Total aortic RNA was isolated by homogenization in RNA STAT-60 (Tel-Test, Inc., Friendswood, TX) and purification by chloroform extraction, with a yield of approximately 6 ug total RNA per aorta. Quantity and quality of each samples was measured at the spectrophotometer (OD 260, 280, 260/280) and RNA integrity checked with the use of a Bioanalyzer (18s and 28s peaks) confirming good quality of the samples (Agilent 2100 Bioanalyzer, Agilent Technologies, Palo Alto, CA).
Label
biotin
Label protocol
Total RNA (5 ug; a separate aortic sample per microarray) was used for labeling (One-Cycle Eukaryotic Target Labeling Assay (Affymetrix P/N900493, Affymetrix, Santa Clara, CA) according to the manufacturer’s instructions. Total RNA was reverse transcribed using a T7-Oligo(dT) Promoter Primer in the first-strand cDNA synthesis reaction. Following RNase H-mediated second-strand cDNA synthesis, the double-stranded cDNA was purified and served as a template in the subsequent in vitro transcription (IVT) reaction. The IVT reaction was carried out in the presence of T7 RNA Polymerase and a biotinylated nucleotide analog/ribonucleotide mix for complementary RNA (cRNA) amplification and biotin labeling.
Hybridization protocol
Unamplified, labeled cRNA (15 ug) was hybridized to whole mouse genome 430 2.0 microarrays(Affymetrix) according to the manufacturer's instructions. Affymetrix GeneChip® Operating Software (GCOS) was used for the control of GeneChip® Fluidics Stations for automated washing, staining, and scanning.
Scan protocol
Affymetrix GeneChip® Operating Software (GCOS) was used for the control of GeneChip® Scanners were used for scanning and data acquisition, according to the manufacturer's instructions.
Description
Gene expression data from ovarioectomized mouse aortae treated with estrogen or placebo.
Data processing
The gene expression values for each probe set were first estimated from the hybridization intensities using the corrected for GC content Robust Multichip Analysis (GCRMA) method as implemented in Bioconductor (61–63). Gene expression values for each sample were estimated using the linear model of the data as implemented by the LIMMA package in BioConductor (63). The differences in log (base 2) expression levels were evaluated by the t test as implemented by the LIMMA package in BioConductor by comparing distribution of expression values between different sample categories.
