Identifying the cell-type specific gene networks operating within the Substantia nigra and their dysfunctions across neurological disease
This research project is in competition for funding with one or more projects available through the UK Dementia Research Institute (DRI) at Cardiff. Usually the projects which receive the best applicants will be awarded the funding. Find out more information about the UK DRI and how to apply.
Our knowledge of individual cell types, let alone their functions and how cell type dysfunction underlies disease, is very incomplete.
Increasing molecular data, including genomic, epigenomic and transcriptomic data, about each cell type that makes up a tissue is providing new definitions of cell functions and new insights into how different types of cells work together in health and disease.
Understanding which cell types disease initially arises within and how other cell types within the same tissue respond is key to understanding the evolution of a diseased tissue. If each molecular data type provides only limited information, integrating several omics data types will enable us to find new insights on how dysfunctions within and across different cell types causes complex disease.
Project aims and methods
Building on our group’s expertise on single cell approaches and functional genomics data integration, we will use a range of external and internal datasets to build Substantia nigra cell-type-specific gene networks that elucidate functional and regulatory associations between genes.
We will exploit these cell-type-specific networks to dissect the cell type-specific genetic components of Parkinson’s Disease and Schizophrenia and test our insights within existing cellular models in our lab.
A minimum of a 2.1 or master's in a relevant degree subject is required.
Relevant degree subjects include, for example:
- biological sciences
- molecular biology/genetics
- computer science or statistics.
Candidates with a biological science background would need to demonstrate a keen interest/capability with computational approaches, while those from a computational or mathematical background would need to demonstrate an interest in biological systems and applications.