bioRxivGeneticsPreprint
The architecture of brain co-expression reveals the brain-wide basis of disease susceptibility
Christopher HartliD, Gokul RamaswamiiD, William G. PembrokeiD, Sandrine MulleriD, Greta PintacudaiD, Ashis SahaiD, Princy ParsanaiD, Alexis J. BattleiD, Kasper LageiD, Daniel H. GeschwindiD
Abstract
Gene networks have proven their utility for elucidating transcriptome structure in the brain, yielding numerous biological insights. Most analyses have focused on expression relationships within a circumspect number of regions - how these relationships vary across a broad array of brain regions is largely unknown. By leveraging RNA-sequencing in 864 samples representing 12 brain regions in a cohort of 131 phenotypically normal individuals, we identify 12 brain-wide, 114 region-specific, and 50 cross-regional co-expression modules. We replicate the majority (81%) of modules in regional microarray datasets. Nearly 40% of expressed genes fall into brain-wide modules corresponding to major cell classes and conserved biological processes. Region-specific modules comprise 25% of expressed genes and correspond to region-specific cell types and processes, such as oxytocin signaling in the hypothalamus, or addiction pathways in the nucleus accumbens. We further leverage these modules to capture cell-type-specific lncRNA and gene isoforms, both of which contribute substantially to regional synaptic diversity. We identify enrichment of neuropsychiatric disease risk variants in brain wide and multi-regional modules, consistent with their broad impact on cell classes, and highlight specific roles in neuronal proliferation and activity-dependent processes. Finally, we examine the manner in which gene co-expression and gene regulatory networks reflect genetic risk, including the recently framed omnigenic model of disease architecture.
- organism: human
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: GWAS / association mapping
- approach: statistical model
- approach: benchmark study
- Citations
- 7
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