Biological systems are robust to perturbations, with many genetic, stochastic and environmental challenges having no or little phenotypic consequence. However, the extent of this robustness varies across individuals, for example the same mutation or treatment may only affect a subset of individuals. The overall objective of this project is to understand the cellular and molecular mechanisms that confer this robustness and why it varies across individuals.
We will address three specific questions:
1. Why do inherited mutations have different outcomes in different individuals, even when they are genetically identical and share a common environment?
2. What are the mechanisms during development that confer robustness to mechanical deformation?
3. How can the loss of robustness be exploited to specifically kill cancer cells?
To address the first two questions, we will use live imaging procedures that we have developed that make the C. elegans embryo a unique animal system to link early inter-individual variation in gene expression and cellular behaviour to later variation in phenotypes. To address the third question, we will apply our understanding of genetic robustness and genetic interaction networks in model organisms to the comprehensive analysis of cancer genome datasets. The predictions from these hypothesis-driven computational analyses will then be evaluated using wet-lab experiments.
Understanding and predicting variation in robustness is both a fundamental challenge for biology and one that is central to the development of personalised and predictive medicine. A patient does not want to know the typical outcome of a mutation or treatment; they want to know what will actually happen to them. The work outlined here will contribute to our basic understanding of robustness and its variation among individuals, and it will also directly tackle the problem of predicting and targeting variation in robustness as a strategy to kill tumour cells.
Fields of science
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