA+EGS) and multiple fragmentation strategies (restriction enzymes and MNase) in several cell types. Quantitative metrics included cis/trans ratios, distance-dependent contact decay, loop detection and compartment strength.

  • Cross-linking: formaldehyde alone or FA + DSG for high-confidence loop detection.
    • Ligation: dilution-based proximity ligation using T4 DNA ligase.
    • Detection: qPCR or multiplex PCR with high-sensitivity quantification options.
  • Restriction enzymes: HindIII, BglII, DpnII, DdeI (selected based on locus and design).
  • Ligation: dilution-based proximity ligation using T4 DNA ligase.
  • Detection: qPCR or multiplex PCR with high-sensitivity quantification options.

FA+DSG cross-linking substantially improved detection of enhancer–promoter loops by reducing random ligation noise and stabilising fine-scale contacts. MNase-based fragmentation produced the highest loop detection sensitivity, whereas larger fragments (e.g. HindIII) provided stronger A/B compartment signals. Combining FA+DSG with fine fragmentation yielded the strongest and most numerous loop calls.

This benchmark highlights that enzyme choice and cross-linking chemistry critically influence 3C-Seq accuracy. For targeted assays such as 3C-qPCR and Multiplex 3C, FA+DSG cross-linking and finer fragmentation (DpnII/DdeI or MNase) are recommended for sensitive enhancer–promoter quantification, while HindIII-based strategies remain valuable when compartment-level architecture is of interest.

  • Restriction enzymes: HindIII, BglII, DpnII, DdeI (selected based on locus and design).
  • Ligation: dilution-based proximity ligation using T4 DNA ligase.
  • Cross-linking: formaldehyde alone or FA + DSG for high-confidence loop detection.
    • Ligation: dilution-based proximity ligation using T4 DNA ligase.
    • Detection: qPCR or multiplex PCR with high-sensitivity quantification options.
  • Detection: qPCR or multiplex PCR with high-sensitivity quantification options.

3C-Seq Demo Results (Representative Examples)

  • Processed count matrices linked to spatial coordinates and cluster labels.
  • Spatial maps, UMAP and t-SNE plots, cell cycle and trajectory visualisations.
  • Tables of marker genes, enriched functions, interaction metrics, and spatially variable genes.
  • A concise analysis report describing methods, key quality metrics, and main biological findings.

Primer Pair Interaction Map

Multiplex Panel Heatmap

Interaction Bar Plot

Bar Plot

Frequently Asked Questions

References

  1. Rodriques SG, Stickels RR, Goeva A, et al. Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution. Science. 2019;363(6434):1463–1467.
  2. Yang M, Ong J, Meng F, et al. Spatiotemporal insight into early pregnancy governed by immune-featured stromal cells. Cell. 2023;186(20):4271–4288.e24.
  3. Langlieb J, Sachdev NS, Balderrama KS, et al. The molecular cytoarchitecture of the adult mouse brain. Nature. 2023;624(7991):333–342.
  4. Causer A, Tan X, Lu X, et al. Deep spatial-omics analysis of head and neck carcinomas provides alternative therapeutic targets and rationale for treatment failure. NPJ Precision Oncology. 2023;7(1):89.
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