Pat Brown admits to grand schemes. When he set up his lab at Stanford in 1988, he wanted to compare a million people's genes to determine which ones make some people, say, wallflowers and others cheerleaders. And this offbeat idea was only one of many, though sweeping studies of gene activity were impossible at that time. Instead, scientists used to focus on a favorite gene and deduce all manner of supposed functions. But then Brown devised a way to monitor all of an organism's genes at one time to see which ones are active. He likens the old approach to looking at a couple of pixels on a screen and trying to deduce a movie's plot. His invention made all the pixels visible at the same time.
To study gene activity on this grand scale, Brown arrayed snippets of an organism's genes on a glass slide. He then exposed the slide to fluorescently labeled RNA from the same organism to light up those genes that had been active in a particular environment or developmental stage. Affymetrix, a company founded in 1991, had a similar idea, but Brown was unaware of the competition.
Making the DNA microarray was straightforward, but a few years passed before comprehensive collections of genes became available. Since then, Brown's group and collaborators have systematically monitored changes in yeast gene expression as yeast responds to environmental changes or enters a new developmental stage. For example, they have identified several hundred genes that become active at specific times between one cell division and the next. Such experiments have helped scientists view genes in a new light. Instead of just classifying them by the chromosomes they are on, they now associate them with scripts that choreograph different functions.
After the Human Genome Project began, collections of human genes gradually became available, enabling Brown's group to study tumor development and regression. The researchers have now studied patterns of gene expression in more than 500 types of tumor, finding marked differences among ones that are normally grouped together. They are now analyzing thousands of human cancers to develop a system for classifying them by gene expression. Such a system should make it possible for clinicians to differentiate, say, prostate tumors that are likely to metastasize from those that pose no immediate threat. Similar studies are shedding light on abnormal expression patterns associated with a variety of other diseases, such as scleroderma or certain types of infection.
Sophisticated data analysis is needed for such studies. "At first, people were saying that microarray experiments would be ridiculous because you would get so much data that you couldn't make sense of it," Brown recalls. But the yeast experiments revealed that unknown genes often change their expression in sync with known genes, giving clues to their functions and the times at which they come into play. "So we had a general approach to organizing the data that allowed us to take advantage of its systematic nature," Brown says.
The group devised many of the methods now used to systematically interpret and visualize microarray data. One of the tricks was to make movies that show gene expression patterns changing over time. "The fact that you can look at a whole movie enables you to see how coordinated and ordered the whole [developmental] program is, which you can't easily see by just looking at little bits of it," Brown says. By analyzing such programs, Brown is deducing the rules that govern the expression of each yeast gene and the processes that control the production, processing, transport, and breakdown of the corresponding proteins.
Brown has always believed in sharing data in a timely manner. So in 2000, he pioneered open access to the scientific literature by founding, with Harold Varmus and Michael Eisen, the Public Library of Science (PLoS). PLoS has launched several high-quality electronic scientific journals that anyone can read, print, or distribute at no cost. Thus, students and teachers, who usually cannot afford subscriptions, can keep up with what's new in science. "PLoS has brought credibility to open-access publishing, and helped move it into the mainstream," Brown says. "Most of the established publishers are moving more and more toward open access, and the major scientific funding agencies are steadily moving toward mandating it."
But what happened to the idea of looking for human genes that determine subtle personality traits? "I set it aside for practical reasons—it's a huge organizational challenge," Brown admits. "But I recently started brainstorming with a scientific buddy of mine about how we might pull something like this off."