A Community-Based Transcriptomics Classification and Nomenclature Of
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COMMENT | FOCUS comment | FOCUS A community-based transcriptomics classifcation and nomenclature of neocortical cell types 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 unifed taxonomy of neuronal or glial cell types, partly due to limited data. Single-cell transcriptomics is enabling, for the frst 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 defned 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 classifcation should be hierarchical and use a standardized nomenclature. It should be based on a probabilistic defnition of a cell type and incorporate data from diferent approaches, developmental stages and species. A community-based classifcation and data aggregation model, such as a knowledge graph, could provide a common foundation for the study of cortical circuits. This community-based classifcation, nomenclature and data aggregation could serve as an example for cell type atlases in other parts of the body. Rafael Yuste, Michael Hawrylycz, Nadia Aalling, Argel Aguilar-Valles, Detlev Arendt, Ruben Armananzas Arnedillo, Giorgio A. Ascoli, Concha Bielza, Vahid Bokharaie, Tobias Borgtoft Bergmann, Irina Bystron, Marco Capogna, Yoonjeung Chang, Ann Clemens, Christiaan P. J. de Kock, Javier DeFelipe, Sandra Esmeralda Dos Santos, Keagan Dunville, Dirk Feldmeyer, Richárd Fiáth, Gordon James Fishell, Angelica Foggetti, Xuefan Gao, Parviz Ghaderi, Natalia A. Goriounova, Onur Güntürkün, Kenta Hagihara, Vanessa Jane Hall, Moritz Helmstaedter, Suzana Herculano, Markus M. Hilscher, Hajime Hirase, Jens Hjerling-Lefer, Rebecca Hodge, Josh Huang, Rafq Huda, Konstantin Khodosevich, Ole Kiehn, Henner Koch, Eric S. Kuebler, Malte Kühnemund, Pedro Larrañaga, Boudewijn Lelieveldt, Emma Louise Louth, Jan H. Lui, Huibert D. Mansvelder, Oscar Marin, Julio Martinez-Trujillo, Homeira Moradi Chameh, Alok Nath, Maiken Nedergaard, Pavel Němec, Netanel Ofer, Ulrich Gottfried Pfsterer, Samuel Pontes, William Redmond, Jean Rossier, Joshua R. Sanes, Richard Scheuermann, Esther Serrano-Saiz, Jochen F. Steiger, Peter Somogyi, Gábor Tamás, Andreas Savas Tolias, Maria Antonietta Tosches, Miguel Turrero García, Hermany Munguba Vieira, Christian Wozny, Thomas V. Wuttke, Liu Yong, Juan Yuan, Hongkui Zeng and Ed Lein Classifcations of cortical cell types: ideally systematized into ‘cell taxonomies’, neuron2. Since then, generations of from Cajal to the Petilla Convention classifying groups of cells based on shared investigators have described hundreds of cell The conceptual foundation of modern characteristics and grouping them into taxa types in nervous systems of different species. biology is the cell theory of Virchow, with ranks and a hierarchy. Taxonomies This effort has been particularly arduous which described the cell as the basic unit are important: they provide a conceptual in the cerebral cortex (or neocortex), the of structure, reproduction and pathology foundation for a field and also enable the largest part of the brain in mammals and the of biological organisms1. This idea, which systematic accumulation of knowledge. primary site of higher cognitive functions. arose from the use of microscopes by Essential to this effort is the clear definition The mammalian neocortex has a thin Leeuwenhoek, Hooke, Schleiden and of cell type, normally understood as cells layered structure, composed of mixtures of Schwann, among others, generated the need with shared phenotypic characteristics. excitatory and inhibitory neurons arranged to build catalogs of the cellular components Virchow’s cell theory was introduced in circuits of a forbidding complexity, called of tissues as the first step toward studying to neuroscience by Cajal, whose ‘neuron “impenetrable jungles” by Cajal3. This basic their structure and function. As with doctrine’ postulated that the structural unit structure is very similar in different cortical species, these cell catalogs, or atlases, can be of the nervous system was the individual areas and in different species, which has 1456 NATURE NEUROSCIENCE | VOL 23 | DECEMBER 2020 | 1456–1468 | www.nature.com/natureneuroscience FOCUS | COMMENT FOCUS | comment given rise to the possibility that there is a agreement as to which would form an a few hundred cells per experiment, effective ‘canonical’ cortical microcircuit4–7, replicated optimal basis for classification. In principle, new methods have emerged for profiling during evolution, which underlies all many criteria can be