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<p>Morphogens direct neuroepithelial fates toward discrete regional identities in vivo. Neural organoids provide models for studying neural regionalization through morphogen exposure; however, we lack a comprehensive survey of how the developing human neuroepithelium responds to morphogen cues. Here we produce a detailed survey of morphogen-induced effects on the regional specification of human neural organoids using multiplexed single-cell transcriptomic screens. We find that the timing, concentration and combination of morphogens strongly influence organoid cell-type and regional composition, and that cell line and neural induction method impact the response to a given morphogen condition. We apply concentration gradients in microfluidic chips or increasing static concentrations in multi-well plates and observe different patterning dynamics in each scenario. Altogether, we provide a detailed resource on neural lineage specification that, in combination with deep learning models, can enable the prediction of differentiation outcomes in human stem-cell-based systems.</p>

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Systematic scRNA-seq screens profile neural organoid response to morphogens

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月15日

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  • Fátima Sanchís-Calleja,
  • Nadezhda Azbukina,
  • Akanksha Jain,
  • Zhisong He,
  • Ryoko Okamoto,
  • Charlotte Rusimbi,
  • Pedro Rifes,
  • Gaurav Singh Rathore,
  • Malgorzata Santel,
  • Jasper Janssens,
  • Makiko Seimiya,
  • Benedikt Eisinger,
  • Jonas Simon Fleck,
  • Agnete Kirkeby,
  • J. Gray Camp,
  • Barbara Treutlein

摘要

Morphogens direct neuroepithelial fates toward discrete regional identities in vivo. Neural organoids provide models for studying neural regionalization through morphogen exposure; however, we lack a comprehensive survey of how the developing human neuroepithelium responds to morphogen cues. Here we produce a detailed survey of morphogen-induced effects on the regional specification of human neural organoids using multiplexed single-cell transcriptomic screens. We find that the timing, concentration and combination of morphogens strongly influence organoid cell-type and regional composition, and that cell line and neural induction method impact the response to a given morphogen condition. We apply concentration gradients in microfluidic chips or increasing static concentrations in multi-well plates and observe different patterning dynamics in each scenario. Altogether, we provide a detailed resource on neural lineage specification that, in combination with deep learning models, can enable the prediction of differentiation outcomes in human stem-cell-based systems.