|Application:||Gene expression microarray analysis|
|Number of samples:||8|
|Release date:||Oct 13 2012|
|Last update date:||Aug 23 2018|
|Diseases:||Heart Diseases, Heart Failure|
|Dataset link||SRC-2 Coactivator Deficiency Decreases Functional Reserve in Response to Pressure Overload of Mouse Heart|
For microarray analysis, 250ng of RNA isolated from total heart (RNeasy kit, Qiagen) for each sample was labeled using the new standard Affymetrix linear amplification protocol using the 3' IVT Express Kit. This was reverse-transcribed and cRNA was produced and biotinylated via in vitro transcription. A hybridization cocktail containing Affymetrix spike-in controls and 15 μg fragmented, labeled cRNA was loaded onto a GeneChip® Mouse 430 2.0 array. The array was hybridized for 16 hours at 45°C with rotation at 60 rpm then washed and stained with a strepavidin, R-phycoerythrin conjugate stain using the FS 450_0001 Fluidics protocol setting. Signal amplification was done using biotinylated antistreptavidin. The stained array was scanned on the Affymetrix GeneChip® Scanner 3000. The images were analyzed and quality control metrics recorded using Affymetrix Command Console v3. Experiments were run using Affymetrix MG 430 2.0 chip with 45,101 probesets representing 20,757 unique genes. There were 8 experiments in 2 groups: WT-unstressed – 4 experiments, and KO-unstressed – 4 experiments. QC parameters for all experiments were within the acceptable limits. We used the following software packages for data QC, statistical analysis and presentation of the results: Affymetrix Expression Console (www.affymetrix.com), Partek (www.partek.com), BRB Array Tools (linus.nci.nih.gov/BRB-ArrayTools.html), and dChip (biosun1.harvard.edu/complab/dchip). Expressions were estimated using the RMA (Multi-Array Analysis) method  with Partek software. Differentially expressed genes were found using the RVM (Random Variance Model) t-test, which is designed for small sample size experiments . We used BRB Array Tools software, developed by Dr. Richard Simon and the BRB-ArrayTools Development Team. All genes were included in the comparison. For the genes represented by more than one probeset, we used the most highly expressed probeset. The cutoffs for differentially expressed genes were False Discovery Rate (FDR) = 0.05 .
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