Hi-C / Genome-Wide 3C Sequencing Service for 3D Chromatin Architecture

Genes do not function in isolation; they operate within a complex three-dimensional chromatin network. While standard NGS reveals the linear sequence, it misses the spatial regulatory landscape.

CD Genomics provides comprehensive Chromosome Conformation Capture (Hi-C / 3C-Seq) services to bridge this gap. By combining in situ proximity ligation with high-throughput sequencing, we capture genome-wide chromatin interactions without the bias of selected viewpoints. Whether you are mapping Topologically Associating Domains (TADs), identifying distal enhancer-promoter loops, or assembling chromosome-scale genomes, our optimized Hi-C workflow delivers the high-resolution data required for breakthrough epigenetics research.

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3D chromatin folding illustration showing a specific chromatin loop and biotin-labeled ligation junction, visualized alongside a high-resolution Hi-C interaction heatmap with TADs and loop peaks.
Workflow Service Packages Hi-C Specs Advantage 3C vs 4C vs Hi-C Data Analysis Applications Sample Requirements Demo Case Study FAQ

Why 3D Genomics? Beyond the Linear Sequence

In eukaryotic nuclei, chromatin is folded into a hierarchical 3D structure that brings distant regulatory elements into close proximity. Traditional 3C (One-vs-One) or 4C (One-vs-All) methods are hypothesis-driven and limited to specific loci.

To fully understand gene regulation, researchers need a Discovery-Driven approach. Hi-C Sequencing (All-vs-All) is the gold standard for mapping the entire interactome. It reveals:

How Hi-C Works: The "Proximity Ligation" Principle

Our Hi-C service utilizes an optimized in situ protocol to minimize background noise and maximize valid interaction pairs.

  1. Cross-linking: Cells are treated with formaldehyde to covalently link DNA-protein complexes, "freezing" the chromatin in its native 3D conformation.
  2. Digestion: Chromatin is digested with a specific restriction enzyme (typically MboI or HindIII). This creates sticky ends at the interaction sites.
  3. Biotin Fill-in: The cohesive ends are filled in with nucleotides, including a biotinylated residue. This crucial step marks the ligation junction.
  4. Proximity Ligation: Ligase joins the blunt, biotin-marked ends. Crucially, ligation occurs preferentially between fragments that are spatially close, even if they are distant on the linear chromosome.
  5. DNA Purification & Shearing: Cross-links are reversed, proteins are removed, and DNA is sheared into small fragments.
  6. Streptavidin Enrichment: Biotinylated ligation junctions are pulled down using streptavidin beads. This ensures that only the chimeric fragments representing 3D interactions are sequenced.
  7. Sequencing: The library is sequenced on the Illumina NovaSeq platform (PE150) to generate billions of paired-end reads.

Step-by-step in situ Hi-C workflow diagram illustrating cross-linking, restriction digestion, biotin fill-in of DNA ends, proximity ligation to form loops, streptavidin enrichment of biotinylated junctions, and high-throughput sequencing.

Service Packages: From Standard to Multi-Omics

Service Package Description Key Applications
Standard Hi-C Genome-wide map of chromatin interactions (Resolution: 20-40kb). A/B Compartments, TADs identification, Genome Scaffolding.
Deep Hi-C High-depth sequencing (Resolution: <5kb). Enhancer-Promoter Loops, Structural Variations (SVs).
Low-Input Hi-C Optimized protocol for rare samples (50k+ cells). Clinical biopsies, FACS-sorted cells, Embryos.
3D Multi-Omics (Hi-C + RNA-Seq) Integrated analysis of chromatin architecture and gene expression. Correlating structure with function; Validating regulatory loops.

Why Integrate Hi-C with RNA-Seq?

Structure dictates function. While Hi-C identifies physical interactions (e.g., a loop between an enhancer and a gene), it does not tell you if that interaction is functional. By combining Hi-C with RNA-Seq, CD Genomics enables you to:

Validate Regulatory Loops: Confirm that a specific chromatin loop actually drives the upregulation of its target gene.

