Classical tree view of cell cycle data (Spellman, et al MolBiolCell 9, 3273)

VxInsight topography of cell-cycle data G1 S M

Strong similarities show relationships among clusters

Genome-scale datasets available in yeast: Essential genes Essential genes since 1998 Several microarray datasets Protein-protein interactions How can we learn more from this analysis?

Stationary-phase genes are not essential Essential genes Newly identified essential genes Ribosome ridge Essential genes as a function of gene expression: what does it tell us? Assumptions; biases; potentially new, useful targets, how cells “protect” themselves; evolution, etc.

Are G1-regulated genes clustered during exit from stationary phase? Comparison of gene-expression datasets to test hypotheses Cell cycleExit 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 Cell cycle 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

Protein -interaction networks as a function of gene expression Schwikowski’s data Ito full dataset Interactions common to both Genes common to both 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 accepted or whether the data should be combined

A B Interactions in ribosome ridge C Similarity in gene expression Exit from stationary phase’ Ribosome ridge. 290 genes Conclusion: Two-hybrid methods don’t “see” interactions between ribosomal proteins 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: Identification of biases and assumptions in our methods Faster and broader evaluation of the datasets Novel insights into biological processes  new and more focused questions

The Biological Process: the yeast cell cycle

Ribosome ridge Stationary-Phase genes VxInsight clustering of exit from stationary phase data: T=0, 15, 30, 45, and 60 minutes after re-feeding