Project description:Background: Functional enrichment analysis of genome-wide association study (GWAS)-summary statistics has suggested that immune cell-types, and especially CD4+ T-cells, play an important role in asthma pathogenesis. Despite this, CD4+ T-cells are under-represented in asthma transcriptome studies. Objective: To identify differences in gene expression between asthmatics and healthy controls in CD4+ T-cells. Methods: CD4+ T-cells were isolated within 2 hours from collection from peripheral blood from people with well-established asthma (n=33) and healthy controls (n=12). 3'-RNA-Seq was used to generate gene expression data. Weighted Gene Co-expression Network Analysis (WGCNA) was used to identify sets of co-expressed genes (modules). The asthma-associated modules were tested for enrichment of GWAS-identified asthma genes and gene ontology (GO) biological processes. For the genes in the asthma-associated modules, integration of eQTL and GWAS summary statistics (colocalisation), and protein-protein interaction (PPI) data was used to identify master regulators. Results: After quality control, 43 samples were available for the analysis. WGCNA identified three modules associated with asthma, which are strongly enriched for GWAS-identified asthma genes, antigen processing/presentation and immune response to viral infections. Colocalisation analysis of eQTL and GWAS summary statistics, together with PPI data, identified PTPRC as a master regulator of asthma gene-expression profiles in CD4+ T-cells. Conclusion: Unstimulated CD4+ T-cells from peripheral blood from asthmatics have different expression profiles, compared to healthy controls, for sets of genes involved in immune response to viral infections and antigen processing/presentation . Integration of genetic and protein-protein interaction data identified PTPRC as a master regulator of genes in asthma.
Project description:Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. In this study, we obtained genome-wide RNA-Seq and ChIP-Seq (for H3K4me3 and H3K27ac histone modifications) data in the human liver. We mapped quantitative trait loci (QTLs) of gene expression levels and histone modification states. We integrated our findings with summary statistics of genome-wide association studies (GWAS) and identified candidate genes, gene regulatory regions, and variants in GWAS loci.
