A Novel Statistical Framework to Detect Complex 3D Genome Organisation Patterns into Topologically Associated Domains

Topologically associated domains (TADs) are highly compacted regions of DNA that are suggested to be involved in proper gene regulation and cellular functioning. TADs maintain long-range interactions between distal enhancers and target genes, as well as restrict enhancers contacting genes that are not their target and, consequently, block their inappropriate regulation by these enhancers. The widely used TAD calling tools either restrict TAD borders to be allocated in a “head-to-tail” manner or allow hierarchical TAD folding to be detected. We propose a R-based TAD calling tool that detects start and end TAD border positions separately, so the partial overlapping of TADs as well as large gaps between TADs are also allowed. Using the ratio between the average upstream and downstream Hi-C interaction frequencies, our method detects where the difference between inside-TAD and outside TAD area within the Hi-C matrix is most significant. The novel TAD allocation combined with various genomics data reveals the interplay between architectural proteins and active transcription in the establishment of the TAD border insulation strength and insulation imbalances between neighbouring TADs.