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Extraction of Distinct Cell Types from within a Genetically Continuous Population

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NIAID Data Ecosystem2026-03-13 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE133230
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The brain is composed of millions of diverse neurons that differ systematically in the genes that they express. Analyses of single cell gene expression data reveal clusters which correspond to different cell types that differ in their connectivity and function. Can the connections formed by genetically identical neurons systematically alter their gene expression? Here we address this question by combining retrograde labeling, single cell gene expression, and rabies-based analyses of connectivity to assess cortical-cortical projection neurons in the mouse primary visual cortex. We find that pyramidal neurons projecting to different cortical targets and with known functional differences differ systematically in their gene expression and connectivity despite forming only a single genetic cluster with continuous variability. These observations demonstrate that single cell gene expression analysis in isolation is insufficient to identify neuron types. We used fluorescent tagged retrograde tracers, single-nuclei sequencing combined by projection profile via retrogradely labeling virus, and rabies-based projection- and layer-dependent input tracing to identify distinctive cell types from V1 L2/3 pyramidal neurons.
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2022-03-28
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