Abstract
Interest in the evolution of protein-protein and genetic interaction networks has been rising in recent years, but the lack of large-scale high quality comparative datasets has acted as a barrier. Here, we carried out a comparative analysis of computationally predicted protein-protein interaction (PPI) networks from five closely related yeast species. We used the Protein-protein Interaction Prediction Engine (PIPE), which uses a database of known interactions to make sequence-based PPI predictions, to generate high quality predicted interactomes. Simulated proteomes and corresponding PPI networks were used to provide null expectations for the extent and nature of PPI network evolution. We found strong evidence for conservation of PPIs, with lower than expected levels of change in PPIs for about a quarter of the proteome. Furthermore, we found that changes in predicted PPI networks are poorly predicted by sequence divergence. Our analyses identified a number of functional classes experiencing fewer PPI changes than expected, suggestive of purifying selection on PPIs. Our results demonstrate the added benefit of considering predicted PPI networks when studying the evolution of closely related organisms.
Highlights
Physical and genetic interactions are fundamental to the understanding of cell biology [1,2,3]
Expectations must be formulated with respect to the effects of mutations on the inferred proteinprotein interaction (PPI) network: in the case of controlling for bias associated with protein Interaction Prediction Engine (PIPE), how do random mutations affect PIPE’s inferences? And, with respect to a null hypothesis for network evolution, how much change in a PPI network is expected given random mutation? We provide null expectations for changes in the inferred PPI network using simulated proteomes from the four non-cerevisiae yeasts
It is clear that the bulk of proteins are inferred to experience very few PPI changes, but the long tail of the distribution suggests a subset of proteins experiencing many changes
Summary
Physical and genetic interactions are fundamental to the understanding of cell biology [1,2,3]. Changes in protein-protein interactions (PPIs) can have important consequences for organismal fitness: several disease causing mutations are known to disrupt PPIs [4, 5], and single nucleotide polymorphisms (SNPs) associated with a number of diseases tend to occur in sites predicted to mediate PPIs [6]. Given the potential importance of PPIs to fitness, there is increasing interest in understanding the evolution of protein-protein and genetic interaction networks, as well as in clarifying the role of network architecture in determining the pace and trajectory of molecular evolution. Knight et al demonstrated that the pleiotropic effects of a single adaptive mutation can be understood, at least in part, by its effects on protein co-regulatory networks [10]
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