Extraction of Distinct Neuronal Cell Types from within a Genetically Continuous Population

Neuron. 2020 Jul 22;107(2):274-282.e6. doi: 10.1016/j.neuron.2020.04.018. Epub 2020 May 11.


Single-cell transcriptomics of neocortical neurons have revealed more than 100 clusters corresponding to putative cell types. For inhibitory and subcortical projection neurons (SCPNs), there is a strong concordance between clusters and anatomical descriptions of cell types. In contrast, cortico-cortical projection neurons (CCPNs) separate into surprisingly few transcriptomic clusters, despite their diverse anatomical projection types. We used projection-dependent single-cell transcriptomic analyses and monosynaptic rabies tracing to compare mouse primary visual cortex CCPNs projecting to different higher visual areas. We find that layer 2/3 CCPNs with different anatomical projections differ systematically in their gene expressions, despite forming only a single genetic cluster. Furthermore, these neurons receive feedback selectively from the same areas to which they project. These findings demonstrate that gene-expression analysis in isolation is insufficient to identify neuron types and have important implications for understanding the functional role of cortical feedback circuits.

Keywords: cell types; connectivity; cortico-cortical projection neurons; feedback circuits; rabies tracing; single-cell RNA sequencing; visual cortex.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Cerebral Cortex / cytology
  • Cerebral Cortex / physiology
  • Feedback
  • Female
  • Gene Expression
  • Gene Knock-In Techniques
  • Male
  • Mice
  • Mice, Inbred C57BL
  • Mice, Transgenic
  • Neocortex / cytology
  • Neocortex / physiology
  • Nerve Net / physiology
  • Neural Pathways / cytology
  • Neural Pathways / physiology
  • Neurons / classification
  • Neurons / physiology*
  • Rabies virus
  • Transcriptome
  • Visual Cortex / cytology
  • Visual Cortex / physiology