ArticlePLoS computational biology2019
An enriched network motif family regulates multistep cell fate transitions with restricted reversibility.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Design principles for robust multistability in coupled feedforward-feedback regulatory circuits.NPJ systems biology and applications · 2026Article
- Dissecting reversible and irreversible single cell state transitions from gene regulatory networks.Molecular systems biology · 2026Article
- Network hypermotifs in biological systems: structure, dynamics, and functional implications.NPJ systems biology and applications · 2026Review
- Intercellular signaling reinforces single-cell level phenotypic transitions and facilitates robust re-equilibrium of heterogeneous cancer cell populations.Cell communication and signaling : CCS · 2025Article
- Gene regulatory network inference during cell fate decisions by perturbation strategies.NPJ systems biology and applications · 2025Article
- Operating principles of interconnected feedback loops driving cell fate transitions.NPJ systems biology and applications · 2025Article
- OneSC: a computational platform for recapitulating cell state transitions.Bioinformatics (Oxford, England) · 2024Article
- Machine Learning Inference of Gene Regulatory Networks in DevelopingPlants (Basel, Switzerland) · 2024Article
- General relationship of local topologies, global dynamics, and bifurcation in cellular networks.NPJ systems biology and applications · 2024Article
- An updated model of shoot apical meristem regulation by ERECTA family and CLAVATA3 signaling pathways in Arabidopsis.Development (Cambridge, England) · 2024Article
- OneSC: A computational platform for recapitulating cell state transitions.bioRxiv : the preprint server for biology · 2024Article
- Matrix stability and bifurcation analysis by a network-based approach.Theory in biosciences = Theorie in den Biowissenschaften · 2023Article
- Theoretical and computational tools to model multistable gene regulatory networks.Reports on progress in physics. Physical Society (Great Britain) · 2023Review
- A data-driven Boolean model explains memory subsets and evolution in CD8+ T cell exhaustion.NPJ systems biology and applications · 2023Article
- A quantitative evaluation of topological motifs and their coupling in gene circuit state distributions.iScience · 2023Article
- Multi-modular structure of the gene regulatory network for specification and commitment of murine T cells.Frontiers in immunology · 2023Review
- Distance covariance entropy reveals primed states and bifurcation dynamics in single-cell RNA-Seq data.iScience · 2022Article
- What Makes a Functional Gene Regulatory Network? A Circuit Motif Analysis.The journal of physical chemistry. B · 2022Article
- Network topology metrics explaining enrichment of hybrid epithelial/mesenchymal phenotypes in metastasis.PLoS computational biology · 2022Article
- Emergence of qualitative states in synthetic circuits driven by ultrasensitive growth feedback.PLoS computational biology · 2022Article
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Authors and funding
5 authors.
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Abstract
Multistep cell fate transitions with stepwise changes of transcriptional profiles are common to many developmental, regenerative and pathological processes. The multiple intermediate cell lineage states can serve as differentiation checkpoints or branching points for channeling cells to more than one lineages. However, mechanisms underlying these transitions remain elusive. Here, we explored gene regulatory circuits that can generate multiple intermediate cellular states with stepwise modulations of transcription factors. With unbiased searching in the network topology space, we found a motif family containing a large set of networks can give rise to four attractors with the stepwise regulations of transcription factors, which limit the reversibility of three consecutive steps of the lineage transition. We found that there is an enrichment of these motifs in a transcriptional network controlling the early T cell development, and a mathematical model based on this network recapitulates multistep transitions in the early T cell lineage commitment. By calculating the energy landscape and minimum action paths for the T cell model, we quantified the stochastic dynamics of the critical factors in response to the differentiation signal with fluctuations. These results are in good agreement with experimental observations and they suggest the stable characteristics of the intermediate states in the T cell differentiation. These dynamical features may help to direct the cells to correct lineages during development. Our findings provide general design principles for multistep cell linage transitions and new insights into the early T cell development. The network motifs containing a large family of topologies can be useful for analyzing diverse biological systems with multistep transitions.
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