used, including thousands of cells or nuclei at a time44–48. cortical function. (i) anatomical or connectivity-based With simultaneous computational advances After more than a hundred years of features19,20, (ii) parametrization of intrinsic for analyzing large sequence-based data49,50, sustained progress, it is clear that neocortical electrophysiological properties21, (iii) it is now possible to systematically neurons and glial cells, like cells in any combination of structural and physiological classify and characterize the diversity of tissue, belong to many distinct types. criteria22,23, (iv) molecular markers14,24,25, (v) neural cells in any tissue, including the Different cell types likely play discrete developmental origins26,27, (vi) epigenetic neocortex (Fig. 2). roles in cortical function and computation, attractor states28 or (vii) evolutionary Conceptually, as much as the genome making it important to characterize and approaches identifying homology across is the internal genetic description for each describe them accurately and in their species29,30. Ideally, these classifications species, the transcriptome, as the complete absolute and relative numbers. Towering should converge and agree, or at least set of genes being expressed, provides an historical figures like Cajal, Lorente de Nó substantially overlap. Indeed, there is internal code that can describe each cell and Szentágothai, among others, proposed substantial concordance among categories within an organism in a spatiotemporal classifications of cortical cells based on their based on anatomical, molecular and context. Practically, the scale of scRNAseq morphologies as visualized with histological physiological criteria13,22,31–34, but it has not promises near-saturating analysis of stains4,8,9 (Fig. 1a–c). These anatomical been easy to combine these approaches complex cellular brain regions like the classifications described several dozen types into a unified taxonomy. There are neocortex, providing, for the first time, a of pyramidal neurons, short-axon cells substantial differences between researchers comprehensive and quantitative description and glial cells, and they were subsequently in assigning neurons to particular types of cellular diversity and the prospect of complemented by morphological accounts in the literature19, and even experts often simplifying tissue cell composition to a finite of additional cortical cell types by many disagree on what constitutes ground truth. number of cell types and states defined by researchers10–12, but without arriving at a For example, while most publications agree statistical clustering. Importantly, however, clear consensus as to the number or even the on what a chandelier cell is, the concept of these transcriptionally defined clusters definition of a cortical cell type. basket cells, a major subtype of inhibitory represent a probabilistic description of cell Over the last few decades, the neuron, is much less clear19. types in a high-dimensional landscape of introduction of new morphological, This uncertainty is explained and gene expression across all cells in a tissue, ultrastructural, immunohistochemical and exacerbated by technical challenges: rather than a definition based on a small set electrophysiological methods, new molecular conventional approaches have been of necessary and sufficient cellular markers markers, and a growing appreciation of the laborious, low-throughput, frequently or other features (see below). developmental origins of distinct neuronal non-quantitative and generally plagued by The scale, precision and information subtypes (Fig. 1d–h), have provided an inability to sample cells in standardized content of these current methods now far increasingly finer phenotypic measurements and systematic ways. Thus, setting aside outpace other classical methods of cellular of cortical cells and enabled new efforts to debates about the importance of various phenotyping in neuroscience and have the classify them more quantitatively, using criteria and the nature or even existence potential to approach the complete, accurate supervised or unsupervised methods such of discrete cell types, it is not surprising and permanent (CAP) criteria cited by as cluster analysis13–16. A community effort that the cell-type problem has remained Brenner as the gold standard in biological to classify neocortical inhibitory cells was challenging. science51. Indeed, major efforts now aim attempted at the 2005 Petilla Convention, to generate a complete description of cell held in Cajal’s hometown