One chromatin, many structures: From ensemble contact maps to single-cell 3D organization.

Area of Science:

• * Molecular Biology
• * Genomics
• * Computational Biology

Background:

• * Understanding the three-dimensional folding of chromatin is crucial for gene regulation but remains experimentally challenging due to limitations in current assays.
• * Existing methods often provide low-dimensional views of a complex, heterogeneous polymer.
• * Interpreting experimental data requires robust models that can capture the dynamic and variable nature of chromatin organization.

Purpose of the Study:

• * To present an ensemble-based interpretive framework using the Self-Returning Excluded Volume (SR-EV) model for chromatin conformation.
• * To demonstrate how this model can recapitulate key experimental signatures across multiple scales.
• * To provide a unified link between 3D chromatin packing, 2D contact maps, and 1D genomic profiles.

Main Methods:

• * Development of the Self-Returning Excluded Volume (SR-EV) model, a coarse-grained representation of chromatin based on stochastic rules and excluded-volume geometry.
• * Generation of large ensembles of complete three-dimensional chromatin configurations.
• * Projection of these configurations onto 2D contact maps and 1D genomic profiles, incorporating architectural protein effects via ensemble selection.

Main Results:

• * The SR-EV model successfully recapitulates heterogeneous nanoscale packing domains (ChromEMT/ChromSTEM), sparse single-cell contact patterns (Hi-C), and ensemble-level contact enrichments (TADs).
• * Topologically associating domains (TADs) and Hi-C loops are interpreted as statistical enrichments within the ensemble, not invariant single-cell features.
• * Coordination number and probe-based accessibility computed from SR-EV link 3D packing to 2D and 1D experimental observables.

Conclusions:

• * The SR-EV model provides a minimal, geometrically grounded framework for interpreting multimodal chromatin experimental data.
• * Chromatin features like TADs can emerge as statistical properties of heterogeneous ensembles rather than deterministic 3D structures.
• * This framework reconciles diverse experimental observations by linking them to the underlying heterogeneous chromatin ensemble.