"When studying the genome of any organism, be it yeast, worm, fly or human, scientists are faced with a problem -- the incredible number of genes," explains Susan Mango, Ph.D., an HCI investigator and leader of the research team. Mango's research centered on a common garden-variety nematode worm, C. elegans, which shares many genes in common with humans. She explains that although worms appear simple, the worm genome is comprised of 20,000 genes. The human genome has over 30,000 genes. "When you look at the numbers, it becomes very clear that the old way -- studying one gene at a time -- is too slow. It becomes a problem of scale, with high throughput the only answer."
Mango's team used a unique process that combines microarray technology with computational approaches to predict, based on probabilities, where in the genome a particular regulatory sequence might be found. With co-authors Wanyuan Ao, Ph.D.; Jeb Gaudet, Ph.D.; James Kent, Ph.D.; and Srikanth Mattumu, Mango searched C. elegans's genome to find certain "punctuation marks" in the code that might be regulatory sequences responsible for the growth and development of the worm's foregut, or pharynx. They were able to identify a total of seven candidate gene sequences; after testing, they discovered that of the seven, five proved to be bona fide regulatory sequences.
"Up to now, identifying transcription factor target genes has been a challenge to biologists. Using our unique algorithm, the Improbizer algorithm developed by James Kent, one of our collaborators, we were able to pick out regulatory s