All life 2

Abstract

The files contain the gene expression results from microarray experiments and matching elaborations reported in the paper entitled “Ataxia Teleangiectasia transcriptomic profile: low dose for long-time dexamethasone administration impacts”. Microarray analysis. Total RNA was extracted from all the used cell lines using the RNeasy kit plus (QIAGEN). Quality control of RNA was assayed by Nanodrop and by Agilent Bioanalyzer-TapeStation. Labelling procedure was performed by using Affymetrix GeneChip WT Pico kit as recommended by the manufacturer. The employed array chips were the Human Clariom D from Affymetrix and procedures were carried out as indicated by the manufacturer. The GeneChip Scanner 3000 7G platform was used for data acquisition. The data analysis, after pre-processing at probe level (CEL files), was performed by RMA background adjustment, quantile method for normalization and median polish for summarization. For the functional annotation of DEGs (differentially expressed genes) were selected by the Affymetrix TAC console, using an FDR p-value ≤0.05. Quantitative PCR Some of the genes resulting as modulated by dex were further investigated by qPCR. For this purpose, five hundred nanograms of RNA were employed in each experiment to obtain cDNA by PrimeScript™ RT Master Mix (Takara). One nanogram of cDNA was employed in each TaqMan Gene Expression Assay (Thermo Fisher Scientific) for the genes: FKBP5, HDAC4 and DDIT4, according to the manufacturer’s instructions. PPIC and PPIA gene expressions were used as housekeeping genes. Amplification plots were analysed using the ABI PRISM 7500 sequence detection system (Applied Biosystems) and the relative expression data were calculated by DCt method and represented as 1/2^DCt. Data analysis and functional networks Statistical analyses and graphs plotting were performed by GraphPad Prism. Statistical tests were chosen according to the sample size and variance homogeneity. The gene symbol lists resulting from the gene selection procedure and the matching gene expression values, were used to compute functional networks by using the Reactome (FI) Functional Interaction Network plugin for Cytoscape [34]. Biological processes (BP) and pathway enrichment of moduli were assessed by FDR p-value ≤0.01, while the whole network functions were computed by using FDR ≤0.1