Data from: A global genetic interaction network maps a wiring diagram of cellular function

INTRODUCTION: Genetic interactions occur when mutations in two or more
genes combine to generate an unexpected phenotype. An extreme negative or
synthetic lethal genetic interaction occurs when two mutations, neither
lethal individually, combine to cause cell death. Conversely, positive
genetic interactions occur when two mutations produce a phenotype that is
less severe than expected. Genetic interactions identify functional
relationships between genes and can be harnessed for biological discovery
and therapeutic target identification. They may also explain a
considerable component of the undiscovered genetics associated with human
diseases. Here, we describe construction and analysis of a comprehensive
genetic interaction network for a eukaryotic cell. RATIONALE: Genome
sequencing projects are providing an unprecedented view of genetic
variation. However, our ability to interpret genetic information to
predict inherited phenotypes remains limited, in large part due to the
extensive buffering of genomes, making most individual eukaryotic genes
dispensable for life. To explore the extent to which genetic interactions
reveal cellular function and contribute to complex phenotypes, and to
discover the general principles of genetic networks, we used automated
yeast genetics to construct a global genetic interaction network. RESULTS:
We tested most of the ~6000 genes in the yeast Saccharomyces cerevisiae
for all possible pairwise genetic interactions, identifying nearly 1
million interactions, including ~550,000 negative and ~350,000 positive
interactions, spanning ~90% of all yeast genes. Essential genes were
network hubs, displaying five times as many interactions as nonessential
genes. The set of genetic interactions or the genetic interaction profile
for a gene provides a quantitative measure of function, and a global
network based on genetic interaction profile similarity revealed a
hierarchy of modules reflecting the functional architecture of a cell.
Negative interactions connected functionally related genes, mapped core
bioprocesses, and identified pleiotropic genes, whereas positive
interactions often mapped general regulatory connections associated with
defects in cell cycle progression or cellular proteostasis. Importantly,
the global network illustrates how coherent sets of negative or positive
genetic interactions connect protein complex and pathways to map a
functional wiring diagram of the cell. CONCLUSION: A global genetic
interaction network highlights the functional organization of a cell and
provides a resource for predicting gene and pathway function. This network
emphasizes the prevalence of genetic interactions and their potential to
compound phenotypes associated with single mutations. Negative genetic
interactions tend to connect functionally related genes and thus may be
predicted using alternative functional information. Although less
functionally informative, positive interactions may provide insights into
general mechanisms of genetic suppression or resiliency. We anticipate
that the ordered topology of the global genetic network, in which genetic
interactions connect coherently within and between protein complexes and
pathways, may be exploited to decipher genotype-to-phenotype
relationships.