Human chromosomes have a complex 3D spatial organization in the cell nucleus, which comprises a hierarchy of physical interactions across genomic scales. Such an architecture serves important functional roles, as genes and their regulators have to physically interact to control gene regulation. However, the molecular mechanisms underlying the formation of those contacts remain poorly understood. Here, we describe a polymer-physics-based approach to investigate the machinery shaping genome folding and function. In silico model predictions on DNA single-molecule 3D structures are validated against independent super-resolution single-cell microscopy data, supporting a scenario whereby chromosome architecture is controlled by thermodynamics mechanisms of phase separation. Finally, as an application of our methods, the validated single-polymer conformations of the theory are used to benchmark powerful technologies to probe genome structure, such as Hi-C, SPRITE, and GAM.
Keywords: Chromosome architecture; Gene regulation; Machine learning; Phase separation; Polymer physics; Statistical mechanics.
© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.