Significance Monosynaptic rabies tracing using glycoprotein (G)-deleted rabies virus is widely applied to study cortical circuit connectivity. However, connectivity tracing using rabies virus could benefit from higher throughput methods of assigning rabies-labeled inputs to neuronal cell types and the ability to assign cells to finer genetically defined subtypes. Using single-nucleus RNA sequencing, we demonstrate that rabies-infected cortical neurons can be transcriptomically characterized according to established cell types when using transcriptome-wide analysis. Furthermore, we find that rabies infection differentially affects distinct host genes, suggesting that some genes may be more vulnerable to transcriptional modulation than others, which may impede the classification of rabies-infected cells when using methods that rely on the detection of single or few genes.

Retrograde monosynaptic tracing using glycoprotein-deleted rabies virus is an important component of the toolkit for investigation of neural circuit structure and connectivity. It allows for the identification of first-order presynaptic connections to cell populations of interest across both the central and peripheral nervous system, helping to decipher the complex connectivity patterns of neural networks that give rise to brain function. Despite its utility, the efficiency with which genetically modified rabies virus spreads retrogradely across synapses remains uncertain. While past studies have revealed conditions that can increase or decrease the numbers of presynaptic cells labeled, it is unknown what proportion of total inputs to a starter cell of interest are labeled. It is also unknown whether synapses that are more proximal or distal to the cell body are labeled with different efficiencies. Here we use a new rabies virus construct that allows for the simultaneous labeling of pre and postsynaptic specializations to quantify efficiency of spread at the synaptic level in mouse primary visual cortex. We demonstrate that with typical conditions about 40% of first-order presynaptic excitatory inputs are labeled. We show that using matched tracing conditions there is similar efficiency of spread from excitatory or inhibitory starter cell types. Furthermore, we find no difference in the efficiency of labeling of excitatory inputs to postsynaptic sites at different subcellular locations.

Single-cell genetic and epigenetic analyses parse the brain′s billions of neurons into thousands of ″cell type″ clusters, each residing in different brain structures. Many of these cell types mediate their unique functions by virtue of targeted long-distance axonal projections to allow interactions between specific cell types. Here we have used Epi-Retro-Seq to link single cell epigenomes and associated cell types to their long-distance projections for 33,034 neurons dissected from 32 different source regions projecting to 24 different targets (225 source→target combinations) across the whole mouse brain. We highlight uses of this large data set for interrogating both overarching principles relating projection cell types to their transcriptomic and epigenomic properties and for addressing and developing specific hypotheses about cell types and connections as they relate to genetics. We provide an overall synthesis of the data set with 926 statistical comparisons of the discriminability of neurons projecting to each target for every dissected source region. We integrate this dataset into the larger, annotated BICCN cell type atlas composed of millions of neurons to link projection cell types to consensus clusters. Integration with spatial transcriptomic data further assigns projection-enriched clusters to much smaller source regions than afforded by the original dissections. We exemplify these capabilities by presenting in-depth analyses of neurons with identified projections from the hypothalamus, thalamus, hindbrain, amygdala, and midbrain to provide new insights into the properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription factor binding motifs, and neurotransmitter usage.