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PhD Studentship: How do schizophrenia risk variants influence the local synaptic translatome? MRC GW4 BioMed DTP PhD studentship 2023/24 Entry, PhD in Medical Studies

University of Exeter - Faculty of Health and Life Sciences

Qualification Type: PhD
Location: Exeter
Funding for: UK Students, EU Students, International Students
Funding amount: From £17,688 Consists of UK tuition fees, as well as a Stipend matching UK Research Council National per annum
Hours: Full Time
Placed On: 16th September 2022
Closes: 2nd November 2022
Reference: 4516

Summary

To improve treatments for schizophrenia there is a need to better understand the biology impacted by genetic mutations conferring risk to the disorder. This project will aim to investigate the effects of high-risk genetic variants on synapses and their molecular constituents. We will make use of cell-specific RNA sequencing and large-scale patient genomic data to quantify these effects and predict biological vulnerability in the brain.

Details

Recent years have seen genomics research unearth hundreds of genes associated with risk for schizophrenia (1), yet these discoveries have not yet translated to the development of new treatments. To reach a point where we can improve treatments, there is a need to refine when and where genetic risk converges on vulnerable biological systems, taking into account the dynamic and compartmentalised nature of cellular processes over development. Time- and spatially-sensitive synaptic events utilise local translation of gene transcripts to rapidly produce selected proteins. Such events include plasticity, neurite outgrowth and synapse maturation, all of which have been implicated in schizophrenia risk through genetic and functional studies (2), highlighting the importance of studying synaptic dynamics driven by local translation. Modelling the developmental effects of risk variants in genes important for synaptic function may reveal critical periods of vulnerability in the synaptic translatome and targets for intervention.

New findings from exome sequencing have revealed a small group of 10 genes containing a genome-wide excess of highly penetrant coding mutations in patients with schizophrenia (3). This greatly increases the feasibility of studying relevant pathology in model organisms. This project will focus on modelling the effects of missense variants in the NMDA receptor subunit gene, GRIN2A, to investigate the role of the local synaptic translatome in conferring risk to schizophrenia during brain development, taking advantage of the most recent techniques for ribosome profiling and single-cell transcriptomics. Working with the GW4 BioMed2 Associate Partner the MRC Mary Lyon Centre, a new mouse line has been generated modelling a GRIN2A missense variant found in patients with schizophrenia (3). The student will use cortical tissue from this mouse line to test the hypothesis that the mutation exerts pathogenic effects through disruption to locally translated synaptic transcripts, using the following objectives:

  • Profile changes in ribosome-associated transcripts at the synaptosome caused by the Grin2a variant. By crossing the mouse line with a RiboTag strain, cell-specific ribosomes will be tagged for immunoprecipitation and RNA isolation. RNA from different stages of postnatal brain development will be sequenced and analysed.
  • Identify cell type specific changes using single-cell transcriptional sequencing. Informed by the first objective, the student will choose one developmental stage to obtain cortical cells for dissociation and sequencing using 10X Genomics. The student will determine genotype effects and prioritise cell types based on susceptibility of differentially expressed genes to schizophrenia risk.
  • Use human genomics and developmental transcriptomes to predict when and where human expression dynamics may be most susceptible to alterations observed in the mouse model. Through collaborators at the Lieber Institute for Brain Development (Baltimore) and data available at Exeter, we will compare new mouse transcriptomes with expression dynamics from human dorsolateral prefrontal cortex, hippocampus and caudate nucleus, including foetal, single-cell and methylation datasets.
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