Genechip mouse genome 2.0 array

Mouse livers were harvested at 9 AM–11 AM. Fresh liver samples were immersed in RNALater (Ambion) overnight. Afterwards, the samples were extracted with STAT-60^TM (Tel-Test, Inc.) to retrieve total RNA. The RNA was purified further with RNeasy^R Mini Kit (QIAGEN). An RNA Analyzer (Agilent) was used to check RNA quality. RNAs with high quality were reverse transcribed and the cDNAs were labeled and hybridized to the Affymetrix GeneChip mouse genome 2.0 array. Gene expression data generated by the Affymetrix MOE430 chip (two samples per condition) were imported to GeneSpring for analysis. Absence and presence call for each probe was made by MAS5. To identify differentially expressed genes between any 2 conditions (fold-change >1.5 and p-value < 0.05; t-test), probes labeled by absence on both duplicates in either condition were discarded.

Microarray gene expression data for 7 MG and 5 NSC samples were obtained using the GeneChip Mouse Genome 2.0 Array from Affymetrix. The raw data were preprocessed using the RMA algorithm that includes background correction, normalization, and calculation of expression steps. The resulting expression values were in log base 2 scale. Differential gene expression analysis was performed in the R statistical environment: p values were calculated using a linear model fit from the “limma” package and the BH method was used for multiple testing correction. Differentially expressed genes were defined using a cut-off of absolute value of the log fold change between average expression values in MG and NSC cases of 1.5 and of corrected p values of 10⁻² (n = 2402 genes). Pathway analysis of the differentially expressed genes was performed using ClueGO plug-in for Cytoscape.