GENOVA

GENOVA analyzes Hi-C conformation capture data to quantify and visualize genome organization, including compartment structure, insulation scores, annotated contact heatmaps, and aggregated Hi-C signals over genomic regions for genome-wide chromatin architecture studies.

Key Features:

• Compartment and insulation analysis: Implements compartment analysis and insulation score calculations for assessing large-scale and local chromatin organization.
• Annotated contact heatmaps: Generates annotated heatmaps that visualize contact frequency at specific loci.
• Aggregate signal over regions: Aggregates Hi-C signals over user-defined genomic regions, including regions defined by ChIP-seq data.
• Compatibility with mapping pipelines: Accepts outputs from major mapping pipelines for integration into existing Hi-C workflows.
• Scalability: Supports analysis of large-scale Hi-C datasets at genome-wide resolution.

Scientific Applications:

• HAP1 ΔSA1 cells: Analysis revealed increased intra-TAD interactions and heightened compartmentalization, suggesting cohesinSA1 involvement in forming longer loops.
• HAP1 ΔSA2 cells: Analysis showed longer loops and reduced compartmentalization, indicating a role for cohesinSA2 in maintaining intra-TAD interactions.
• Cohesin subunit functional dissection: Results support the hypothesis that three-dimensional genome structure arises from a balance between loop formation and compartmentalization modulated by cohesin subunits SA1 and SA2.

Methodology:

Processes Hi-C conformation capture data to elucidate chromosome structures at genome-wide scale and supports qualitative and quantitative analyses of chromatin organization.