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3C-qPCR Service for Hi-C Loop Validation & Locus-Specific Quantification

Verify 3D genome structures with gold-standard precision. While Hi-C provides the global map, our 3C-qPCR service provides the local precision needed to validate specific enhancer-promoter loops and Variant-to-Gene (V2G) assignments.

  • Locus-specific quantification for defined chromatin contacts.
  • Rigorous QC including digestion efficiency and random ligation controls.
  • Analysis-ready deliverables including Relative Interaction Frequencies.
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3C-qPCR workflow illustration showing enhancer-promoter validation

Overview: Verify 3D Genome Structures with Gold-Standard Precision

In the rapidly evolving field of 3D genomics, high-throughput discovery tools like Hi-C, Micro-C, and ChIA-PET have revolutionized how we map chromatin architecture globally. However, these genome-wide maps often suffer from a "resolution gap." While they excel at identifying Topologically Associating Domains (TADs) and compartments, they frequently generate thousands of candidate interactions with insufficient read depth to statistically confirm specific regulatory loops. For Principal Investigators and Biotech Leads, relying solely on low-resolution Hi-C maps for downstream functional studies can be risky.

Our 3C-qPCR (Quantitative Chromosome Conformation Capture) Service serves as the critical "validation bridge" in your research pipeline. While Hi-C provides the global map, 3C-qPCR provides the local precision. By converting physical chromatin contacts into measurable quantitative PCR (qPCR) signals, we enable you to verify specific enhancer-promoter loops, confirm Variant-to-Gene (V2G) assignments, and validate structural variation effects with the highest dynamic range available.

Designed for researchers who need defensible evidence for publications, grant applications, or "Go/No-Go" decisions in drug discovery, our service covers the entire workflow—from custom primer design and restriction enzyme selection to the statistical analysis of Relative Interaction Frequencies (RIF). We do not just run samples; we provide a fully controlled, optimized assay to transform your "candidate loops" into "validated mechanisms."

(Note: This service is for Research Use Only. It is not intended for use in diagnostic procedures or clinical decision-making.)

Service Highlights

  • Gold-Standard Validation: Orthogonal confirmation for Hi-C and Micro-C candidates.
  • Custom Primer Design: In silico optimization for HindIII, EcoRI, or DpnII sites.
  • Rigorous QC System: Includes digestion efficiency checks and random ligation controls.
  • High Sensitivity: Detect rare interactions in low-input samples.
  • Analysis-Ready: Deliverables include statistical analysis and publication-grade figures.

Applications: From V2G Discovery to Functional Confirmation

High-throughput data is often noisy, and false positives are common in loop calling algorithms. Our 3C-qPCR service is optimized for the following critical research scenarios where orthogonal validation is required:

Enhancer-Promoter Loop Validation

Hi-C maps often lack the resolution to distinguish between adjacent promoters. We isolate the specific interaction between an enhancer anchor and a promoter target to provide a quantitative "interaction frequency" that validates candidate enhancers identified by ATAC-seq or ChIP-seq.

Variant-to-Gene (V2G) Mapping

Determine which gene a GWAS variant regulates. 3C-qPCR tests the physical proximity between a specific risk locus and potential effector genes, bridging the gap between statistical association and biological causation.

Structural Variant (SV) Analysis

Large-scale chromosomal rearrangements can create "neo-loops" or disrupt TADs. We design assays to span breakpoints, quantitatively confirming whether an SV facilitates a new pathological interaction or abolishes an existing one.

CRISPR-Cas9 Perturbation Checks

Verify that your enhancer deletion or CTCF site mutation successfully disrupted the physical loop. 3C-qPCR offers a direct readout of "Loop Loss" by comparing interaction frequency in edited clones vs. parental lines.

Differential Interaction Quantification

Detect subtle changes in loop strength across conditions (e.g., Drug Treated vs. Vehicle). 3C-qPCR offers a wider dynamic range than sequencing, enabling precise statistical comparison of interaction frequencies.

Our 3C-qPCR Workflow: Rigorous Design & QC

A successful 3C experiment relies entirely on precise experimental design and strict Quality Control (QC). We prioritize transparency to ensure your data is reproducible.

Step 1: Project Consultation & In Silico Design
We analyze your locus to select the optimal restriction enzyme (typically HindIII, EcoRI, BglII, or DpnII) and design custom unidirectional primers. All primers are screened for thermodynamic compatibility and specificity.

Step 2: 3C Library Preparation
We perform cross-linking and overnight restriction digestion. QC Checkpoint: We verify digestion efficiency (>80%) via gel or qPCR before proceeding. Diluted ligation then favors intramolecular events to capture true proximity.

