ArticleNature methods2026
Systematic scRNA-seq screens profile neural organoid response to morphogens.
Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Pathological Priming and Developmental Heterochrony as Organizing Concepts in Human iPSC Models of Autism Spectrum Disorder.Molecular neurobiology · 2026Review
- Brain organoids in Alzheimer disease and related tauopathies: Challenges and opportunities for translational readiness.Stem cell reports · 2026Review
- Morphogen-Directed, High-Throughput Development of hiPSC-Derived Telencephalic Organoids for Comparative In Vitro Phenotyping.Current protocols · 2026Article
- Developmental signaling reveals functionally enriched human-specific gene regulation in telencephalic progenitors.bioRxiv : the preprint server for biology · 2026Article
- Single-cell multi-omic atlas and morphogen screening informs midbrain and hindbrain organoid engineering.Nature neuroscience · 2026Article
- Organizers in a dish: Modeling human CNS morphogenesis.Developmental cell · 2026Review
- Systematic scRNA-seq screens profile neural organoid response to morphogens.Nature methods · 2026Article
- Modeling Alzheimer's disease with brain organoids: mechanisms, applications, and future directions.Frontiers in cell and developmental biology · 2026Review
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
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.
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Registered trials
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