Link TADs to Transcription: Analyze how changes in TAD boundaries (e.g., during differentiation or in cancer) directly impact the global transcriptome.

Mechanism Discovery: Distinguish between direct structural causes of disease and secondary expression changes.

Hi-C Service Specifications

Feature Standard Hi-C Low-Input Hi-C Capture Hi-C
Primary Application Genome-wide TADs & Compartments Rare samples / FACS sorted cells Validating specific Promoter/Enhancer loops
Input Requirement 1 - 5 million cells 50,000 - 500,000 cells > 5 million cells
Resolution Goal 20kb - 40kb 40kb - 100kb < 5kb (Target Region)
Sequencing Strategy Illumina PE150 Illumina PE150 Illumina PE150
Bioinformatics Interaction Matrix, TAD Calling Interaction Matrix, Scaffolding Targeted Loop Calling

The CD Genomics Advantage: Resolution & Sensitivity

We address the two biggest challenges in 3D genomics: Sample Quantity and Data Resolution.

CD Genomics Track Record in 3D Genomics

3C vs. 4C vs. Hi-C: Choosing the Right Method

To help you select the optimal technology, we compare the "C-family" methods below.

Method Scope Key Application Pros Cons
3C (Standard) One-vs-One Validating a specific loop Low Cost Low Throughput
4C-Seq One-vs-All Profiling interactions of one "viewpoint" High Resolution for one locus Requires known bait
Hi-C (Genome-Wide) All-vs-All Global architecture (TADs, Loops) Unbiased, Discovery-driven Requires high sequencing depth
Capture Hi-C Many-vs-All High-res analysis of promoters Cost-effective high resolution Requires probe design

Comprehensive Data Analysis

We don't just deliver Raw Data (FASTQ). Our standard bioinformatics pipeline includes analysis compatible with popular visualization tools like Juicebox and HiGlass.

Standard Deliverables:

Comprehensive Data Analysis

Key Applications of Hi-C Sequencing

Oncology & Disease Mechanisms

Detect structural variants (SVs) such as translocations and inversions that create neo-TADs, leading to oncogene activation. Hi-C provides a higher resolution for complex rearrangements than standard WGS.

Developmental Biology

Track how chromatin architecture reorganizes during cell differentiation. Understand how lineage-specific transcription factors reshape the 3D genome.

Plant & Animal Genomics

Achieve chromosome-level genome assembly

Hi-C data provides the long-range linkage information needed to scaffold fragmented contigs into complete chromosomes.

Metagenomics (Meta-Hi-C)

Resolve complex microbial communities. By linking plasmids and antibiotic resistance genes to their specific host chromosomes based on physical proximity, Meta-Hi-C solves the "who carries what" problem in microbiome studies.

Sample Requirements

Sample Type Recommended Input Handling & Preservation Note
Cell Lines Standard: 1×106 – 5×106 cells Low-Input: ≥50,000 cells Flash-frozen in liquid nitrogen OR Cross-linked with 1-2% Formaldehyde (protocol provided). Pellet cells, remove supernatant, store at -80°C.
Animal Tissue ≥50 mg Flash-frozen immediately in liquid nitrogen to preserve chromatin structure. Avoid thawing. Connective tissues may require specific disruption.
Plant Tissue ≥1 g (Young leaves) Flash-frozen in liquid nitrogen. High-polyphenol samples require special buffers.
Blood ≥2 mL Whole Blood EDTA anticoagulant tube (Purple top). Isolate PBMCs if possible for better results.
Shipping / Strictly on Dry Ice (>5 kg) to maintain -80°C environment during transport. Chromatin degradation leads to loss of long-range interactions.
Deliverables Data: Clean Data (FastQ), Alignment (BAM), Interaction Matrix (.hic/.cool)Visuals: Heatmaps, TAD boundaries, Loop Lists, Circos Plots Report: Comprehensive QC & Methods Report

