Abstract

Cortical circuit activity is shaped by the parvalbumin (PV) and somatostatin (SST) interneurons that inhibit principal excitatory (EXC) neurons and the vasoactive intestinal peptide (VIP) interneurons that suppress activation of other interneurons. To understand the molecular-genetic basis of functional specialization and identify potential drug targets specific to each neuron subtype, we performed a genome wide assessment of both gene expression and splicing across EXC, PV, SST and VIP neurons from male and female mouse brains. These results reveal numerous examples where neuron subtype-specific gene expression, as well as splice-isoform usage, can explain functional differences between neuron subtypes, including in presynaptic plasticity, postsynaptic receptor function, and synaptic connectivity specification. We provide a searchable web resource for exploring differential mRNA expression and splice form usage between excitatory, PV, SST, and VIP neurons (http://research-pub.gene.com/NeuronSubtypeTranscriptomes). This resource, combining a unique new dataset and novel application of analysis methods to multiple relevant datasets, identifies numerous potential drug targets for manipulating circuit function, reveals neuron subtype-specific roles for disease-linked genes, and is useful for understanding gene expression changes observed in human patient brains.SIGNIFICANCE STATEMENT Understanding the basis of functional specialization of neuron subtypes and identifying drug targets for manipulating circuit function requires comprehensive information on cell-type-specific transcriptional profiles. We sorted excitatory neurons and key inhibitory neuron subtypes from mouse brains and assessed differential mRNA expression. We used a genome-wide analysis which not only examined differential gene expression levels but could also detect differences in splice isoform usage. This analysis reveals numerous examples of neuron subtype-specific isoform usage with functional importance, identifies potential drug targets, and provides insight into the neuron subtypes involved in psychiatric disease. We also apply our analysis to two other relevant datasets for comparison, and provide a searchable website for convenient access to the resource.

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