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Promoter Capture Hi-C (PCHi-C) Service: Human & Mouse Panels

Map the complete regulatory landscape of the human or mouse genome. Our Promoter Capture Hi-C (PCHi-C) Service utilizes standardized, high-density probe panels to capture interactions for over 20,000 coding and non-coding promoters in a single assay. Achieve high-resolution Variant-to-Gene (V2G) assignment and enhancer mapping at a fraction of the cost of whole-genome Hi-C (RUO).

  • Pan-Promoter Coverage: Target 20,000+ promoters (Human/Mouse) simultaneously.
  • Cost-Efficient: 15-20x enrichment allows high resolution with moderate sequencing depth.
  • Standardized Workflow: Validated probe designs based on canonical reference genomes.
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Promoter Capture Hi-C data showing genome-wide promoter-enhancer interactions

Overview: Genome-Wide V2G Mapping with Standardized Panels

For researchers and drug developers, the "Variant-to-Gene" (V2G) problem remains a critical bottleneck. Thousands of GWAS hits sit in non-coding regions, their target genes unknown. Whole-genome Hi-C Sequencing provides a global map, but achieving the resolution necessary to link a specific enhancer to a promoter requires billions of reads per sample—often making large-scale comparative studies cost-prohibitive.

Our Promoter Capture Hi-C (PCHi-C) Service solves this resolution-versus-cost dilemma. By combining in situ Hi-C library preparation with Standardized Oligonucleotide Capture Panels, we selectively enrich interactions involving gene promoters.

Unlike custom capture approaches that target a few specific loci, our Off-the-Shelf Human and Mouse Panels target all annotated promoters (coding and non-coding) in the genome simultaneously. This allows you to construct a Global Promoter Interactome Atlas with ~15-20x enrichment efficiency, achieving high-resolution loop detection (fragment level) with a fraction of the sequencing depth required for standard Hi-C. This approach effectively converts ambiguous "distance-based" gene assignments into definitive "contact-based" regulatory networks.

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

Key Benefits

  • Global V2G Mapping: Assign target genes to GWAS variants genome-wide in a single experiment.
  • High Resolution: Detect specific enhancer contacts at <5kb resolution (fragment level).
  • Cost Efficiency: Requires only ~100-200M reads per sample, compared to ~800M for comparable Hi-C resolution.
  • Validated Content: Pre-designed panels covering >20,000 promoters ensure no targets are missed.

Applications: System-Level Regulatory Discovery

PCHi-C is the preferred tool for "System-Wide" regulatory mapping, allowing you to screen the entire genome for functional loops without the bias of selecting candidate genes. It bridges the gap between linear genomics (GWAS/ChIP-seq) and functional phenotypes.

High-Throughput V2G Assignment

Instead of validating variants one by one, PCHi-C allows you to assign target genes to all GWAS risk variants in your sample simultaneously. If a disease-associated SNP lies in an enhancer, PCHi-C captures the physical loop connecting that enhancer to its target promoter (often skipping the nearest gene). This results in a prioritized list of "Effector Genes" for your disease model, supported by direct physical evidence.

Comparative Interactomics (Healthy vs. Disease)

The high coverage depth on promoters allows for robust quantitative comparison. You can compare the interactomes of Healthy vs. Diseased tissue (e.g., Tumor vs. Normal) to identify Differential Loops. PCHi-C enables the discovery of "Rewired" promoter interactions—such as the gain of an enhancer loop activating an oncogene or the loss of a repressive loop—that drive phenotypic changes, often invisible to RNA-seq alone.

Mapping "Orphan" Enhancers

Many enhancers identified by ChIP-seq (H3K27ac) or ATAC-seq are "orphans" with unknown targets. PCHi-C provides the "address book" for these regulatory elements, linking them to the promoters they regulate globally. This is particularly valuable for understanding the function of super-enhancers and clustered regulatory elements that may regulate distant genes via complex chromatin folding.

Panel Specifications: Human & Mouse

We utilize high-density, pre-validated capture panels designed to cover the vast majority of the annotated transcriptome. These panels are optimized for compatibility with standard restriction enzyme digestion workflows.

Feature Human Promoter Panel Mouse Promoter Panel
Target Region Promoters of protein-coding genes, non-coding RNAs, and miRNA promoters Promoters of protein-coding genes and annotated non-coding transcripts
Number of Promoters ~22,000+ ~20,000+
Total Target Size ~30 - 40 Mb ~25 - 35 Mb
Probe Design 120-mer RNA baits, tiled across digestion fragments containing TSS 120-mer RNA baits, tiled across digestion fragments containing TSS
Enzyme Compatibility Optimized for HindIII (6-cutter) or MboI/DpnII (4-cutter) libraries Optimized for HindIII (6-cutter) or MboI/DpnII (4-cutter) libraries

Comparison: PCHi-C vs. Whole Genome Hi-C

The decision between PCHi-C and Hi-C comes down to Resolution per Read. While Hi-C provides a comprehensive overview of genome architecture, PCHi-C offers a magnifying glass for regulatory interactions.

  • Whole Genome Hi-C: Spends sequencing power on everything—including gene deserts, vast intergenic regions, and structural scaffolds (TADs/Compartments). To see a specific promoter loop clearly, you need extreme depth (~800M reads).
  • Promoter Capture Hi-C: Focuses sequencing power exclusively on the Promoters. This enrichment means you can detect specific regulatory loops with high statistical confidence using only ~100-200M reads.

