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Hi-C Sequencing Service: Mapping the 3D Genome Architecture

Unlock spatial gene regulation mechanisms with high-resolution chromatin interaction mapping.

Linear genome sequencing often fails to explain complex regulatory phenotypes. CD Genomics provides end-to-end Hi-C sequencing services—from protocol optimization to advanced bioinformatic data analysis. We enable researchers to visualize chromatin folding, identifying Topologically Associating Domains (TADs) and enhancer-promoter loops that drive development and disease. Whether you are investigating structural variations in cancer or trait regulation in crops, our platform delivers the Hi-C sequencing depth and precision required for high-impact publications.

  • High-Resolution Mapping: Detect chromatin loops and TAD boundaries with kilobase-level precision for granular insights.
  • Low Input Compatibility: Optimized workflows for rare cell populations (>2×10⁶ cells) and challenging tissue samples (>500mg).
  • Multi-Omics Integration: Seamlessly integrate Hi-C matrices with RNA-seq, ChIP-seq, and ATAC-seq to reconstruct regulatory networks.
  • Customizable Solutions: Flexible sequencing strategies tailored to your specific research goals and budget.
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3D chromatin folding illustration showing enhancer-promoter loops and high-resolution TAD structures for Hi-C sequencing services

Overview - Why 3D Genome Organization Matters

From Linear Sequence to Spatial Regulation

For decades, genomics has focused primarily on the linear sequence of DNA—the "code" of life. However, inside the nucleus, the two meters of human DNA are not strung out in a straight line; they are tightly packed into a hierarchical three-dimensional (3D) architecture. This spatial organization is not random; it is a sophisticated regulatory layer that dictates gene expression, DNA replication, and cell fate decisions.

Hi-C sequencing (High-throughput Chromosome Conformation Capture) is the technological breakthrough that allows us to visualize this architecture, transforming our understanding from a 1D sequence to a 3D regulatory map.

Traditional sequencing methods, such as RNA-seq or ChIP-seq, often fail to explain why a gene is upregulated when its promoter appears normal. The answer often lies in the 3D space: a distal enhancer, located megabases away on the linear genome, may loop around to physically contact the promoter. By utilizing Hi-C sequencing services, researchers can capture these long-range DNA-DNA interactions genome-wide, identifying the "missing links" in gene regulatory networks.

Decoding the Hierarchy of Chromatin

Our analysis pipelines decompose chromatin structure into three biologically significant layers, providing a granular view of genome folding:

  • A/B Compartments: At the megabase scale, the genome segregates into distinct compartments. Compartment A typically contains open, transcriptionally active chromatin (euchromatin) rich in genes and accessible to transcription factors. Compartment B consists of closed, inactive chromatin (heterochromatin) often associated with the nuclear periphery. Changes in compartment status (A-to-B or B-to-A switching) are hallmark signatures of cell differentiation and cancer progression.
  • Topologically Associating Domains (TADs): Zooming in to the sub-megabase scale (hundreds of kilobases), chromatin forms self-interacting neighborhoods called TADs. DNA sequences within a TAD interact frequently with each other but are insulated from interactions with neighboring TADs. These domains are fundamental regulatory units; disrupting TAD boundaries (e.g., via structural variants) can lead to "enhancer hijacking" and pathogenic gene misexpression.
  • Chromatin Loops: At the finest resolution (< 10kb), we identify specific point-to-point interactions, such as those between super-enhancers and target promoters. Mapping these loops is critical for defining the target genes of non-coding variants identified in GWAS studies.

Service Portfolio - Modular Hi-C Solutions

We understand that a "one-size-fits-all" approach does not apply to complex genomic research. Whether you are scaffolding a novel plant genome or investigating subtle loop dynamics in rare tumor cells, we offer a tailored portfolio of Hi-C sequencing protocols.

1. Standard Hi-C (In Situ Hi-C)

The Gold Standard: Unlike traditional "dilution Hi-C," our In situ Hi-C protocol performs the critical proximity ligation step inside the nucleus. This prevents random ligation between non-interacting DNA fragments, drastically reducing background noise and false positives.
Application: Ideal for defining TAD boundaries, A/B compartments, and genome-wide scaffolding.
Deliverables: Interaction matrices, TAD calls, and compartment eigenvectors.

