Cells -either from unicellular organism such as Saccharomyces cerevisiae to multicellular ones such as humans- are constantly sensing the environment for signals and stresses. They must do so in order to decide if they can continue their cell cycle, need to activate a defence response, or must commit to apoptosis. This implies a complicated coordination of gene expression at different levels: transcription, translation and protein degradation. Single-gene knock out experiments in yeast showed that a fifth of genes are essential for its survival, while double-gene knock out experiments demonstrated that concurrent deletion of non-essential genes may be lethal as well. We have shown in the past that essentiality and synthetic lethality are related to participation in protein complexes and metabolic pathways, which are the reason of gene expression coordination. Now, we are interested in studying the consequences of gene deletions (or loss-of-function mutations) for this overall gene expression coordination, to better understand how deletions/mutations lead to phenotype differences. In the first half of the project, we propose the quantitative modelling of the whole yeast gene expression system, and the analysis of perturbations caused by gene deletions. Saccharomyces cerevisiae is one of the most studied model organisms because of a series of interesting features: 1) it is unicellular; 2) the yeast genome only contains 6,000 genes; 3) there is no alternative splicing; and, 4) it is easy to grow in the lab. This has allowed its wide use in biotechnology and synthetic biology, with industrial applications ranging from biofuels to food production. The project will enhance our understanding of the complexity of gene expression coordination, and open the door to cutting edge biotechnological innovations. In the second part of the project, we are interested in scaling up the model to multicellular organisms (i.e. human), which could help us to understand development programmes and origin of diseases. Human genetic/molecular research has hugely expanded since the advent of high-throughput methodologies, especially next-generation sequencing. Therefore, the availability of data will permit us to test multiple hypotheses; from changes occurring during cell differentiation, to the systemic consequences of specific mutations. The student will use a variety of computational approaches including data mining, network analyses, modelling optimisation and single-cell transcriptomics. The project builds on the existing knowledge and complementary expertise of the different laboratories involved. It represents an ideal opportunity for an individual with a keen interest in mathematical and statistical approaches applied to deciphering Biology.
https://www.research.manchester.ac.uk/portal/david.talavera.html
http://www.bioinf.manchester.ac.uk/schwartz/
https://www.research.manchester.ac.uk/portal/pawel.paszek.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.
Applicants interested in this project should make direct contact with the Primary Supervisor to arrange to discuss the project further as soon as possible.
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 BBSRC DTP website www.manchester.ac.uk/bbsrcdtpstudentships
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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