A polymer model for the quantitative reconstruction of 3d chromosome architecture from Hi-C and GAM data

TL;DR

This paper introduces a novel polymer-based method for reconstructing 3D chromosome architecture from Hi-C and GAM data, providing high accuracy contact predictions and insights into chromatin dynamics.

Contribution

It presents an exact Gaussian polymer model that directly uses experimental contact probabilities, improving 3D genome reconstruction accuracy over previous methods.

Findings

Reproduces experimental contact maps with high accuracy

Provides a thermodynamic equilibrium expression for contact probabilities

Enables simulation of chromatin dynamics using Brownian Dynamics

Abstract

It is widely believed that the folding of the chromosome in the nucleus has a major effect on genetic expression. For example co-regulated genes in several species have been shown to colocalize in space despite being far away on the DNA sequence. In this manuscript, we present a new method to model the three-dimensional structure of the chromosome in live cells, based on DNA-DNA interactions measured in high-throughput chromosome conformation capture experiments (Hi-C) and genome architecture mapping experiments (GAM). Our approach incorporates a polymer model, and directly uses the contact probabilities measured in Hi-C and GAM experiments rather than estimates of average distances between genomic loci. Specifically, we model the chromosome as a Gaussian polymer with harmonic interactions and extract the coupling coefficients best reproducing the experimental contact probabilities. In contrast to existing methods, we give an exact expression of the contact probabilities at thermodynamic equilibrium. The Gaussian effective model (GEM) reconstructed with our method reproduces experimental contacts with high accuracy. We also show how Brownian Dynamics simulations of our reconstructed GEM can be used to study chromatin organization, and possibly give some clue about its dynamics.