modularity

Beltrao P, Cagney G & Krogan NJ 2010 Quantitative genetic interactions reveal biological modularity. Cell 141:739-745.

• new technologies have increased the size and scope of biological data
• systems approaches have broadened the view of how these components are interconnected
• we discuss how quantitative mapping of genetic interactions enhances our view of biological systems, allowing their deeper interrogation across different biological scales

• biological research has largely focused on characterizing the components that make up systems of interest
• only recently, with the advent of systems biology, has the emphasis shifted toward integrative studies that aim to describe how observed biological phenomena depend on the interplay of these components

• the study of genetic interactions (or epistasis) has a strong theoretical basis in genetic linkage studies
• a genetic interaction between two genes implies that they impact each other's functions
• genetic interactions between two loci can be mapped by measuring how the phenotype of an organism lacking both genes (double mutant) differs from that expected when the phenotypes of the single mutations are combined

• the development of high-throughput genetic interaction screening was made possible by the creation of deletion libraries for single nonessential genes in the budding yeast Saccharomyces cerevisiae
• an important landmark was the first implementation, termed synthetic genetic array (SGA), where each S. cerevisiae single gene deletion strain was mated to produce arrays of double-mutant strains

• a decade ago, Hartwell stated:
• "cell biology is in transition from a science that was preoccupied with assigning functions to individual proteins or genes, to one that is now trying to cope with the complex sets of molecules that interact to form functional modules"
• one clear example of this modular organization is the assembly of protein macromolecular structures (complexes) from smaller modular groups of proteins that cooperate to carry out biochemical tasks
• although datasets comprising only physical protein interactions tend to arrange into distinct (albeit modular) complexes, these in turn are often connected by negative epistatic interactions

• evolutionary changes are an important source of time-dependent variation, casting light on how nature uses genes and proteins to solve a variety of biological problems
• studies of genetic interactions in different species have begun to elucidate how DNA mutations generate phenotypic variation across species
• early cross-species genetic interaction studies have shown us that genetic interactions diverge quickly
• despite this high divergence rate, within-module genetic interactions (i.e., within protein complexes) exhibit marked conservation
• these genetic results are consistent with data from other experimental methods showing that protein complexes are highly conserved across species
• whereas their regulation by gene expression or by posttranslational modifications appears to change quickly
• these results are consistent with the notion that modularity increases evolutionary plasticity by allowing the cell to reuse modules to adapt to changing environments