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Mapping Genetic Networks in Yeast
Summary: Charles Boone is mapping yeast genetic networks on a large scale to assign gene function. In particular, he is identifying genes responsible for causing vegetative, yeast-like fungi to grow in a filamentous form, which can augment the fungus's virulence. A detailed understanding of the genes that control these processes will provide new insights into fungal pathogenicity and should identify targets for the development of novel antifungal drugs. Dr. Boone plans to disseminate his findings to the research community through an open database.
One of the major projects in my lab is investigating the basic principles of genetic interaction networks. This work stems from the finding that most yeast genes (about 80 percent, about 5,000 in total) are not required for viability, which suggests that multiple compensatory pathways regulate essential processes. One way to test for and identify these compensatory pathways is to make double mutants and examine their phenotypes systematically.
In particular, synthetic lethality defines a relationship in which mutants with a single mutation in two different genes are viable but that combining the mutations in a double mutant results in lethality. Identifying synthetically lethal double mutant combinations highlights genes whose products buffer one another and impinge on the same essential process—defining a functional relationship between the genes and their corresponding pathways. Thus, large-scale mapping of synthetic lethal networks should generate a global map of functional relationships. My group has established the methodology and infrastructure to generate this global genetic interaction map for yeast. We are applying an automated approach to yeast genetics, referred to as synthetic genetic array analysis, to enable systematic isolation of yeast double mutants and subsequent large-scale mapping of genetic interaction networks.
Analysis of our first major network, containing approximately 1,000 genes and 4,000 interactions, revealed some general principles of genetic networks. Whereas some genes show only a few interactions and others, such as essential genes, appear to be highly connected hubs on the network, the average gene shows about 30 genetic interactions, which by extrapolation suggests there are about 100,000 synthetic lethal genetic interactions in the yeast network. To put this in perspective, there are 1,000 essential genes in which a single mutation causes cell death and about 100,000 ways to generate the same phenotype through a digenic complex interaction.
The genetic network is highly complex, but the interactions are not random; genes with similar roles tend to interact with one another. Thus, the network is also highly ordered and reflects gene and cellular function. Moreover, genes with a similar function often show the same pattern of genetic interactions. In particular, genes within the same pathway show very similar genetic interaction patterns; clustering of genetic interactions therefore sorts gene sets into functional pathways and complexes. Thus, the position and connectivity of a gene on the genetic network are predictive of its function.
From a comparison of genetic interaction networks and protein-protein interaction networks, it is clear that some genetic interactions occur between genes within the same essential pathway and overlap with protein-protein interactions. However, most genetic interactions occur among genes in different pathways and identify those that buffer one another in the cell. Thus, genetic interactions add functional information to protein-protein interaction networks.
When considering inherited diseases, a major challenge is to identify the combination of natural genetic variants that modulate the activity of specific disease-associated pathways. One way to address this challenge is to map allele combinations or genetic networks that control specific phenotypes. Synthetic lethal genetic interaction maps may provide a key to predicting which allele combinations control pathway activity and generate detectable phenotypes. In other words, synthetic lethality defines a relationship in which the presence of one gene allows an organism to tolerate genetic variation in a different gene. Thus, genetic interaction maps provide valuable insights into the concept of genetic robustness—that is, how an organism is able to buffer or tolerate the phenotypic consequences of genetic variation.
Chemical Genetics
Because a deletion mutant models the physiological effects of an inhibitory compound that blocks the action of the corresponding deleted gene product, yeast genetic interaction maps are related to yeast chemical-genetic interaction maps, which can be created by scoring the sensitivities of single mutants to bioactive compounds. In a proof-of-principle study, we showed that compounds whose chemical-genetic profile resembles the synthetic lethal genetic interaction profile of a specific gene may very well target the product of the identified gene or its corresponding pathway. We are comparing our synthetic lethal and chemical-genetic interaction networks computationally and predicting the target pathways of specific compounds.
Systematic Analysis of Fungal Dimorphism
Systematic phenotypic and genetic analysis of the yeast Saccharomyces cerevisiae deletion mutant collection has proven incredibly powerful because it enables researchers to examine comprehensively mutations in each gene for specific phenotypes. To further expand the use of the yeast-deletion mutant collection, we developed a system for moving all the deletion alleles from S288C, the standard laboratory strain genetic background, to sigma1278b, a wild-type background, which is capable of filamentous growth, a complex developmental process of relevance to fungal pathogenesis.
Many fungal species can switch between two distinct morphological forms, a single-cell yeast form and a multicellular filamentous form. The transition between the two forms is termed the dimorphic switch; this developmental program is often initiated by environmental stimuli. The dimorphic transition has clinical relevance, given that the virulence of the most common human fungal pathogen Candida albicans is associated with its capacity to reversibly switch between the single-cell and filamentous forms. With rates of systemic Candida infections (candidiasis) on the rise and mortality rates of more than 40 percent, it has become increasingly important to study the mechanisms that lead to dimorphic switching. Because S. cerevisiae is also dimorphic, it provides a powerful model organism in which to study this developmental program. We have moved virtually all deletion-mutant alleles from the S288C genetic background into the filamentation-competent S. cerevisiae sigma1278b background. The abilities to form invasive filaments and fungal biofilms and to adhere to inert surfaces are all associated with the onset of systemic candidiasis. Sigma1278b is capable of forming each of these developmental states; the complete set of sigma1278b deletion-mutant strains is being studied systematically for defects in these processes. The result will be a comprehensive genetic analysis of fungal dimorphism. Data generated from the analyses in S. cerevisiae will provide functional insights into homologous genes in C. albicans, which are expected to be important for pathogenicity.
Last updated September 2008
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