Computational methods to identify neo-TADs and enhancer-hijacking in rearranged genomes

Structural variations (SVs), including inversions, deletions, duplications, and translocations, are prevalent in cancer and other diseases. It has been shown recently that SVs can disrupt the 3D genome structure and directly contribute to pathogenesis. For example, in T-cell acute lymphoblastic leukemia, deletion of a TAD boundary disrupted the insulated chromatin domains and activates proto-oncogenes. Two main consequences of SVs on 3D genome structures are the formations of “neo-TADs” and “enhancer-hijacking.” Neo-TADs refers to the scenarios when a SV event leads to the formation new chromatin domains, particularly in the cancer genomes, while enhancer-hijacking means when a SV event rearranges the cancer genome and juxtaposes an enhancer to the proximity of an oncogene. 3D genome organization has been shown to be essential in proper gene regulation and cell fate. Previous studies have shown that mammalian genomes are organized in megabase pair topologically associating domains (TADs). Genes located within the same TADs tend to be co-regulated and the functions of enhancers are usually restrained by TADs boundaries. Both genetic and epigenetic alteration of TADs boundaries can lead to gene misregulation and severe human diseases. To study the 3D genome organization, Hi-C is by far the most popular method, as it can measure chromatin interactions genome-wide. It facilitates the original discovery of TADs and many enhancer-promoter interactions. Recently, Hi-C has been applied to tens of cancer cell lines and a small number of patient samples. However, to our knowledge, no methods exist that can identify neo-TADs or enhancer-hijacking events using the Hi-C interaction data in cancer cells. Therefore, in this study, we propose the following aims: 1) Develop computational method to detect neo-TADs in cancer genome; 2) Develop computational method to detect chromatin interactions in cancer genomes; 3) Perform validation experiments for the hijacked enhancers by CRISPR/Cas9 and investigate their effect on target genes and cell phenotypes.