Bioinformatics Techniques to Analyze Dynamic Changes of 3D Genome

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Project Summary Three-dimensional (3D) folding of the genome plays fundamental roles in the regulation of transcription, replication, DNA repair and many other biological processes. Facilitated by Hi-C and related techniques, it is becoming clear that the eukaryotic genome folds at multiple genomic scales to form different types of 3D architecture, including topologically associated domains (TADs) and stripes. Different physical patterns of change may happen to a type of 3D architecture, e.g., a TAD may show change of overall connectivity, or split into smaller TADs. Whereas the existence and functional importance of the genome’s 3D architecture is increasingly recognized, analyzing its dynamic changes is currently a major challenge to biologists. The community urgently needs novel bioinformatics techniques to define potential physical patterns of change for each type of 3D architecture, to systematically detect all changes in the genome, and to statistically determine the significance of each change. Our preliminary data strongly suggest that two physical patterns of change to the genome’s 3D architecture -- TAD splittings and stripe strengthenings -- regulate cell identity transitions. Accordingly, we propose to develop TADsplit and StripeDiff, two bioinformatics toolkits to systematically define these and additionally physical patterns of change to TADs and stripes between samples. As a proof of principle, we will utilize the new techniques to investigate 3D genome alterations during endothelial-to- mesenchymal transition (EndMT), a cell identity transition that plays critical roles in both normal development and many prevalent cardiovascular diseases. We will illustrate new mechanisms by which transcription factors regulate genome’s 3D architectures to oppose EndMT. These investigations have the potential to better guide the treatment of many diseases in which EndMT plays important roles. The novel bioinformatics techniques in TADsplit and StripeDiff will enable researchers to investigate 3D genome changes in diverse biological models of development and diseases.