Prediction of the 4D Chromosome Structure From Time-Series Hi-C Data

Abstract

Chromatin conformation plays an important role in a variety of genomic processes. Hi-C Data is frequently used to analyse structural features of chromatin such as AB compartments, topologically associated domains, and 3D structural models. Recently the genomics community has displayed growing interest in chromatin dynamics over time. Here we present 4DMax, a novel method which uses time-series Hi-C data to predict dynamic chromosome conformation. Using both synthetic data and real time-series Hi-C data from processes such as induced pluripotent stem cell reprogramming and cardiomyocyte differentiation, we construct fluid four dimensional models of individual chromosomes. These predicted 4D models effectively interpolate chromatin position across time, permitting prediction of unknown Hi-C contact maps at intermittent time points. Our results demonstrate that 4DMax correctly recovers higher order features of chromatin such as AB compartments and topologically associated domains, even at time points where Hi-C data is not made available to the algorithm. Use of 4DMax may alleviate the cost of expensive Hi-C experiments by interpolating intermediary timepoints while also providing valuable visualization of dynamic chromatin changes.