ArticleProceedings of the National Academy of Sciences of the United States of America2017
Cell population structure prior to bifurcation predicts efficiency of directed differentiation in human induced pluripotent cells.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.
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Who cites it
58 citing papers in PubMed, 124 citations in OpenAlex.
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- FatePredictor: Cell fate decision-making prediction with an ensemble deep learning model.Innovation (Cambridge (Mass.)) · 2025Article
- Integrating Spatial Omics and Deep Learning: Toward Predictive Models of Cardiomyocyte Differentiation Efficiency.Bioengineering (Basel, Switzerland) · 2025Review
- Neural network approaches, including use of topological data analysis, enhance classification of human induced pluripotent stem cell colonies by treatment condition.PLoS computational biology · 2025Article
- Single-cell analyses reveal increased gene expression variability in human neurodevelopmental conditions.American journal of human genetics · 2025Article
- Fokker-Planck diffusion maps of microglial transcriptomes reveal radial differentiation into substates associated with Alzheimer's pathology.Communications biology · 2025Article
- The network structural entropy for single-cell RNA sequencing data during skin aging.Briefings in bioinformatics · 2024Article
- FateNet: an integration of dynamical systems and deep learning for cell fate prediction.Bioinformatics (Oxford, England) · 2024Article
- Fokker-Planck diffusion maps of multiple single cell microglial transcriptomes reveals radial differentiation into substates associated with Alzheimer's pathology.bioRxiv : the preprint server for biology · 2024Article
- CPMI: comprehensive neighborhood-based perturbed mutual information for identifying critical states of complex biological processes.BMC bioinformatics · 2024Article
- Topological and geometric analysis of cell states in single-cell transcriptomic data.Briefings in bioinformatics · 2024Article
- MIWE: detecting the critical states of complex biological systems by the mutual information weighted entropy.BMC bioinformatics · 2024Article
- Reconstructing growth and dynamic trajectories from single-cell transcriptomics data.Nature machine intelligence · 2024Article
- Identifying a developmental transition in honey bees using gene expression data.PLoS computational biology · 2023Article
- Cell Features Reconstruction from Gene Association Network of Single Cell.Interdisciplinary sciences, computational life sciences · 2023Article
- Self-Regulated Symmetry Breaking Model for Stem Cell Differentiation.Entropy (Basel, Switzerland) · 2023Article
- The transcriptional portraits of the neural crest at the individual cell level.Seminars in cell & developmental biology · 2023Review
- Concepts of multi-level dynamical modelling: understanding mechanisms of squamous cell carcinoma development in Fanconi anemia.Frontiers in genetics · 2023Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Steering the differentiation of induced pluripotent stem cells (iPSCs) toward specific cell types is crucial for patient-specific disease modeling and drug testing. This effort requires the capacity to predict and control when and how multipotent progenitor cells commit to the desired cell fate. Cell fate commitment represents a critical state transition or "tipping point" at which complex systems undergo a sudden qualitative shift. To characterize such transitions during iPSC to cardiomyocyte differentiation, we analyzed the gene expression patterns of 96 developmental genes at single-cell resolution. We identified a bifurcation event early in the trajectory when a primitive streak-like cell population segregated into the mesodermal and endodermal lineages. Before this branching point, we could detect the signature of an imminent critical transition: increase in cell heterogeneity and coordination of gene expression. Correlation analysis of gene expression profiles at the tipping point indicates transcription factors that drive the state transition toward each alternative cell fate and their relationships with specific phenotypic readouts. The latter helps us to facilitate small molecule screening for differentiation efficiency. To this end, we set up an analysis of cell population structure at the tipping point after systematic variation of the protocol to bias the differentiation toward mesodermal or endodermal cell lineage. We were able to predict the proportion of cardiomyocytes many days before cells manifest the differentiated phenotype. The analysis of cell populations undergoing a critical state transition thus affords a tool to forecast cell fate outcomes and can be used to optimize differentiation protocols to obtain desired cell populations.
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Registered trials
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