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  Enhanced variant interpretation for the discovery of mechanisms underpinning Ophthalmic genomic disorders

   Faculty of Biology, Medicine and Health

  ,  Applications accepted all year round  Self-Funded PhD Students Only
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Manchester United Kingdom Bioinformatics Data Analysis Genetics Ophthalmology Food Sciences Software Engineering Statistics

About the Project

This project will utilize large genomic sequencing datasets from the 100,000 genomes project and the UK BioBank to understand how genomic variation impacts the development and function of cells vital for correct vision. We will develop and undertake bioinformatics and functional investigations to better interpret genomic variation in this context and to better understand how the normal development and function of the retina can be disrupted. We will focus on the function and development of the neurosensory retina. This project is highly relevant to individuals with an enthusiasm to identify novel causes of genomic diseases, and for individuals interested in elucidating how genomic variation may contribute to an individual’s vision and/or for individuals who are motivated to translate findings from their research into diagnostic and clinical medicine.

Entry Requirements

Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area/subject. Candidates with previous laboratory experience are particularly encouraged to apply.

How To Apply

For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select the appropriate subject title.

For international students, we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences.

Equality, Diversity and Inclusion

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/”

Biological Sciences (4) Computer Science (8) Food Sciences (15) Mathematics (25) Medicine (26)

Funding Notes

Applications are invited from self-funded students. This project has a Band 2 fee. Details of our different fee bands can be found on our website (View Website).

References

Ellingford, J., Barton, S., Bhaskar, S., Williams, S., Sergouniotis, P., O'Sullivan, J., Lamb, J., Perveen, R., Hall, G., Newman, W., Bishop, P., Roberts, S., Leach, R., Tearle, R., Bayliss, S., Ramsden, S., Nemeth, A. H. & Black, G. (2016). Whole genome sequencing increases molecular diagnostic yield compared with current diagnostic testing for inherited retinal disease. Ophthalmology 123:1143–1150.

Conte, I., Hadfield, K. D., Barbato, S., Carrella, S., Pizzo, M., Bhat, R. S., Carissimo, A., Karali, M., Porter, L. F., Urquhart, J., Hateley, S., O'Sullivan, J., Manson, F. D., Neuhauss, S. C., Banfi, S., & Black, G. C. (2015). MiR-204 is responsible for inherited retinal dystrophy associated with ocular coloboma. PNAS. 112(25), E3236–E3245. https://doi.org/10.1073/pnas.1401464112

Green DJ, Sallah SR, Ellingford JM, Lovell SC, Sergouniotis PI. (2020). Variability in Gene Expression is Associated with Incomplete Penetrance in Inherited Eye Disorders. Genes. doi: 10.3390/genes11020179

Ellingford, J., Horn, B., Campbell, C., Arno, G., Barton, S., Tate, C., Bhaskar, S., Sergouniotis, P., Taylor, R. L., Carss, K. J., Raymond, F. L., Michaelides, M., Ramsden, S. C., Webster, A. R. & Black, G. (2018). Assessment of the incorporation of CNV surveillance into gene panel next-generation sequencing testing for inherited retinal diseases. (2018). Journal of Medical Genetics 55:114-121.

Charlie Rowlands, Huw B Thomas, Jenny Lord, Htoo A Wai, Gavin Arno, Glenda Beaman, Panagiotis Sergouniotis, Beatriz Gomes-Silva, Christopher Campbell, Nicole Gossan, Claire Hardcastle, Kevin Webb, Christopher O’Callaghan, Robert A Hirst, Simon Ramsden, Elizabeth Jones, Jill Clayton-Smith, Andrew R Webster, Genomics England Research Consortium, Andrew GL Douglas, Raymond T O’Keefe, William G Newman, Diana Baralle, Graeme CM Black, Jamie M Ellingford. Comparison of in silico strategies to prioritize rare genomic variants impacting RNA splicing for the diagnosis of genomic disorders. doi: 10.22541/au.160157595.59675486.

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 About the Project

 About the Project  Funding Notes  References
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