Hi-C sequencing

Hi-C-seq is an advanced genomic technique for studying the spatial organisation of chromatin in the cell nucleus. It identifies DNA regions that are close to each other in three-dimensional space, even when they are separated by thousands or millions of base pairs in the linear genome sequence.

Hi-C-seq enables the generation of chromosome-interaction maps and the study of higher-order genome organisation, including chromatin loops, Topologically Associating Domains (TADs) and interchromosomal contacts. The technology plays a key role in research on gene expression regulation, developmental biology, cancer and epigenetic mechanisms.

Hi-C seq workflow

The Hi-C-seq workflow includes several stages that preserve and identify natural contacts between chromatin fragments.

1. 01Fixation of chromatin interactionsCells are fixed with formaldehyde, which stabilises natural contacts between chromatin fragments located close to each other in the cell nucleus.
2. 02Chromatin digestionDNA is then cut at multiple genomic sites using restriction enzymes, producing shorter DNA fragments.
3. 03Ligation of contacting fragmentsAfter digestion, DNA fragments that are spatially close are ligated. This produces chimeric DNA fragments containing sequences from distant genomic regions that were in contact within the nucleus.
4. 04Library preparationThe resulting fragments are purified, amplified and enriched with sequencing adapters required for sequencing.
5. 05NGS sequencingHi-C libraries are sequenced in paired-end mode. The reads contain information about pairs of genomic regions that were in spatial contact.

Applications of Hi-C seq

Hi-C-seq enables the study of genome organisation at a level inaccessible to conventional sequencing methods.

Technical specifications of Hi-C seq

• Sequencing mode: 2x150 bp
• Sequencers: Illumina platform, NovaSeq 6000 and NovaSeq X sequencers.
• Recommended genome coverage per sample:
  • 150x per sample - for chromatin-loop analysis
  • 50x per sample - for TAD analysis
• Other configurations are also available depending on the client's needs.

• Recommended Sample Requirements - DNA/RNA:
  • Sample type:
    • Cells: >5x10⁷
    • Frozen tissue: 1 to 2 g

Hi-C seq bioinformatics analysis

Hi-C data analysis enables comprehensive characterisation of three-dimensional genome organisation, identification of chromatin interactions and comparison of changes in genome architecture between the conditions studied.

• Library quality control:) - The first stage assesses data quality and correct preparation of Hi-C libraries.
  • Assessment of the Hi-C interaction distribution - The distribution of chromosomal contacts and the proportion of intrachromosomal (cis) and interchromosomal (trans) interactions are analysed to assess experimental quality and DNA-fragment ligation efficiency.
  • Interaction Decay Exponent (IDE) analysis - The relationship between contact frequency and genomic distance is examined. This parameter is an important indicator of data quality and chromatin organisation in the analysed samples.
• Chromatin-interaction analysis - A detailed spatial genome-contact map is generated from mapped reads.
  • Genome-wide Hi-C interaction profiling. Interactions are analysed to determine the overall spatial organisation of the genome:
    • intrachromosomal (cis),
    • interchromosomal (trans),
  • Hi-C contact maps (Hi-C Heatmaps) - Contact matrices showing interaction frequencies between genomic regions are generated. These visualisations enable identification of chromatin structures at different organisational levels.
  • A/B compartment analysis - Hi-C identifies two basic types of chromatin domains:
    • Compartment A - transcriptionally active regions rich in genes and open chromatin,
    • Compartment B - less active regions associated with heterochromatin.
  • Identification of TADs (Topologically Associating Domains) - Genomic domains characterised by frequent internal interactions are detected. TADs are fundamental units of spatial chromatin organisation.
  • Identification of chromatin loops - The analysis detects direct contacts between distant genomic regions, such as promoters and enhancers involved in gene expression regulation.
• Differential analysis of three-dimensional chromatin structure - Comparison of two or more biological groups identifies changes in genome architecture associated with biological or disease processes.
  BIOINFORMATICS ANALYSIS SCOPE4 analyses

  Differential chromatin interactionsRegions showing significant changes in contact frequency between the study groups are detected.

  A/B compartment changesThe analysis identifies genomic regions transitioning between active and inactive chromatin states.

  Differential TAD analysisChanges in TAD boundaries and structural reorganisation can be detected.

  Differential chromatin-loop analysisNew or lost regulatory interactions that may affect gene expression are identified.