Alzheimer's disease

Site corrals data to predict gene behavior

PRINCETON (US)—A new Web site created by researchers at Princeton University offers one-stop shopping for genetic information—and could yield clues to DNA’s role in aging and disease.

The site links computers and genomics, the field of biology concerned with mapping organisms’ entire DNA and understanding how genes interact to keep an organism healthy or cause disease. Dubbed the Human Experimental/Functional Mapper, or HEFalMp, the site focuses on discerning connections among genes, biological processes, and diseases to help scientists determine which relationships are most important.

“The scientific community has produced millions of points of genetic data in recent years, but has not achieved an equivalent understanding of how genes work,” says Olga Troyanskaya, the Princeton professor who led the project. “We need to translate this into knowledge about disease.”

The team’s paper on its methodology was published in the May issue of the journal Genome Research.

The site is based on the principle of “functional mapping,” shorthand for mapping out the tangled web of relationships among genes, based on how they work together in cellular function. A single gene, for example, might help a cell become heart or brain tissue, but a cell’s overall function emerges from the interactions of many genes.

Understanding these functional relationships is key to developing new medical treatments, since most medications target proteins—the primary product of genes. Proteins are complex molecules that serve as cogs in the cellular machinery or, in the case of disease, wrenches in the works.

Genomics researchers seek to understand which genes and proteins are involved in certain aspects of cell function. Working out how genes keep cells running normally helps scientists understand what goes wrong in the case of a harmful genetic mutation. Discovering a link between a gene and a disease can tell researchers what cellular processes are involved in the disease, which in turn fingers other genes involved in those processes as potential culprits.

But discerning these connections is no easy feat. Discoveries of genes resemble early discoveries of Egyptian hieroglyphs, but while Egyptologists struggled to decode the meaning of around 2,000 hieroglyphs, genomics researchers are faced with an estimated 20,000 to 25,000 human genes that could potentially interact with each other in 300 million different ways.

With so many genes and so many possible avenues of inquiry, predicting which genes and relationships are important in certain diseases, and therefore worthwhile to study, presents an enormous challenge involving a lot of guesswork.

This is where computers come in handy. The computer program created by Troyanskaya sorts through 350 sets of genome data from thousands of separate experiments.

“Knowing which genes are most likely to be involved helps researchers choose where to focus,” Troyanskaya says. “The program is a magnifying glass,” she adds, “that shows you what is trustworthy and what is relevant.”

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