Adult Mouse Cortical Cell Taxonomy by Single Cell Transcriptomics

By Bosiljka Tasic, V. Menon, T. Nguyen, Tae Kyung Kim, T. Jarsky, Zizhen Yao, Boaz P. Levi, Lucas T Gray, S. Sorensen, Tim Dolbeare and 12 more. 2016

1,012 citations recorded by the source corpus.

Nervous systems are composed of various cell types, but the extent of cell type diversity is poorly understood. We constructed a cellular taxonomy of one cortical region, primary visual cortex, in adult mice on the basis of single-cell RNA sequencing. We identified 49 transcriptomic cell types, including 23 GABAergic, 19 glutamatergic and 7 non-neuronal types. We also analyzed cell type–specific mRNA processing and characterized genetic access to these transcriptomic types by many transgenic Cre lines. Finally, we found that some of our transcriptomic cell types displayed specific and differential electrophysiological and axon projection properties, thereby confirming that the single-cell transcriptomic signatures can be associated with specific cellular properties.

Subfields: Biophysics, Molecular Biology, Neurology

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Citations in the corpus

Challenges in unsupervised clustering of single-cell RNA-seq data (2019, methodology): “Tasic et al. left out a subset of cells as the data were repeatedly clus tered 28 .”
Classes and continua of hippocampal CA 1 inhibitory neurons revealed by single ‐ cell transcriptomics (2017, methodology): “This class is homologous to the Int1 and Sst Chodl classes defined in isocortex, which have been identified with long‐range projecting sleep‐active neurons (Gerashchenko et al., 2008; Magno et al., 2012; Tasic et al., 2016; Zeisel et al., 2015).”
Physiology of Astroglia. (2018, neutral): “A few studies have collected transcriptome information of single astrocytes (384, 1732, 1938).”
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation (2020, positive): “For scalability reasons, our current implementation of constellation plots does not rely on core and intermediate cells as in previous work (Tasic et al., 2016, 2018) but a new nearest-neighbor approach.”
A Single-Cell Atlas of Cell Types, States, and Other Transcriptional Patterns from Nine Regions of the Adult Mouse Brain (2018, background): “…among cells of the same class presents formidable analytical challenges – particularly when these distinctions are to be made in systematic, inductive (unsupervised), data-driven ways (Mayer et al., 2015; Satija et al., 2015; Shekhar et al., 2016; Tanay and Regev, 2017; Tasic et al., 2016b).”
In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus (2016, neutral): “Cluster 11 cells expressed Laptm5, a known microglia marker (Zeisel et al., 2015, Tasic et al 2016).”
Three-dimensional intact-tissue sequencing of single-cell transcriptional states (2018, positive): “1A and 2, A and B) to survey a large but focused and curated gene set [160 genes including 112 putative cell-type markers collated from mouse cortical single-cell RNA sequencing (24, 25) and 48 activity-regulated genes (ARGs) (26, 27)].”
Identification of cell types in a mouse brain single-cell atlas using low sampling coverage (2018, result): “These in-between cells have been previously observed in other datasets [8].”
Comprehensive integration of single-cell data (2018, positive): “We identiﬁed four representative cases (Figure 5D), each of which contains strong external support in the published literature (Syken and Shatz, 2003; Venkatadri and Lee, 2014) or the Allen Brain Atlas (Tasic et al., 2016, 2018) (Figure S4B).”