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An integrated transcriptomic cell atlas of human endoderm-derived organoids

  • Quan Xu
  • , Lennard Halle
  • , Soroor Hediyeh-zadeh
  • , Merel Kuijs
  • , Rya Riedweg
  • , Umut Kilik
  • , Timothy Recaldin
  • , Qianhui Yu
  • , Isabell Rall
  • , Tristan Frum
  • , Lukas Adam
  • , Shrey Parikh
  • , Raphael Kfuri-Rubens
  • , Manuel Gander
  • , Dominik Klein
  • , Fabiola Curion
  • , Zhisong He
  • , Jonas Simon Fleck
  • , Koen Oost
  • , Maurice Kahnwald
  • Silvia Barbiero, Olga Mitrofanova, Grzegorz Jerzy Maciag, Kim B. Jensen, Matthias Lutolf, Prisca Liberali, Jason R. Spence, Nikolche Gjorevski, Joep Beumer, Barbara Treutlein, Fabian J. Theis, J. Gray Camp
  • Roche Pharma Research & Early Development
  • Helmholtz Zentrum München German Research Center for Environmental Health
  • Technical University of Munich
  • Biocenter of the University
  • University of Michigan Medical School
  • ETH Zurich
  • Friedrich Miescher Institute for Biomedical Research
  • University of Copenhagen
  • EPFL
  • Department of Biomedical Engineering

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Human pluripotent stem cells and tissue-resident fetal and adult stem cells can generate epithelial tissues of endodermal origin in vitro that recapitulate aspects of developing and adult human physiology. Here, we integrate single-cell transcriptomes from 218 samples covering organoids and other models of diverse endoderm-derived tissues to establish an initial version of a human endoderm-derived organoid cell atlas. The integration includes nearly one million cells across diverse conditions, data sources and protocols. We compare cell types and states between organoid models and harmonize cell annotations through mapping to primary tissue counterparts. Focusing on the intestine and lung, we provide examples of mapping data from new protocols and show how the atlas can be used as a diverse cohort to assess perturbations and disease models. The human endoderm-derived organoid cell atlas makes diverse datasets centrally available and will be valuable to assess fidelity, characterize perturbed and diseased states, and streamline protocol development.

Original languageEnglish
Article numbereabl4896
Pages (from-to)1201-1212
Number of pages12
JournalNature Genetics
Volume57
Issue number5
DOIs
StatePublished - May 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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