( A new technique for analyzing the netwo...)Technique offers new view of dynamic biological landscape

A new technique for analyzing the network of genetic interactions promises to change how researchers study the dynamic biological landscape of the cell. The technology, which is called epistatic mini array profiles (E-MAP), has already been used to assign new functions to known genes, to uncover the roles of previously uncharacterized proteins, and to define how biochemical pathways and proteins interact with one another.

E-MAP will enable new understanding of how genes and proteins function in the cell, said Jonathan S. Weissman, a Howard Hughes Medical Institute (HHMI) investigator at the University of California, San Francisco (UCSF) and leader of the team that developed the technique. For example, E-MAPs of human gene interactions could enable researchers to optimize drug treatments to patients' genetic backgrounds. It might also be possible to use E-MAP to develop effective combinations of antiviral drugs that target proteins produced by interacting genes. Such a strategy would help to prevent these genes from acting together to compensate for an attack on just one protein, said Weissman.

The researchers, led by Weissman, Maya Schuldiner, a post-doctoral fellow working in his lab, and Nevan Krogan at the University of Toronto, described initial studies of E-MAP in yeast in the November 4, 2005, issue of the journal Cell. Weissman and his colleagues at UCSF collaborated on the studies with researchers at the University of Toronto.

Previous techniques for analyzing epistatic interactions -- how the activity of one gene affects that of another -- involved altering single genes and analyzing their impact on growth in combination with all other genes in the yeast genome. "The one-to-one method has been an extremely powerful way of studying biological systems," said Weissman. "But we wanted to approach such analyses in a systematic way and to use the new generation of high-throughput technology to quantitatively explore large numbers
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Source:Howard Hughes Medical Institute

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