Joint profiling of cell morphology and gene expression during in vitro neurodevelopment

Differentiation of induced pluripotent stem cells (iPSCs) toward neuronal lineages has enabled diverse cellular models of human neurodevelopment and related disorders. Here, we jointly profiled neuronal morphology and gene expression at single-cell resolution across 60,000 iPSC-derived cortical neurons at three developmental time points with Cell Painting (CP) and single-cell RNA-sequencing (scRNA-seq). By modeling the relationship between morphological features and gene expression within our differentiation system, we annotated image-based features with biological functions and showed that while CP resolves broader neuronal classes than scRNA-seq, it complements transcriptomic data by quantifying the biological processes that drive neuronal differentiation over time, such as mitochondrial function and cell cycle. Further, we found that while over 60% of the cells resembled those seen in the fetal brain, 28% represented metabolically abnormal cell states and broader neuronal classes specific to <i>in vitro</i> cells. We show that iPSC-derived cortical neurons are nonetheless a relevant model for a range of brain-related complex traits, including schizophrenia and bipolar disorder, and that disease heritability can also be captured in the morphological feature space. Finally, we applied CP to iPSC-derived neural progenitors from patients with Kabuki syndrome, revealing morphological signatures of precocious differentiation and altered cell cycling. These results highlight the potential of multi-modal single-cell characterization to reveal complementary and disease-relevant cellular and molecular phenotypes.

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Publication Details

Journal
eLife
Published
2025-11-03
DOI
https://doi.org/10.7554/elife.102578
Citations
1
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.81
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article

Joint profiling of cell morphology and gene expression during in vitro neurodevelopment

Zhiyu Yang, Riina Lampela, Dimitri Meistermann, Rosa Woldegebriel et al.
1 citations
eLife
Single-cell and spatial transcriptomics
0.81
article

Joint profiling of cell morphology and gene expression during in vitro neurodevelopment

Zhiyu Yang, Riina Lampela, Dimitri Meistermann, Rosa Woldegebriel, Pau Puigdevall, Andrea Ganna, Helena Kilpinen, Adithi Sundaresh
article en
1 citations

Abstract

Differentiation of induced pluripotent stem cells (iPSCs) toward neuronal lineages has enabled diverse cellular models of human neurodevelopment and related disorders. Here, we jointly profiled neuronal morphology and gene expression at single-cell resolution across 60,000 iPSC-derived cortical neurons at three developmental time points with Cell Painting (CP) and single-cell RNA-sequencing (scRNA-seq). By modeling the relationship between morphological features and gene expression within our differentiation system, we annotated image-based features with biological functions and showed that while CP resolves broader neuronal classes than scRNA-seq, it complements transcriptomic data by quantifying the biological processes that drive neuronal differentiation over time, such as mitochondrial function and cell cycle. Further, we found that while over 60% of the cells resembled those seen in the fetal brain, 28% represented metabolically abnormal cell states and broader neuronal classes specific to <i>in vitro</i> cells. We show that iPSC-derived cortical neurons are nonetheless a relevant model for a range of brain-related complex traits, including schizophrenia and bipolar disorder, and that disease heritability can also be captured in the morphological feature space. Finally, we applied CP to iPSC-derived neural progenitors from patients with Kabuki syndrome, revealing morphological signatures of precocious differentiation and altered cell cycling. These results highlight the potential of multi-modal single-cell characterization to reveal complementary and disease-relevant cellular and molecular phenotypes.

eLifeVol. 14
University of Helsinki (FI), Institute for Molecular Medicine Finland (FI)
Openalex Percentile: Top 21%
Single-cell and spatial transcriptomics
0.81
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