Organization principles in genetic interaction networks

Abstract

Understanding how genetic modifications, individual or in combinations, affect phenotypes is a challenge common to several areas of biology, including human genetics, metabolic engineering, and evolutionary biology. Much of the complexity of how genetic modifications produce phenotypic outcomes has to do with the lack of independence, or epistasis, between different perturbations: the phenotypic effect of one perturbation depends, in general, on the genetic background of previously accumulated modifications, i.e., on the network of interactions with other perturbations. In recent years, an increasing number of high-throughput efforts, both experimental and computational, have focused on trying to unravel these genetic interaction networks. Here we provide an overview of how systems biology approaches have contributed to, and benefited from, the study of genetic interaction networks. We focus, in particular, on results pertaining to the global multilevel properties of these networks, and the connection between their modular architecture and their functional and evolutionary significance.