About the Project
This project will investigate early cell fate decisions in stem cell populations during early embryonic development [1,2], using a combination of quantitative analysis of gene expression, RNA velocity, and statistical modelling of cell state transitions. We have developed a Bayesian modelling approach  and successfully applied this to data from key transcription factors . This project extends this approach further to high dimensional transcriptomic data. Models will be calibrated against single-cell time-course data to quantify the cell state transition rates, and how these are constrained by genetic regulatory interactions. Model predictions will then be tested with in vivo and in vitro experiments.
The student will receive training in relevant ‘wet lab’ techniques, such as cell culture and microscopy/image analysis, while working with existing bioinformatic data from mice and computational tools for modelling and analysis of cell state transitions. The student will experimentally test predictions from the model. Depending on the student’s interests, the project can then be taken into several further directions, such as working with human cell lines, or quantifying spatial variation of gene expression in stem cell colonies (e.g. using RNAscope).
This project is a great opportunity for students with previous experience in physics, mathematics/statistics or bioinformatics and interest in both computational and experimental research. The student will benefit from integration in an active biomedical research environment at the Centre for Regenerative Medicine and interaction with a cross-institutional network of collaborators.
Training in professional and research skills will be tailored to the individual student’s background and training needs. The student’s critical understanding of primary data and research literature will be advanced through regular group meetings and journal clubs at the Centre for Regenerative Medicine. The student will also have the opportunity to engage with the mathematical and systems biology research community at other departments in Edinburgh and St Andrews.
This 4 year PhD project is part of a competition funded by EASTBIO BBSRC Doctoral Training Partnership (DTP) http://www.eastscotbiodtp.ac.uk/how-apply-0.
EASTBIO Application, Equality, Diversity and Inclusion (EDI) survey and Reference Forms can be downloaded via http://www.eastscotbiodtp.ac.uk/how-apply-0
Please send your completed EASTBIO Application Form and EDI survey along with a copy of your academic transcripts to [Email Address Removed] before the deadline.
You should also ensure that two references have been sent to [Email Address Removed] by the deadline using the EASTBIO Reference Form.
Please refer to UKRI website and Annex B of the UKRI Training Grant Terms and Conditions for full eligibility criteria.
Dias, A., Lozovska, A., Wymeersch, F.J., Nóvoa, A., Binagui-Casas, A., Sobral, D., Martins, G.G., Wilson, V. and Mallo, M., 2020. A Tgfbr1/Snai1-dependent developmental module at the core of vertebrate axial elongation. Elife, 9, p.e56615
Ruske LJ, Kursawe J, Tsakiridis A, Wilson V, Fletcher AG, Blythe RA, Schumacher LJ. Coupled differentiation and division of embryonic stem cells inferred from clonal snapshots. Physical Biology (in press, arXiv preprint 2004.12902)
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