Seeing the forest through the trees: Identifying functional interactions from Hi-C

Eukaryotic genomes are highly organised within the nucleus of a cell, allowing widely dispersed regulatory elements such as enhancers to interact with gene promoters through physical contacts in three-dimensional space. Recent chromosome conformation capture methodologies such as Hi-C have enabled the analysis of interacting regions of the genome providing a valuable insight into the three-dimensional organisation of the chromatin in the nucleus, including chromosome compartmentalisation and gene expression. Complicating the analysis of Hi-C data however is the massive amount of identified interactions, many of which do not directly drive gene function, thus hindering the identification of potentially biologically functional 3D interactions. In this review, we collate and examine the downstream analysis of Hi-C data with particular focus on methods that identify significant functional interactions. We classify three groups of approaches; structurally-associated domain discovery methods e.g. topologically-associated domains and compartments, detection of statistically significant interactions via background models, and the use of epigenomic data integration to identify functional interactions. Careful use of these three approaches is crucial to successfully identifying functional interactions within the genome.