Reassessment of marker genes in human induced pluripotent stem cells for enhanced quality control

Human induced pluripotent stem cells (iPSCs) have great potential in research, but pluripotency testing faces challenges due to non-standardized methods and ambiguous markers. Here, we use long-read nanopore transcriptome sequencing to discover 172 genes linked to cell states not covered by current guidelines. We validate 12 genes by qPCR as unique markers for specific cell fates: pluripotency (CNMD, NANOG, SPP1), endoderm (CER1, EOMES, GATA6), mesoderm (APLNR, HAND1, HOXB7), and ectoderm (HES5, PAMR1, PAX6). Using these genes, we develop a machine learning-based scoring system, "hiPSCore", trained on 15 iPSC lines and validated on 10 more. hiPSCore accurately classifies pluripotent and differentiated cells and predicts their potential to become specialized 2D cells and 3D organoids. Our re-evaluation of cell fate marker genes identifies key targets for future studies on cell fate assessment. hiPSCore improves iPSC testing by reducing time, subjectivity, and resource use, thus enhancing iPSC quality for scientific and medical applications.

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Publication Details

Journal
Nature Communications
Published
2024-10-02
DOI
https://doi.org/10.1038/s41467-024-52922-1
Citations
28
Primary Topic
Pluripotent Stem Cells Research
Type
article
Field-Weighted Citation Impact
6.55

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article

Reassessment of marker genes in human induced pluripotent stem cells for enhanced quality control

Alessandro Prigione, Sebastian Diecke, Jochen Dobner, Jean Krutmann et al.
28 citations
Nature Communications
Pluripotent Stem Cells Research
6.55
article

Reassessment of marker genes in human induced pluripotent stem cells for enhanced quality control

Alessandro Prigione, Sebastian Diecke, Jochen Dobner, Jean Krutmann, Andrea Rossi
article en
28 citations

Abstract

Human induced pluripotent stem cells (iPSCs) have great potential in research, but pluripotency testing faces challenges due to non-standardized methods and ambiguous markers. Here, we use long-read nanopore transcriptome sequencing to discover 172 genes linked to cell states not covered by current guidelines. We validate 12 genes by qPCR as unique markers for specific cell fates: pluripotency (CNMD, NANOG, SPP1), endoderm (CER1, EOMES, GATA6), mesoderm (APLNR, HAND1, HOXB7), and ectoderm (HES5, PAMR1, PAX6). Using these genes, we develop a machine learning-based scoring system, "hiPSCore", trained on 15 iPSC lines and validated on 10 more. hiPSCore accurately classifies pluripotent and differentiated cells and predicts their potential to become specialized 2D cells and 3D organoids. Our re-evaluation of cell fate marker genes identifies key targets for future studies on cell fate assessment. hiPSCore improves iPSC testing by reducing time, subjectivity, and resource use, thus enhancing iPSC quality for scientific and medical applications.

Nature CommunicationsVol. 15(1)
Max Delbrück Center (DE), Düsseldorf University Hospital (DE), Leibniz Institute of Environmental Medicine (DE), Heinrich Heine University Düsseldorf (DE)
European Commission, Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, AFM-Téléthon, Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, Leibniz-Gemeinschaft
Openalex Percentile: Top 2%
Pluripotent Stem Cells Research
6.55
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