Summary: Choose Hi-C for TADs, A/B compartments, and SV detection (translocations). Choose PCHi-C for linking Enhancers to Promoters genome-wide at high resolution.

Our Workflow: From Hi-C Library to Capture

Our end-to-end service integrates standard Hi-C library construction with high-efficiency hybridization capture. This workflow is optimized to maximize on-target rates and library complexity.

Step 1: In Situ Hi-C Library Preparation
Cells are cross-linked with formaldehyde to freeze 3D chromatin structures in place. Chromatin is digested (typically with HindIII or DpnII), ends are filled with biotinylated nucleotides, and spatially proximal fragments are ligated. This creates the "3D Library" representing the whole genome interactions.

Step 2: Hybridization with Pan-Promoter Probes
The Hi-C library is denatured and hybridized with the biotinylated RNA probe panel (Human or Mouse). These 120-mer RNA baits are tiled specifically around Transcription Start Sites (TSS). Streptavidin beads pull down only the DNA fragments containing promoter sequences (and whatever distal elements they are ligated to). This step washes away the vast majority of non-informative genomic background.

Step 3: Sequencing & CHiCAGO Analysis
Enriched libraries are sequenced on Illumina platforms (PE150). For analysis, we use specialized pipelines such as CHiCAGO (Capture Hi-C Analysis of Genomic Organization). This algorithm specifically models the background noise and distance-decay inherent to capture data to call significant Promoter-Interaction Peaks with high specificity, filtering out technical artifacts and random collisions.

Workflow of Promoter Capture Hi-C using biotinylated RNA probe panels

Sample Requirements

Promoter Capture Hi-C requires high-quality starting material to ensure library complexity. The following inputs are recommended for optimal results.

Sample Type Minimum Input Preferred Input Key Notes
Cell Lines 1 × 10^6 cells 5 × 10^6 cells Cross-link with 1-2% Formaldehyde. Fresh harvest preferred.
Whole Blood 2 mL 5 - 10 mL Must segregate PBMCs or granulocytes before fixing. Do not freeze whole blood.
Animal Tissue 50 mg 100 - 200 mg Flash-frozen tissue is acceptable. Pulverize in liquid nitrogen.
Primary Cells 500,000 cells 2 × 10^6 cells High viability (>90%) is critical. Low-input protocols available upon request.
FFPE Tissue Not Recommended Not Recommended PCHi-C requires intact nuclei for 3D structure preservation.

Demo Results: Pan-Promoter Connectivity Maps

Figure 1: Genomic Track Visualization (Arc Plot)

The visual output of PCHi-C is distinct from standard Hi-C matrices.

  • The View: A visualization of a specific chromosomal region (e.g., Chr 8) showing promoter connectivity.
  • Top Track (Gene Annotation): Shows the linear location of genes and Transcription Start Sites (TSSs).
  • Bottom Track (PCHi-C Arcs): Unlike the sparse matrix of standard Hi-C, the PCHi-C track shows dense Arcs originating from promoters. Each arc connects a promoter to a distal genomic region (enhancer).
  • Interpretation: The height or color intensity of the arc represents the interaction frequency (CHiCAGO score). You can clearly see promoters "reaching out" to contact specific regulatory elements located hundreds of kilobases away, skipping over non-interacting regions.

Promoter Capture Hi-C data showing genome-wide promoter-enhancer interactionsFigure 1: Pan-Promoter Interactome

Case Study: Fine-Tuned Regulation in Colorectal Cancer

The following study demonstrates the power of combining PCHi-C with Hi-C to decipher disease-specific regulatory rewiring.

The Challenge

Colorectal cancer (CRC) involves complex genetic and epigenetic alterations. While TAD structures are generally stable, researchers hypothesized that fine-scale enhancer-promoter (E-P) loops might be "rewired" in cancer cells to drive oncogene expression, but standard Hi-C lacked the resolution to see these subtle changes.

The Solution

The research team integrated Promoter Capture Hi-C (PCHi-C) with standard Hi-C. This dual approach allowed them to map the global chromatin architecture (Hi-C) while simultaneously zooming in on thousands of promoter interactions (PCHi-C) with high sensitivity.

The Results

The study identified thousands of Differential Promoter Interactions (DPIs) between CRC samples and controls. PCHi-C revealed that specific risk variants (GWAS hits) in non-coding regions were physically looping to contact and activate known CRC oncogenes. These loops were absent in normal tissue. The data showed that chromatin topology is fine-tuned at the loop level during tumorigenesis.

PCHi-C data revealing colorectal cancer specific promoter-enhancer loops

The Conclusion

PCHi-C successfully linked non-coding genetic variance to transcriptional dysregulation in cancer, identifying novel therapeutic targets that were invisible to expression profiling alone.

Source: Wang, X., et al. "Integrated promoter-capture Hi-C and Hi-C analysis reveals fine-tuned regulation of the 3D chromatin architecture in colorectal cancer." Frontiers in Genetics (2025).

FAQ: Input & Customization

References

  1. Wang, X., et al. Integrated promoter-capture Hi-C and Hi-C analysis reveals fine-tuned regulation of the 3D chromatin architecture in colorectal cancer. Frontiers in Genetics. 2025.
  2. Javierre, B.M., et al. Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters. Cell. 2016;167(5):1369-1384.
  3. Montefiori, L., et al. Comparison of cohesin-mediated chromatin interactions revealed by HiChIP and ChIA-PET. Cell Reports. 2018;25(8):2296-2309.
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