Abstract
Chromosome conformation capture (3C) techniques have revealed many fascinating insights into the spatial organization of genomes. 3C methods typically provide information about chromosomal contacts in a large population of cells, which makes it difficult to draw conclusions about the three-dimensional organization of genomes in individual cells. Recently it became possible to study single cells with Hi-C, a genome-wide 3C variant, demonstrating a high cell-to-cell variability of genome organization. In principle, restraint-based modeling should allow us to infer the 3D structure of chromosomes from single-cell contact data, but suffers from the sparsity and low resolution of chromosomal contacts. To address these challenges, we adapt the Bayesian Inferential Structure Determination (ISD) framework, originally developed for NMR structure determination of proteins, to infer statistical ensembles of chromosome structures from single-cell data. Using ISD, we are able to compute structural error bars and estimate model parameters, thereby eliminating potential bias imposed by ad hoc parameter choices. We apply and compare different models for representing the chromatin fiber and for incorporating singe-cell contact information. Finally, we extend our approach to the analysis of diploid chromosome data.
Highlights
The rapid development of chromosome conformation capture techniques such as 3C [1], chromosome conformation capture-on-chip [2], the closely related circular chromosome conformation capture [3] and 5C [4] culminated in a genome-wide variant, HiC [5], which provides all-against-all contact information
We show that Markov chain Monte Carlo (MCMC) sampling allows us to compute diverse ensembles of coarse-grained chromosome conformations that reflect the sparsity of single-cell Hi-C contacts
We model the chromatin fiber with a beads-on-a-string representation
Summary
The rapid development of chromosome conformation capture techniques such as 3C [1], chromosome conformation capture-on-chip [2], the closely related circular chromosome conformation capture [3] (both named 4C) and 5C [4] culminated in a genome-wide variant, HiC [5], which provides all-against-all contact information. The single-cell Hi-C approach provided only very sparse contact data, the structural information was sufficient to reveal unprecedented insights into genome organization including a high cell-tocell variability of interdomain and trans-chromosomal contacts as well as the persistence of TADs across single cells. Many structural insights such as the existence of TADs or the scaling behavior of contact probabilities with genomic distance can be found by analyzing genome-wide contact matrices. To compute representative 3D structures of genomes, various approaches have been explored
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