Project description

Primary Supervisor: Prof Cock van Oosterhout

Scientific background:

Population bottlenecks erode genetic variation, which makes threatened species susceptible to viral epidemics. So, what makes an individual Resistant, Tolerant, or Susceptible (R/T/S) to a virus? That is the key question we aim to answer in this PhD study. We have gathered data on viral outbreaks over ~20 years and sequenced hundreds of bird genomes, working on some of the best-studied avian models (Mauritius parakeet, ringneck parakeet, red-crowned parakeet, and orange-bellied parrot). The PhD candidate will study data from the Mauritius parakeet to develop an AI model that can predict the response to viral infection based on genomics data. Moreover, there is the option to conduct fieldwork in Mauritius to gather additional field data, and for comparative genomics analyses.

Research methodology:

During this PhD project, we will sequence genomes of 531 already-sampled full-sib pairs with known R/T/S status. (This is funded by recently awarded NERC grant). The PGR will conduct bioinformatic analyses on these data, focussing on immune genes, and perform a comparative genomic analysis across parakeets and parrots. They will construct an AI model to identify genomic predictors of R/T/S in the Mauritius parakeet, and they will conduct analysis in SLiM to examine how genomic erosion reduces immunogenetic diversity, and how that affects disease susceptibility. The PGR will test the following hypotheses:

1. Genome erosion increases susceptibility to viral infection.

2. Inbred individuals are more susceptible to viral infection.

3. Individuals with Runs of Homozygosity (ROH) spanning immune genes are more susceptible to viral infection.

4. Differences in alleles at immune genes explain variation in disease status of birds.

Training:

AI modelling, SLiM modelling (i.e., an individual based model to assess population viability), genomics analysis, immune gene analysis, applied bird conservation, comparative genomics, and tropical field work (optional).

Person specification:

Prior experience in computer coding (e.g., Python, SLiM), AI modelling, and understanding of evolutionary or conservation genetics / genomics is desirable. Good teamwork skills are essential.

Entry requirements

At least UK equivalence Bachelors (Honours) 2:1. English Language requirement (Faculty of Science equivalent: IELTS 6.5 overall, 6 in each category).

Acceptable first degree: Evolutionary Biology, Genetics, Conservation Biology

Funding

ARIES studentships are subject to UKRI terms and conditions. Successful candidates who meet UKRI’s eligibility criteria will be awarded a fully-funded studentship, which covers fees, maintenance stipend (£20,780 p.a. for 2025/26) and a research training and support grant (RTSG). A limited number of studentships are available for international applicants, with the difference between 'home' and 'international' fees being waived by the registering university. Please note, however, that ARIES funding does not cover additional costs associated with relocation to, and living in, the UK, such as visa costs or the health surcharge.

ARIES is committed to equality, diversity, widening participation and inclusion in all areas of its operation. We encourage applications from all sections of the community regardless of gender, ethnicity, disability, age, sexual orientation and transgender status. Projects have been developed with consideration of a safe, inclusive and appropriate research and fieldwork environment. Academic qualifications are considered alongside non-academic experience, with equal weighting given to experience and potential.

Please visit www.aries-dtp.ac.uk for further information.

References

Speak, S.A., Birley, T., Bortoluzzi, C., Clark, M.D., Percival-Alwyn, L., Morales, H.E., van Oosterhout, C., 2024. Genomics-informed captive breeding can reduce inbreeding depression and the genetic load in zoo populations. Molecular Ecology Resources, 24(7), e13967.
https://doi.org/10.1111/1755-0998.13967

van Oosterhout, C., Supple, M.A., Morales, H.E., Birley, T., Tatayah, V., Jones, C.G., Whitford, H.L., Tollington, S., Ruhomaun, K., Groombridge, J.J. et al., 2025. Genome engineering in biodiversity conservation and restoration. Nature Reviews Biodiversity, pp.1-13.
https://doi.org/10.1038/s41586-024-08458-x

Femerling, G., van Oosterhout, C., Feng, S., Bristol, R.M., Zhang, G., Groombridge, J.J., Gilbert, M.T.P. & Morales, H.E., 2023. Genetic load and adaptive potential of a recovered avian species that narrowly avoided extinction. Molecular Biology and Evolution, 40(12), msad256. https://doi.org/10.1093/molbev/msad256

Silver, L. W., Farquharson, K. A., Peel, E., Gilbert, M. T. P., Belov, K., Morales, H. E., and Hogg, C. J. 2025. Temporal loss of genome‐wide and immunogenetic diversity in a near‐extinct parrot. Molecular Ecology, 34(9), e17746. https://doi.org/10.1111/mec.17746

van Oosterhout, C., 2024. AI-informed conservation genomics. Heredity, 132(1), pp.1-4. https://www.nature.com/articles/s41437-023-00666-x

AI-powered insights into susceptibility of parrots to viral infection, CASE project with Ebony Forest and Durrell Wildlife Conservation Trust / Jersey Zoo (VANOOSTHERHOUT_UEA_ARIES26)

Project description

Entry requirements

Funding

References