A Probabilistic Model of Neutral and Selective Dynamics of Protein Network Evolution

Abstract

Abstract

Comparative approaches in genomics have long relied on rigorous mathematical models of sequence evolution. Such models provide the basis for formulating and solving well-defined computational problems, in turn yielding key insights into the evolutionary processes acting on the genome. Analogous model-based approaches for analyzing biological networks are still under development. Here we describe a model-based approach for estimating the probability of network rewiring events during evolution. Our method builds on the standard duplication-and-divergence model and incorporates phylogenetic analysis to guide the comparison of protein networks across species. We apply our algorithm to study the evolution of functional modules and unconstrained network regions in seven available eukaryotic interactomes. Based on this analysis we identify a map of co-functioning protein families whose members participate in strongly conserved interactions and form major complexes and pathways in the eukaryotic cell. The proposed approach provides principled means for inferring the probability of network rewiring events, enabling insights into the conservation and divergence of protein interactions and the formation of functional modules in protein networks.