Connectome-seq: High-throughput Mapping of Neuronal Connectivity at Single-Synapse Resolution via Barcode Sequencing [snRNA-seq, ssRNA-seq]
Understanding neuronal connectivity at single-cell resolution remains a fundamental challenge in neuroscience, with current methods constrained by an inherent trade-off between throughput and synaptic precision. Here we present Connectome-seq, a high-throughput method that combines engineered synaptic proteins, RNA barcoding, and single-compartment sequencing to map neuronal connectivity at single-synapse resolution. We validate this approach in the mouse pontocerebellar circuit, successfully identifying thousands of connections including the predominant excitatory projections from pontine neurons to cerebellar granule cells, while also revealing potentially novel synaptic partnerships. By enabling systematic mapping of neuronal connectivity across brain regions with single-cell precision, Connectome-seq provides a scalable platform for comprehensive circuit analysis across different experimental conditions and biological states. This advance in connectivity mapping methodology opens new possibilities for understanding circuit organization in complex mammalian brains. Overall design: Pons and cerebellum tissue was obtained from Sun1-sfGFP-Myc mice, and nuclei and synaptosomes were subsequently isolated via fluorescence-activated cell sorting, selecting based on GFP, HA, or V5 signals, before undergoing single-nucleus and single-synaptosome RNA sequencing (snRNA-seq, ssRNA-seq) analysis. mRNA library: read 1 file contains cell barcode and UMI; read 2 file contains transcript sequence NB library: read 1 file contains cell barcode and UMI; read 2 file contains neuronal barcode