Human inherited retinal dystrophies (IRDs) result from mutations in over 200 different genes, many of them first implicated by the Leeds Vision Research Group (eg Panagiotou E et al 2017, AJHG 100:960-968; El-Asrag M et al 2015, 96:948-54). By comparison with other inherited human conditions they are relatively well understood. Genetic approaches have implicated defects in several well characterised pathways, including phototransduction, cilia formation, pre-mRNA splicing and the recycling of the 11-cis-retinal chromophore. Screening the known genes solves between 50 and 70% of cases, a remarkably high success rate for such a genetically heterogeneous condition. However, it is likely that the common IRD genes have now been found. Further significant improvement in screening success rate is therefore dependent on improving our ability to detect new classes of mutations, present in known genes, which are being missed by existing screening protocols.
This project will use massively parallel sequencing and cutting edge bioinformatics to identify new variants implicated in human retinal diseases, particularly targeting those classes of mutations that are missed or poorly detected by exome screening. To identify these classes of mutation we will use WGS on pre-screened, unsolved cases recruited through Leeds ophthalmic genetics clinics. Cases from other consortia with which the Leeds Vision Research Group collaborates (BRIDGE-SPEED, 100,000 Genomes project, European Retinal Degeneration Consortium) will also be included in the analysis. RNAseq on blood will also be used in selected cases to determine whether this pinpoints a splicing defect or other mechanism in a known IRD gene in a proportion of unsolved cases. Potential causative variants highlighted in these analyses will be subjected to functional testing as appropriate, depending on the nature of the variant and protein and the level of information available in the existing literature.
The student will be based in the section of Ophthalmology and Neuroscience (OPNE), School of Medicine, University Of Leeds. The appointed student will have the opportunity to learn and carry out bioinformatics analyses of next generation sequencing, both genome and transcriptome, and to study the expression patterns and function of the implicated genes and proteins using a wide range of molecular and cellular biology techniques. Depending on initial findings, work may progress to tissue culture, confocal microscopy, live cell imaging, transcript analysis, genome editing and protein modelling studies.
This project is available immediately to both Home/EU rate applicants and International applicants who are able to self-fund their studies. Students must be able to provide the appropriate level of fees based on their fee status plus laboratory consumables costs per year. This is in addition to the provision of personal living expenses.
You should hold a first degree equivalent to at least a UK upper second class honours degree in a relevant subject.
Candidate whose first language is not English must provide evidence that their English language is sufficient to meet the specific demands of their study, the Faculty minimum requirements are:
• British Council IELTS - score of 6.5 overall, with no element less than 6.0
• TOEFL iBT - overall score of 92 with the listening and reading element no less than 21, writing element no less than 22 and the speaking element no less than 23.
Applicants with sufficient funding must still undergo formal interview prior to acceptance in order to demonstrate scientific aptitude and English language capability.
How to apply
Applications can be made at any time. To formal apply for this project applicants should complete a Faculty Application form using the link below https://medicinehealth.leeds.ac.uk/downloads/download/78/fmh_scholarship_application_form_2018_2019
and send this alongside a full academic CV, degree certificates and transcripts (or marks so far if still studying) to the Faculty Graduate School at [email protected]
We also require 2 academic references to support your application. Please ask your referees to send these references on your behalf, directly to [email protected]
Any queries regarding the application process should be directed to [email protected]
Potential applicants are welcome to contact Prof Chris Inglehearn at [email protected]
with informal enquiries about this research project.