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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.11338 |
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| _version_ | 1866918419731841024 |
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| author | Mills, Hayley Janes, George Bishopp, Anthony Savage, Natasha |
| author_facet | Mills, Hayley Janes, George Bishopp, Anthony Savage, Natasha |
| contents | Arabidopsis root hair patterning is controlled by a complex transcription factor network containing positive and negative feedback loops, epidermal cell-cell signalling, and positional signalling from underlying tissue. Recently, several long accepted regulatory interactions within the network have been revised, and while there are extensive data regarding individual components, the complexity of the network has made it difficult to understand how these components combine to ensure correct and robust epidermal patterning. Here, mathematical modelling was used to integrate the wealth of experimental data into a single transcription factor network model.
Current understanding of the epidermal patterning network was found to be insufficient to reproduce experimental data, and thus an additional negative feedback loop was hypothesized which enabled the model to reproduce both wildtype and mutant data. The negative feedback was supported by sequence analysis of candidate regulators. Modelling investigations uncovered interactions, mechanisms, and constraints essential for patterning, and revealed how a recently redefined reaction functions to produce mutant data while contributing to network robustness in wildtype. When analysed together, these results provide a holistic understanding of epidermal cell fate determination in Arabidopsis, shown here to be governed by a spontaneously patterning reaction-diffusion network containing combined activator-inhibitor and substrate depletion mechanisms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_11338 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A spontaneously patterning reaction diffusion network, containing an integrated activator inhibitor and substrate depletion mechanism, specifies trichoblast cell fate in Arabidopsis roots Mills, Hayley Janes, George Bishopp, Anthony Savage, Natasha Molecular Networks Arabidopsis root hair patterning is controlled by a complex transcription factor network containing positive and negative feedback loops, epidermal cell-cell signalling, and positional signalling from underlying tissue. Recently, several long accepted regulatory interactions within the network have been revised, and while there are extensive data regarding individual components, the complexity of the network has made it difficult to understand how these components combine to ensure correct and robust epidermal patterning. Here, mathematical modelling was used to integrate the wealth of experimental data into a single transcription factor network model. Current understanding of the epidermal patterning network was found to be insufficient to reproduce experimental data, and thus an additional negative feedback loop was hypothesized which enabled the model to reproduce both wildtype and mutant data. The negative feedback was supported by sequence analysis of candidate regulators. Modelling investigations uncovered interactions, mechanisms, and constraints essential for patterning, and revealed how a recently redefined reaction functions to produce mutant data while contributing to network robustness in wildtype. When analysed together, these results provide a holistic understanding of epidermal cell fate determination in Arabidopsis, shown here to be governed by a spontaneously patterning reaction-diffusion network containing combined activator-inhibitor and substrate depletion mechanisms. |
| title | A spontaneously patterning reaction diffusion network, containing an integrated activator inhibitor and substrate depletion mechanism, specifies trichoblast cell fate in Arabidopsis roots |
| topic | Molecular Networks |
| url | https://arxiv.org/abs/2412.11338 |