Exploring the three-dimensional organization of genomes: interpreting chromatin interaction data

Mining increasingly comprehensive chromatin interaction maps for chromosomal domains and complete genomes requires novel computational methods and modelling tools.Looping interactions between specific genomic elements — for example, gene promoters and regulatory elements — can be identified from chromatin interaction data by detecting interaction frequencies that are significantly higher than empirically estimated background levels. Looping interactions appear to be very abundant: most promoters interact with several other genomic elements.Statistical analysis of Hi-C data identifies multiple scales of domain organization: larger (1–10 Mb) chromosomal compartments and smaller (<1 Mb) topologically associating domains.Restraint-based modelling provides experiment-based models of genomes and genomic domains. Such models can be used as a starting point for targeted structure–function analyses.Polymer simulations provide insights into the global chromatin organization that are consistent with statistical features of the interaction data, suggesting physical principles of chromatin folding.