NEW YORK (GenomeWeb News) – In a paper appearing online today in Science, an international research team reported that they have created a genome-wide genetic interaction map for the budding yeast Saccharomyces cerevisiae.
The team used synthetic genetic interaction data to create a functional map for the model organism. As expected, they found that genes involved in similar processes tend to cluster together. By looking at the connections between genes and functional sub-groups, the researchers were able to get clues about gene function that are expected to inform future studies of yeast and other organisms.
"[G]enetic interaction maps provide a model for understanding the link between genotype and phenotype and for outlining the general principles of complex genetic interaction networks, which play a key role in governing inherited phenotypes, including human disease," senior author Charles Boone, a molecular genetics researcher at the University of Toronto, and his co-workers wrote.
And, they found, by overlaying information on chemical-gene interactions, the network approach appears to hold promise for finding drug targets and understanding how drugs affect the cell.
Just 20 percent or so of S. cerevisiae's 6,000 genes are essential for growth. By systematically knocking out or impairing pairs of budding yeast genes and looking at the fitness effects, if any, researchers can identify functionally related or redundant genes — an approach dubbed synthetic genetic array, or SGA.
For the current study, Boone and his team screened 1,712 yeast genes (representing roughly 5.4 million gene pairs), identifying some 170,000 or so gene-gene interactions.
The researchers then mapped these interactions to create a network containing clusters of functionally related genes, demonstrating that these clusters could be used to help predict the functions of known and previously uncharacterized genes.
Along with information on gene function, they showed that such networks offer insights into everything from regulatory relationships between genes to the rate at which genes in the network evolve.
When they compared the genetic interaction map with protein-protein interaction data generated through yeast two hybrid, affinity purification-mass spectrometry, or protein-fragment complementation experiments, the team found between 10 percent and 20 percent of interacting proteins also interacted genetically — though a much smaller fraction of interacting genes also interact physically.
Finally, by exposing about 4,700 of their S. cerevisiae gene deletion mutants to hundreds of chemicals, the researchers began bringing together information on gene-gene and chemical-genetic interactions — work that they say should help in understanding how various chemicals affect the cell.
"Because chemical perturbations mimic genetic perturbations, the genetic network should be useful for predicting the cellular targets of bioactive molecules," Boone and his co-workers wrote.