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

Research output: Contribution to journal › Journal article › peer-review

Standard

A community-based transcriptomics classification and nomenclature of neocortical cell types. / Yuste, Rafael; Hawrylycz, Michael; Aalling, Nadia; Aguilar-valles, Argel; Arendt, Detlev; Arnedillo, Ruben Armananzas; 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, 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; Moradi Chameh, Homeira; Nath, Alok; Nedergaard, Maiken; Němec, Pavel; Ofer, Netanel; Pfisterer, Ulrich Gottfried; Pontes, Samuel; Redmond, William; Rossier, Jean; Sanes, Joshua R.; Scheuermann, Richard; Serrano-saiz, Esther; Steiger, Jochen F.; Somogyi, Peter; Tamás, Gábor; Tolias, Andreas Savas; Tosches, Maria Antonietta; García, Miguel Turrero; Vieira, Hermany Munguba; Wozny, Christian; Wuttke, Thomas V.; Yong, Liu; Yuan, Juan; Zeng, Hongkui; Lein, Ed.

In: Nature Neuroscience, Vol. 23, 2020, p. 1456-1468.

Research output: Contribution to journal › Journal article › peer-review

Harvard

Yuste, R, Hawrylycz, M, Aalling, N, Aguilar-valles, A, Arendt, D, Arnedillo, RA, Ascoli, GA, Bielza, C, Bokharaie, V, Bergmann, TB, Bystron, I, Capogna, M, Chang, Y, Clemens, A, De Kock, CPJ, Defelipe, J, Dos Santos, SE, Dunville, K, Feldmeyer, D, Fiáth, R, Fishell, GJ, Foggetti, A, Gao, X, Ghaderi, P, Goriounova, NA, Güntürkün, O, Hagihara, K, Hall, VJ, Helmstaedter, M, Herculano, S, Hilscher, MM, Hirase, H, Hjerling-leffler, J, Hodge, R, Huang, J, Huda, R, Khodosevich, K, Kiehn, O, Koch, H, Kuebler, ES, Kühnemund, M, Larrañaga, P, Lelieveldt, B, Louth, EL, Lui, JH, Mansvelder, HD, Marin, O, Martinez-trujillo, J, Moradi Chameh, H, Nath, A, Nedergaard, M, Němec, P, Ofer, N, Pfisterer, UG, Pontes, S, Redmond, W, Rossier, J, Sanes, JR, Scheuermann, R, Serrano-saiz, E, Steiger, JF, Somogyi, P, Tamás, G, Tolias, AS, Tosches, MA, García, MT, Vieira, HM, Wozny, C, Wuttke, TV, Yong, L, Yuan, J, Zeng, H & Lein, E 2020, 'A community-based transcriptomics classification and nomenclature of neocortical cell types', Nature Neuroscience, vol. 23, pp. 1456-1468. https://doi.org/10.1038/s41593-020-0685-8

APA

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., ... Lein, E. (2020). A community-based transcriptomics classification and nomenclature of neocortical cell types. Nature Neuroscience, 23, 1456-1468. https://doi.org/10.1038/s41593-020-0685-8

Vancouver

Yuste R, Hawrylycz M, Aalling N, Aguilar-valles A, Arendt D, Arnedillo RA et al. A community-based transcriptomics classification and nomenclature of neocortical cell types. Nature Neuroscience. 2020;23:1456-1468. https://doi.org/10.1038/s41593-020-0685-8

Author

Yuste, Rafael ; Hawrylycz, Michael ; Aalling, Nadia ; Aguilar-valles, Argel ; Arendt, Detlev ; Arnedillo, Ruben Armananzas ; 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, 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 ; Moradi Chameh, Homeira ; Nath, Alok ; Nedergaard, Maiken ; Němec, Pavel ; Ofer, Netanel ; Pfisterer, Ulrich Gottfried ; Pontes, Samuel ; Redmond, William ; Rossier, Jean ; Sanes, Joshua R. ; Scheuermann, Richard ; Serrano-saiz, Esther ; Steiger, Jochen F. ; Somogyi, Peter ; Tamás, Gábor ; Tolias, Andreas Savas ; Tosches, Maria Antonietta ; García, Miguel Turrero ; Vieira, Hermany Munguba ; Wozny, Christian ; Wuttke, Thomas V. ; Yong, Liu ; Yuan, Juan ; Zeng, Hongkui ; Lein, Ed. / A community-based transcriptomics classification and nomenclature of neocortical cell types. In: Nature Neuroscience. 2020 ; Vol. 23. pp. 1456-1468.

