Abstract
Chromosomes are not positioned randomly within a nucleus, but instead, they adopt preferred spatial conformations to facilitate necessary long-range gene–gene interactions and regulations. Thus, obtaining the 3D shape of chromosomes of a genome is critical for understanding how the genome folds, functions and how its genes interact and are regulated. Here, we describe a method to reconstruct preferred 3D structures of individual chromosomes of the human genome from chromosomal contact data generated by the Hi-C chromosome conformation capturing technique. A novel parameterized objective function was designed for modeling chromosome structures, which was optimized by a gradient descent method to generate chromosomal structural models that could satisfy as many intra-chromosomal contacts as possible. We applied the objective function and the corresponding optimization method to two Hi-C chromosomal data sets of both a healthy and a cancerous human B-cell to construct 3D models of individual chromosomes at resolutions of 1 MB and 200 KB, respectively. The parameters used with the method were calibrated according to an independent fluorescence in situ hybridization experimental data. The structural models generated by our method could satisfy a high percentage of contacts (pairs of loci in interaction) and non-contacts (pairs of loci not in interaction) and were compatible with the known two-compartment organization of human chromatin structures. Furthermore, structural models generated at different resolutions and from randomly permuted data sets were consistent.
Highlights
The 3D organization of a genome was found to play an important role in gene–gene interaction, gene regulation and genome methylation [1,2,3,4]
Because the standard TM-Score was originally designed to score protein structures with distance thresholds used for calculating the percentage of aligned residue–residue pairs that are too large to distinguish the difference between chromosomal models, we lowered its four thresholds from 4.0, 2.0, 1.0 and 0.5 to 2.0, 1.5, 1.0 and 0.5, respectively, to compute the average percentage of pairs of regions whose distance is below these thresholds after two chromosomal models are superimposed
We presented an optimization method to construct preferred 3D structural models for human chromosomes by directly satisfying the chromosomal contacts obtained from the Hi-C data sets, which is different from other distance-based chromosome model construction methods
Summary
The 3D organization of a genome was found to play an important role in gene–gene interaction, gene regulation and genome methylation [1,2,3,4]. It was shown that genes at long sequential genomic distances could functionally interact through physical spatial contacts [5], often leading to long-range gene regulation and collaboration. Owing to lack of experimental techniques of directly determining the 3D shape of a genome consisting of billions of nucleotides, little is known about the 3D organization of a genome and its largest discrete components—chromosomes. Chromosome conformation capture (3C)-based techniques have emerged as powerful tools for capturing physical interactions (e.g. spatial contacts) between pairs of chromosomal regions (e.g. loci) [6] on the same or two different chromosomes. An advanced 3C technique—Hi-C—has been developed to determine both intra- and inter-chromosomal contacts at a genome scale rather uniformly and unbiasedly [7], which provides crucial information necessary for studying and reconstructing the 3D shape of a chromosome or genome for the first time
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