Systems genetics for drug target discovery

The collection and analysis of genomic data has the potential to reveal novel druggable targets by providing insight into the genetic basis of disease. However, the number of drugs targeting new molecular entities, approved by the US Food and Drug Administration has not increased in the years since the collection of genomic data has become commonplace. The paucity of translatable results can be partly attributed to conventional analysis methods that test one gene at a time in an effort to identify disease-associated factors as candidate drug targets. By disengaging genetic factors from their position within the genetic regulatory system, much of the information stored within the genomic data set is lost. Here we discuss how genomic data is used to identify disease-associated genes or genomic regions, how disease-associated regions are validated as functional targets, and the role network analysis can play in bridging the gap between data generation and effective drug target identification.

Microarray analysis of cytoplasmic versus whole cell RNA reveals a considerable number of missed and false positive mRNAs

With no known exceptions, every published microarray study to determine differential mRNA levels in eukaryotes used RNA extracted from whole cells. It is assumed that the use of whole cell RNA in microarray gene expression analysis provides a legitimate profile of steady-state mRNA. Standard labeling methods and the prevailing dogma that mRNA resides almost exclusively in the cytoplasm has led to the long-standing belief that the nuclear RNA contribution is negligible. We report that unadulterated cytoplasmic RNA uncovers differentially expressed mRNAs that otherwise would not have been detected when using whole cell RNA and that the inclusion of nuclear RNA has a large impact on whole cell gene expression microarray results by distorting the mRNA profile to the extent that a substantial number of false positives are generated. We conclude that to produce a valid profile of the steady-state mRNA population, the nuclear component must be excluded, and to arrive at a more realistic view of a cell's gene expression profile, the nuclear and cytoplasmic RNA fractions should be analyzed separately.

MicroRNAs and regeneration: Let-7 members as potential regulators of dedifferentiation in lens and inner ear hair cell regeneration of the adult newt

MicroRNAs are known to regulate the expression of many mRNAs by binding to complementary target sequences at the 3'UTRs. Because of such properties, miRNAs may regulate tissue-specific mRNAs as a cell undergoes transdifferentiation during regeneration. We have tested this hypothesis during lens and hair cell regeneration in newts using microarray analysis. We found that distinct sets of miRNAs are associated with lens and hair cell regeneration. Members of the let-7 family are expressed in both events and they are regulated in a similar fashion. All the let-7 members are down regulated during the initiation of regeneration, which is characterized by dedifferentiation of terminally differentiated cells. This is the first report to correlate expression of miRNAs as novel regulators of vertebrate regeneration, alluding to a novel mechanism whereby transdifferentiation occurs.