Adaptation is the process in which organisms become better suited to the
environment, in order to survive and thrive. Identifying genomic regions involved in this process is key to understanding the genetic basis of adaptation. In addition, finding these targets helps us identify functionally important genomic regions, which may lead to important applications in areas such as medicine, pest control, and animal/plant breeding. The rapid accumulation of population genomic data (consisted of the genomes of multiple individuals) from a wide variety of organisms offers us an unprecedented opportunity to detect targets of natural selection in the genome.
Most previous studies focus on detecting genomic regions under positive selection (where a single allele is favoured and replaces other alleles), whereas little attention has been paid to balancing selection (where the maintenance of multiple alleles is favoured by selection). However, well known examples, such as the immune systems of vertebrates and host invasion systems of pathogens, suggest that loci subject to balancing selection often have important biological functions. Furthermore, recent theoretical studies predict that adaptation is far more likely to proceed through balancing selection than previously thought. Unfortunately, progress towards understanding the importance of balancing selection has been hampered by the fact that existing methods for detecting balancing selection are not sufficiently well developed to have high sensitivity, especially when balancing selection targets arose relatively recently.
This PhD project combines method development and analysis of large datasets. The student will contribute to ongoing efforts in the Zeng group to develop and test new methods of detecting balancing selection that overcome known shortfalls of existing methods. The student will then use these methods to find genes that are targets of balancing selection in the human genome, the human pathogen Leishmania, great tits (Parus major), and zebra finches (Taeniopygia guttata).
This project intends to fill a gap in our understanding of evolution, i.e., the importance of balancing selection in adaptation. It promises to provide new, generic data analysis methods that are applicable to many different organisms, including those of medical, environmental, agricultural importance. At the end of this PhD you would have the skills to work not only in evolutionary biology, but also in fields utilising genomics such as personalised medicine, sustainable agriculture or microbial resistance to antibiotics.
This project would suit a highly motivated student interested in population/evolutionary genetics with an enthusiasm for analysing large genomics datasets. Applications are welcomed from those who have a degree in a biological or any other relevant discipline (e.g., statistics, computer science, physics, mathematics).
Science Graduate School
As a PhD student in one of the science departments at the University of Sheffield, you’ll be part of the Science Graduate School. You’ll get access to training opportunities designed to support your career development by helping you gain professional skills that are essential in all areas of science. You’ll be able to learn how to recognise good research and research behaviour, improve your communication abilities and experience the breadth of technologies that are used in academia, industry and many related careers. Visit http://www.sheffield.ac.uk/sgs
to learn more.
Fully funded studentships cover: (i) a stipend at the UKRI rate (£15,009 per annum for 2019-2020), (ii) research costs, and (iii) tuition fees. Studentship(s) are available to UK and EU students who meet the UK residency requirements.
This PhD project is part of the NERC funded Doctoral Training Partnership “ACCE” (Adapting to the Challenges of a Changing Environment View Website. ACCE is a partnership between the Universities of Sheffield, Liverpool, York, CEH, and NHM.
Shortlisted applicants will be invited for an interview to take place in the w/c 10th February 2020.