Scientists at the University of California at San Francisco have developed a way to quickly measure hundreds of thousands of interactions between genes in parallel.

Sometimes it helps to have a “cheat sheet” when you are working on a problem as difficult as deciphering the relationships among hundreds of thousands of genes. At least that's the idea behind a powerful new technique developed by Howard Hughes Medical Institute (HHMI) researchers to analyze how genes function together inside cells.

The new approach is called epistatic miniarray profiles (E-MAP). The scientists who developed it — HHMI investigator Jonathan S. Weissman, HHMI postdoctoral fellow Sean Collins, and colleague Nevan Krogan, who are all at the University of California, San Francisco — have used E-MAP to unravel a key process that prevents DNA damage during cellular replication.

In the first use of this technique researchers tested for 200,000 different gene interactions.

Using the new technique, which enabled them to rapidly analyze more than 200,000 gene interactions, the researchers have made a discovery that helps explain how cells mark which sections of DNA have been replicated during cell division. If the marking process goes awry, DNA becomes damaged as it is copied.

Hundreds of yeast colonies can be grown in the same agar plate and their speed of growth can be measured and analyzed automatically with software. Since yeast share many genes with humans these studies will turn up interactions that provide insight into human biology as well.

The key to E-MAPs is the ability to eliminate single genes or gene pairs and then analyze how each change impacts the growth of yeast colonies. Each yeast colony grows in a tiny spot on an agar plate, and each plate holds around 750 colonies. Software makes it possible to determine the growth rate of each colony and then compare the effect on growth of eliminating one gene at a time with the effect when two genes are simultaneously disabled.

The scientists looked only at the genes involved in maintaining and replicating chromosomes.

The end result is a database that details the functional relationship of each gene to every other gene studied, revealing cases where the product of one gene depends on a second gene in order to carry out its cellular functions. In this experiment, Weissman's team looked at 743 yeast genes involved in basic chromosome biology. “We wanted to look at everything that had to do with chromosome biology, including DNA replication, DNA repair, transcription to RNA, and so on,” said Weissman. “These are very basic cellular processes that are conserved from yeast to man.”

But this same technique could be applied to other subsets of genes to study other aspects of cellular metabolism. This is the way biology is going: Rather than studying one or two things at once thousands of genes or interactions get measured at a time. Automated equipment and methods for working with large numbers of very small samples allows massive parallelism and orders of magnitude more data collected per experiment.