This PhD project aims to provide comprehensive training for the successful candidate in potato genetics (diploid and tetraploid) as well as plant-pathogen genomics/coevolution. The student will be exposed to complex computational aspects of state-of-the-art diverse NGS data and different scripting languages. Importantly, the student will be a full member of the Dundee Effector Consortium (DEC), which unites more than 50 researchers on all aspects (including computational genetics/genomics) of plant-pathogen coevolution. DEC will provide a forum to gain experience in communicating results in a friendly environment and receiving critical but constructive feedback on progress and direction of the PhD.
The student will have the opportunity to spend time at the computational facilities at the James Hutton Institute and the University of Dundee. Interactions with other computational experts will be fostered to enable the student to also gain an in-depth knowledge of genome browsers, databases and visualization software. Additional training needs (based on past experience of the student and future needs of the project) will be assessed and a plan developed to meet them, through in-house training or external courses, as appropriate.
The data analyses will be focused on studying the interaction between Phytophthora infestans and potato. The oomycete pathogen P. infestans is a widespread and economically significant threat to global crop production. Phytophthora species are very destructive and can adapt rapidly to new selection pressures imposed by modern agriculture. On a molecular level pathogen avirulence or virulence to naturally occurring or deployed host disease resistances is determined by effectors. The effector recognition-based inducible plant defense response is often governed by nucleotide-binding, leucine-rich repeat (NLR) disease resistance proteins.
We have successfully developed target enrichment sequencing for potato NLRs as well as pathogen effectors from P. infestans that determine recognition in the plants and therefore resistance. We have coined these novel methods RenSeq [1-2] and PhytoPathSeq. The student will be involved in the development of analysis tools for RenSeq and PhytoPathSeq data with the aim to determine the pattern of deployed host resistances and how this deployment has shaped the diversity of known avirulence genes. This knowledge is a prerequisite to define the potential durability of resistances.
- Van Weymers, P., Baker K., Chen. X., Harrower B., Cooke D.E.L., Gilroy, E.M., Birch P.R.J., Thilliez G., Lees A.K., Lynott J.S., Armstrong M.R., McKenzie G., Bryan G.J. and Hein I.* (2016) Utilizing ‘Omic’ technologies to identify and prioritize novel sources of resistance to the oomycete pathogen Phytophthora infestans in potato germplasm collections. Front in Plant Science; 7:672.
- Jupe F., Witek K., Verweij W., Sliwka J., Pritchard L., Etherington G.J., Maclean D., Cock P.J., Leggett R.M., Bryan G.J., Milne L., Hein I.* and Jones D.J.* (2013) Resistance gene enrichment sequencing (RenSeq) enables re-annotation of the NB-LRR gene family from sequenced plant genomes and rapid mapping of resistance loci in segregating populations. The Plant Journal; 76, 530-544