278P Mapping human skeletal muscle enhancers to increase rates of genetic diagnosis

Abstract

Despite the identification of almost 600 disease genes for neuromuscular disorders, only 30-50% of affected individuals receive a genetic diagnosis following diagnostic screening via targeted gene panels or clinical exomes. For a subset of those patients who do not receive a genetic diagnosis, the disease causing variant may be located in the 98% of the human genome that is non-coding. Approximately 20-40% of the non-coding genome has a regulatory function, dictating when in development, in which tissues, and at what level our coding genes are expressed. Genetic variation in regulatory regions has been shown to cause Mendelian disease by reducing or abolishing the expression of the corresponding coding gene. However, regulatory regions are not routinely screened because we do not know where these regions are in the genome. In order to differentiate the functional non-coding variants from the vast number of benign non-coding variants we need to know which regions of the genome regulate gene expression in the tissues relevant to the disease. We have approached this systematically with a focus on identifying the distal regulatory elements involved in expression of skeletal muscle disease genes. We have mapped enhancer-promoter interactions in healthy adult human skeletal muscle tissue (n=3 unrelated donors) by creating genome-wide chromatin conformation capture libraries at 5kb resolution using the Dovetail Genomics OMNI-C workflow. We also profiled human skeletal muscle regulatory regions (n=3 donors) by performing ChIP-seq for histone modifications associated with enhancers (H3K4me1) and promoters (H3K4me3), as well as the chromatin architecture protein CTCF. These data were integrated with human skeletal muscle snRNA-seq (n=4 donors) and various public datasets associated with skeletal muscle relevant phenotypes. We have created a high-quality map of human skeletal muscle enhancers and their linked promoters and show that this map is capable of identifying statistically significant interactions between key muscle gene promoters with both known and novel distal regulatory elements. Our hope is that this map can now be used as a screening tool to prioritise non-coding sequence variants that are likely to be causal for Mendelian muscle diseases.