Step 3: Control Library Generation
We generate a Random Ligation Control (using BACs) to correct for primer efficiency and an Internal Genomic Control to normalize for DNA template loading. This ensures signals reflect true looping, not technical bias.

Step 4: qPCR Quantification & Analysis
Samples are run in technical triplicate using TaqMan or SYBR chemistry. Data is processed using the comparative Ct method to derive Relative Interaction Frequencies (RIF), with statistical testing between conditions.

3C-qPCR workflow steps from cross-linking to qPCR quantification

Demo Results: High-Resolution Interaction Quantification

We deliver clear, analysis-ready data including raw Ct values and normalized interaction plots.

Figure 1: 3C Library Quality Control

Before qPCR, we validate physical library generation. The gel image typically shows:

  • Genomic DNA: High integrity.
  • Digestion: Effective cutting (smear to lower MW).
  • Ligation: Successful re-ligation (shift to higher MW), confirming the library is valid for analysis.

Figure 2: Relative Interaction Frequency Analysis

The final output displays the Relative Interaction Frequency (RIF) across the locus.

  • Peak Detection: A specific peak at the Enhancer-Promoter site significantly higher than background.
  • Condition Comparison: Grouped bars (e.g., WT vs. KO) showing statistical changes in loop strength.

Agarose gel showing 3C library digestion and ligation efficiencyFigure 1: 3C Library QC Gel

Bar chart showing relative interaction frequency of enhancer-promoter loopFigure 2: Interaction Frequency Plot

Sample Requirements

To ensure high-complexity 3C libraries with minimal noise, high-quality starting material is essential. 3C-qPCR requires intact nuclei; therefore, sample preservation is critical. Please consult with us before shipping samples.

Sample Type Recommended Input Minimum Input (Risk) Preparation Notes
Cell Lines (Human/Mouse) 5 - 10 Million cells 1 - 2 Million cells Fresh cells preferred. If freezing, wash in PBS and flash freeze dry pellets. Do not use lysis buffers before shipping.
Animal Tissue 50 - 100 mg 20 mg Must be flash frozen in liquid nitrogen immediately after dissection. Powdering recommended for tough tissues (muscle, heart).
Plant Tissue 0.5 - 1 g 0.2 g Young leaves/shoots preferred. Requires specialized nuclei isolation buffer (additional charge).
Blood (PBMC) 5 - 10 Million PBMCs 2 Million PBMCs Critical: Must be free of Red Blood Cells (RBCs) and granulocytes. Isolate via Ficoll gradient.
FACS Sorted Cells > 1 Million cells 0.5 Million cells Fixation immediately after sorting is recommended for low input samples to preserve chromatin structure.

For protein-centric interaction studies (e.g., loops mediated by specific transcription factors like CTCF or Cohesin), please refer to our ChIP-Loop / HiChIP Services.

Case Study: Validating FTO-IRX3 Long-Range Interactions

The following case study summarizes a seminal application of 3C/4C methods in the field, representing the type of validation work we support.

The Challenge

Genome-wide association studies (GWAS) had strongly linked variants in the FTO gene to obesity risk. FTO was the strongest genetic risk factor for obesity, but the mechanism remained elusive. The variants were in a non-coding intron. The biological question was: Do these non-coding variants regulate FTO expression, or do they bypass FTO to regulate a distant gene?

The Solution

Researchers employed Chromosome Conformation Capture (3C/4C) technology to map the physical interactions of the FTO risk interval. They designed experiments to query the interaction frequency between the FTO enhancer region (harboring the obesity-associated SNVs) and promoters of all neighboring genes in a large genomic window, spanning over 1 Megabase.

The Result

The 3C data revealed a surprising, strong long-range chromatin loop. The FTO enhancer did not interact significantly with the FTO promoter. Instead, it formed a robust physical loop with the promoter of IRX3, a gene located several hundred kilobases away. Furthermore, 3C analysis in human, mouse, and zebrafish models showed this interaction was evolutionarily conserved.

The Conclusion

This validation provided the "smoking gun" evidence that IRX3 (not FTO) was the true effector gene for obesity risk in this locus. This discovery, enabled by 3C technology, shifted the entire paradigm of obesity drug development for this target.

Source: Smemo, S., et al. "Obesity-associated variants within FTO form long-range functional connections with IRX3." Nature (2014). Link to Paper

FAQ: Technical Specs & Decisions

References

  1. Dekker, J., et al. (2002). Capturing chromosome conformation. Science, 295(5558), 1306-1311.
  2. Smemo, S., et al. (2014). Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature, 507(7492), 371-375.
  3. Hagege, H., et al. (2007). Quantitative analysis of chromosome conformation capture assays (3C-qPCR). Nature Protocols, 2(7), 1722-1733.
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