USING FUNCTIONAL GENOMICS TO LINK GENOMIC VARIANTS TO FUNCTION IN COMPLEX DISEASES

Abstract

Many traits and disorders in the human population are a result of the interaction between the environment and a complex underlying genetic mechanism. In contrast to Mendelian disorders for which the cause of the disease can be narrowed down to a single or a few genetic mutations, complex diseases involve a large number of common genetic variants, each of which have very low penetrance. Most of these variants are single nucleotide polymorphisms (SNPs) and can be identified by running large scale genome-wide association studies (GWAS) comparing a population of affected individuals with a healthy control group. Unfortunately, the identification of these associated variants has frequently not contributed directly to the better understanding of disease mechanisms. Most of them are thought to affect the regulation of genes rather than the protein coding sequence itself, which is challenging to study. These regulatory regions containing disease risk variants are highly cell type and state specific and can regulate genes located very far away, likely thanks to chromatin interaction mechanisms, which obscures their target genes. The aim in the post-GWAS era is to explain the underlying mechanisms by which these genetic variants affect the likelihood of developing a complex disorder. In this PhD project I have used a combination of functional genomics methods to study these genetic variants and infer plausible genes that could mediate increased disease risk. First, I have developed a novel method to analyse chromatin conformation (HiChIP) data, identifying the peaks that represent enrichment in the immunoprecipitated protein. Next, I applied this method and other available methods to analyse data from cell lines and identified the genes that were linked to GWAS loci associated with several dermatological conditions. Focusing on psoriasis I highlighted 4 loci for which I identified novel candidate genes that might affect disease risk. Finally, I have used these functional genomics methods on data generated from cells isolated from patients, first on Systemic Sclerosis and finally on Psoriatic Arthritis patients. In Systemic Sclerosis I have linked genes to these GWAS loci in a cell type specific manner using data generated using an improved promoter Capture Hi-C protocol, for which I have optimized the analysis in my lab. From the cells isolated from Psoriatic Arthritis patients, we have instead opted for high resolution Hi-C, for which we have generated the largest chromatin conformation dataset to date for T cells, which are the most relevant cell types for autoimmune disorders such as Psoriatic Arthritis. Carrying out a preliminary analysis on this dataset, I found strong correlation between gene expression and chromatin loops and show how chromatin conformation is significantly altered in T cells isolated from synovial fluid, highlighting the importance of using primary cells in the correct activation state when doing studies on GWAS loci. Overall, the studies presented here have integrated our knowledge of functional genomics to advance the understanding of the mechanisms behind GWAS loci, which in turn have linked novel genes or confirmed previous associations to a variety of autoimmune conditions.

Date of Award	31 Dec 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Magnus Rattray (Supervisor) & Gisela Orozco (Supervisor)