GW4 MRC DTP studentships- Codes within codes: How genetic variation influences disease through regional changes in methylation

Location
University of Bristol
Funding for (UK/EU/o’seas)
UK and EU applicants only
Funding amount
RCUK £14,553 plus research and training grant
Hours
Full time
Closing date
9.30am, Thursday 8th
Rationale:
Genetic differences that exist between individuals make a significant contribution to variation in disease risk across populations, but understanding the molecular path from genotype to phenotype is a big scientific question. For example, it is broadly understood that methylation (chemical modification to DNA) plays a central role in the rate of gene expression, which in turn influences disease outcomes. Elucidating such pathways requires novel statistical and computational methods applied to large datasets. We can use high throughput assaying technologies to identify genetic influences on thousands of regulatory elements, including DNA methylation and gene expression levels.

Currently, these different molecular measures of regulation tend to be treated as individual entities, but this does not appropriately reflect the complex relationships that exist between them. One way to better model regulatory measures is to construct causal networks using Mendelian randomisation. Such networks will be used to understand how different regions of the genome work together, enabling us to construct a computational model of gene expression. We can then exploit this model to understand how changes in regulation can increase or decrease disease risk.

Specific Training: Statistical methods- Methods in statistical genetics are key for finding genetic associations, methods from econometrics and epidemiology are used to construct causal networks.

Diverse types of big data: High throughput molecular assays for gene expression, DNA methylation and other 'omic variables will be used in conjunction with genotype data on thousnads of individuals. Computational methods: Key to this type of analysis is producing high quality, reproducible analytical scripts and software, with interactive visualisations of complex data being an important element.

Added Value Features: The student will gain access to data through the Genetics of DNA Methylation Consortium (GoDMC), which provides a brilliant opportunity to build collaborations with 44 cohorts from around the world, including several that are housed at GW4 institutes.

Knowledge Transfer and Impact: The IEU has a strong track record in public engagement and the student will have the opportunity to develop and deliver activities that explain and promote new research findings to different audiences. Through various projects related to this project, such as the MR-Base platform, we also have partnerships with pharmaceutical companies and there will be opportunities to build collaborations in that direction also.
How to apply:
Please see http://www.gw4biomed.ac.uk/available-projects/national-productivity-investment-fund-studentships/ .
A university of Bristol application will need to be completed only when you are successful at interview.

For more information, please contact Dr G Hemani ([Email Address Removed])