The emergence of RNA viruses from mammal or bird reservoirs is a serious threat to public health, as illustrated by recent, large outbreaks of Ebola, Zika and Chikungunya viruses.
This project will use phylogenetic analyses to characterise the non-human origins of human RNA viruses. Key questions to be addressed are whether specific host taxa (e.g. primates) are disproportionately likely sources of viruses that can infect and transmit in human populations and whether such effects are modified by proximity (domestic animals vs wildlife), transmission route (e.g. vector-borne) or other factors.
The number of RNA virus sequences available from natural infections of non-human mammals/birds openly available on public access resources such as NCBI is increasing exponentially. This affords unprecedented opportunities to investigate the evolutionary origins of human viruses using genome sequence analysis. Sequence data will be integrated with existing information on virus phenotypes, including known host range, transmission route and other variables.
Data analysis will build on previous work and will involve a combination of genome sequence analysis, evolutionary models, computational biology and machine learning methods, likelihood based tests and approximate Bayesian computation. The student will receive one-to-one training in the use of state-of-the-art software platforms for implementing these powerful techniques. In addition, broader training will be provided, as required, in bioinformatics, computational biology, data science and epidemiology, plus access to considerable expertise in molecular virology.
One of the unresolved challenges for this type of analysis is the problem of data gaps: though we have a good (though still incomplete) knowledge of human RNA virus diversity, we have less knowledge of viruses from domestic animals and far less knowledge of viruses from wildlife. Rarefaction curves are one way to explore the impact of data availability on the outputs of the analyses.
Our earlier work in this field has contributed to both WHO and CDC policy on emerging viruses. An anticipated output of this new project is recommendations for strategies for surveillance for potential zoonotic viruses, a hotly debated topic.
• Professor Mark Woolhouse, Usher Institute, the University of Edinburgh
• Professor Andrew Leigh Brown, School of Biological Sciences, the University of Edinburgh
• Dr Lu Lu, Usher Institute, the University of Edinburgh.
A strong academic track record with a 2:1 or higher in a relevant undergraduate degree, or its equivalent if outside the UK.
Good computational and statistical skills are required, as well as an interest in applying these skills to biological problems of global public health significance. The successful applicant will not necessarily be familiar with the analytical approaches needed, but should be able to demonstrate an aptitude and enthusiasm for learning new skills and applying them to the rapidly expanding global resource of genome sequence data. A background in biology, genetics or epidemiology with good quantitative skills would be suitable, as would a background in computation or physics with an interest in biomedicine.
Following interview, the selected candidate will need to apply and be accepted for a place on the Usher Institute Global Health PhD programme. Details about the PhD programme and further requirements can be found here: https://www.ed.ac.uk/studying/postgraduate/degrees?r=site/view&id=698
Please download the EASTBIO application form from: http://www.eastscotbiodtp.ac.uk/how-apply-0
The required supporting documents for this application are:
• The completed application form
• Academic transcript
• 2 References
Please send the above documents to [email protected]
. Referees should send their completed reference forms (also available from http://www.eastscotbiodtp.ac.uk/how-apply-0
) to [email protected]
All documents must be received by the application deadline on 5th January.