Visualizing Interchromosomal Interactions at Sub-Megabase Resolution Using Network Clustering Coefficients

Specific interchromosomal interactions indicate direct and nonrandom physical associations between pairs of genome positions on two different chromosomes. These contact interactions can be direct communication between non-homologous chromosomes and can enable coordinated activities. It is useful to annotate these complex contact interaction patterns and render them to a property associated with a single genome position, both for a clean visualization of the patterns and for facilitating the comparison with linear genomic annotations and underpinning biological functions. We utilize abstract graphs to characterize interchromosomal interaction, as network analysis may succinctly summarize complex interaction structures. We built a graph representation of cross-chromosomal contact interactions derived from Hi-C data and implemented three network-based annotations which consistently indicate the interchromosomal interaction strength associated with specific genomic positions. Equipped with these metrics, we further investigate whether a chromosome relies on shared hot spots to communicate with other chromosomes. We found that half of the strong interaction positions of chromosome 19 are shared for interacting with chromosomes 17 and 22. We further found that lamina-associated domains (LADs) participate in fewer interchromosomal contacts. Overall, the network-based annotation framework reveals distinct chromosome regulation patches and provides insight into how chromosomes associate with each other and organize with respect to the nuclear envelope.