Exploiting rare human disease genomics to discover novel developmental control genes

Lead Research Organisation: University of Southampton
Department Name: Sch of Biological Sciences

Abstract

A huge number of rare gene variants associated with phenotypes has been identified by next generation sequencing in ongoing genome projects. The number of phenotypes analysed far exceeds that in a traditional forward genetics screen. We will combine bioinformatic analysis of these "mutants" and high throughput gene function determination in Xenopus to discover new genes that have important, evolutionarily conserved roles in development.

The first phase of the project, will involve the detection of gene variants that are deemed highly likely to underpin pathogenic human phenotypes, but where the specific gene involved is of unknown developmental function. The student will be trained to access, analyse and prioritise these gene variants from clinical and genomic data generated as part of ongoing projects at the UoS and through the Genomics England Clinical Interpretation Partnerships (GECIPS). Variants to undergo modelling in Xenopus will be prioritised on the basis of: sequencing quality, in silico metrics of pathogenicity and frequency, inheritance patterns and biological background data gleaned from the published literature.

Gene editing will then be used to make a knockout of each bioinformatically-prioritised gene in X. tropicalis. Since this is routinely done in >100 embryos it will test whether the function suggested by the very small number of humans with this variant gene is both genuine and evolutionarily conserved. These experiments are performed in a week allowing high throughput. To make detailed analysis of the phenotype easier, knockouts will be performed in lines of transgenic frogs with the appropriate fluorescent cell type, we have >200 of these lines.

The impact of this study will be discovering novel developmental genes and, by distributing many of them to other developmental biologists (prioritising those in SoCoBio), to integrate them into the gene regulatory networks of systems biology that underpin our understanding of health and disease.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
BB/T008768/1 01/10/2020 30/09/2028
2451250 Studentship BB/T008768/1 01/10/2020 30/09/2024