Deciphering mechanisms of gene regulation through novel strategies for mapping genome architecture

Abstract

The regulation of gene expression plays a crucial role in development and disease. Regulation at the level of transcription is intimately linked with the positions of genes within the nucleus, both in terms of their association with structural components such as the nuclear lamina and in terms of their proximity to genomic elements such as enhancers or other genes. Methods based on Chromosome Conformation Capture (3C) have begun to disentangle the complicated relationship between chromatin folding and gene expression. However, 3C-based techniques have important limitations that restrict their ability to address important biological questions. Crucially, they struggle to detect interactions involving three or more genomic features because they rely on ligation of DNA fragment ends. To address these limitations, I implemented and optimized Genome Architecture Mapping (GAM), a ligation-free approach for determining genome topology. GAM infers the spatial proximity between genomic elements by measuring their co-segregation in thin nuclear slices, and places no upper limit on the number of regions that can be detected in a simultaneous interaction. I apply GAM to mouse embryonic stem cells and develop a computational pipeline to analyse the resulting dataset. GAM independently verifies key features of chromosome folding identified by 3C-based methods, including topologically associating domains (TADs). Using a statistical model, we find many non-random interactions spanning tens of megabases, which preferentially involve interactions between active genes and enhancers, between pairs of active genes and between pairs of enhancers at 30 kb resolution. We also explore simultaneous, three-way contacts between TADs and identify super-enhancers and highly-transcribed TADs as the most likely to interact at higher multiplicity. Strikingly, we uncover an antagonistic relationship between lamina association and TAD triplet formation. Finally, we show that GAM can be used to measure chromatin compaction and radial positioning.