GrapHi-C: Graph-based visualization of Hi-C Datasets

Abstract

BackgroundHi-C is a proximity-based ligation reaction used to detect regions of the genome that are close in 3D space (or \"interacting\"). Typically, results from Hi-C experiments (whole-genome contact maps) are visualized as heatmaps or Circos plots. While informative, these visualizations do not intuitively represent the complex organization and folding of the genome in 3D space, making the interpretation of the underlying 3D genomic organization difficult. Our objective was to utilize existing tools to generate a graph-based representation of a whole-genome contact map that leads to a more intuitive visualization.\n\nMethodologyWhole-genome contact maps were converted into graphs where each vertex represented a genomic region and each edge represented a detected or known interaction between two vertices. Three types of interactions were represented in the graph: linear, intra-chromosomal (cis-), and inter-chromosomal (trans-) interactions. Each edge had an associated weight related to the linear distance (Hi-C experimental resolution) or the associated interaction frequency from the contact map. Graphs were generated based on this representation scheme for whole-genome contact maps from a fission yeast dataset where yeast mutants were used to identify specific principles influencing genome organization (GEO accession: GSE56849). Graphs were visualized in Cytoscape with an edge-weighted spring embedded layout where vertices and linear interaction edges were coloured according to their corresponding chromosome.\n\nResultsThe graph-based visualizations (compared to the equivalent heatmaps) more intuitively represented the effects of the rad21 mutant on genome organization. Specifically, the graph based visualizations clearly highlighted the loss of structural globules and a greater intermingling of chromosomes in the mutant strain when compared to the wild-type. The graph-based representation and visualization protocol developed here will aid in understanding the complex organization and folding of the genome.