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.我们针对27个大鼠脑区，构建了氟西汀（一种选择性5-羟色胺再摄取抑制剂（SSRI）类抗抑郁药）的分子效应综合多组学图谱。我们对覆盖全啮齿类动物脑的27个脑区构成的广谱无偏检测队列，开展了基因表达谱分析（批量RNA测序（bulk RNA-seq），共210组数据集）与染色质状态谱分析（针对组蛋白标记H3K27ac的批量染色质免疫沉淀测序（ChIP-seq），共100组数据集），实验对象涵盖未经给药处理的空白对照动物与经氟西汀处理的动物。我们还通过对两个脑区的单细胞RNA测序（scRNA-seq）分析对该研究方案进行了补充。借助多种整合数据分析技术，我们解析了氟西汀对脑区特异性与细胞类型特异性基因调控网络及通路的复杂多维度效应。值得注意的是，我们在全脑范围内观察到了显著的分子变化（每组均存在超过4000个差异表达基因与差异乙酰化ChIP-seq峰），且这些变化具有极强的脑区依赖性。我们依托该多组学图谱，鉴定出了受氟西汀调控的基因与基因调控位点，预测出了可提示潜在上游调控因子的富集基序，并验证了氟西汀发挥作用的全局分子机制。