Nuclear RNA-seq of single neurons reveals molecular signatures of activation

Abstract

Single-cell sequencing methods have emerged as powerful tools for identification of heterogeneous cell types within defined brain regions. Application of single-cell techniques to study the transcriptome of activated neurons can offer insight into molecular dynamics associated with differential neuronal responses to a given experience. Through evaluation of common whole-cell and single-nuclei RNA-sequencing (snRNA-seq) methods, here we show that snRNA-seq faithfully recapitulates transcriptional patterns associated with experience-driven induction of activity, including immediate early genes (IEGs) such as Fos, Arc and Egr1. SnRNA-seq of mouse dentate granule cells reveals large-scale changes in the activated neuronal transcriptome after brief novel environment exposure, including induction of MAPK pathway genes. In addition, we observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone. In summary, snRNA-seq of activated neurons enables the examination of gene expression beyond IEGs, allowing for novel insights into neuronal activation patterns in vivo.

Variation in Activity State, Axonal Projection, and Position Define the Transcriptional Identity of Individual Neocortical Projection Neurons

“…To test whether any modules reflect activity state, we assessed enrichment of a curated set of genes induced by neural activity (Table S4; Cho et al, 2016; Kim et al, 2010; Lacar et al, 2016; Mardinly et al, 2016). Three of the seven modules correlated with transcriptional subtype identity (black, purple, and midnight blue) were significantly enriched for genes induced by neuronal activity (Figures 3E and S5E; p < 0.01, hypergeometric test).…”

“…These weights were used to rank-order all expressed genes for input into a pre-ranked GSEA (Subramanian et al, 2005). Gene sets for the GSEA were derived from the Monocle2 differential gene tests described above or a curated list of neuronal activity genes (Cho et al, 2016; Kim et al, 2010; Lacar et al, 2016; Mardinly et al, 2016) using an adjusted p value cutoff of <0.01.…”

Genomics implicates adaptive and innate immunity in Alzheimer's and Parkinson's diseases

“…Data from brain regions contain a mixture of different cell types such as microglia and neurons. Single‐cell sampling may reduce this heterogeneity in the future 55. This analysis should be revisited as brain annotation information improves.…”

Dissecting Cell-Type Composition and Activity-Dependent Transcriptional State in Mammalian Brains by Massively Parallel Single-Nucleus RNA-Seq

“…This requirement poses an even greater challenge for cells with complex morphology, such as mature neurons. Enzymatic treatment not only favors recovery of easily dissociated cell types, but also introduces aberrant transcriptional changes during the whole-cell dissociation process (Lacar et al, 2016; Wu et al., 2017). In addition, skeletal and cardiac muscle cells are frequently multinucleated and are large in size.…”