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Genetic interactions are the key to understanding complex traits
Date:1/22/2009

Jan. 23, 2009 -- In recent years, genetic studies have uncovered hundreds of DNA variations linked to common diseases, such as cancer or diabetes, raising the prospect that scientists can gauge disease risk based on information in an individual's genome. But the variations identified to date only account for a small percentage typically one to three percent of the overall genetic risk of any common disease.

This disappointment has led geneticist Barak Cohen, Ph.D., of Washington University School of Medicine in St. Louis, to suggest that scientists need to get a better handle on the ways genes interact to influence disease risk.

"For diseases that are major health problems, many different genetic variants combine to affect an individual's risk," says Cohen. "The problem is that we as scientists are really lousy at predicting how these variations interact to determine whether an individual is likely to develop a common disease or respond to a particular drug."

This reality begs the question: Is it possible to tease apart a complex genetic trait to reveal the precise genetic variations that have combined to produce it? Yes, Cohen and his group report in the Jan. 23 issue of Science. If the research can be replicated, it suggests that scientists need better statistical models and other tools to understand genetic interactions.

The researchers turned to a simple organism, the yeast Saccharomyces cerevisiae, culled from North American oak trees and vineyards, where it grows naturally, to find their answer.

"This was a test case," Cohen explains. "If we can't dissect a complex genetic trait that occurs naturally in yeast and show how multiple genes interact to produce a particular trait, then there's no hope for doing it in humans."

The researchers probed the genome of yeast to find the DNA variations that determine the efficiency with which the yeast undergo sexual reproduction, a process ca
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Contact: Caroline Arbanas
arbanasc@wustl.edu
314-286-0109
Washington University School of Medicine
Source:Eurekalert  

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