NucleoMap

NucleoMap identifies nucleosome positions at high resolution using ultra-high-resolution chromatin contact maps (Micro-C, DNase Hi-C, Hi-CO) to characterize nucleosome organization and associations with chromatin features.

Key Features:

• Integration of chromatin conformation techniques: Leverages Micro-C, DNase Hi-C, and Hi-CO chromatin contact maps to obtain nucleosome-level proximity data for profiling mono-nucleosomes and pairwise nucleosome spacing.
• Multi-modal data integration: Combines nucleosome read density, contact distances, and binding preferences to locate nucleosomes across prokaryotic and eukaryotic genomes.
• Detection of poorly positioned nucleosomes: Identifies nucleosome positions in regions with weak or variable positioning.
• Performance metrics: Demonstrates improved precision and recall relative to existing nucleosome identification methods.
• Genome-wide association analysis: Characterizes associations between mono-nucleosome spatial organization and histone modifications, protein binding activities, and higher-order chromatin functions.
• Structural insights: Identified two tetra-nucleosome folding structures in human embryonic stem cells and their associations with structural and functional regions.
• Nucleosome contact map construction: Constructs nucleosome contact maps that reflect inter-nucleosome distances while preserving original contact distance profiles from chromatin contact maps.

Scientific Applications:

• Chromatin architecture analysis: Maps nucleosome positions and contact maps to study chromatin folding and spatial organization.
• Gene regulation studies: Relates nucleosome arrangement to histone modifications and protein binding activities affecting gene regulation.
• Structural nucleosome research: Investigates tetra-nucleosome folding structures and their genomic associations in human embryonic stem cells.
• Comparative nucleosome positioning: Profiles nucleosome organization across prokaryotic and eukaryotic genomes, including poorly positioned regions.

Methodology:

Uses chromatin contact maps from Micro-C, DNase Hi-C, and Hi-CO and integrates nucleosome read density, contact distances, and binding preferences to identify nucleosome positions and construct nucleosome contact maps that preserve original contact distance profiles.