GSM4983505: HFD7L-s102990-040; Mus musculus; RNA-Seq
RNA was isolated from snap-frozen liver tissue samples (left lobe, 24wk) from all mice using RNA-BeeTotal-RNA Isolation Kit (Bio-Connect, Huissen, the Netherlands). RNA concentration was determinedspectrophotometrically using Nanodrop 1000 (Isogen Life Science, De Meern, the Netherlands) andRNA quality was assessed using a 2100 Bioanalyzer (Agilent Technologies, Amstelveen, theNetherlands). Next-generation RNA sequencing was performed on livers from all mice. For this, RNA was used to generate strand-specific cDNA libraries for Next Generation Sequencing according to the manufacturer's protocol by GenomeScan B.V. (Leiden, the Netherlands; using oligo-dT magnetic beads, mRNA fragmentation, NEBNext Ultra Directional RNA Library Prep Kit of Illumina NEB #E7420S/L resulting in 300-500bp amplified libraries/sample). Libraries were multiplexed, clustered, and sequenced on a NextSeq500 system (Illumina, San Diego, CA, USA, using 1.6 pM of DNA/sample and  NextSeq control software 2.0.2 and ) with a single-read 75 cycles sequencing protocol, 12 million reads per sample and indexing. Image analysis, base calling, and quality check was performed with the Illumina data analysis pipeline RTA v2.4.11 and Bcl2fastq v2.17.   Three mice were excluded as biological outliers (described below under statistical analysis), and one mouse (from the HFD + vehicle group) was excluded as a technical outlier (based on principal component analysis of the sequencing data), resulting in: n=10 chow, n=13 HFD+vehicle, n=13 HFD+HC-24 for further statistical analysis of the sequencing data. The number of differentially expressed genes (DEG)between groups was determined using an established statistical analysis procedure (DEseq2 pipeline40). These DEG were determined using a statistical cut-off of p<0.01 for the following two comparisons: HFD+vehicle vs chow; and HFD+HC-24 vs HFD+vehicle. Next, these DEG were used as an input for an upstream regulator analysis through Ingenuity Pathway Analysis suite (IPA; www.ingenuity.com,accessed 2017). This analysis integrates the expression of a multitude of genes downstream from predefined upstream regulators (e.g. transcription factors, signaling proteins, metabolites) thus allowing summation of multiple (small) gene expression changes to provide information on the predicted activation state of such an upstream regulator. A negative Z-score <-2 indicates a predicted reduction in activity based on the direction of gene expression changes of target genes. A positive Z-score>2 indicates activation of the upstream regulator.