Reconstructing Chromatin Structural Connectivity from Sparse Locus Tracking Experiments Using Polymer Dynamics Modeling

Chromatin dynamics is key to understanding a number of biological processes such as transcriptional regulation that is linked to establishment of cellular identity. However, visualization of chromatin is mostly limited to live imaging of a few fluorescently labeled chromosomal segments (or loci) or high-resolution reconstruction of multiple loci from a single time frame. In this study, we present an exact analytical framework that provides a probabilistic description of the time evolution of a flexible polymer structure given its structure at an earlier time point. Using this framework, we propose an algorithm that tracks the polymer configuration from live images of chromatin marked with fluorescent markers. Our theory identifies the time resolution of microscopy for a given spacing of markers, where the algorithm will track the polymer with high confidence, and we demonstrate the feasibility of our algorithm using synthetic data generated from numerical simulations. We then leverage experimental locus-tracking measurements as a basis for interpreting the strength of our modeling approach. Altogether, this study provides a computational approach founded on polymer physics to describe the dynamic configuration of biopolymers generated with increasingly sophisticated and high-resolution experimental tools.