RNA sequencing and data analysis

In all, 1 μg of the total RNA, with RIN (RNA integrity number) numbers above 7 (Agilent 2100 Bioanalyzer), were used. mRNA was enriched using NEBNext^® Poly(A) mRNA Magnetic Isolation Module and cDNA library was prepared with NEBNext^® Ultra™ II Directional RNA Library Prep Kit. Sequencing was performed on the NextSeq 500 system (75 cycles, high output, v2.5). The sequencing is performed in Core Facility Genomics of the Medical Faculty, University of Münster.

The RNA sequencing reads were aligned to the mouse genome mm10 with TopHat2 aligner (v2.1.1)⁶⁰ with default input parameters. The number of reads that were mapped to each Ensembl gene (GRCm38) was counted using the Python package HTSeq (v0.7.2)^60,61 with “htseq-count –stranded no”. Principal component analysis and differential expression analysis was performed with raw counts using the R package DESeq2 (v1.18.1)⁶². Genes were considered as deregulated if |log2FC | > 1 and FDR < 0.01 using Benjamini–Hochberg multiple test adjustment⁶³. Gene set enrichment analysis (GSEA) was performed by using GSEA software version 4.0.1⁶⁴ with default settings. Input files were adapted from normalised counts generated with VST function in DESeq2 package. In total, 1000 permutations were used to calculate P values based on the phenotype annotation.