Demo

Multi-panel Hi-C data analysis figure. (A) Circos plot showing inter-chromosomal interactions. (B) Hi-C heatmap showing Topologically Associating Domains (TADs). (C) High-resolution heatmap zooming in on a specific chromatin loop peak. (D) Integrated multi-omics tracks showing ChIP-seq H3K27ac and RNA-seq peaks at the loop anchors. Comprehensive Hi-C Data Analysis and Multi-Omics Integration. (A) Global Interaction Map: A Circos plot visualizing genome-wide trans (inter-chromosomal) interactions. (B) TAD Identification: A Hi-C interaction heatmap (Chr7) revealing Topologically Associating Domains (TADs) outlined in dashed black lines. The deep red diagonal indicates high contact frequency. (C) High-Resolution Loop Calling: A zoomed-in view of a specific chromatin loop (off-diagonal peak). The arc above illustrates the physical connection between two distal loci. (D) Structure-Function Correlation: Integration of the loop anchors from (C) with 1D genomics tracks. The left anchor coincides with an active enhancer mark (ChIP-seq H3K27ac), and the right anchor aligns with an actively transcribed gene (RNA-seq), demonstrating a functional enhancer-promoter interaction detected by Hi-C.

Case Study: Unraveling the 3D Regulatory Landscape of Cotton Fiber

Project Source: Genome Biology

Title: Dynamic 3D genome architecture of cotton fiber reveals subgenome-coordinated chromatin topology for 4-staged single-cell differentiation

Publication Date: 2022

DOI: 10.1186/s13059-022-02616-y

Cotton fiber quality is regulated by a complex gene network during rapid cell elongation. The researchers aimed to decode the "black box" of how dynamic 3D chromatin architecture drives this differentiation process in a single-cell model.

A comprehensive Multi-Omics approach was applied across four key developmental stages:

  • Hi-C Sequencing: To map genome-wide chromatin interactions (TADs and A/B compartments).
  • RNA-Seq: To track dynamic gene expression changes.
  • ChIP-Seq (H3K27ac/H3K4me3): To identify active regulatory elements.
  • Compartment Switching: The study revealed that chromatin compartment status (A/B) changes significantly during development, directly correlating with the activation or silencing of fiber-related genes.
  • TAD Dynamics: While TAD boundaries were largely stable, internal interaction frequencies shifted, facilitating stage-specific regulation.
  • Subgenome Coordination: In the allotetraploid genome, the two subgenomes displayed distinct 3D packing strategies to coordinate fiber elongation.

Hi-C interaction heatmap showing TADs and A/B compartment switching in plant genome, sourced from Genome Biology case study Figure 1. Dynamic 3D Chromatin Architecture. High-resolution Hi-C interaction heatmaps showing clear Topologically Associating Domains (TADs) and A/B compartment tracks in the cotton genome. The data quality allows for precise boundary identification.

Figure 2. Integrated Multi-Omics Analysis (Hi-C + RNA-seq + ChIP-seq). Visualization of a functional chromatin loop (purple arc) connecting a distal enhancer (ChIP-seq peak) to its target gene promoter. This structural interaction directly correlates with the gene's high expression level (RNA-seq track).

This study demonstrates that the 3D genome dynamically remodels to regulate cell differentiation. Integrating Hi-C with RNA-seq successfully linked spatial chromatin changes to phenotypic traits, offering new targets for molecular breeding.

FAQ

References:

  1. Ramani V, Deng X, Qiu R, et al. Massively multiplex single-cell Hi-C. Nature methods. 2017;14(3):263-6.
  2. Williamson I, Berlivet S, Eskeland R, et al. Spatial genome organization: contrasting views from chromosome conformation capture and fluorescence in situ hybridization. Genes & development. 2014;28(24):2778-91.
  3. Stadhouders R, Kolovos P, Brouwer R, et al. Multiplexed chromosome conformation capture sequencing for rapid genome-scale high-resolution detection of long-range chromatin interactions. Nature protocols. 2013;8(3):509-24.
  4. Lan X, Witt H, Katsumura K, et al. Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages. Nucleic acids research. 2012;40(16):7690-704.
  5. Pei, L., et al. Dynamic 3D genome architecture of cotton fiber reveals subgenome-coordinated chromatin topology for 4-staged single-cell differentiation. Genome Biology. 2022;23:45.


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