Investigating Phase Separation in Genome Folding via Multiscale Computational Modeling.

Area of Science:

• Genomics
• Biophysics
• Computational Biology

Background:

• The 3D genome organization is crucial for gene regulation.
• Phase separation is a key physical mechanism underlying genome architecture.

Purpose of the Study:

• To review how phase separation influences genome folding across various scales.
• To highlight computational advances in modeling genome organization.
• To integrate different modeling paradigms with experimental data.

Main Methods:

• Physics-based simulations (all-atom to coarse-grained polymer models).
• Data-driven approaches (machine learning on genomic and imaging data).
• Integration of computational models with experimental findings.

Main Results:

• Phase separation contributes to compartmentalization, TADs, transcriptional condensates, and nucleosome arrays.
• Computational models elucidate chromatin condensation mechanisms.
• Integration clarifies interplay between phase separation, loop extrusion, epigenetics, and chromatin properties.

Conclusions:

• Combined computational and experimental approaches provide mechanistic insights into genome folding.
• These insights link molecular interactions to nuclear organization and gene regulation.
• The study paves the way for predictive 4D nucleome models.