2. HiFi-C (High-Fidelity Long-Read Hi-C)

The Game Changer: Combining PacBio HiFi long-read sequencing with chromatin conformation capture, HiFi-C overcomes the limitations of short-read sequencing. Traditional short reads often struggle to map uniquely in repetitive regions (like centromeres and telomeres). HiFi-C reads (5-10 kb) span these difficult regions, enabling the resolution of haplotypes and structural variants (SVs) with Q40+ accuracy.
Key Advantage: Unlike Pore-C, HiFi-C offers superior base-level accuracy (>99.9%), allowing for precise breakpoint detection in complex genomes. This is the premier choice for T2T (Telomere-to-Telomere) genome assembly and structural variation analysis.

3. Micro-C (Nucleosome-Resolution Hi-C)

Ultimate Resolution: Standard Hi-C uses restriction enzymes (like DpnII or HindIII), which limits resolution to the distribution of restriction sites. Micro-C replaces these enzymes with Micrococcal Nuclease (MNase), which digests chromatin into mononucleosomes.

Benefit: This achieves physical resolution down to ~150bp, allowing researchers to visualize ultra-fine chromatin loops, promoter-enhancer interactions, and even nucleosome positioning. It is the preferred method for high-depth regulatory studies in transcriptional mechanisms.

4. Low-Input Hi-C

For Precious Samples: Standard protocols require millions of cells. Our optimized Low-Input Hi-C workflow utilizes refined lysis and purification chemistry to generate high-complexity libraries from as few as 500,000 cells (or even lower for specific applications). This is crucial for studying primary patient biopsies, FACS-sorted cell populations, or embryonic tissues.

5. Capture Hi-C (Targeted Hi-C)

Cost-Effective Focus: When you are interested only in the interactions of a specific set of promoters or disease loci, Capture Hi-C uses hybridization probes to enrich for regions of interest. This reduces sequencing costs while increasing the effective depth at target sites, making it perfect for validating large cohorts of GWAS hits.

Applications Across Industries

Biotech & Pharmaceutical Development

  • Target Discovery & Validation: Many potential drug targets are regulated by distant enhancers. Hi-C sequencing links these non-coding regulatory elements to coding genes, validating novel therapeutic targets that linear sequencing would miss.
  • Mechanism of Action (MoA): For epigenetic drugs (e.g., HDAC inhibitors), Hi-C can reveal how treatment remodels 3D chromatin architecture, correlating structural changes with therapeutic efficacy.
  • Biomarker Identification: In oncology, specific chromosomal rearrangements create unique "neo-loops" or fusion TADs. These structural fingerprints can serve as highly specific biomarkers for patient stratification.

Academic Research: Functional Genomics & Development

  • Developmental Biology: From limb bud formation to neural differentiation, cell fate is driven by chromatin rewiring. Integrating Hi-C with RNA-seq allows researchers to trace how the establishment of TADs precedes and enables lineage-specific gene expression.
  • Neuroscience: The brain exhibits arguably the most complex 3D genome organization. Hi-C maps in specific neuronal subtypes reveal how chromatin folding underlies synaptic plasticity and cognitive disorders like Fragile X Syndrome.

Agricultural Biotechnology (AgBio)

  • Genome Assembly: Plant genomes are notoriously complex, polyploid, and repetitive. Hi-C data provides the long-range linkage information necessary to scaffold fragmented contigs into chromosome-length assemblies, a critical step for modern molecular breeding.
  • Trait Regulation: Understanding how chromatin structure influences traits like drought resistance or yield helps in selecting non-coding variants for gene editing (CRISPR) or marker-assisted selection.

Workflow - From Sample to Data

Our end-to-end service ensures sample integrity and data reproducibility. We adhere to strict SOPs derived from over a decade of optimization.

Step 1: Sample Preparation & Quality Control

  • Sample Requirements:
    • Cells: Fresh culture is preferred. We recommend 2-5 × 10⁶ cells with viability >90%. Cells must be fixed with 2% formaldehyde for exactly 10 minutes at room temperature, followed by glycine quenching.
    • Animal Tissue: >500 mg is recommended. Tissue must be flash-frozen in liquid nitrogen immediately after dissection to prevent chromatin degradation. Avoid necrotic areas and connective tissue.
    • Plant Tissue: >1 g of young, tender leaves. Older tissues often contain high polysaccharides and polyphenols that interfere with enzymatic digestion. We employ specialized nuclei isolation buffers for recalcitrant plant species.
  • QC: We perform rigorous QC including cell viability checks and DNA integrity assessment before library prep.

