A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for ~75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.

According to what we term the balance hypothesis, an imbalance in the concentration of the subcomponents of a protein-protein complex can be deleterious. If so, there are two consequences: first, both underexpression and overexpression of protein complex subunits should lower fitness, and second, the accuracy of transcriptional co-regulation of subunits should reflect the deleterious consequences of imbalance. Here we show that all these predictions are upheld in yeast (Saccharomyces cerevisiae). This supports the hypothesis that dominance is a by-product of physiology and metabolism rather than the result of selection to mask the deleterious effects of mutations. Beyond this, single-gene duplication of protein subunits is expected to be harmful, as this, too, leads to imbalance. As then expected, we find that members of large gene families are rarely involved in complexes. The balance hypothesis therefore provides a single theoretical framework for understanding components both of dominance and of gene family size.

Many disease states result from gene overexpression, often in a specific genetic context. To explore gene overexpression phenotypes systematically, we assembled an array of 5280 yeast strains, each containing an inducible copy of an S. cerevisiae gene, covering >80% of the genome. Approximately 15% of the overexpressed genes (769) reduced growth rate. This gene set was enriched for cell cycle-regulated genes, signaling molecules, and transcription factors. Overexpression of most toxic genes resulted in phenotypes different from known deletion mutant phenotypes, suggesting that overexpression phenotypes usually reflect a specific regulatory imbalance rather than disruption of protein complex stoichiometry. Global overexpression effects were also assayed in the context of a cyclin-dependent kinase mutant (pho85Delta). The resultant gene set was enriched for Pho85p targets and identified the yeast calcineurin-responsive transcription factor Crz1p as a substrate. Large-scale application of this approach should provide a strategy for identifying target molecules regulated by specific signaling pathways.