"Whereas it might have taken 7,000 experiments to verify a thousand genes, with our method it now will take only about 1,500," said Michael R. Brent, Ph.D., associate professor of computer science at Washington University in St. Louis.
Brent developed TWINSCAN, one of the programs used to predict genes by looking at both the alignment between the two genomes and statistical patterns in the individual DNA sequences of each genome. DNA is comprised of four varieties of bases (commonly abbreviated as A, T, G, C). The myriad different arrangements of these base pairings -- or sequences -- are the instructions for making proteins, which in turn give physiological traits such as color, hair type, muscle variations, etc. DNA looks like a long string of unintelligible pairings, but programs such as Brent's highlight the genes in the sequence, making sense of it for biomedical researchers.
Simply put, what Brent and his colleagues did was develop computer programs that use patterns of evolutionary conservation -- DNA sequences that have not changed since the common ancestor of mouse and man -- to improve the accuracy of gene prediction. They identified a set of 1,019 predicted novel mouse genes and showed that genes in this set can be verified experimentally with a very high success rate.
A paper describing the results was published in the Feb. 4, 2003, issue of the Proceedings of the National Academy of Scie
Contact: Tony Fitzpatrick
Washington University in St. Louis