MBE Chromosome structure detection

1. Experimental Purpose¶

Scientific Question: How does three-dimensional genome organization influence gene regulation and cellular function?
Design Rationale: Chromosome conformation capture technologies reveal spatial organization of chromatin, regulatory interactions, and topological domains
Follow-up Studies: Correlation with gene expression, epigenetic marks, functional validation of regulatory interactions, dynamic changes during development or disease

2. Model System¶

Primary Systems: Cell lines, primary cells, tissue samples, embryos
Rationale: These systems provide sufficient material for capturing chromatin interactions while maintaining native nuclear architecture
Alternatives:
In vitro nuclear preparations (pros: enriched nuclei; cons: potential disruption of architecture)
Single-cell approaches (pros: cellular heterogeneity; cons: technical noise)
Tissue sections (pros: spatial context; cons: fixation artifacts)
Ethical Considerations: Standard considerations for cell and tissue sources, potential insights into disease mechanisms

3. Measurement Approach¶

Common Elements:
Crosslinking to preserve chromatin interactions
Restriction enzyme digestion
Proximity ligation of interacting fragments
DNA purification and analysis
Technical Replicates: Multiple libraries recommended due to complexity of protocols
Potential Biases:
Restriction enzyme bias (site distribution)
Crosslinking efficiency variations
PCR amplification bias
Mapping biases in repetitive regions

4. Group Setting¶

Experimental Groups:
Test: Samples under experimental condition of interest
Control 1: Untreated/baseline samples
Control 2: Technical controls (random ligation controls)
Control 3: Biological reference samples for normalization
Controlled Variables: Cell cycle stage, fixation conditions, cell density
Biological Replicates: Minimum 2-3 biological replicates; more for heterogeneous samples
Modified Design: Time-course analysis, cell type comparisons, treatment effects

5. Data Analysis & Presentation¶

Common Analysis Elements:
Interaction matrix generation
Normalization for technical biases
Identification of significant interactions
Domain calling (TADs, compartments)
Presentation Approaches:
Heatmaps at various resolutions
Virtual 4C plots for specific viewpoints
Circos plots for genome-wide interactions
3D models of chromatin folding

6. Technique Comparison¶

Feature	3C (Chromosome Conformation Capture)	4C (Circular Chromosome Conformation Capture)	5C (Carbon Copy Chromosome Conformation Capture)	Hi-C
Primary Application	One-to-one interactions	One-to-all interactions	Many-to-many interactions	All-to-all interactions
Scope	Focused (few loci)	Viewpoint-centric	Regional (multiple loci)	Genome-wide
Resolution	High (restriction fragment)	High at viewpoint	High within region	Variable (10kb-1Mb)
Coverage	Limited (targeted)	Genome-wide from viewpoint	Selected regions	Genome-wide
Throughput	Low	Medium	High for target regions	Very high
Input Material	Low (millions of cells)	Low to moderate	Moderate	High (millions of cells)
Complexity	Low	Moderate	High	Very high
Cost	Low	Moderate	Moderate to high	High
Sequencing Depth	Low (targeted)	Moderate	High for covered regions	Very high
Analysis Complexity	Simple	Moderate	Moderate to high	Very high
Best For	• Testing specific interactions • Validating predictions • Focused hypothesis testing • Quantitative comparison	• Single locus regulation • Enhancer-promoter mapping • Identifying all contacts for a region • Detailed viewpoint analysis	• Regulatory landscapes • Complex locus organization • Multiple candidate interactions • Medium-scale mapping	• Global architecture • TAD identification • Compartment analysis • Comprehensive interaction maps
Limitations	• Limited to predefined regions • Labor-intensive for multiple loci • No global context • Primer design challenges	• Limited to single viewpoint • Uneven coverage away from viewpoint • Complex library preparation • Viewpoint bias	• Limited to predefined regions • Primer design complexity • Coverage gaps • Labor-intensive design	• Lower resolution • High sequencing costs • Complex computational analysis • High cell input requirements

7. Complementary Usage Strategy¶

Hypothesis Generation:
Begin with Hi-C for global chromosome architecture
Identify domains, compartments, and potential regulatory hubs
Focused Investigation:
Use 4C to explore all interactions from key regulatory elements
Apply 5C to comprehensively map interactions across candidate regions
Validate specific interactions with 3C for quantitative assessment
Functional Validation:
Correlate interactions with gene expression data
Integrate with epigenetic marks (ChIP-seq, ATAC-seq)
Perform genetic perturbation of interaction sites
Integrated Approach: Design multi-platform studies for comprehensive characterization:
Hi-C to map global architecture and identify domains
4C to explore key regulatory elements in detail
5C to comprehensively analyze complex regulatory regions
3C to validate and quantify specific interactions of interest

8. Technology-Specific Considerations¶

3C (Chromosome Conformation Capture)¶

Design Considerations:
Primer design critical for efficiency and specificity
Control for primer efficiency with BAC templates
Quantitative PCR for accurate interaction measurement
Applications:
Validation of predicted interactions
Quantitative comparison between conditions
Focused analysis of specific regulatory elements
Variations:
Real-time PCR vs. traditional PCR detection
Multiplexed 3C for multiple simultaneous interactions
Nested 3C for improved specificity

4C (Circular Chromosome Conformation Capture)¶

Design Considerations:
Viewpoint selection critical (regulatory elements, promoters)
Secondary restriction enzyme choice affects resolution
Inverse PCR conditions optimization important
Applications:
Enhancer-promoter interaction mapping
Identifying novel regulatory contacts
Comparing interaction profiles between conditions
Variations:
4C-seq with high-throughput sequencing
r3C-seq with reduced complexity
e4C with enhanced sensitivity

5C (Carbon Copy Chromosome Conformation Capture)¶

Design Considerations:
Primer design complexity (hundreds of primers)
Balanced primer pool important for even coverage
Optimization of multiplex PCR conditions
Applications:
Comprehensive mapping of complex loci
Regulatory landscapes of developmental genes
Comparing multiple regions simultaneously
Variations:
5C with next-generation sequencing
Targeted 5C for specific pathways
Condition-specific 5C designs

Hi-C¶

Design Considerations:
Biotin incorporation efficiency
Streptavidin bead enrichment optimization
Sequencing depth vs. resolution trade-off
Applications:
Global chromatin organization
Topologically associating domain (TAD) identification
A/B compartment analysis
Long-range interaction discovery
Variations:
In situ Hi-C for improved signal-to-noise
Capture Hi-C for targeted regions
Micro-C with micrococcal nuclease for nucleosome-level resolution
HiChIP/PLAC-seq for protein-centric interactions
Single-cell Hi-C for cellular heterogeneity

9. Integration with Other Technologies¶

Epigenomic Integration:
ChIP-seq data to correlate interactions with histone marks
ATAC-seq to identify accessible regions at interaction sites
DNA methylation data to assess regulatory potential
Transcriptomic Integration:
RNA-seq to correlate interactions with gene expression
eQTL analysis to link genetic variation to interaction changes
Nascent RNA analysis for direct regulatory effects
Imaging Validation:
DNA FISH to validate specific interactions
Super-resolution microscopy for fine-scale organization
Live-cell imaging for dynamic changes

This integrated framework provides researchers with a structured approach to selecting and combining chromosome conformation capture technologies. The complementary use of these methods, from genome-wide to locus-specific, enables a comprehensive understanding of chromatin architecture and its functional implications in gene regulation.