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

Yuste, R., Hawrylycz, M., Aalling, N., Arendt, D., Armananzas, R., Ascoli, G., et al. (2020). A community-based transcriptomics classification and nomenclature of neocortical cell types. Nature Neuroscience, 23(12), 1456-1468. doi:10.1038/s41593-020-0685-8.

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Yuste, R, Author
Hawrylycz, M, Author
Aalling, N, Author
Arendt, D, Author
Armananzas, R, Author
Ascoli, G, Author
Bielza, C, Author
Bokharaie, VS1, 2, Author              
Bergmann, T, Author
Bystron, I, Author
Capogna, M, Author
Chang, Y, Author
Clemens , A, Author
de Kock, C, Author
DeFelipe, J, Author
Dos Santos, S, Author
Dunville, K, Author
Feldmeyer, D, Author
Fiáth, R, Author
Fishell, G, Author
Foggetti, A, AuthorGao, X, AuthorGhaderi, P, AuthorGüntürkün, O, AuthorHall, VJ, AuthorHelmstaedter, M, AuthorHerculano-Houzel, S, AuthorHilscher, M, AuthorHirase, H, AuthorHjerling-Leffler, J, AuthorHodge, R, AuthorHuang, ZJ, AuthorHuda, R, AuthorJuan, Y, AuthorKhodosevich, K, AuthorKiehn, O, AuthorKoch, H, AuthorKuebler, E, AuthorKühnemund, M, AuthorLarrañaga, P, AuthorLelieveldt, D, AuthorLouth, EL, AuthorLui, J, AuthorMansvelder, H, AuthorMarin, O, AuthorMartínez-Trujillo, J, AuthorMoradi, H, AuthorGoriounova, N, AuthorMohapatra, A, AuthorNedergaard, M, AuthorNěmec, P, AuthorOfer, N, AuthorPfisterer, U, AuthorPontes, S, AuthorRedmond , W, AuthorRossier, J, AuthorSanes, J, AuthorScheuermann, R, AuthorSerrano Saiz, E, AuthorSomogyi, P, AuthorTamás, G, AuthorTolias, A, Author              Tosches, M, AuthorTurrero Garcia, M, AuthorAguilar-Valles, A, AuthorMunguba, H, AuthorWozny, C, AuthorWuttke, T, AuthorYong, L, AuthorZeng, H, AuthorLein, ES, Author more..
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 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.

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 Dates: 2020-082020-12
 Publication Status: Published in print
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1038/s41593-020-0685-8
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Title: Nature Neuroscience
  Other : Nat. Neurosci.
Source Genre: Journal
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Publ. Info: New York, NY : Nature America Inc.
Pages: - Volume / Issue: 23 (12) Sequence Number: - Start / End Page: 1456 - 1468 Identifier: ISSN: 1097-6256
CoNE: https://pure.mpg.de/cone/journals/resource/954925610931