Michael R. Brent, Ph.D., associate professor of computer science, has applied software developed in his Washington University laboratory that sorts through the maize of genetic information and finds predicted sequences.
"Normally, you get one 600 to 700 base pair sequence in a reaction, but under certain conditions, we've figured out how to get more than one sequence out of a single sequencing reaction," said Brent. "In most cases, people would throw out a reaction with more than one sequence but we've developed software that allows us to sort out the mess and figure out the different sequences."
Writing in the April issue of Genome Research, Brent and collaborators at Baylor College of Medicine, led by Richard A. Gibbs, Ph.D., director of Baylor's Human Genome Sequencing Center, discuss related techniques in genome analysis, while noting that the recent publication of a third mammalian genome, the brown rat, suggests a new approach to genome annotation is needed. Sequencing genomes has proven to be so labor-intensive and expensive that researchers fear little headway will be made in future genome analyses. Thus, the need for automated analysis.
The researchers describe their method of predicting genes in the brown rat using Brent's TWINSCAN software, which predicts the existence of genes by looking at two genomes in parallel and homing in on statistical patterns in the individual DNA sequences of each genome. The recently completed sequencing of the brown rat genome was conducted primarily using another program called Ensembl.
Brent and his collaborators tested 444 TWINSCAN-predicted rat genes that showed significant homology, or correspondence, to known human genes implicated in disease. Ensembl and other
Contact: Tony Fitzpatrick
Washington University in St. Louis