The topography of a worm's genetic activity may prove the key to understanding the functions of genes, according to researchers at Stanford's School of Medicine.

A new visualization tool they developed allows researchers to fly through mountains of genes, search for a selected gene and zoom in for a closer look.

The new tool is a three-dimensional topographical map that turns what scientists know about worm genetic activity into a landscape that researchers can explore. The map is the result of 553 genetic experiments on the nematode worm Caenorhabditis elegans, performed in collaboration with 30 different laboratories from around the world. Associate professor Stuart Kim and researchers at Stanford and Sandia National Laboratories pooled the data from the 553 experiments and, using computer software and a variety of visualization techniques, created the three-dimensional gene expression map.

Unlike a standard genome map, a gene expression map focuses on gene activity ­ when genes turn on and start producing proteins, and when they turn off. For this type of map, genes are placed spatially according to activity rather than where they are physically located on a chromosome. Researchers have known for more than a year where genes were located on the worm's chromosomes, but the functions of most of those genes remained a mystery. The C. elegans genome contains more than 19,000 genes, 53 percent of which are homologous to human genes. And yet less than 6 percent had been studied using traditional genetic research, Kim said.

"We now know the magnitude of our ignorance and it is big," he said. Because coordinated regulation often implies that genes may have similar functions, researchers have needed a tool that could help them see the patterns of coordinated gene activity. The new map brings together data on all 19,232 genes in the worm's genome and gives researchers a chance to visualize how those genes work together.

"I often see studying genes as being similar to learning how to read a foreign language," Kim said. "Right now we know the total number of words in the language, but we don't know what they all mean nor how they fit together to form sentences, paragraphs and stories."

The gene expression map revealed a number of surprising biological patterns, Kim said. For example, even though the genes involved in DNA synthesis, RNA synthesis, protein synthesis and lipid synthesis are not part of one common biochemical pathway, they appear as one mountain. Kim said this occurs because all three pathways must be active in order to make new cells as the worm grows. Seeing such groupings can help researchers better understand the complex functions of many genes.

The map was created using the computer software VxInsight that took data from a gene expression database showing which genes are expressed together. Genes that became active in similar conditions were placed closer together on the map than genes that express under other circumstances. With VxInsight, each gene became like a boulder or tree in a landscape. Genes associated with a specific activity formed hills and mountains in the gene expression topography. An explanation of the map and the data used to create it appears in the Sept.14 edition of Science. The map, accompanying data and copies of the software used to create it are also available online at http://cmgm.stanford.edu/~kimlab/topomap/c._elegans_ topomap.htm.

On the map, the height of a mountain indicates the number of genes associated with that activity. The width of the mountain's base indicates the amount of functional correlation between genes. Tall, thin mountains, for example, indicate a large number of genes that are expressed in a very similar pattern.

To add to the visualization, researchers can search the map for specific genes, specific gene activities, or correlated expressions. Researchers can then fly thorough the map, examining where genes are clustered and where they are more isolated, zoom in on genes that match the search and look at other genes located nearby. With every search lies the potential of igniting new ideas for anything from drug development to cures for cancer and other diseases. The key lies in researchers' abilities to begin to un- ravel the complex language of genetic function.

"If genes are the words in the language we are trying to understand," said Kim, "then this map is like being able to present the world with a dictionary."

Kim's collaborators at Stanford include James Lund, PhD; Monica Kiraly; Kyle Duke; Min Jiang, PhD; and Andreas Eizinger, PhD. He also collaborated with Brian Wylie, PhD, from Sandia National Laboratories and George Davidson, PhD, from Stanford Medical Informatics.