Linking disease-associated variants to target genes in 17 primary haematopoietic cell types identifies novel type 1 diabetes candidate genes

The majority of disease associated variants in type 1 diabetes (T1D) are located in non-coding DNA and are enriched in areas of open or active chromatin. Functional annotation of the genome has revolutionised our ability to understand the “grammar” of the non-coding genome and integration of such data with GWAS summary statistics showed strong enrichment of T1D-associated SNPs in enhancers in lymphocytes, thymus tissue and haematopoietic stem cells. The practice of nominating candidacy to the closest or most biologically relevant candidate gene in a disease-associated region ignores the growing evidence that enhancers can act over long distances and upon multiple genes. 

We used promoter capture Hi-C (PCHi-C), a method that can indicate which regions physically interact with gene promoters genome-wide, in combination with total RNA-sequencing, ChIP-seq, Immunochip and GWAS summary statistics to explore principles underlying induction of gene expression and to prioritise genes in 17 primary human haematopoietic cell types including activated CD4⁺ T cells.

Activation of CD4⁺ T cells induced changes in gene transcription that correlated with acquisition of promoter interacting regions (PIRs) and expression of enhancer RNAs and revealed the complexity underlying gene regulation where, for example, enhancers can interact with multiple gene promoters, “skip” multiple gene promoters and switch target promoters upon activation or differentiation. Using blockshifter, a method developed to examine the enrichment of GWAS summary statistics between tissue specific PIRs, we found T1D associated SNPs were most strongly enriched in activated CD4⁺ T cells when compared to non-activated CD4⁺ T cells and two non-lymphoid  haematopoietic cell types. Integration of PCHi-C data from 17 different blood cell types using a novel Bayesian method and a conservative statistical threshold identified 97 novel protein coding and 39 non-coding transcripts in 29 of the 58 T1D regions, 4 of which had no previously nominated candidate genes.