Context/background
Before the instructions in a gene can be used, non-coding parts called introns must be cut out in a process called splicing. Most introns are spliced out by the major spliceosome. However, around 700 human genes contain a rare type of intron (U12 introns) that can only be removed by a separate minor spliceosome.
We recently discovered that inherited changes in two core minor spliceosome components, RNU4ATAC and RNU6ATAC, cause a single-gene (monogenic) form of autoimmune diabetes. In this condition, the immune system destroys the insulin-producing beta cells of the pancreas. This is a puzzle, as the minor splicing machinery is used by every cell in the body, yet when it goes wrong it results in a highly specific immune attack on the pancreatic beta cells. We do not yet know which of the 700 affected genes drive disease, or in which cells, though preliminary data suggests a major role for T cells, B cells and beta cells. Answering this could reveal new biology relevant to type 1 diabetes and to autoimmunity more broadly, uncovering new drug targets for autoimmune diseases.
Key question
Which incorrectly spliced U12-intron genes drive the immune system to attack beta cells and how?
Objectives
- Develop a computational framework to rank U12-intron genes by how likely they are to cause disease. This will combine single-cell gene expression atlases, genetic studies of type 1 diabetes and autoimmunity, and annotation to predict how sensitive each intron is to minor spliceosome failure
- Confirm that the top-ranked genes are misspliced in patient cells
- Switch off a small shortlist of genes in B cell, T cell and/or beta cell models. Test the effect on key processes such as immune activation, tolerance, antigen presentation, cell stress and survival.
Methodology
- Year 1 - prioritise candidate genes by analysis of publicly available data including single-cell RNA sequencing data from immune and pancreas cells, alongside existing patient RNAseq and immune data
- Year 2 - measure intron retention of key genes in patient-derived cells using our established droplet digital PCR assay and establish the cell models
- Years 2–3 - knockdown/knockout (e.g. CRISPR or siRNA) of 3–5 highest priority genes. Readouts will include flow cytometry, cytokine measurement and RNA sequencing
- Final year - integrate findings, publish data, write and submit thesis
Interdisciplinary aspects of the project
The project spans data science, human genetics, immunology and cell biology. The student will be trained in computational analysis (R/Python, single-cell and public genomic data) and in laboratory methods (cell culture, CRISPR gene editing, digital PCR, flow cytometry).
We welcome applicants from biological, biomedical, computational, mathematical or data science backgrounds. Full training will be provided in unfamiliar areas.
Expected outcomes
- An empirically defined set of U12-intron genes implicated in autoimmune diabetes
- New understanding of how U12-intron containing genes shape immune and beta cell behaviour
- New biomarkers and/or drug targets for type 1 diabetes and other common autoimmune conditions
- Publications, conference presentations and a versatile skill set spanning dry (computational) and wet laboratory research
