A community-based transcriptomics classification and nomenclature of neocortical cell types

Yuste, R., Hawrylycz, M., Aalling, N., Aguilar-Valles, A., Arendt, D., Arnedillo, R. A., Ascoli, G. A., Bielza, C., Bokharaie, V., Bergmann, T. B., Bystron, I., Capogna, M., Chang, Y., Clemens, A., de Kock, C. P. J., DeFelipe, J., Dos Santos, S. E., Dunville, K., Feldmeyer, D., Fiáth, R., Fishell, G. J., Foggetti, A., Gao, X., Ghaderi, P., Goriounova, N. A., Güntürkün, O., Hagihara, K., Hall, V. J., Helmstaedter, M., Herculano, S., Hilscher, M. M., Hirase, H., Hjerling-Leffler, J., Hodge, R., Huang, J., Huda, R., Khodosevich, K., Kiehn, O., Koch, H., Kuebler, E. S., Kühnemund, M., Larrañaga, P., Lelieveldt, B., Louth, E. L., Lui, J. H., Mansvelder, H. D., Marin, O., Martinez-Trujillo, J., Moradi Chameh, H., Nath, A., Nedergaard, M., Němec, P., Ofer, N., Pfisterer, U. G., Pontes, S., Redmond, W., Rossier, J., Sanes, J. R., Scheuermann, R., Serrano-Saiz, E., Steiger, J. F., Somogyi, P., Tamás, G., Tolias, A. S., Tosches, M. A., García, M. T., Vieira, H. M., Wozny, C., Wuttke, T. V., Yong, L., Yuan, J., Zeng, H., Lein, E. (August 2020) A community-based transcriptomics classification and nomenclature of neocortical cell types. Nat Neurosci, 23 (12). pp. 1456-1468. ISSN 1097-6256

URL: https://pubmed.ncbi.nlm.nih.gov/32839617/
DOI: 10.1038/s41593-020-0685-8

Abstract

To understand the function of cortical circuits, it is necessary to catalog their cellular diversity. Past attempts to do so using anatomical, physiological or molecular features of cortical cells have not resulted in a unified taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the first time, systematic high-throughput measurements of cortical cells and generation of datasets that hold the promise of being complete, accurate and permanent. Statistical analyses of these data reveal clusters that often correspond to cell types previously defined by morphological or physiological criteria and that appear conserved across cortical areas and species. To capitalize on these new methods, we propose the adoption of a transcriptome-based taxonomy of cell types for mammalian neocortex. This classification should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic definition of a cell type and incorporate data from different approaches, developmental stages and species. A community-based classification and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classification, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > genetics & nucleic acid processing > DNA, RNA structure, function, modification > transcription
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neocortical interneurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neocortical interneurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neocortical interneurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons > neocortical interneurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons > neocortical interneurons
organs, tissues, organelles, cell types and functions > cell types and functions > cell types > neurons > neocortical interneurons
Investigative techniques and equipment > assays > Single cell sequencing
CSHL Authors:
Communities: CSHL labs > Huang lab
Depositing User: Matthew Dunn
Date: 24 August 2020
Date Deposited: 30 Nov 2020 19:38
Last Modified: 29 Jun 2021 18:05
PMCID: PMC7683348
Related URLs:
URI: https://repository.cshl.edu/id/eprint/39753

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