Background: >98% of the human genome does not code for proteins and is sometimes referred to as the ‘dark matter’ of the genome. However, large areas of this ‘non-coding genome’ are critical for normal regulation of genes. Our knowledge of effect of variants in the non-coding genome on human health is severely limited.
The aim of this project is to reveal the contribution of variants in the non-coding regions of the genome to human genetic disorders.
Objectives and methods:
1. Understanding the landscape of variability of the regulome: The student will define ‘regulomes’ for a range of human tissues by integrating publicly available epigenomic, regulatory, and transcriptomic data. Then areas of the these regulomes that are most depleted for genetic variations in the humans will be ranked using population variant frequencies and integrated with evolutionary conservation data. We hypothesise that this will predict regions of the regulomes enriched for disease-causing variants in patients.
2. Identifying human disease-causing variants in the regulome: The student will interrogate whole genome databases from patients (e.g. the 100,000 Genomes project) to identify variants within the critical regions of the regulome curated in Objective 1. Correlations with clinical features, information from the segregation of the variants within families and the predicted/known functions of the regulatory region will be used to prioritise the variants that are highly likely to be responsible for the patients’ diseases.
3. Studying the functional impact of disease-causing regulatory variants: Depending on the predicted impact of the variant, targeted (e.g. QPCR) or high-throughput (e.g. RNASeq, Hi-C, dropSeq) assays will be performed either using patient samples or cell lines. This will allow functional interrogation of the variants. Finally these results will be linked back with the clinical data.
Outcome: We expect this project to make major contributions to our understanding of the role of variants in the non-coding genome on human health and disease. The project is expected to result in high-impact publication(s).
Training: The student will benefit from working in a multi-disciplinary environment at the genomic, clinical, and functional interface. Prof Banka and Dr Ellingford will provide training in the analysis/clinical correlation of whole genome data. Prof Eyre and Dr Orozco will train in generation of regulomes and analysis of high-throughput functional assays. This will be an ideal opportunity for someone looking to develop strong foundations in Medical Genomics and gain experience in cutting edge bioinformatic and wet-lab approaches.
https://www.research.manchester.ac.uk/portal/siddharth.banka.html
https://www.research.manchester.ac.uk/portal/en/researchers/stephen-eyre(371e1ee8-b1ed-4f51-b2c3-f7d02e6afd27).html
https://www.research.manchester.ac.uk/portal/en/researchers/gisela-orozco(2bf29dce-2d02-46b0-9a85-148a505aa37a).html
Entry Requirements
Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in an appropriate area of science, engineering or technology.
How to Apply
To be considered for this project you MUST submit a formal online application form - full details on how to apply can be found on the MRC Doctoral Training Partnership (DTP) website www.manchester.ac.uk/mrcdtpstudentships
Applicants interested in this project should make direct contact with the Primary Supervisor to arrange to discuss the project further as soon as possible.
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/
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