Integrative multi-omics landscape of fluoxetine action across 27 brain regions [bulk RNA-seq]

We constructed a comprehensive multi-omics map of the molecular effects of fluoxetine (an SSRI antidepressant), in 27 rat brain regions. We profiled gene expression (bulk RNA-seq, 210 datasets) and chromatin state (bulk chromatin immunoprecipitation sequencing (ChIP-seq) for the histone marker H3K27ac, 100 datasets) in a broad, unbiased panel of 27 brain regions across the entire rodent brain, in naive and fluoxetine-treated animals. We complemented this approach with single-cell RNA-seq (scRNA-seq) analysis of two brain regions. Using diverse integrative data analysis techniques we characterized the complex and multifaceted effects of fluoxetine on region-specific and cell-type-specific gene regulatory networks and pathways. Remarkably, we observed profound molecular changes across the brain (>4,000 differentially expressed genes and differentially acetylated ChIP-seq peaks each) that were highly region-dependent. We leveraged this atlas to identify fluoxetine-moduated genes and gene-regulatory loci, predict enriched motifs that suggest potential upstream regulators, and validate global mechanisms of fluoxetine action. Overall design: To complement our multi-regional epigenome map, we used bulk RNA-seq to profile genome-wide fluoxetine-induced transcriptome changes in 27 brain regions. Here we deposit these RNA-seq profiles (27 regions,2 treatment groups - Sham and Fluoxetine, 4 replicates; 27*8= 216 profiles, postQC- 210 RNAseq datasets). To reduce the effects of inter-animal biological variation each RNA-seq sample was pooled from 10 animals (40 in Sham, 40 in FT; 80 animals in total). Some samples lack raw data due to file corruption.