Project description:Transcriptional profiling of rat liver after a three days caloric restriction or 3 days starvation. In the present study, we wanted to investigate the expression of multiple genes linked to pathways of energy metabolism. We developed a metabolism dedicated microarray tool: the Mitoligo. This microarray gathers genes linked to the main functions of energy metabolism, such as glycolysis or fatty acid oxidation. This biochip has also been designed to study the expression of genes encoding for all the subunits of proteins constituting the ETC. Eventually, genes coding for protein linked to ROS scavenging systems can also be studied using the Mitoligo. Keywords: Nutritional intervention
Project description:Mice were killed between 24 to 26 months of age, tissues removed, rapidly frozen on dry ice, and stored in liquid nitrogen. Total liver RNA was isolated from frozen tissue as described (T. Tsuchiya, J.M. Dhahbi, X. Cui, P.L. Mote, A. Bartke, S.R. Spindler, Physiological Genomics, Submitted). mRNA levels were measured using the Affymetrix mouse U74Av2 array according to standard protocols. After hybridization, arrays were scanned using a Hewlett-Packard GeneArray Scanner. Image analysis was performed as described (Cao SX, Dhahbi JM, Mote PL, and Spindler SR. Genomic profiling of short- and long-term caloric restriction effects in the liver of aging mice. Proc Natl Acad Sci U S A 98: 10630-10635, 2001). A more detailed description of the methods can be found in (T. Tsuchiya, J.M. Dhahbi, X. Cui, P.L. Mote, A. Bartke, S.R. Spindler, Physiological Genomics, Submitted). This SuperSeries is composed of the SubSeries listed below.
Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.