NatureNeurosciencePeer-reviewed journal article
Shared and distinct transcriptomic cell types across neocortical areas
Bosiljka TasiciD, Zizhen YaoiD, Lucas T. GraybuckiD, Kimberly A. SmithiD, Thuc Nghi NguyeniD, Darren BertagnolliiD, Jeff GoldyiD, Emma J. Garren, Michael N. EconomoiD, Sarada Viswanathan, Osnat Penn, Trygve E. BakkeniD, Vilas MenoniD, Jeremy A. MilleriD, Olivia FongiD, Karla E. HirokawaiD, Kanan B. LathiaiD, Christine RimoriniD, Michael TieuiD, Rachael LarseniD, Tamara CasperiD, Eliza R. BarkaniD, Matthew KrolliD, Sheana E. Parry, Nadiya V. ShapovalovaiD, , Hongkui ZengiD
Abstract
Neocortex contains a multitude of cell types segregated into layers and functionally distinct regions. To investigate the diversity of cell types across the mouse neocortex, we analyzed 12,714 cells from the primary visual cortex (VISp), and 9,035 cells from the anterior lateral motor cortex (ALM) by deep single-cell RNA-sequencing (scRNA-seq), identifying 116 transcriptomic cell types. These two regions represent distant poles of the neocortex and perform distinct functions. We define 50 inhibitory transcriptomic cell types, all of which are shared across both cortical regions. In contrast, 49 of 52 excitatory transcriptomic types were found in either VISp or ALM, with only three present in both. By combining single cell RNA-seq and retrograde labeling, we demonstrate correspondence between excitatory transcriptomic types and their region-specific long-range target specificity. This study establishes a combined transcriptomic and projectional taxonomy of cortical cell types from functionally distinct regions of the mouse cortex.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: cell-cell communication
- research focus: spatial domain detection
- approach: deep learning
- approach: statistical model
- Citations
- 1,745
- FWCI
- 56.78
- Field percentile
- top 1%
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