RNA-Seq and differential analysis

RNA-Seq data generated from Illumina HiSeq 2500 were processed following an open source pipeline ⁴². A total of n=9 rats of each genotype (Tcf7l2^WT and Tcf7l2^mut) were used. RNA libraries for each brain region were generated from pooled RNA from three animals per group. Briefly, the paired-end sequencing reads were aligned to the human genome (version hg19) and rat genome (version rn6), using the Spliced Transcripts Alignment to a (STAR) ⁴³. Next, featureCount ⁴⁴ was employed to assign aligned reads to genes. Count per Million (CPM) was used as the expression quantification method. The CPM matrix was log2 transformed and Z-score scaled to center the expression values of each gene to 0 with a standard deviation of 1 before performing Principal Component Analysis (PCA) and Hierarchical Clustering (HC). The Characteristic Direction ⁴⁵ was used to identify differentially expressed (DE) genes between the Tcf7l2^mut and Tcf7l2^WT samples. Enrichment analyses for DE genes were performed using Enrichr ^46,47. RNA-Seq data generated from TRAP were processed and analyzed as previously described ^16,17.