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Genomics of oak trees and their microbiota

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  • Full or part time
    Dr R Buggs
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (European/UK Students Only)
    Funded PhD Project (European/UK Students Only)

Project Description

Oaks are the most common trees in England, and of huge ecological, economic and cultural value. They support large communities of microbes, some of which are beneficial and some of which are pathogenic. Oaks are affected by health problems including acute oak decline, chronic oak decline, mildews, and honey fungus. This project will use whole genome sequence data for oak trees and their microbiomes to investigate factors affecting oak health. In collaboration with Royal Botanic Gardens Kew and Forest Research we have just generated short read sequence data for the genomes and leaf microbiomes of 400 oak trees from five UK populations. We are seeking a talented student to analyse these data. The project will uncover the population diversity of English oak trees and their microbiota and begin to understand the genetic component of oak health problems. Around 60% of the project will involve bioinformatic analyses including read-mapping to reference genomes, SNP calling, diversity analyses, and database searching. The student will graduate with a highly transferable set of genomic bioinformatics skills that will be applicable to all genomics projects including human medical genomics. Around 10% of the project will consist of fieldwork, phenotyping oak trees in UK populations. About 30% of the project will consist of writing papers and attending genomics conferences. The student will join a team of researchers working on the genomics of broad-leaved trees who will provide training on the techniques needed for the project. This is an exciting project with significant stakeholder interest. In the past, it has been hard to do genetic research on oak trees due to their long generation times and large size. We hope that by using novel genomic approaches first developed for humans we can make rapid progress in understanding the genetic component of oak susceptibility to pathogens.

Funding Notes

This studentship is funded by UK Department for Environment, Food and Rural Affairs and Royal Botanic Gardens, Kew. The studentship is open to UK and EU applicants. It will cover tuition fees and provide an annual tax-free maintenance allowance for 3 years at Research Councils UK rate (£16,553 in 2017/18).

Informal enquiries about the project can be made by email to Dr Richard Buggs ([Email Address Removed]). For formal applications, please submit an online application before the stated deadline.

References

[1] Elizabeth S. A. Sollars, Andrea L. Harper, Laura J. Kelly, Christine M. Sambles, Ricardo H. Ramirez-Gonzalez, David Swarbreck, Gemy Kaithakottil, Endymion D. Cooper, Cristobal Uauy, Lenka Havlickova, Gemma Worswick, David J. Studholme, Jasmin Zohren, Deborah L. Salmon, Bernardo J. Clavijo, Yi Li, Zhesi He, Alison Fellgett, Lea Vig McKinney, Lene Rostgaard Nielsen, Gerry C. Douglas, Erik Dahl Kjær, J. Allan Downie, David Boshier, Steve Lee, Jo Clark, Murray Grant, Ian Bancroft, Mario Caccamo and Richard J. A. Buggs (2017) Genome sequence and genetic diversity of European ash trees. Nature 541: 212–216
[2] Andrea L. Harper, Lea Vig McKinney, Lene Rostgaard Nielsen, Lenka Havlickova, Yi Li, Martin Trick, Fiona Fraser, Lihong Wang, Alison Fellgett, Elizabeth S. A. Sollars, Sophie H. Janacek, J. Allan Downie, Richard. J. A. Buggs , Erik Dahl Kjær and Ian Bancroft. (2016) Molecular markers for tolerance of European ash (Fraxinus excelsior) to dieback disease identified using Associative Transcriptomics. Scientific Reports 6, Article number: 19335
[3] David Boshier and Richard J. A. Buggs. (2014) The potential for field studies and genomic technologies to enhance resistance and resilience of British tree populations to pests and pathogens. Forestry 88: 27-40

How good is research at Queen Mary University of London in Biological Sciences?

FTE Category A staff submitted: 23.39

Research output data provided by the Research Excellence Framework (REF)

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