Genome tools pass big test in fruit flies

September 01, 1999

August 31, 1999
—With the effort to sequence the entire human genome speeding toward completion, some researchers are now focusing their energy on developing the next generation of tools that can be used to extract valuable scientific information from the unabridged human genetic sequences.

Howard Hughes Medical Institute investigators, Allan Spradling at the Carnegie Institution of Washington, and Gerald Rubin at the University of California, Berkeley, and more than two dozen colleagues have developed and used several types of tools to analyze the genome of the fruit fly Drosophila melanogaster, which has provided a treasure trove of information about genes and their function.

"When the Human Genome Project started eight years ago, the organizers had the foresight to sequence a number of other organisms to serve as models and as interpretive guides to the much larger human genome," said Rubin.

"The kinds of analyses we can do on the Drosophila genome, and on the genomes of other model organisms, will enable us to get far more information more quickly from the human genome effort," added Spradling.

In 1982, Spradling and Rubin discovered how to use a transposable element, a piece of DNA that can jump from place to place in the genome, to engineer changes in the fly’s genome. The two researchers turned this piece of DNA—the P element—into a powerful tool for creating large numbers of mutant fruit flies, each containing a mutation in a single gene.

Many laboratories have been using this technique to generate mutant flies, which Rubin and Spradling have collected under the aegis of the Berkeley Drosophila Genome Project (BDGP), a program backed by HHMI. BDGP makes the fly strains available to researchers around the world, and scientists have used the flies to characterize more than 250 Drosophila genes.

In a research article published in the September, 1999 issue of the journal Genetics, Rubin, Spradling and their colleagues present the results of generating and characterizing 1,052 mutant fly strains that contain P element disruptions in more than 25 percent of Drosophila’s 3,600 vital genes. The researchers examined each fly strain for obvious changes from wild-type flies, including phenotypes such as lethality, near-lethality and other readily apparent physical abnormalities.

"Our goal was not to identify every gene we could, but to show that it was feasible to generate large numbers of P element mutations randomly throughout the Drosophila genome and to use them to find new genes," said Rubin. "We did that." More sophisticated examinations—for behavioral deficits or biochemical changes—should turn up even more genes since only about a third of genes show phenotypes we would have recognized in the current study, he added. Since the Drosophila genome is thought to contain more than 12,000 genes, Rubin and Spradling have concluded that the P element approach, which has been successful in characterizing a large number of fly genes, merits an even larger trial.

Of course, the P element disruption technique is not the only tool that researchers are developing to analyze genomes. In a second research article that will appear in the same issue of Genetics, Rubin, Spradling and more than two dozen colleagues at several institutions in the United States and England, used a wide variety of tools to probe a 2.9 million base pair region of the Drosophila genome.

"We chose a region of the Drosophila genome that had been characterized in substantial detail already from a genetic perspective, partly though the use of P elements, and for which we now have a sequence. The idea, then, was to apply all the available tools to this wealth of genetic and molecular information in an attempt to understand this piece of DNA—what genes are there, what they do, how are they organized—as completely as possible," said Rubin.

"One very interesting finding for evolutionary biology came out of this analysis," explained Rubin, "Genes with mutant phenotypes are far more likely to have counterparts in other organisms, including humans, than are genes with no known mutant phenotype."

Their analysis also provided a test for the tools being developed by computational biologists. For example, researchers have obtained gene sequence information from dozens of organisms and have drawn some general conclusions about what those genes "look" like when buried within the millions of consecutive As, Ts, Gs, and Cs, the four bases that make up an organism’s chromosomes.

Computational biologists have used this information to create software programs that scan large stretches of raw sequence data—the exact order of the four bases in DNA—and predict where functional genes might lie within the large stretches of DNA that have not been well studied. Members of the BDGP’s informatics team organized a workshop at a recent international meeting of computational biologists where they compared the experimentally generated data with the predictions generated by several different software programs.

"This kind of competition showed that some programs worked better than others, but the important outcome is that people will be able to take these results and improve their software," said Rubin. "We will have a better set of computational tools as a result."

Howard Hughes Medical Institute

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