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Gene expression regulation is a set of critical biological processes that give rise to the diversity of cell types across tissues and development stages. Noncoding regions of the genome (intergenic + intronic, >98% of genome) play an important role in these processes, with noncoding genetic variation quantitatively affecting transcriptional activity, splicing of pre-mRNA, and localization, stability, and translational control of mRNA transcripts. Previous genetic studies of human disease have implicated numerous common noncoding loci with small but significant effect in common conditions. Recently, we and others have reported evidence supporting a role of rare noncoding variants with larger effect in early onset conditions such as birth defects and neurodevelopmental disorders. These early onset conditions are quite common in aggregate, affecting over 3% of young children. A better understanding of the functional impact of rare regulatory noncoding variants will enable novel genetic discovery, give insights of disease mechanisms, and ultimately improve diagnosis, treatment, and clinical care. In this thesis dissertation, I describe three related projects. First, we used a combinatorial multi-testing framework to find excess burden of noncoding de novo mutations in congenital heart disease (impacting both transcriptional and post-transcriptional regulatory stages). This finding was central to the rest of my work, motivating the development of new computational approaches to predict genetic effect of noncoding variants through the lens of post-transcriptional regulation. Second, we used convolutional neural networks to model and understand sequence specific RBP binding processes. Finally, we designed a graphical neural network model capable of integrating cause and consequence to predict genetic effect of rare noncoding variants. In summary, we developed new machine learning methods to analyze multimodal human genome sequencing data, uncover deeper insights into post-transcriptional gene regulatory processes, and advance genomic medicine.

A genetic etiology is identified for one-third of patients with congenital heart disease (CHD), with 8% of cases attributable to coding de novo variants (DNVs). To assess the contribution of noncoding DNVs to CHD, we compared genome sequences from 749 CHD probands and their parents with those from 1,611 unaffected trios. Neural network prediction of noncoding DNV transcriptional impact identified a burden of DNVs in individuals with CHD (n = 2,238 DNVs) compared to controls (n = 4,177; P = 8.7 × 10-4). Independent analyses of enhancers showed an excess of DNVs in associated genes (27 genes versus 3.7 expected, P = 1 × 10-5). We observed significant overlap between these transcription-based approaches (odds ratio (OR) = 2.5, 95% confidence interval (CI) 1.1-5.0, P = 5.4 × 10-3). CHD DNVs altered transcription levels in 5 of 31 enhancers assayed. Finally, we observed a DNV burden in RNA-binding-protein regulatory sites (OR = 1.13, 95% CI 1.1-1.2, P = 8.8 × 10-5). Our findings demonstrate an enrichment of potentially disruptive regulatory noncoding DNVs in a fraction of CHD at least as high as that observed for damaging coding DNVs.

Congenital diaphragmatic hernia (CDH) is a severe birth defect that is often accompanied by other congenital anomalies. Previous exome sequencing studies for CDH have supported a role of de novo damaging variants but did not identify any recurrently mutated genes. To investigate further the genetics of CDH, we analyzed de novo coding variants in 362 proband-parent trios including 271 new trios reported in this study. We identified four unrelated individuals with damaging de novo variants in MYRF (P = 5.3x10-8), including one likely gene-disrupting (LGD) and three deleterious missense (D-mis) variants. Eight additional individuals with de novo LGD or missense variants were identified from our other genetic studies or from the literature. Common phenotypes of MYRF de novo variant carriers include CDH, congenital heart disease and genitourinary abnormalities, suggesting that it represents a novel syndrome. MYRF is a membrane associated transcriptional factor highly expressed in developing diaphragm and is depleted of LGD variants in the general population. All de novo missense variants aggregated in two functional protein domains. Analyzing the transcriptome of patient-derived diaphragm fibroblast cells suggest that disease associated variants abolish the transcription factor activity. Furthermore, we showed that the remaining genes with damaging variants in CDH significantly overlap with genes implicated in other developmental disorders. Gene expression patterns and patient phenotypes support pleiotropic effects of damaging variants in these genes on CDH and other developmental disorders. Finally, functional enrichment analysis implicates the disruption of regulation of gene expression, kinase activities, intra-cellular signaling, and cytoskeleton organization as pathogenic mechanisms in CDH.