Fine-mapping variants and genes that contribute to celiac disease

Complex diseases like type-1 diabetes, multiple sclerosis, and celiac disease (CeD) are difficult to unravel from a genetic perspective because they are caused by many mutations (DNA variants) that can be present in many different combinations. This is further complicated by the fact that over 95% of these variants are located in non-coding DNA, making it difficult to identify which genes they affect. Hence, in this thesis we applied cutting-edge, high-throughput fine-mapping methods to identify the variants, genes, non-coding regulatory elements, and cell states that contribute to CeD. We developed the high-throughput method Survey of Regulatory Elements and SNPs (SuRE-SNP) that tests over 400 million plasmids (small circular DNA of interest) in multiple CeD-associated cell-types to identify which non-coding CeD-associated locations and variants have gene regulatory potential. SuRE-SNP identified hundreds of non-coding regulatory elements in epithelial cells, of which three contain CeD-associated variants that we validated to strongly alter their regulatory potential. In a second fine-mapping project, we explored the binding of STAT proteins to DNA in CD8+ intraepithelial lymphocytes (IELs) under CeD-specific stimulations. We identified a possible central regulatory role for STATs in CD8+ IELs during CeD-specific stimulations. Moreover, we identified a possible role for T-cell stimulation in cytotoxic activation of CD8+ IELs. A total of 73 CeD-associated genes that are regulated by STATs and play a role in the activation of CD8+ IELs were prioritized, including the RGS1 gene whose gene expression can be disrupted by a STAT-binding CeD-associated variant

Balanced chromosomal rearrangements offer insights into coding and noncoding genomic features associated with developmental disorders

Balanced chromosomal rearrangements (BCRs), including inversions, translocations, and insertions, reorganize large sections of the genome and contribute substantial risk for developmental disorders (DDs). However, the rarity and lack of systematic screening for BCRs in the population has precluded unbiased analyses of the genomic features and mechanisms associated with risk for DDs versus normal developmental outcomes. Here, we sequenced and analyzed 1,420 BCR breakpoints across 710 individuals, including 406 DD cases and the first large-scale collection of 304 control BCR carriers. We found that BCRs were not more likely to disrupt genes in DD cases than controls, but were seven-fold more likely to disrupt genes associated with dominant DDs (21.3% of cases vs. 3.4% of controls; P = 1.60×10$^{−12}$). Moreover, BCRs that did not disrupt a known DD gene were significantly enriched for breakpoints that altered topologically associated domains (TADs) containing dominant DD genes in cases compared to controls (odds ratio [OR] = 1.43, P = 0.036). We discovered six TADs enriched for noncoding BCRs (false discovery rate < 0.1) that contained known DD genes (MEF2C, FOXG1, SOX9, BCL11A, BCL11B, and SATB2) and represent candidate pathogenic long-range positional effect (LRPE) loci. These six TADs were collectively disrupted in 7.4% of the DD cohort. Phased Hi-C analyses of five cases with noncoding BCR breakpoints localized to one of these putative LRPEs, the 5q14.3 TAD encompassing MEF2C, confirmed extensive disruption to local 3D chromatin structures and reduced frequency of contact between the MEF2C promoter and annotated enhancers. We further identified six genomic features enriched in TADs preferentially disrupted by noncoding BCRs in DD cases versus controls and used these features to build a model to predict TADs at risk for LRPEs across the genome. These results emphasize the potential impact of noncoding structural variants to cause LRPEs in unsolved DD cases, as well as the complex interaction of features associated with predicting three-dimensional chromatin structures intolerant to disruption

Supplementary tables from A practical view of fine-mapping and gene prioritization in the post-genome-wide association study era

Tables containing a description of current functional and computational fine-mapping tools and database