Decoding mutational hotspots in human disease through the gene modules governing thymic regulatory T cells.

Computational strategies to extract meaningful biological information from multiomics data are in great demand for effective clinical use, particularly in complex immune-mediated disorders. Regulatory T cells (Tregs) are essential for immune homeostasis and self-tolerance, controlling inflammatory and autoimmune processes in many diseases with a multigenic basis. Here, we quantify the Transcription Factor (TF) differential occupancy landscape to uncover the Gene Regulatory Modules governing lineage-committed Tregs in the human thymus, and show that it can be used as a tool to prioritise variants in complex diseases. We combined RNA-seq and ATAC-seq and generated a matrix of differential TF binding to genes differentially expressed in Tregs, in contrast to their counterpart conventional CD4 single-positive thymocytes. The gene loci of both established and novel genetic interactions uncovered by the Gene Regulatory Modules were significantly enriched in rare variants carried by patients with common variable immunodeficiency, here used as a model of polygenic-based disease with severe inflammatory and autoimmune manifestations. The Gene Regulatory Modules controlling the Treg signature can, therefore, be a valuable resource for variant classification, and to uncover new therapeutic targets. Overall, our strategy can also be applied in other biological processes of interest to decipher mutational hotspots in individual genomes.