Optimal control of gene regulatory networks for morphogen-driven tissue patterning
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Abstract
The generation of distinct cell types in developing tissues depends on establishing spatial patterns of gene expression. Often, this is directed by spatially graded chemical signals-known as morphogens. In the "French Flag model," morphogen concentration instructs cells to acquire specific fates. How this mechanism produces timely and organized cell-fate decisions, despite the presence of changing morphogen levels, molecular noise, and individual variability, is unclear. Moreover, feedback is present at various levels in developing tissues, breaking the link between morphogen concentration, signaling activity, and position. Here, we develop an alternative framework using optimal control theory to tackle the problem of morphogen-driven patterning: intracellular signaling is derived as the control strategy that guides cells to the correct fate while minimizing a combination of signaling levels and time. This approach recovers experimentally observed properties of patterning strategies and offers insight into design principles that produce timely, precise, and reproducible morphogen patterning.
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A cFFL consists of a fast direct pathway and a slow indirect pathway, which filters out short-lived and spurious signals by integrating these inputs.
“A cFFL consists of a fast direct pathway and a slow indirect pathway, which filters out short-lived and spurious signals by integrating these inputs.”
From Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies (2026) · cites this paper as [43]
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Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies
Tottori, T., & Kobayashi, T. J. (2026) · Physical Review Letters · doi:10.1103/5ynb-7k4v
- Authors
- Pezzotta, A., & Briscoe, J.
- Affiliations
- The Francis Crick Institute (GB)
- Corresponding author
- Pezzotta, Alberto
- Briscoe, James
- Venue
- Cell Systems
- Publisher
- Elsevier BV
- Published
- 2023-11
- Volume
- 14
- Issue
- 11
- Pages
- 940-952.e11
- ISSN
- 2405-4712 (ISSN-L)
- OpenAlex
- W4388696149
- Cited by
- 34
- References
- 64
- Citations by year
- 2026: 16 · 2025: 9 · 2024: 5 · 2023: 4
- FWCI
- 3.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell Systems (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- The Francis Crick Institute (cc-by)
- Funders
- Wellcome Trust (FC001051)
- European Research Council (742138)
- Francis Crick Institute
- Horizon 2020
- Medical Research Council
- European Molecular Biology Organization (ALTF 860-2019)
- European Commission
- Cancer Research UK (CC001051)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Developmental Biology and Gene Regulation
- Physical Sciences › Computer Science › Computer Networks and Communications › Nonlinear Dynamics and Pattern Formation
- Keywords
- tissue patterning, gene regulatory networks, optimal control, cell fate specification, intracellular signaling, morphogen gradients, feedback, molecular noise, developmental robustness
- MeSH terms
- Cell Differentiation, Signal Transduction, Gene Regulatory Networks
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