Classical tree view of cell cycle data (Spellman, et al. 1998. MolBiolCell 9, 3273) VxInsight topography of cell-cycle data G1 M S Strong similarities show relationships among clusters How can we learn more from this analysis? Genome-scale datasets available in yeast: •Essential genes •Essential genes since 1998 •Several microarray datasets •Protein-protein interactions Essential genes as a function of gene expression: what does it tell us? Ribosome ridge Stationary-phase genes are not essential Essential genes Newly identified essential genes Assumptions; biases; potentially new, useful targets, how cells “protect” themselves; evolution, etc. Comparison of gene-expression datasets to test hypotheses Are G1-regulated genes clustered during exit from stationary phase? Cell cycle Exit from stationary phase What might this say? Exit from stationary phase is either: 1) not a synchronous process with respect to the cell cycle. 2) a cell-cycle process that requires a subset of cell-cycle genes Exit from stationary phase •If this is true, the two processes may be sensitive to different toxins. •This has important implications in treatment of infectious diseases if the infectious agent spends a great deal of time in the quiescent state •This may also help us understand why unculturable microorganisms can’t exit stationary phase Cell cycle Protein -interaction networks as a function of gene expression Schwikowski’s data Interactions common to both Ito full dataset Conclusions: 1. Interactions do not generally follow expression patterns 2. Few interactions common to both datasets 3. Need to look at specific clusters, known interactions to determine whether one dataset should be Genes common to both accepted or whether the data should be combined A Exit from stationary phase’ Ribosome ridge. 290 genes B Similarity in gene expression Conclusion: Two-hybrid methods don’t “see” interactions between ribosomal proteins C Interactions in ribosome ridge In fact, there may not be many interactions among ribosomal proteins – so this may be the strongest evidence for the lack of false positives in this analysis Summary: Visualization of the datasets enables a more intuitive approach and speeds hypothesis development Visual comparison of genome-scale datasets supports: Faster and broader evaluation of the datasets Identification of biases and assumptions in our methods Novel insights into biological processes new and more focused questions The Biological Process: the yeast cell cycle VxInsight clustering of exit from stationary phase data: T=0, 15, 30, 45, and 60 minutes after re-feeding Ribosome ridge Stationary-Phase genes