Systematic mapping and discovery of immune system's long-distance regulatory networks in severe COVID-19

The COVID-19 pandemic, as a result of SARS-CoV-2 infection, has affected most countries with more than 6 million related deaths worldwide. Despite significant progress in understanding the pathophysiology of COVID-19 and the determinants of its severity and susceptibility, there are still gaps in understanding its wider regulatory networks. These involve both genetic and protein elements, often located significant distances away from target genes. Identification of such distal elements within those networks remains a challenge. I aim to use high-throughput CRISPR-based methods such as CRISPRi screens to characterise the large (~500kb) regions of DNA around key loci potentially involved in COVID-19 severity. I will also apply machine learning and multi-omic approaches to the existing large-scale datasets of COVID-19 patients to identify immune-related loci and disease-relevant non-coding regions, as well as integrate the experimental data generated with CRISPR screens. Characterisation of distal enhancers, promoters, and their connections on a genome scale for clinically significant loci may help to identify new pathways and therapeutic targets to alleviate the burden of infectious disease, autoimmunity and improve cancer immunotherapy.