Bibtex

@article{c22191a397da4d5fb8ced11633a25684,
title = "A community-based transcriptomics classification and nomenclature of neocortical cell types",
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.",
author = "Rafael Yuste and Michael Hawrylycz and Nadia Aalling and Argel Aguilar-valles and Detlev Arendt and Arnedillo, {Ruben Armananzas} and Ascoli, {Giorgio A.} and Concha Bielza and Vahid Bokharaie and Bergmann, {Tobias Borgtoft} and Irina Bystron and Marco Capogna and Yoonjeung Chang and Ann Clemens and {De Kock}, {Christiaan P. J.} and Javier Defelipe and {Dos Santos}, {Sandra Esmeralda} and Keagan Dunville and Dirk Feldmeyer and Rich{\'a}rd Fi{\'a}th and Fishell, {Gordon James} and Angelica Foggetti and Xuefan Gao and Parviz Ghaderi and Goriounova, {Natalia A.} and Onur G{\"u}nt{\"u}rk{\"u}n and Kenta Hagihara and Hall, {Vanessa Jane} and Moritz Helmstaedter and Suzana Herculano and Hilscher, {Markus M.} and Hajime Hirase and Jens Hjerling-leffler and Rebecca Hodge and Josh Huang and Rafiq Huda and Konstantin Khodosevich and Ole Kiehn and Henner Koch and Kuebler, {Eric S.} and Malte K{\"u}hnemund and Pedro Larra{\~n}aga and Boudewijn Lelieveldt and Louth, {Emma Louise} and Lui, {Jan H.} and Mansvelder, {Huibert D.} and Oscar Marin and Julio Martinez-trujillo and {Moradi Chameh}, Homeira and Alok Nath and Maiken Nedergaard and Pavel N{\v e}mec and Netanel Ofer and Pfisterer, {Ulrich Gottfried} and Samuel Pontes and William Redmond and Jean Rossier and Sanes, {Joshua R.} and Richard Scheuermann and Esther Serrano-saiz and Steiger, {Jochen F.} and Peter Somogyi and G{\'a}bor Tam{\'a}s and Tolias, {Andreas Savas} and Tosches, {Maria Antonietta} and Garc{\'i}a, {Miguel Turrero} and Vieira, {Hermany Munguba} and Christian Wozny and Wuttke, {Thomas V.} and Liu Yong and Juan Yuan and Hongkui Zeng and Ed Lein",
year = "2020",
doi = "10.1038/s41593-020-0685-8",
language = "English",
volume = "23",
pages = "1456--1468",
journal = "Nature Neuroscience",
issn = "1097-6256",
publisher = "nature publishing group",

}

RIS

TY - JOUR

T1 - A community-based transcriptomics classification and nomenclature of neocortical cell types

AU - Yuste, Rafael

AU - Hawrylycz, Michael

AU - Aalling, Nadia

AU - Aguilar-valles, Argel

AU - Arendt, Detlev

AU - Arnedillo, Ruben Armananzas

AU - Ascoli, Giorgio A.

AU - Bielza, Concha

AU - Bokharaie, Vahid

AU - Bergmann, Tobias Borgtoft

AU - Bystron, Irina

AU - Capogna, Marco

AU - Chang, Yoonjeung

AU - Clemens, Ann

AU - De Kock, Christiaan P. J.

AU - Defelipe, Javier

AU - Dos Santos, Sandra Esmeralda

AU - Dunville, Keagan

AU - Feldmeyer, Dirk

AU - Fiáth, Richárd

AU - Fishell, Gordon James

AU - Foggetti, Angelica

AU - Gao, Xuefan

AU - Ghaderi, Parviz

AU - Goriounova, Natalia A.

AU - Güntürkün, Onur

AU - Hagihara, Kenta

AU - Hall, Vanessa Jane

AU - Helmstaedter, Moritz

AU - Herculano, Suzana

AU - Hilscher, Markus M.

AU - Hirase, Hajime

AU - Hjerling-leffler, Jens

AU - Hodge, Rebecca

AU - Huang, Josh

AU - Huda, Rafiq

AU - Khodosevich, Konstantin

AU - Kiehn, Ole

AU - Koch, Henner

AU - Kuebler, Eric S.

AU - Kühnemund, Malte

AU - Larrañaga, Pedro

AU - Lelieveldt, Boudewijn

AU - Louth, Emma Louise

AU - Lui, Jan H.

AU - Mansvelder, Huibert D.

AU - Marin, Oscar

AU - Martinez-trujillo, Julio

AU - Moradi Chameh, Homeira

AU - Nath, Alok

AU - Nedergaard, Maiken

AU - Němec, Pavel

AU - Ofer, Netanel

AU - Pfisterer, Ulrich Gottfried

AU - Pontes, Samuel

AU - Redmond, William

AU - Rossier, Jean

AU - Sanes, Joshua R.

AU - Scheuermann, Richard

AU - Serrano-saiz, Esther

AU - Steiger, Jochen F.

AU - Somogyi, Peter

AU - Tamás, Gábor

AU - Tolias, Andreas Savas

AU - Tosches, Maria Antonietta

AU - García, Miguel Turrero

AU - Vieira, Hermany Munguba

AU - Wozny, Christian

AU - Wuttke, Thomas V.

AU - Yong, Liu

AU - Yuan, Juan

AU - Zeng, Hongkui

AU - Lein, Ed

PY - 2020

Y1 - 2020

N2 - 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.

AB - 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.

U2 - 10.1038/s41593-020-0685-8

DO - 10.1038/s41593-020-0685-8

M3 - Journal article

C2 - 32839617

VL - 23

SP - 1456

EP - 1468

JO - Nature Neuroscience

JF - Nature Neuroscience

SN - 1097-6256

ER -

ID: 247388258