Interphase Human Chromosome Exhibits Out of Equilibrium Glassy Dynamics

Abstract

The structural organization of the condensed chromosomes, which hold the secrets to gene regulation, is being revealed using chromosome conformation capture experiments and super resolution imaging techniques. To determine the structure and dynamics of human interphase chromosomes, we created the Chromosome Copolymer Model (CCM) by representing the chromosomes as a self-avoiding polymer with two loci types corresponding to euchromatin and heterochromatin. Using advanced clustering algorithms we establish quantitatively that the simulated contact maps for chromosomes 5 and 10 and those inferred from Hi-C experiments are in agreement. Ward Linkage Matrix (WLM), constructed from spatial distance information, shows that the spatial organization of the Topologically Associating Domains (TADs) and compartments predicted from simulation are in agreement with inferred WLM computed using data from super resolution microscopy experiments. Glassy dynamics is manifested in the stretched exponential relaxation of the structure factor, a pronounced peak in the fourth order susceptibility accounting for the fluctuations in F (k, t), and caging in the mean square displacement of individual loci, ∆ i (t) ∼ t α with 0 < α < 1. Remarkably, the distribution of α, is extremely broad suggestive of highly heterogeneous dynamics. Chromosome folding is hierarchical involving the formation of chromosome droplets (CDs) on short genomic scale followed by coalescence of the CDs, reminiscent of Ostwald ripening. We propose that glassy landscapes for the folded chromosomes might provide a balance between stability and biological functions.

Conformational Heterogeneity in Human Interphase Chromosome Organization Reconciles the FISH and Hi-C Paradox

“…By assuming that the Redner-des Cloizeaux form for P (r| R mn ) also holds for chromosomes (see Supplementary Equation 1 for details), we find that g = 1 and δ = 5/4 in Supplementary Equation 1. These parameters were previously extracted using experimental data [8], and the Chromosome Copolymer Model (CCM) for chromosomes [24]. The value of g is inferred from the scaling relationship between mean spatial distance R and contact probability P , P ∼ R 3+g .…”

“…However, how to utilize the data reported in these experiments to enhance our understanding of 3D genome structural heterogeneity has not been unexplored. One approach is to create an appropriate polymer model based on Hi-C and imaging data, which would readily allow us to probe the structural variability using simulations [23][24][25][26]. Indeed, it has been shown, using Hi-C and FISH data as well simulations [26], that if the conformation of the chromatin fiber is taken to be homogeneous then trends observed in the FISH data could not be predicted.…”

Single particle trajectory statistic to reconstruct chromatin organization and dynamics

“…LAMMPS could also be used to simulate realizations of many types of molecular dynamics scenarios, such as blood flow in capillaries. LAMMPS was used in [72,59,14] to study the folding landscape of chromatin calibrated from CC contact data.…”

Characterizing chromatin folding coordinate and landscape with deep learning

“…Encouraged by its accuracy in reproducing the microscopic energy of a synthetic system, we applied VAE over the WT and the cohesin-depleted imaging data separately to derive the corresponding chromatin energy landscapes. We note that these landscapes are deemed effective as chromatin exhibits slow dynamics (45,58,59) and is subject to perturbations driven by ATP-powered molecular motors (60). Nevertheless, provided that they can reproduce the corresponding steady-state distributions, effective landscapes are powerful concepts for characterizing nonequilibrium systems (61,62).…”