Project No. 2326
Prof Matthew Guille – University of Portsmouth
Prof Diana Baralle – University of Southampton
Prof Mariana Vargas-Caballero – University of Southampton
Rationale and Impact: There are around 100 genes encoding potassium channels, and around 40% of these are associated with diseases, generally displaying developmental delay, ataxia and epilepsy.
We aim to systematically assess the function of the remaining potassium channel genes to better understand this gene family. This understanding will have impact, the data will help improve diagnosis and interventions for people who have pathogenic variants in these genes.
We recently identified a novel syndrome characterised by ataxia and developmental delay caused by variants in a potassium channel gene, KCNC4. Our innovative approach combined bioinformatics investigation of human variation, molecular modelling of channel function, and recapitulation of the human phenotype in the Xenopus model organism to link the gene to the disorder and understand its molecular basis. We will extend this successful approach to other potassium channels.
Bioinformatics: Whole genome sequences from patients with rare disorders in the 100,000 Genomes Project (100KGP) and NHS Genomic Medicine Service will be interrogated for damaging variants in potassium channel genes. These will be prioritised based on bioinformatics tools, number of probands and their phenotypes to determine the most likely disease causing genes.
Ion channel function: Using well established electrophysiological assays, the impact of the detected variants on ion channel function will be measured relative to the wild-type channel using patch clamp in HEK cells. This will establish whether the variants impact channel function, and what the nature of that disruption is.
Xenopus models: Promising genes will be knocked-out using CRISPR in Xenopus, and the resultant morphological, physiological and behavioural changes systematically assessed. This will determine the normal function of the gene in the whole organism.
Candidate qualities: An ability to engage with a multi-disciplinary project within an existing, successful collaboration. Specifically, an interest in bioinformatics, electrophysiology, molecular genetics and phenotyping.