Aimée Dudley Group

The Dudley group integrates the questions and methods of systems biology with those of genetics to probe the interactions among genetic and environmental factors in complex traits and disease. Using yeast as a model system, the group is seeking to understand how genetic information is integrated, coordinated and transmitted through molecular, cellular and physiological networks. A major goal is to identify biological and environmental targets that can be used to treat and prevent disease.

Research Overview

As the costs of gathering molecular-level data about biological systems continue to drop, researchers face the challenge of analyzing vast stores of information to understand how biological networks function in health and disease. Aimée Dudley’s group at ISB is seeking to meet this challenge through a branch of systems biology known as systems genetics. Instead of examining the effects of genes one by one, she and her colleagues study how networks of genes interact to shape the traits of organisms. These investigations can reveal, for example, how each person’s unique genetic sequences can affect susceptibility to a disease or response to a medical therapy. They also can determine how the interactions among a limited number of genes give can give rise to a very broad array of biological traits.

To understand gene interactions at this level, researchers must study large numbers of individuals that are genetically distinct. Dudley’s group uses yeast as a model system, since yeast have less than one-third as many genes as humans yet exhibit many of the same biochemical pathways as more complex organisms. Dudley and her collaborators have gathered a collection of more than 200 strains of yeast isolated from six continents, including yeast used in wine making, sake production, and baking; yeast infecting immunocompromised people; and yeast from natural sources such as palm fronds, oak trees and insects. Using a wide range of robotic technologies, the lab generates and automatically assays thousands of recombinant progeny to measure the responses of these organisms to combinations of genetic and environmental perturbations. These responses then are analyzed to probe the interactions between genes, and the results are used to build models of genetic systems.

One focus for the group has been how genetic variation affects posttranscriptional mechanisms of gene regulation -- and specifically the consequences of variation for protein-RNA complexes called P-bodies that regulate translation and mRNA degradation. Dudley’s work on P-bodies grew out of a broader interest in the mechanisms of gene regulation and a collaboration with computer scientists, including Daphne Koller’s group at Stanford University. An algorithm the group has developed identifies collections of genes whose expression is statistically correlated with mutations in regulatory factors.

Approaches developed by the Dudley group have direct applications in humans. For example, in genetic networks, modifications in one gene can modify the effects of another gene. Manipulating these modifier genes has the potential to restore the normal biological function of a disease-causing gene. This approach offers hope for the millions of people born annually around the world who have disease-causing mutations in specific genes.

As with much of the work being done at ISB, research in Dudley’s lab is inherently collaborative. Besides working with many of the other faculty members at ISB, she works with groups at Washington University in St. Louis, Boston University and the University of British Columbia on such topics as automated image analysis, mathematical modeling and microfluidics-based technologies. In particular, the adoption and adaptation of new technologies have been critical components of her research. This approach requires a unique blend of biological understanding and engineering expertise.

Research Focus

New technologies now permit the study of genetic interactions on a genome-wide scale. In a collaboration with Daniel Segrè at Boston University, Dudley’s group has developed computerized models of genetic interactions in yeast that reflect current understandings of biological networks. They measured the growth rates of 465 yeast strains in which specific genes had been deleted under 16 different environmental conditions. They then compared these results with the predictions of the model. Differences between the experimental results and predictions of the model were used to refine both the experiments and the model. Building on this work, Segrè, Dudley, and their collaborators have begun the construction of a computerized map of all the phenotypic effects of deleting genes that encode metabolic enzymes. This map is expected to produce a much richer view of the interactions among multiple genes and metabolic processes.

Source: Snitkin ES, Dudley AM, Janse DM, Wong K, Church GM, Segrè D. 2008. Model-driven analysis of experimentally determined growth phenotypes for 465 yeast gene deletion mutants under 16 different conditions. Genome Biology 9(9):R140.