Conserved rules govern genetic interaction degree across species

Using a combination of physiological and evolutionary properties of genes, we built models that successfully predicted the genetic interaction degree of S. cerevisiae genes. Importantly, a model trained on S. cerevisiae gene features and degree also accurately predicted interaction degree in the fission yeast Schizosaccharomyces pombe, suggesting that many of the predictive relationships discovered in S. cerevisiae also hold in this evolutionarily distant yeast. In both species, high single mutant fitness defect, protein disorder, pleiotropy, protein-protein interaction network degree, and low expression variation were significantly predictive of genetic interaction degree. A comparison of the predicted genetic interaction degrees of S. pombe genes to the degrees of S. cerevisiae orthologs revealed functional rewiring of specific biological processes that distinguish these two species. Finally, predicted differences in genetic interaction degree were independently supported by differences in co-expression relationships of the two species.Our findings show that there are common relationships between gene properties and genetic interaction network topology in two evolutionarily distant species. This conservation allows use of the extensively mapped S. cerevisiae genetic interaction network as an orthology-independent reference to guide the study of more complex species.Most genes are not essential for eukaryotic life under standard laboratory conditions, which may reflect that organisms are highly buffered from genetic and environmental perturbations [1]. However, rare combinations of singly benign genetic variation can lead to synergistic effects, such as synthetic lethality, where mutations in two genes, neither of which is lethal independently, combine to generate an inviable double-mutant phenotype [2]. Because natural variations that distinguish two people occur relatively frequently [3] and complex genetic interactions may underlie most individual phenotypes [1]