ABSTRACT
Single-cell analyses parse the brain's billions of neurons into thousands of 'cell-type' clusters residing in different brain structures1. Many cell types mediate their functions through targeted long-distance projections allowing interactions between specific cell types. Here we used epi-retro-seq2 to link single-cell epigenomes and cell types to long-distance projections for 33,034 neurons dissected from 32 different regions projecting to 24 different targets (225 source-to-target combinations) across the whole mouse brain. We highlight uses of these data for interrogating principles relating projection types to transcriptomics and epigenomics, and for addressing hypotheses about cell types and connections related to genetics. We provide an overall synthesis with 926 statistical comparisons of discriminability of neurons projecting to each target for every source. We integrate this dataset into the larger BRAIN Initiative Cell Census Network atlas, composed of millions of neurons, to link projection cell types to consensus clusters. Integration with spatial transcriptomics further assigns projection-enriched clusters to smaller source regions than the original dissections. We exemplify this by presenting in-depth analyses of projection neurons from the hypothalamus, thalamus, hindbrain, amygdala and midbrain to provide insights into properties of those cell types, including differentially expressed genes, their associated cis-regulatory elements and transcription-factor-binding motifs, and neurotransmitter use.
Subject(s)
Brain , Epigenomics , Neural Pathways , Neurons , Animals , Mice , Amygdala , Brain/cytology , Brain/metabolism , Consensus Sequence , Datasets as Topic , Gene Expression Profiling , Hypothalamus/cytology , Mesencephalon/cytology , Neural Pathways/cytology , Neurons/metabolism , Neurotransmitter Agents/metabolism , Regulatory Sequences, Nucleic Acid , Rhombencephalon/cytology , Single-Cell Analysis , Thalamus/cytology , Transcription Factors/metabolismABSTRACT
Cortical circuit tracing using modified rabies virus can identify input neurons making direct monosynaptic connections onto neurons of interest. However, challenges remain in our ability to establish the cell type identity of rabies-labeled input neurons. While transcriptomics may offer an avenue to characterize inputs, the extent of rabies-induced transcriptional changes in distinct neuronal cell types remains unclear, and whether these changes preclude characterization of rabies-infected neurons according to established transcriptomic cell types is unknown. We used single-nucleus RNA sequencing to survey the gene expression profiles of rabies-infected neurons and assessed their correspondence with established transcriptomic cell types. We demonstrated that when using transcriptome-wide RNA profiles, rabies-infected cortical neurons can be transcriptomically characterized despite global and cell-type-specific rabies-induced transcriptional changes. Notably, we found differential modulation of neuronal marker gene expression, suggesting that caution should be taken when attempting to characterize rabies-infected cells with single genes or small gene sets.