Step 2: Chromatin Fixation & Digestion

  • Chromatin is crosslinked in situ to "freeze" DNA-protein and DNA-DNA contacts.
  • We utilize specific restriction enzymes (e.g., DpnII, MboI, or HindIII) to digest DNA. For HiFi-C or Micro-C, alternative fragmentation strategies are used to preserve long reads or nucleosome positioning.

Step 3: Proximity Ligation

  • Sticky ends are filled in with biotinylated nucleotides.
  • Ligation is performed under dilute conditions (or in situ) to favor intramolecular ligation—joining DNA ends that are physically close in 3D space, even if they are distant in sequence.

Step 4: Library Construction & Sequencing

  • Crosslinks are reversed, and DNA is purified. Biotinylated junctions are enriched using streptavidin beads.
  • Libraries are sequenced on Illumina NovaSeq (PE150) for standard Hi-C, or PacBio Revio for HiFi-C projects.
  • Sequencing Depth: We recommend 300-600 million reads per sample for high-resolution loop calling (5-10kb resolution).

Step 5: Bioinformatic Analysis

  • Mapping & Filtering: Reads are aligned to the reference genome. Invalid pairs (self-circles, unligated fragments) are filtered out.
  • Normalization: We use ICE (Iterative Correction and Eigenvector decomposition) to remove systematic biases (e.g., GC content, fragment length).
  • Visualization: Interaction heatmaps, Circos plots, and 3D models are generated.

Hi-C Sequencing Workflow Diagram: Sample Preparation to Bioinformatics Analysis

Sample Requirement Specifications

Sample Type Recommended Input Minimum Input Preparation & Storage Special Notes
Cultured Cells 5×106 cells 2×106 cells Fresh: Pellet and flash freeze in liquid nitrogen.
Fixed: 2% Formaldehyde fixation for 10 min, quenched with Glycine.		 Cell viability must be >90% prior to fixation. Avoid flow cytometry sorting if possible to prevent cell damage.
Animal Tissue >500 mg 100 mg Fresh: Rinse with saline, remove fat/connective tissue, cut into small pieces, and flash freeze. Avoid necrotic or fatty tissues (e.g., adipose), as they interfere with chromatin isolation.
Plant Tissue >1 g 500 mg Fresh: Select young, tender leaves. Wash surface dirt, cut into 5×2cm pieces, and flash freeze. Crucial: Select young tissues to minimize polysaccharides and polyphenols, which can inhibit enzymatic digestion.
Blood/Fluid >5 mL 2 mL Collect in EDTA (purple top) tubes to prevent coagulation. Process immediately or freeze at -80°C. Transport on dry ice.

Comprehensive Hi-C Bioinformatic Analysis

Analysis Module Specific Analysis Items Description & Key Deliverables
1. Standard Data Processing Raw Data QC & Alignment • Quality control of raw sequencing reads (FastQC).
• Iterative mapping to the reference genome.
• Valid interaction pair filtering (removing self-circles, dangling ends).
Matrix Construction • Construction of interaction matrices at various resolutions (e.g., 10kb, 40kb, 100kb).
• ICE/KR Normalization to correct for systematic biases.
Interaction Decay • Analysis of interaction frequency vs. genomic distance to assess library quality.
2. Global Structure Analysis A/B Compartments • PCA eigenvector analysis to identify active (A) and inactive (B) chromatin compartments.
• Visualization of compartment switching events.
• Statistics on compartment number and length distribution.
3. Local Structure Analysis TAD Identification • Calculation of insulation scores to identify Topologically Associating Domains (TADs).
• Visualization of TAD boundaries and hierarchies.
• Statistical distribution of TAD numbers and sizes.
Loop Calling • Identification of significant chromatin loops (e.g., Enhancer-Promoter loops) using HICCUPS or similar algorithms.
• Annotation of loop anchors.
4. Comparative Analysis Differential 3D Architecture • Differential Compartments: Identification of A-to-B or B-to-A switching regions.
• Differential TADs: Analysis of gained/lost TAD boundaries between groups.
• Differential Loops: Quantitative comparison of loop strength (e.g., Wild-type vs. Mutant).
5. Biological Interpretation Functional Enrichment • GO & KEGG Pathway Analysis for genes located within differential compartments, differential TADs, or distinct loop anchors.
• Integration with gene expression data to reveal regulatory mechanisms.

