Hi-C Analysis
Hi-C Analysis of 3D Genome Organization and Chromatin Interactions · Also known as: Chromosome conformation capture, 3D genome, Chromatin contact mapping
Hi-C (High-Chromosome Conformation Capture) is a technique and associated computational methods for mapping the 3D architecture of the genome within cells. Developed by Lieberman-Aiden and Dekker in 2009, Hi-C identifies physical interactions between genomic regions that may be distant in linear sequence but spatially proximal in 3D nuclear space. Hi-C analysis has revealed fundamental principles of genome organization, including the existence of topologically associating domains (TADs), and provides insights into how 3D structure regulates gene expression and DNA replication.
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When to use it
Use Hi-C to understand how the 3D genome is organized, to identify long-range regulatory interactions, or to compare genome architecture across cell types or disease states. Hi-C is particularly powerful for identifying enhancer-promoter loops and understanding how structural variants affect genome function. Avoid Hi-C when studying individual loci in detail (imaging methods are better), or when cells are highly heterogeneous (averaged contact patterns obscure individual variation).
Strengths & limitations
- Provides genome-wide view of 3D genome organization at high resolution
- Identifies topologically associating domains and long-range regulatory interactions
- Reveals how genome architecture varies across cell types and conditions
- Can detect structural variants and large-scale chromatin rearrangements
- Integrates well with other omics data (RNA-seq, chromatin marks) for mechanistic insights
- Provides population average; individual cell heterogeneity is lost
- Computationally intensive; requires significant data storage and processing
- Contact distance strongly influenced by technical factors (restriction enzyme choice, ligation efficiency)
- Does not directly measure physical distance; contact frequency depends on multiple factors
- Resolution limited by sequencing depth; very high-resolution mapping requires billions of reads
Frequently asked
What is a topologically associating domain (TAD)?
A TAD is a chromosomal region (typically 200 kb to 1 Mb) within which chromatin interacts frequently, but between which interactions are rare. TADs appear as block-diagonal patterns in Hi-C contact matrices and are thought to represent functional regulatory units. TAD boundaries often coincide with genes and regulatory elements.
How does Hi-C differ from other chromosome conformation capture methods?
3C measures a single interaction between two genomic locations. 4C measures interactions of one locus with all others. 5C measures many pre-selected interactions. Hi-C measures all-to-all interactions genome-wide. Each method trades off throughput for targeted information.
Why do Hi-C matrices need normalization?
Contact frequencies depend on technical factors: restriction sites near a locus affect fragmentation, mappability varies across genomic regions, ligation efficiency is sequence-dependent. Without normalization, these biases create spurious patterns. Normalization removes biases while preserving true biological signal.
Can Hi-C identify causal enhancer-promoter interactions?
Hi-C identifies physically proximal loci but does not directly reveal causality. Causality requires functional validation (CRISPR perturbation, reporter assays). Hi-C identifies candidate interactions; additional experiments test whether they are functionally important.
Sources
- Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., & Dekker, J. (2009). Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science, 326(5950), 289–293. DOI: 10.1126/science.1181369 ↗
- Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., & Ren, B. (2012). Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature, 485(7398), 376–380. DOI: 10.1038/nature11082 ↗
- Szabo, Q., Bantignies, F., & Cavalli, G. (2019). 3D chromatin architecture. Nature Reviews Molecular Cell Biology, 20(4), 207–220. link ↗
How to cite this page
ScholarGate. (2026, June 3). Hi-C Analysis of 3D Genome Organization and Chromatin Interactions. ScholarGate. https://scholargate.app/en/genetics/hi-c-analysis
Which method?
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