Factoring Out Common Genes To Find Unknown Ones
ProgressiveCynic writes "Dr. Michael Brent has designed a novel algorithm for discovering unknown genes by factoring out commonalities between the genomes of different species. Using the algorithm to compare the genomes of mice and men, he and his collegues have already discovered over a thousand new genes.
So why didn't he just use ZIP?"
So why didn't he just use ZIP?"
As for the molecular biology aspects, the abstract states that they verified the existence of "112 previously unknown homologs of known proteins" , at least in some cases using RT_PCR (which suggests that the gene is real since it is expressed as mRNA). Apparently the "1019" refers to 907 additional predictions for which they have only computer-based speculations. Clearly it's nice to have some predictions to work from, but that's all this is.... wish I could supply more info but I can't get to the full text article without a subscription.
It also occurs to me that if one was drowning, yelling "Help! I'm drowning and I lost my bikini top" would probably be m
This is an interesting paper, but I have no idea why it made it into the mainstream press. The concept of using comparative genomics to identify ORFs is not novel; however, the results of using this tecnique on the mouse a human genomes are interesting. Now that we have the genomes of all of these organisms(mouse, human, fly, worm, fish coming soon) the largest obstacle is just sorting out the genes from all of the crap dna accumulated over the years. These researchers found a large group of genes that hadn't been previously identified by conventional methods designed for analyzing just one genome. They consequently confirmed their data by isolating the RNA from these genes by RT-PCR showing that they were at least transcribed. The highlight of the paper is the apparent lack of conservation beween the mammalian genomes and the fish(I think that they used fugu)as two-thirds of their "new" genes don't have homologues in the fish. Why this paper was in the news-I have no idea. Besides, the article was in PNAS!