multiple genetic interaction experiments provide complementary information useful for gene function prediction多个基因相互作用实验提供补充信息用于基因功能预测.pdfVIP

Multiple Genetic Interaction Experiments Provide Complementary Information Useful for Gene Function Prediction Magali Michaut1¤, Gary D. Bader1,2,3* 1The Donnelly Centre, University of Toronto, Toronto, Ontario, Canada, 2 Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, 3 Department of Computer Science, University of Toronto, Toronto, Ontario, Canada Abstract Genetic interactions help map biological processes and their functional relationships. A genetic interaction is defined as a deviation from the expected phenotype when combining multiple genetic mutations. In Saccharomyces cerevisiae, most genetic interactions are measured under a single phenotype - growth rate in standard laboratory conditions. Recently genetic interactions have been collected under different phenotypic readouts and experimental conditions. How different are these networks and what can we learn from their differences? We conducted a systematic analysis of quantitative genetic interaction networks in yeast performed under different experimental conditions. We find that networks obtained using different phenotypic readouts, in different conditions and from different laboratories overlap less than expected and provide significant unique information. To exploit this information, we develop a novel method to combine individual genetic interaction data sets and show that the resulting network improves gene function prediction performance, demonstrating that individual networks provide complementary information. Our results support the notion that using diverse phenotypic readouts and experimental conditions will substantially increase the amount of gene function information produced by genetic interaction screens. Citation: Michaut