ChromPolymerDB: A High-Resolution Database of Single-Cell 3D Chromatin Structures for Functional Genomics

Area of Science:

• Genomics
• Computational Biology
• Structural Biology

Background:

• The 3D chromatin organization is crucial for gene regulation and genome stability.
• Population-averaged assays like Hi-C obscure crucial single-cell conformational heterogeneity.
• Understanding single-cell genome architecture is vital for deciphering gene regulation.

Purpose of the Study:

• To develop a computational framework for deconvoluting bulk Hi-C data into single-cell 3D chromatin conformations.
• To create a comprehensive, high-resolution database of single-cell chromatin structures.
• To provide tools for exploring the relationship between 3D genome structure and biological processes.

Main Methods:

• Developed the Sequential Bayesian Inference Framework (sBIF), a polymer physics-based modeling approach.
• Applied sBIF to deconvolve population-averaged Hi-C data to reconstruct single-cell chromatin structures.
• Created ChromPolymerDB, a publicly accessible database storing ~10^8 reconstructed 5 kb-resolution single-cell structures.

Main Results:

• Successfully reconstructed ~10^8 single-cell 3D chromatin conformations at 5 kb resolution.
• ChromPolymerDB encompasses over 60,000 genomic loci across 50 human cell types and conditions.
• The database provides an interactive platform for 3D structural analysis and multi-omics integration.

Conclusions:

• ChromPolymerDB offers a unique resource for studying genome architecture and gene regulation at the single-cell level.
• The platform facilitates comparative analyses of chromatin structure across different cell types, developmental stages, and disease contexts.
• This work advances the field of comparative 3D genomics by providing unprecedented insights into genome organization.