PhD Studentship: Allele-resolved genetics and epigenetics in type 2 diabetes

Type 2 diabetes (T2D) affects over 800 million people worldwide. It is a complex disorder and an individual’s genetics influences disease risk. Understanding how DNA differences drive this risk can enable disease prediction and personalised approaches to diagnosis and treatment, addressing the shortfall between genetic discovery and patient benefit.  Large scale genetic studies have identified hundreds of DNA regions linked to increased T2D risk. Most lie in regulatory regions, areas of DNA outside the genes that control when and where a gene is turned on. Changes here impact how islets – clusters of pancreatic cells that produce hormones including insulin – regulate blood glucose.  Interpreting these DNA changes is complicated because we inherit two parental copies of our genome, and the disease-causing changes generally reside on only one. Standard technologies merge data from both copies, making it challenging to resolve which DNA changes contribute to disease. 

This project will use chromatin stencilling (known as Fiber-seq), a cutting-edge technology, to address this problem.  This long-read sequencing technology simultaneously measures regulatory activity, epigenetic state, and genotype and allows us to distinguish the two parental copies of the genome.  Key question How do genetic variants associated with T2D alter regulatory activity on each inherited copy of our genome in pancreatic islets?

This will be achieved by:

1. Generating unprecedented chromatin stencilling maps of DNA regulatory activity from healthy pancreatic islet donors.
2. Targeting specific disease loci in islets from genetically selected type 2 diabetes donors to pinpoint failing regulation.
3. Decoding how genetic changes affect DNA regulation, enabling the interpretation of diabetes associated genetics in large studies like the UK Biobank. Interdisciplinary Approach This project brings together laboratory genetics, epigenetics, long-read sequencing and extensive data science. The student will join the Gene Regulatory Defects in Disease Group at the University of Exeter, an interdisciplinary team of laboratory and computer scientists. The project will allow the student to shape the research direction, and they will receive expert supervision, training, and collaboration with international leaders.

The student will develop translatable skills in experimental design, DNA sequencing, bioinformatics and interpreting complex biological data.  Methodology Healthy and T2D islets will be selected using genetic, clinical, and existing molecular data. The islets will undergo our chromatin stencilling protocol, and the DNA will be sequenced using Oxford Nanopore. These long reads allow us to map activity to each inherited DNA copy and assess copy specific regulation.  Targeted sequencing will also provide deep coverage at selected disease regions. 

Computational analyses will then identify differences in DNA accessibility and methylation, resolving cell-type specific regulation and annotating regulatory protein binding sites. This will be combined with large-scale genetic (e.g. UK Biobank) to improve interpretation of variants in T2D.  Outcomes This project will generate the most detailed maps to date of gene regulation in healthy and T2D pancreatic islets, improving our understanding of the genetic basis for T2D. The resulting openly shared annotations and datasets will be a resource for the community. Student training will also be a significant output, they will gain cross-discipline expertise in long-read sequencing, epigenetics, computational biology, and statistical genetics.

Funded by: EPSRC Engineering and Physical Sciences Research Council 

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