ArticleNucleic acids research2020
Kinetic modeling of stem cell transcriptome dynamics to identify regulatory modules of normal and disturbed neuroectodermal differentiation.
Article in Nucleic acids research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- The chronODE framework for modelling multi-omic time series with ordinary differential equations and machine learning.Nature communications · 2025Article
- Article
- Sex-biased gene expression during neural differentiation of human embryonic stem cells.Frontiers in cell and developmental biology · 2024Article
- Transcriptome-based prediction of drugs, inhibiting cardiomyogenesis in human induced pluripotent stem cells.Cell death discovery · 2023Article
- G × E interactions as a basis for toxicological uncertainty.Archives of toxicology · 2023Article
- Article
- Optimization of the TeraTox Assay for Preclinical Teratogenicity Assessment.Toxicological sciences : an official journal of the Society of Toxicology · 2022Article
- Pluripotent stem cell assays: Modalities and applications for predictive developmental toxicity.Current research in toxicology · 2022Article
- Valproic acid promotes the in vitro differentiation of human pluripotent stem cells into spermatogonial stem cell-like cells.Stem cell research & therapy · 2021Article
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11 authors.
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Abstract
Thousands of transcriptome data sets are available, but approaches for their use in dynamic cell response modelling are few, especially for processes affected simultaneously by two orthogonal influencing variables. We approached this problem for neuroepithelial development of human pluripotent stem cells (differentiation variable), in the presence or absence of valproic acid (signaling variable). Using few basic assumptions (sequential differentiation states of cells; discrete on/off states for individual genes in these states), and time-resolved transcriptome data, a comprehensive model of spontaneous and perturbed gene expression dynamics was developed. The model made reliable predictions (average correlation of 0.85 between predicted and subsequently tested expression values). Even regulations predicted to be non-monotonic were successfully validated by PCR in new sets of experiments. Transient patterns of gene regulation were identified from model predictions. They pointed towards activation of Wnt signaling as a candidate pathway leading to a redirection of differentiation away from neuroepithelial cells towards neural crest. Intervention experiments, using a Wnt/beta-catenin antagonist, led to a phenotypic rescue of this disturbed differentiation. Thus, our broadly applicable model allows the analysis of transcriptome changes in complex time/perturbation matrices.
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