Quantification of mRNA by RT-competitive-PCR and high performance liquid chromatography

The use of RT-competitive-PCR with high performance liquid chromatography (HPLC) detection to quantify the absolute number of mRNA copies in mammalian cells is reported. As an example, the glutathione transferase (GST)-α mRNA in human hepatoma Hep G2 cells has been estimated. A PCR-generated internal standard was used as a competitor, co-amplified with the GST-α target sequence. The RT-competitive-PCR method was improved by designing target and competitor molecules which differed in only 30 base pairs. This allowed the two sequences to be co-amplified with the same efficiency. This improvement also facilitated a wider ratio to be used than previous methods (target:competitor ratio between 0.2 and 5). Products were baseline separated by HPLC using an ion-exchange column readily quantified at 260 nm. To validate the improved methodology, the effect of a known GST-α inducer, the anticancer drug oltipraz, was shown to induce GST-α mRNA up to 3-fold in Hep G2 cells. The RT-competitive PCR-HPLC method provides a reliable and sensitive way to quantify the amount of specific mRNA with 0.1 ng of total RNA.     

New bisexual form of Cavernocypris subterranea (Wolf, 1920) (Crustacea, Ostracoda) from Idaho

Males of Cavernocypris subterranea were found for the first time in an Idaho spring. The bisexual form is described on soft body parts and valves. The genus Cavernocypris now includes 2 bisexual and 1 parthenogenteic species.     

A GIS model to predict the location of fossil packrat ( Neotoma ) middens in central Nevada

Fossil packrat ( Neotoma ) middens provide an important source of paleoecologic data in the arid West. This study describes and tests a predictive GIS model that uses the eights-of-evidence method for determining areas with a high probability of containing fossil middens in central Nevada. Model variables included geology, elevation, and aspect. Geology was found to be the most important variable tested. We produced a map of 4 probability classes validated by field-checking 21 randomly selected 1-km 2 sites throughout the study area. Our high-probability category reduced the search area to only 3.5% of the total study area. Fossil middens were found on 8 of 21 sites (38%). Geologic types that contained middens were granite, limestone, and volcanic tuff. A 2nd run of the model with the new midden localities added to the training set helped narrow the total search area even further. This analysis demonstrates that the weights-of-evidence method provides an effective tool both for guiding research design and for helping locate midden sites within specific localities. With only a limited training dataset and a simple set of mapped criteria, a model can be constructed that is both predictive and testable. We intend to continue development of the model to improve our ability to predict the location of Pleistocene-age middens and to locate middens on low-probability sites. This method, designed for mineral exploration, has wide potential application within the natural sciences.