strain: C57BL/6N tissue: liver Sex: male treatment: CCL4 time post treatment: 8d
Extracted molecule
total RNA
Extraction protocol
RNA was isolated using the TRIzol method. Briefly, 1 ml TRIzol was added to 5 x 106 cells followed by vortexing, a 5-min incubation at room temperature, and the addition of 200 μl chloroform. After mixing, further incubation at room temperature for 2–3 min and centrifugation (12,000 g) at 4 °C for 5 min, the clear supernatant was mixed with 500 μl isopropanol and incubated at room temperature for 10 min. After centrifugation (12,000 g) at 4 °C for 10 min, the supernatant was discarded and the pellet washed with 1 ml cold 75% ethanol followed by vortexing and centrifugation (7,500 g, 4 °C, 5 min). The pellet was dried and dissolved in RNase-free water.
Label
biotin
Label protocol
Affymetrix gene array analysis was performed using the Affymetrix GenChip® Mouse Genome 430 2.0 arrays (Santa Clara, CA, USA). Briefly, five µg RNA were transcribed into cDNA by oligo dT primers, and reverse transcribed to biotinylated cRNA with the Gene Chip IVTÒ Labeling kit (Affymetrix, High Wycombe, UK). Cleanup of the IVT product was done using CHROMA SPIN-100 columns (Clontech, USA). Spectrophotometric analysis was used for the quantification of cRNA with an acceptable A260/A280 ratio of 1.9 to 2.1. Afterward, the cRNA was fragmented using the standard protocol of Affymetrix.
Hybridization protocol
Labeled and fragmented cRNA was hybridized to Mouse Genome 430 2.0 Affymetrix GeneChips for 16 h at 45 °C according to the manufacturer’s instructions. Microarrays were washed using an Affymetrix fluidics station 450 and stained initially with streptavidin-phycoerythrin. For each sample the signal was further enhanced by incubation with biotinylated goat anti-streptavidin followed by a second incubation with streptavidin-phycoerythrin and a second round of intensities were measured.
Scan protocol
Microarrays were scanned with an Affymetrix scanner controlled by Affymetrix Microarray Suite software (Campos et al., 2014; DOI: 10.1007/s00204-014-1240-8).
Data processing
A probe-level model was fitted to the raw data to control the array quality based on the relative log expression values (RLE) and the normalized unscaled standard errors (NUSE) using the R/Bioconductor package oligo (version 1.52.0). Arrays that deviated more than 0.1 from 0 for RLE and from 1 for NUSE were discarded due to expected poor quality. Subsequently, the raw data was normalized with the RMA algorithm, also implemented within the oligo package.
