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 researchers from the Salk Institute for Biological Studies 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, the researchers observe a continuum of activation states, revealing a pseudotemporal pattern of activation from gene expression alone.
IEG RNA expression in single DGC nuclei is associated with animal experience
(a) log2(TPM+1) Normalized RNA-seq values from HC NEUN+PROX1+ (top, n=23), NE PROX1+FOS− (bottom, n=43), and NE PROX1+FOS+ (bottom, n=36) single-nuclei. NE FOS+ nuclei (red) exhibited higher levels of IEG expression than both NE FOS− (blue) and HC nuclei (white). Stars indicate statistically significant differences in expression using edgeR after multiple-testing correction (fdrtool; R). Pie charts indicate the proportion of nuclei with detectable gene expression (yellow=detected). (b) IEG expression in nuclei after exposure to NE. (c) Principal components analysis (PCA) of the full transcriptome for NE nuclei. pseudo-FOS+ cells in red with black outline. (d) Differential expression results for all genes between FOS+ and FOS− nuclei excluding pseudo-FOS+ nuclei. Genes expressed to a higher level in FOS+ nuclei are in red and genes expressed higher in FOS− nuclei are in blue.
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.