An integrated transcriptomic cell atlas of human neural organoids

Zhisong He(ETH Zurich), Leander Dony(Helmholtz Zentrum München), Jonas Simon Fleck(Roche (Switzerland)), Artur Szałata(Helmholtz Zentrum München), Katelyn X. Li(Helmholtz Zentrum München), Irena Slišković(Helmholtz Zentrum München), Hsiu‐Chuan Lin(ETH Zurich), Małgorzata Santel(ETH Zurich), Alexander Atamian(University of Southern California), Giorgia Quadrato(University of Southern California), Jieran Sun(ETH Zurich), Sergiu P. Pașca(Neurosciences Institute), Human Cell Atlas Organoid Biological Network(Stanford University), Neal D. Amin(Neurosciences Institute), Kevin W. Kelley(Neurosciences Institute), Taylor Bertucci(Neural Stem Cell Institute), Sally Temple(Neural Stem Cell Institute), Kathryn R. Bowles(Human Technopole), Nicolò Caporale(University of Milan), Carlo Emanuele Villa(Human Technopole), Giuseppe Testa(University of Milan), Cristiana Cruceanu(Karolinska Institutet), Elisabeth B. Binder(Roche (Switzerland)), J. Gray Camp(Roche (Switzerland)), Fabian J. Theis(Helmholtz Zentrum München), Barbara Treutlein(ETH Zurich)
Nature
November 20, 2024
Cited by 113Open Access
Full Text

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 cells1–26. Mapping to developing human brain references27–30 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. A human neural organoid cell atlas integrating 36 single-cell transcriptomic datasets shows cell types and states and estimates transcriptomic similarity between primary and organoid counterparts, showing potential to assess organoid fidelity and facilitate protocol development.


Related Papers