GSE174293
High-Throughput Transcriptome Profiling of Single Nuclei and Single Synapses Using Single-Cell Total-RNA-Seq [Hs]
We developed the first droplet-based single-cell total-RNA-seq method. We refer to this platform as Multiple Annealing and Tailing-based Quantitative scRNA-seq in Droplet (MATQ-Drop). With the detection of nascent RNA species, we showed that the cell atlas of human brain samples could be effectively constructed based on nascent RNA species. Furthermore, we observed that only lncRNA species are sufficient to construct the cell atlas, suggesting that MATQ-Drop allows a large-scale identification of the cell-type-specific lncRNA species. Beyond total-RNA profiling for single nuclei, we also showed that MATQ-Drop could be used to profile the transcripts in different neuronal sub-compartments. Based on transcriptome profiling, we were able to determine different types of sub-compartments—in particular, synapses. Here we have referred to the transcriptome of individual synapses as the synaptome, and we identified different subtypes of pre-synapses and post-synapses. Furthermore, between pre-synapses and post-synapses, as well as between pre-synapses and the nuclei, we were able to identify different functional enrichments. Our result unveils unprecedented new insights about gene expression in individual synapses. It also demonstrates the feasibility of using MATQ-drop to profile the transcriptome of sub-cellular compartments. Overall design: MATQ-Drop single-cell total-RNA-seq of Hoechst-positive nuclei and Hoechst-negative subneuronal compartments isolated from frozen human brain tissues