Computer-Generated Comparative Maps Developed At Cornell Promise To Speed Up Slow Process Of Comparing Genomes

Now, Cornell University researchers have come up with a way to do the comparison step in a few hours on a computer. In early tests, a computer-generated comparison of the genomes of rice and maize (corn) closely matched a similar map made by hand, and even suggested some relationships that had not shown up in the handmade map.

Debra Goldberg, Cornell graduate student in applied mathematics, developed the new method in collaboration with Susan McCouch, Cornell professor of plant breeding, and Jon Kleinberg, Cornell assistant professor of computer science. Goldberg described their work at the Gene Order Dynamics, Comparative Maps and Multigene Families (DCAF) workshop held September in Sainte-Adèle, Quebec, and will present a later version at the Plant and Animal Genome IX conference in San Diego in January. Their paper, "Algorithms for Constructing Comparative Maps," appears in Comparative Genomics (David Sankoff and Joseph H. Nadeau, Eds., Kluwer Academic Publishers, 2000). A software implementation of the new method soon will be available to geneticists.

"The point of this isn't just to compare rice and corn, but to be able to do it with any two species," Goldberg says. "Ideally we'd like to be able to find new evolutionary pathways."

Every so often, as reproductive cells divide, genes and segments of chromosomes get shuffled around. One chromosome meets another and pieces of DNA are moved or swapped. If those particular cells then happen to be involved in reproduction, the new arrangement is passed on to the next generation and may spread through the population. It doesn't happen very often, but over evolutionary time scales many such events show up. Related species descended from a common ancestor have many genes in common, but they occur in different arrangements. A strand of DNA that used to be on chromosome 2 in some common ancestor ends up on chromosome 10, in between two pieces that used to belong to ancestral chromosomes 3 and 5. The relocated genes often continue to do the same jobs, and often several genes move together, retaining their ancestral order along a segment of DNA.

By comparing genomes, scientists can trace the evolutionary paths, and there are immediate practical applications. If it's known that genes A and B are near each other in the rice genome, and the location of gene A in maize also is known, then a comparative map could help locate gene B in maize. In plant breeding, such a discovery could help to breed corn with better disease resistance or improved nutritional value. In medicine, clues from the genome of the mouse are being used to help find genes associated with human diseases.

The idea of comparative mapping is to align genes in the order they are found along the chromosomes of the first or "base" species with those found in the same order on a single chromosome of the second or "target" species. The raw data consists of ordered lists of the genes and gene markers of both species that have been identified in "wet lab" experiments.

At the simplest level, a computer could look at each gene or marker of the base species, find where it is (on which arm of which chromosome) on the target genome, and label it accordingly. But geneticists want to step back to get a larger view, identifying segments of the base genome that contain arrays of genes that also are found together on the target genome. The catch is what McCouch calls "noise" in the data: the target genome can contain long arrays of genes that look like those on the base genome except that there are a few extra genes here and there that come from somewhere else in the genome. How does the computer decide whether or not to ignore the out-of-place genes? When are two similar linear arrays of genes close enough to be called a match?