This project is offered as part of the University of Dundee 4-year MRC DTP Programme “Quantitative and Interdisciplinary approaches to biomedical science”. This PhD programme brings together leading experts from the School of Life Sciences (SLS), the School of Medicine (SoM) and the School of Science and Engineering (SSE) to train the next generation of scientists at the forefront of international science. The outstanding biomedical research at the University of Dundee was recognised by its very high rankings in REF 2014, with Dundee rated as the top University for Biological Sciences in the UK. A wide range of projects are available within this programme crossing exceptional strengths in four key areas: Infection and Disease; Responses to Cellular Stresses; Development, Stem Cells and Neurobiology; and Big Data and Translation. All students on this programme will receive training in computational biology, mathematical biology and statistics to equip with the quantitative skills in tackling complex biological questions. In the 1st year, students will carry out 3 rotation projects prior to selection of the final PhD project.
One of the unanticipated outcomes of population based genome sequencing has been the finding that genes involved in the regulation of many genes are mutated at high frequency in tissue specific cancers. This is the case for SWI/SNF –related chromatin remodelling enzymes which are mutated in about 20% of all tumors and at higher frequencies in cancers of specific tissues. To understand how these genes function we have engineered STEM cell lines in which specific subunits of these enzymes can be degraded rapidly and specifically. In this project, genomics techniques such as chromatin immunoprecipitation and RNA sequencing will be used to gain insight into how these complexes function. Analysis of this data requires adaption of existing bioinformatics tools to time series datasets. It is also possible to intersect this data with a large number of existing datasets and apply machine learning to discover factors influencing where these complexes function. By combining the use of genome engineering in stem cells with genomics and advanced informatics approaches, the project aims to discover new epigenetic pathways affected by the loss of these tumor suppressors. In the long run these may provide new routes for the development of cancer therapies.
Recent work from the lab can be found in the following references:
1:Farnaby W, Koegl M, Roy MJ, Whitworth C, Diers E, Trainor N, Zollman D,Steurer S, Karolyi-Oezguer J, Riedmueller C, Gmaschitz T, Wachter J, Dank C, Galant M, et al., BAF complex vulnerabilities incancer demonstrated via structure-based PROTAC design. Nat Chem Biol. 2019Jul;15(7):672-680. doi: 10.1038/s41589-019-0294-6. Epub 2019 Jun 10. Erratum in: Nat Chem Biol. 2019 Jul 2;:. PubMed PMID: 31178587; PubMed Central PMCID:PMC6600871.
2: Sundaramoorthy R, Hughes AL, El-Mkami H, Norman DG, Ferreira H, Owen-Hughes T.Structure of the chromatin remodelling enzyme Chd1 bound to a ubiquitinylatednucleosome. Elife. 2018 Aug 6;7. pii: e35720. doi: 10.7554/eLife.35720. PubMedPMID: 30079888; PubMed Central PMCID: PMC6118821.
3: Lukauskas S, Visintainer R, Sanguinetti G, Schweikert GB. DGW: an exploratory data analysis tool for clustering and visualisation of epigenomic marks. BMCBioinformatics. 2016 Dec 13;17(Suppl 16):447. doi: 10.1186/s12859-016-1306-0.PubMed PMID: 28105912; PubMed Central PMCID: PMC5249015.