Sociedad Española de Genética

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PhD studentship in genetic-epidemiological modelling


Assessing the feasibility of controlling infectious disease in livestock
through selective breeding using genetic-epidemiological models


Controlling infectious disease in livestock is high priority for sustaining livestock production
and human health. There is abundant evidence that animals vary genetically in their response
to infectious challenge, and that selective breeding could be a viable alternative to conventional
strategies to improve animal health. However, progress in selective breeding for disease resistance
has been hampered, because available data based on which decisions for selection are made often
provide a poor image of the animals' true genetic merit. Hurdles that need to be overcome include:

• it is difficult to decide which animals are genetically at higher risk to become diseased or
spread the pathogen when infectious challenge is absent or low.
• measurements may be collected at the wrong time (e.g. before sufficient animals have been
exposed to disease) or from too few animals.
• the data collected are often poor indicators for the animal's genetic ability to cope with
infection and existing diagnostic tests are often inaccurate.
• the biological mechanisms and environmental influences underlying an animal's response to
infectious challenge are often poorly understood.

The aim of this PhD project is to address these hurdles using genetic-epidemiological models. In
particular, we aim to better understand the relationship between the animals' genetic pre-disposition
for becoming diseased and spreading infection and the epidemiological consequences for the entire
population. The student will explore how this understanding depends on the type of disease and the
population structure and how it is affected by the number and quality of available measurements.

The student will utilise this knowledge to determine under what conditions selection for disease
resistance is feasible and what information would be needed to make it feasible in the future.
The project will be supervised by Dr. Andrea Doeschl-Wilson and Prof. Stephen Bishop.

The successful candidate will be part of a multi-disciplinary team consisting of mathematicians,
geneticists and epidemiologists and receive training in mathematical modelling, quantitative
genetics and relevant epidemiological and statistical tools.
Specifications and application:

All candidates should have or expect to have a minimum of an upper 2nd class degree in an appropriate
subject (e.g. mathematics, statistics, quantitative genetics, epidemiology, animal science) and have good
computer skills. Experience or an interest in mathematical modeling and computer programming, as well as
in scientific writing would be desirable.

For further details please contact Dr. Andrea Doeschl-Wilson (andrea.wilson@roslin.ed.ac.uk;
phone: 0131 527 4200; http://www.roslin.ed.ac.uk/postgraduate/studentships.php or http://
www.roslin.ed.ac.uk/andrea-wilson/). Applications including a full CV with names and contact details
of 2 academic referees, and a covering letter should be sent to: Human Resources, The Roslin Institute
(Edinburgh), Roslin, EH25 9PS, UK or emailed to roslin.hr@roslin.ed.ac.uk