Characterising the gene regulatory landscape of CD4+ T cells

Despite the high prevalence of immune-mediated diseases, the molecular mechanisms by which they arise and the influence of genetic variation in the predisposition to disease are not well understood. Immune susceptibility loci identified by genome wide association studies (GWAS) overlap with active regulatory elements in CD4+ T cells, and particularly in regulatory T cells (Tregs). CD4+ T cells are the orchestrators of the adaptive immune response and their dysfunction has been associated with immune-mediated disorders through uncontrolled activation and resistance to downregulation, which is usually mediated by Tregs. T cell activation requires the combination of T cell receptor (TCR) recognition of an antigen and CD28 co-stimulation. The role of CD28 co-stimulation requirement in the activation of different T cell subsets has been understudied. Here, I assessed the role of immune disease variants in modulating pathways underlying T cell activation and Treg function. For that, I activated CD4+ T cells using different intensities of CD28 and TCR signals, followed by genome-wide transcriptome and chromatin profiling of naive and memory cells. I observed that CD28 plays a critical role in the expression of genes involved in effector functions, cell cycle regulation in memory T cells and in disease susceptibility. I profiled the gene expression regulatory landscape in Tregs using a combination of genomic assays. Due to the scarce Treg numbers in peripheral blood I first optimised the ChIPmentation (ChM) sequencing protocol to profile H3K4me3 and H3K27ac histone modifications in Tregs. I combined it with chromatin accessibility and gene expression profiling in resting and stimulated Tregs from ten donors. I observed cases of alternative transcription, such as alternative splicing and promoter, induced by stimulation, which could be predicted by changes in the chromatin landscape. Finally, I assessed how genetic variability impacts the function of Tregs and how this can lead to autoimmunity. I carried a quantitative trait locus (QTL) mapping using RNA-seq, ATAC-seq, H3K4me3 and H3K27ac ChM-seq data from Tregs isolated from 100 individuals. Additionally, I processed publicly available data from naive T cells to distinguish the Treg specific effects from generic CD4+ T cell signals. I recapitulated known colocalisations between QTLs and immune GWAS loci, and identified previously unknown Treg specific colocalisations. My findings highlight the value of carrying QTL studies in rare immune cell types relevant to the disease