Genome sequencing projects such as the 1000 genomes project have generated extensive genetic data from which much knowledge about the genetic variation in individuals has been obtained. However, to date the identified genetic variation has only be able to explain a small proportion of the relationship between genotype and phenotype. It is now important to identify which variants have functional roles, particularly those that have a role in disease.
This PhD project will combine structural bioinformatics and systems biology approaches to analyse genetic variation and to also develop methods to predict the functional effect of genetic variants. Particular focus will be on the analysis and use of protein complexes to identify the functional effects of genetic variants. This will build upon recent a analysis demonstrating that disease-associated variants are enriched at protein-protein interfaces (David et al. 2012). The novel methods developed will be applied to extend our understanding of how genetic variation is related to disease and will investigate the potential for application to personalised medicine.
Ideally candidates will have some experience of computer programming and an interest in biochemistry/structural biology and this position would be particularly suited to individuals with an MSc in bioinformatics/systems biology.
Applicants are encouraged to make informal enquiries with Mark Wass m.n.wass@kent.ac.uk. Applications can be made online at www.kent.ac.uk/studying/postgrad/gradapply.html.
The position is available with a start date between October 2012 to March 2013. Applications will first be considered after an initial deadline of 24 September.
Funding Notes:
All candidates are expected to have a minimum of an upper 2nd class degree in an appropriate field. To qualify for funding students must be a UK or EU citizen. Funding is available for 3 years and includes a Stipend paid at RCUK (Research Council UK) standard rate.
References:
Listed below are recent publications by the supervisor Dr Mark Wass that are relevant to the proposed project:
David, A., Razali, R., Wass, M.N., Sternberg, M.J. (2012) Protein-protein interaction sites are hot spots for disease-associated non-synonymous SNPs. Human mutation, 33, 359–363.
Wass, M.N., Kelley, L.A. and Sternberg, M.J. (2010). 3DLigandSite: Predicting ligand binding sites using similar structures. Nucleic Acids Res. 38:W469–73.
Chambers, J.C., Zhang, W., Sehmi, J., Li, X., Wass M.N. et al., (2011) Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma. Nat Genet 43:1131–1138.
Chambers JC, Zhang W, Lord GM, van der Harst P, Lawlor DA, Sehmi JS, Gale DP, Wass M.N., et al., (2010) Genetic loci influencing kidney function and chronic kidney disease. Nat Genet, 42, 373-5.
Chambers, J.C., Zhang, W., Li, Y., Sehmi, J., Wass, M.N. et al., (2009) Genome-wide association study identifies variants in TMPRSS6 associated with hemoglobin levels. Nat Genet, 41, 1170-2.