Non-coding genetic variants in human disease

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Medical genetics is being transformed by next-generation sequencing (NGS) technologies that enable the investigation of the entire genome. So far, the interpretation of disease-related variation has focused on protein coding DNA. This focus on just 1.5% of the genome, i.e. the exome, has been exceptionally successful. However in over 40% of Mendelian phenotypes, no disease-causing coding variants can be found. I propose that this could be due to the fact that the non-coding sequence has been largely ignored despite the fact that most nucleotides and deleterious variants are non-coding. Recent studies including my own work suggest that non-coding mutations contribute to a substantial number of human disease phenotypes and should thus be taken into account for the medical interpretation of genetic variants. My goal in this research project is to achieve a better understanding of genetic variants found in non-coding cis-regulatory elements and their role in human disease.There are several challenges that currently hamper the medical interpretation of the non-coding DNA. First, the regulatory code of the non-coding genome is currently poorly understood. Second, there is dearth of gold standard datasets for non-coding variants. Third, the sheer number of non-coding variants in each individual and generation makes classical functional work-up strategies impossible. Fourth, the topologically associating domain (TAD) architecture of the genome is an important aspect of gene regulation. Structural variations have the potential to alter TAD boundaries: This allows enhancers from neighbouring domains to ectopically activate genes causing mis-expression and disease. This enhancer adoption disease mechanism has largely been ignored by human geneticists so far. To address these challenges, I will apply three experimental approaches: Aim 1: I will use massively parallel reporter assays (MPRA) for random saturation mutagenesis of 12 selected disease associated cis-regulatory elements to investigate the effects of tens-of-thousands of non-coding regulatory mutations in cell lines. Thereby I aim to create a large standardized dataset of functionally validated non-coding variants that will help to develop interpretive schemes for non-coding variants. Aim 2: I aim to develop a next generation functional test to evaluate the functional outcome of all de novo non-coding variants from two whole genome sequencing studies of patients with severe intellectual disability and congenital limb malformation. I plan to synthesize all de novo variants and the corresponding wild type sequences and test them in a MPRA in cells. Aim 3: I aim to evaluate enhancer adoption as a human disease mechanism by multiplexed deletions of topologically associating domain boundaries by CRISPR/Cas9 genome editing in cells. These findings will directly impact future WGS studies and help to identify non-coding genetic variants in cancer and congenital disease.