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DOI 10.1038/s41593-020-0685-8

Медицинская библиотека · Nature neuroscience · 2020

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

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

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Аннотация

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.

Для цитирования: Yuste Rafael, Hawrylycz Michael, Aalling Nadia, Aguilar-Valles Argel, Arendt Detlev, Armañanzas Ruben, Ascoli Giorgio A, Bielza Concha, Bokharaie Vahid, Bergmann Tobias Borgtoft, Bystron Irina, Capogna Marco, Chang YoonJeung, Clemens Ann, de Kock Christiaan P J, DeFelipe Javier, Dos Santos Sandra Esmeralda, Dunville Keagan, Feldmeyer Dirk, Fiáth Richárd, Fishell Gordon James, Foggetti Angelica, Gao Xuefan, Ghaderi Parviz, Goriounova Natalia A, Güntürkün Onur, Hagihara Kenta, Hall Vanessa Jane, Helmstaedter Moritz, Herculano-Houzel Suzana, Hilscher Markus M, Hirase Hajime, Hjerling-Leffler Jens, Hodge Rebecca, Huang Josh, Huda Rafiq, Khodosevich Konstantin, Kiehn Ole, Koch Henner, Kuebler Eric S, Kühnemund Malte, Larrañaga Pedro, Lelieveldt Boudewijn, Louth Emma Louise, Lui Jan H, Mansvelder Huibert D, Marin Oscar, Martinez-Trujillo Julio, Chameh Homeira Moradi, Mohapatra Alok Nath, Munguba Hermany, Nedergaard Maiken, Němec Pavel, Ofer Netanel, Pfisterer Ulrich Gottfried, Pontes Samuel, Redmond William, Rossier Jean, Sanes Joshua R, Scheuermann Richard H, Serrano-Saiz Esther, Staiger Jochen F, Somogyi Peter, Tamás Gábor, Tolias Andreas Savas, Tosches Maria Antonietta, García Miguel Turrero, Wozny Christian, Wuttke Thomas V, Liu Yong, Yuan Juan, Zeng Hongkui, Lein Ed. A community-based transcriptomics classification and nomenclature of neocortical cell types.. Nature neuroscience. 2020. DOI: 10.1038/s41593-020-0685-8.

Предметные рубрики MeSH

AnimalsCellsComputational BiologyHumansNeocortexNeurogliaNeuronsSingle-Cell AnalysisTerminology as TopicTranscriptome
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