An integrated transcriptomic cell atlas of human neural organoids

Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.7 million cells<sup>1-26</sup>. Mapping to developing human brain references<sup>27-30</sup> shows primary cell types and states that have been generated in vitro, and estimates transcriptomic similarity between primary and organoid counterparts across protocols. We provide a programmatic interface to browse the atlas and query new datasets, and showcase the power of the atlas to annotate organoid cell types and evaluate new organoid protocols. Finally, we show that the atlas can be used as a diverse control cohort to annotate and compare organoid models of neural disease, identifying genes and pathways that may underlie pathological mechanisms with the neural models. The human neural organoid cell atlas will be useful to assess organoid fidelity, characterize perturbed and diseased states and facilitate protocol development.

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Publication Details

Journal
Nature
Published
2024-11-20
DOI
https://doi.org/10.1038/s41586-024-08172-8
Citations
101
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
23.38
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article

An integrated transcriptomic cell atlas of human neural organoids

Irena Slišković, Barbara Treutlein, Neal D. Amin, Taylor Bertucci et al.
101 citations
Nature
Single-cell and spatial transcriptomics
23.38
article

An integrated transcriptomic cell atlas of human neural organoids

Irena Slišković, Barbara Treutlein, Neal D. Amin, Taylor Bertucci, Hsiu‐Chuan Lin, Katelyn X. Li, Leander Dony, Jieran Sun, Kevin W. Kelley, Cristiana Cruceanu, Artur Szałata, Małgorzata Santel, Giorgia Quadrato, Carlo Emanuele Villa, J. Gray Camp, Nicolò Caporale, Zhisong He, Alexander Atamian, Fabian Joachim Theis, Sally Temple, Jonas Simon Fleck, Giuseppe Testa, Sergiu P. Pașca, Kathryn R. Bowles, Elisabeth B. Binder
article en
101 citations

Abstract

Human neural organoids, generated from pluripotent stem cells in vitro, are useful tools to study human brain development, evolution and disease. However, it is unclear which parts of the human brain are covered by existing protocols, and it has been difficult to quantitatively assess organoid variation and fidelity. Here we integrate 36 single-cell transcriptomic datasets spanning 26 protocols into one integrated human neural organoid cell atlas totalling more than 1.7 million cells<sup>1-26</sup>. Mapping to developing human brain references<sup>27-30</sup> shows primary cell types and states that have been generated in vitro, and estimates transcriptomic similarity between primary and organoid counterparts across protocols. We provide a programmatic interface to browse the atlas and query new datasets, and showcase the power of the atlas to annotate organoid cell types and evaluate new organoid protocols. Finally, we show that the atlas can be used as a diverse control cohort to annotate and compare organoid models of neural disease, identifying genes and pathways that may underlie pathological mechanisms with the neural models. The human neural organoid cell atlas will be useful to assess organoid fidelity, characterize perturbed and diseased states and facilitate protocol development.

NatureVol. 635(8039)
University of Southern California (US), Roche (Switzerland) (CH), University of Basel (CH), Neurosciences Institute (US), University of Milan (IT), Karolinska Institutet (SE), Helmholtz Zentrum München (DE), ETH Zurich (CH), Neural Stem Cell Institute (US), Human Technopole (IT), UK Dementia Research Institute (GB), Max Planck Institute of Psychiatry (DE), Broad Center (US), Organogenesis (United States) (US), Technical University of Munich (DE), Stanford University (US), University of Edinburgh (GB)
Openalex Percentile: Top 0%
Single-cell and spatial transcriptomics
23.38
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