Accelerated discovery of functional non-coding genomic variation using single molecule real-time (SMRT) sequencing.

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The last decade has seen tremendous advances in our understanding about the role of genetic variation in health and disease, driven largely by developments in technology for sequencing the genome. Genes involved in a spectrum of debilitating disorders and health-related traits have been identified, including many by researchers at the University of Exeter Medical School, and these discoveries are starting to directly impact upon clinical practice. Despite this success, however, many regions of the genome remain hidden to contemporary first- and second-generation sequencing approaches. These include highly complex stretches of repetitive DNA and regions harbouring other types of genetic variation such as deletions and duplications. Furthermore, because the sequencing reads generated by current approaches are relatively short, they cannot be used to examine the long-distance relationships between more distal variants, nor explore the extent to which different genes are expressed in different versions in health and disease. Finally, most focus in disease genetics has been on regions of the genome that actually encode specific genes, ignoring the role of regulatory variation occurring outside of these regions. Of note, current sequencing approaches cannot be used to directly detect the presence of non-sequence-based epigenetic modifications and explore their role in disease. In this application we are requesting funds to support the acquisition of "third generation" sequencing technology, which will enable us to fully characterise genomic complexity. We are also requesting funds to support the high-performance computing infrastructure needed to store and analyse this complex data. Our aim is to advance genomics research into diabetes, neurological and other medical conditions by defining functional genetic and epigenetic variation in non-coding regions of the human genome.