Demo Results

Unlock comprehensive insights with our advanced visualization and analysis package:

  • Genome-wide Interaction Maps: Visualize cis/trans interaction ratios and chromosome territory organization.
  • 3D Structure Identification: Precise calling of A/B compartments, TAD boundaries, and chromatin loops.
  • Differential Analysis: Quantitative comparison of compartment switching (A-to-B) and differential TADs/Loops between conditions.
  • Functional Integration: Correlate chromatin architecture with gene expression (RNA-seq) and identify long-range gene regulation.

Hi-C heatmap showing genome-wide chromosome territoriesGenome-wide Interaction Heatmap

Hi-C A/B compartments aligned with RNA-seq expressionA/B Compartments & Gene Expression

Differential TAD boundary analysis on Hi-C contact mapsTAD Identification & Differential Boundaries

High-resolution significant chromatin loop detectionSignificant Loop Analysis

Case Study: Chromatin Conformation Analysis of Primary Patient Tissue Using Low-Input Hi-C

The application of 3D genomics in clinical diagnostics has been hindered by the high input requirements of standard Hi-C protocols (typically millions of cells). In Diffuse Large B-Cell Lymphoma (DLBCL), identifying structural variants (SVs) like translocations is critical for diagnosis, but patient biopsies often provide limited material. Researchers aimed to validate a low-input Hi-C method to detect pathogenic chromosomal rearrangements and TAD disruptions directly in primary patient tissue1.

The study utilized a "Low-C" protocol optimized for low-input material, applied to primary lymph node biopsies from DLBCL patients. Hi-C sequencing data was generated and integrated with Whole Genome Sequencing (WGS). The analysis pipeline focused on identifying inter-chromosomal interactions (translocations) and mapping changes in local chromatin insulation (TADs) associated with oncogene dysregulation2.

The Hi-C analysis successfully reconstructed the 3D genome from the low-input clinical samples. Most notably, the interaction matrices revealed clear structural variations that linear sequencing could often miss or misinterpret structurally.

Hi-C contact map showing distinct butterfly pattern of t(14;18) chromosomal translocation in lymphoma patient tissue.Figure 1. Detection of chromosomal translocations by Hi-C. The contact map displays a distinct off-diagonal interaction hotspot (butterfly pattern) representing the t(14;18) translocation, which fuses the BCL2 gene with the IGH locus. This structural event is a hallmark driver of the lymphoma.

The Hi-C data provided a distinct visual signature for the t(14;18) translocation. Furthermore, the 3D maps revealed that this rearrangement altered the local chromatin insulation, effectively placing the BCL2 oncogene under the regulatory control of the highly active IGH super-enhancers.

This study confirms that Low-Input Hi-C is a robust tool for analyzing clinical samples. It provides a dual advantage: identifying large-scale structural variants with high precision and revealing the 3D regulatory consequences (enhancer hijacking) of these rearrangements. This establishes Hi-C as a viable assay for precision oncology, even when sample quantity is limited4.

Frequently Asked Questions

References

  1. Montefiori, L.E., et al. "Enhancer hijacking of BCL11A defines a subtype of B cell precursor acute lymphoblastic leukemia." Nature Communications 12, 2615 (2021).
  2. Karasu, N., & Sexton, T. (2020). "4C-Seq: Interrogating Chromatin Looping with Circular Chromosome Conformation Capture." Methods in Molecular Biology.
  3. Schöpflin R, et al. "Integration of Hi-C with short and long-read genome sequencing reveals the structure of germline rearranged genomes." Nat Commun. 2022.
  4. Vian, L., et al. "The Energetics and Physiological Impact of Cohesin Extrusion." Cell. 2018.
  5. Cheng, Y., et al. "Hnrnpk is essential for embryonic limb bud development as a transcription activator and a collaborator of insulator protein Ctcf" Cell Death Differ. 2023.
  6. Díaz, N., Kruse, K., Erdmann, T. et al. Chromatin conformation analysis of primary patient tissue using a low-input Hi-C method. Nature Communications 9, 4938 (2018).
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High-confidence 3D genomics services for chromatin interaction analysis and regulatory insight.

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