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HippocampusNeurosciencePeer-reviewed journal article

Activity-regulated gene expression across cell types of the mouse hippocampus

Erik D. NelsoniD, Kristen R. MaynardiD, Kyndall R. NicholasiD, Matthew Nguyen TraniD, Heena R. DivechaiD, Leonardo Collado‐TorresiD, Stephanie C. HicksiD, Keri MartinowichiD

PDFDOIPreprint

Abstract

Activity-regulated gene (ARG) expression patterns in the hippocampus (HPC) regulate synaptic plasticity, learning, and memory, and are linked to both risk and treatment response for many neuropsychiatric disorders. The HPC contains discrete classes of neurons with specialized functions, but cell type-specific activity-regulated transcriptional programs are not well characterized. Here, we used single-nucleus RNA-sequencing (snRNA-seq) in a mouse model of acute electroconvulsive seizures (ECS) to identify cell type-specific molecular signatures associated with induced activity in HPC neurons. We used unsupervised clustering and a priori marker genes to computationally annotate 15,990 high-quality HPC neuronal nuclei from N=4 mice across all major HPC subregions and neuron types. Activity-induced transcriptomic responses were divergent across neuron populations, with dentate granule cells being particularly responsive to activity. Differential expression analysis identified both upregulated and downregulated cell type-specific gene sets in neurons following ECS. Within these gene sets, we identified enrichment of pathways associated with varying biological processes such as synapse organization, cellular signaling, and transcriptional regulation. Finally, we used matrix factorization to reveal continuous gene expression patterns differentially associated with cell type, ECS, and biological processes. This work provides a rich resource for interrogating activity-regulated transcriptional responses in HPC neurons at single-nuclei resolution in the context of ECS, which can provide biological insight into the roles of defined neuronal subtypes in HPC function.

Citations
17
FWCI
1.51
Field percentile
top 18%

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