Abstract
Genome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T cells over 24 h, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes in gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.
Highlights
Genome-wide association studies have identified genetic variation contributing to complex disease risk
94% occurred within the same chromosome and 57% were within 5 Mb of promoters
It is well established that gene expression changes with time after stimulation in CD4+ T cells[4] and we find similar changes to previous studies, with a range of dynamic expression profiles corresponding to genes activated early, intermediate or late, or repressed (Supplementary Fig. 1e–i)
Summary
Genome-wide association studies have identified genetic variation contributing to complex disease risk. It is well established that the vast majority of SNPs implicated in common complex diseases from genome-wide association studies (GWAS) are found outside protein coding exons and are enriched in both cell type and stimulatory dependent regulatory regions[1,2]. The task of assigning these regulatory enhancers to their target genes is non-trivial They can act over long distances, often ‘skipping’ genes[3]. We have combined simultaneously measured ATAC-seq, Hi-C, Capture Hi-C (CHi-C) and nuclear RNA-seq data in stimulated primary CD4+ T cells (Fig. 1), to define the complex relationship between DNA activity, interactions and gene expression. We go on to incorporate fine-mapped associated variants from RA, and validate long range interactions with CRISPR/Cas[9], to assign SNPs, genes and direction of effect to GWAS loci for this T cell-driven disease
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
