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A systems approach linking genotype and environment to phenotype: oxidative stress response mechanisms in fission yeast (PhenOxiGEn)
Start date: Oct 1, 2008, End date: Mar 31, 2012 PROJECT  FINISHED 

Cellular protection against oxidative damage is relevant to ageing and numerous complex diseases. We plan to use fission yeast as a model organism to gain a systems-level understanding of the oxidative stress response and obtain insights into the interplay of variable genotype, phenotype, and environment. To this end, the four participants will pursue a range of multi-disciplinary and complementing approaches that will be integrated with innovative computational methods for a unified view of a complete regulatory system. We will create a genetically and phenotypically diverse library of yeast strains from crosses of three independent parental strains with distinct stress sensitivities. The parental and segregant strains will be genotyped and phenotyped (in stressed and unstressed cells) using state-of-the-art sequencing, tiling array, and proteomics approaches, thus providing a rich basis for genome-wide association studies and computational modelling. Genetic, functional genomic, and proteomic approaches, along with computational methods, will be applied in parallel to develop protein and gene interaction networks that will further support the modelling efforts. Predictions based on the modelling will be validated with targeted wet-lab experiments to test and refine the mathematical models. Intimate inter-dependency between experimental and bioinformatic approaches based on close collaboration among participants with different expertise will be vital to develop successful models predicting the regulatory response to oxidative stress. The relative simplicity of yeast cells, which can be grown under tightly controlled conditions and with defined genetic and environmental perturbations, promises a thorough and deep understanding of the oxidative stress response system. Concepts developed in the proposed study will provide a valuable framework for research into more complex systems such as response networks and association studies in human cells.

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