TL;DR
This paper introduces DIMES, a maximum-entropy computational model that predicts 3D chromatin structures from pairwise distances, enabling analysis of genome organization, heterogeneity, and structural variations in chromosomes.
Contribution
The novel DIMES method applies maximum entropy principles to generate ensembles of 3D chromatin structures from pairwise distance data, bridging imaging and Hi-C data analysis.
Findings
Successfully predicts 3D chromatin structures from pairwise distances
Quantifies heterogeneity and fluctuations in chromatin shapes
Reveals differences between imaging-based and Hi-C inferred structures
Abstract
The principles that govern the organization of genomes, which are needed for a deeper understanding of how chromosomes are packaged and function in eukaryotic cells, could be deciphered if the three-dimensional (3D) structures are known. Recently, single-cell imaging experiments have determined the 3D coordinates of a number of loci in a chromosome. Here, we introduce a computational method (Distance Matrix to Ensemble of Structures, DIMES), based on the maximum entropy principle, with experimental pair-wise distances between loci as constraints, to generate a unique ensemble of 3D chromatin structures. Using the ensemble of structures, we quantitatively account for the distribution of pair-wise distances, three-body co-localization and higher-order interactions. We demonstrate that the DIMES method can be applied to both small length-scale and chromosome-scale imaging data to quantify…
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