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

Nature Neuroscience 2020 25 cites
2020:12021:22022:32023:42024:42025:52026:6
2020 2026
25

Yuste, Rafael and Hawrylycz, Michael and Aalling, Nadia and Aguilar-Valles, Argel and Arendt, Detlev and Arma\~{n}anzas, Ruben and Ascoli, Giorgio A. and Bielza, Concha and Bokharaie, Vahid and Bergmann, Tobias Borgtoft and Bystron, Irina and Capogna, Marco and Chang, YoonJeung and Clemens, Ann and de Kock, Christiaan P. J. and DeFelipe, Javier and Dos Santos, Sandra Esmeralda and Dunville, Keagan and Feldmeyer, Dirk and Fi\'{a}th, Rich\'{a}rd and Fishell, Gordon James and Foggetti, Angelica and Gao, Xuefan and Ghaderi, Parviz and Goriounova, Natalia A. and G\"{u}nt\"{u}rk\"{u}n, Onur and Hagihara, Kenta and Hall, Vanessa Jane and Helmstaedter, Moritz and Herculano-Houzel, Suzana and Hilscher, Markus M. and Hirase, Hajime and Hjerling-Leffler, Jens and Hodge, Rebecca and Huang, Josh and Huda, Rafiq and Khodosevich, Konstantin and Kiehn, Ole and Koch, Henner and Kuebler, Eric S. and K\"{u}hnemund, Malte and Larra\~{n}aga, Pedro and Lelieveldt, Boudewijn and Louth, Emma Louise and Lui, Jan H. and Mansvelder, Huibert D. and Marin, Oscar and Martinez-Trujillo, Julio and Chameh, Homeira Moradi and Mohapatra, Alok Nath and Munguba, Hermany and Nedergaard, Maiken and Nemec, Pavel and Ofer, Netanel and Pfisterer, Ulrich Gottfried and Pontes, Samuel and Redmond, William and Rossier, Jean and Sanes, Joshua R. and Scheuermann, Richard H. and Serrano-Saiz, Esther and Staiger, Jochen F. and Somogyi, Peter and Tam\'{a}s, G\'{a}bor and Tolias, Andreas Savas and Tosches, Maria Antonietta and Garc\'{i}a, Miguel Turrero and Wozny, Christian and Wuttke, Thomas V. and Liu, Yong and Yuan, Juan and Zeng, Hongkui and Lein, Ed

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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