The molecular basis of glial cell heterogeneity in human brain

This project is available through the MIBTP programme on a competition basis. The successful applicant will join the MIBTP cohort and will take part in all of the training offered by the programme. For further details please visit the MIBTP website - https://warwick.ac.uk/fac/cross_fac/mibtp/

Glial cells constitute a large fraction of the mammalian brain. Although initially considered as non-functional supporter for neuron function, recent studies have revealed that glial cells have critical roles in the brain under both physiological and pathological conditions. Glial-cell pathology is increasingly recognized in several neurodegenerative diseases and in the occurrence of brain tumours. However, the existences of highly heterogeneous glial populations in the brain have limited functional studies.

The aim of this project is (i) to determine the genetic heterogeneity of glial cells in different brain tissues and (ii) identify the genetic factors determining the identity of distinct glial populations. Using computational and experimental approaches, the student will investigate the transcriptional profile of glial-cell populations, determine the genetic pathway(s) implicated in distinct glial identity and use targeted genome editing to reveal their function.

Key Skills involved:

The student will gain skills in single-cell transcriptomic analysis of message RNA and non-coding RNAs. The student will be able to analyse next-generation sequencing (NGS) data to generate hypothesis that will be tested in the laboratory using established CRISPR/Cas9 genome targeting methods. The student is expected to obtain basic training on computational and statistical tools for analysis of genome-wide data.

BBSRC Strategic Research Priority: Integrated Understanding of Health- Ageing

Techniques that will be undertaken during the project:

The student will use a wide range of molecular, histological and computational techniques including: Genomic and Epigenomic analysis using Next Generation Sequencing data and customised computational analysis.