Detecting Activated Cell Populations Using Single-Cell RNA-Seq.

PMID 29024657


Single-cell RNA sequencing offers a promising opportunity for probing cell types mediating specific behavioral functions and the underlying molecular programs. However, this has been hampered by a long-standing issue in transcriptional profiling of dissociated cells, specifically the transcriptional perturbations that are artificially induced during conventional whole-cell dissociation procedures. Here, we develop Act-seq, which minimizes artificially induced transcriptional perturbations and allows for faithful detection of both baseline transcriptional profiles and acute transcriptional changes elicited by behavior/experience-driven activity. Using Act-seq, we provide the first detailed molecular taxonomy of distinct cell types in the amygdala. We further show that Act-seq robustly detects seizure-induced acute gene expression changes in multiple cell types, revealing cell-type-specific activation profiles. Furthermore, we find that acute stress preferentially activates neuronal subpopulations that express the neuropeptide gene Cck. Act-seq opens the way for linking physiological stimuli with acute transcriptional dynamics in specific cell types in diverse complex tissues.