Recent advances in single-cell RNAseq technologies are enabling new cell type classifications. For neurons, electrophysiological properties traditionally guide cell type classification but correlating RNAseq data with electrophysiological parameters has been difficult. Here we demonstrate RNAseq of electrophysiologically and synaptically characterized individual, patched neurons in the hippocampal CA1-region and subiculum, and relate the resulting transcriptome data to their electrical and synaptic properties. In this analysis, we explored the hypothesis that precise combinatorial interactions between matching cell-adhesion and signaling molecules shape synapse specificity. In analyzing interneurons and pyramidal neurons that are synaptically connected, we identified two independent, developmentally regulated networks of interacting genes encoding cell-adhesion, exocytosis and signal-transduction molecules. In this manner, our data allow postulating a presumed cell-adhesion and signaling code, which may explain neuronal connectivity at the molecular level. Our approach enables correlating electrophysiological with molecular properties of neurons, and suggests new avenues towards understanding synaptic specificity. SOURCE: Spyros Darmanis (spyros.darmanis@gmail.com) - Stephen Quake Stanford University

Pluto Bioinformatics

GSE75386: Single cell RNAseq of electrophysiologically characterized neurons of the hippocampus