Molecular Biology Program
GENE DISCOVERY USING RNA FINGERPRINTING BY ARBITRARY PRIMED PCR
We have been working with a method for discovering differentially regulated genes called RNA Arbitrarily Primed PCR, a method that Michael McClelland and I invented several years ago. This and related methods have greatly eased the difficulties of finding genes that are differentially regulated under various experimental and clinical circumstances. Most of our work has been directed toward refinement of the method and application of the method to gene regulation mediated by TGF-beta in a variety of cell lines, and by ultraviolet light in melanocytes. Along the methodological lines, we have devised new and very efficient ways of cloning differentially regulated genes from complex fingerprints. In our studies of TGF-beta, we have discovered two new regulated genes, one of which is a src-homology protein and may be involved in signal transduction, as are other genes with src-homology. The second is a sugar-modifying protein that may be involved in TGF-beta-mediated effects on the extracellular matrix or on the cell's ability to interact with the matrix.
These experiments are proceeding simultaneously with more theoretical studies, the centerpiece of which is a computer program that will, when finished, allow the investigator to quickly obtain information on the regulation of genes by drugs and hormones that is already present in the literature, but for practical purposes lost in the 10,000,000 currently archived medical papers. The readout of the program will be an "action spectrum" describing the behavior of the drug relative to the genes it perturbs. With this tool, we hope to be able to more accurately guess which signal transduction pathways control newly discovered genes, as well as to more accurately guess in which biological processes a new gene might be involved. The idea is, if two genes behave in a very similar way to a wide variety of drugs and hormones, it is likely that they are regulated by the same or similar pathway than two genes that display very different regulatory behavior. Similarly, when two genes are coordinately regulated, they are more likely to be involved in an integrated process than two genes that are not coordinately regulated. Our strategy is to anchor these arguments, wholesale, to the vast biological and medical literature. Strategies of this sort may become very important in the burgeoning field of genomics, as correlation analysis gains importance with the accumulation of vast amounts of sequence and expression data.