Ontology highlight
ABSTRACT:
PROVIDER: PRJNA661700 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12599406_1.fastq.gz | Fastqsanger.gz | |||
| SRR12599406_2.fastq.gz | Fastqsanger.gz | |||
| SRR12599407_1.fastq.gz | Fastqsanger.gz | |||
| SRR12599407_2.fastq.gz | Fastqsanger.gz | |||
| SRR12599408_1.fastq.gz | Fastqsanger.gz |
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Project description:This model is from the article:
The auxin signalling network translates dynamic input into robust patterning at the shoot apex.
Vernoux T, Brunoud G, Farcot E, Morin V, Van den Daele H, Legrand J, Oliva M, Das P, Larrieu A, Wells D, Guédon Y, Armitage L, Picard F, Guyomarc'h S, Cellier C, Parry G, Koumproglou R, Doonan JH, Estelle M, Godin C, Kepinski S, Bennett M, De Veylder L, Traas J. Mol Syst Biol.
2011 Jul 5;7:508. 21734647
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Abstract:
The plant hormone auxin is thought to provide positional information for patterning during development. It is still unclear, however, precisely how auxin is distributed across tissues and how the hormone is sensed in space and time. The control of gene expression in response to auxin involves a complex network of over 50 potentially interacting transcriptional activators and repressors, the auxin response factors (ARFs) and Aux/IAAs. Here, we perform a large-scale analysis of the Aux/IAA-ARF pathway in the shoot apex of Arabidopsis, where dynamic auxin-based patterning controls organogenesis. A comprehensive expression map and full interactome uncovered an unexpectedly simple distribution and structure of this pathway in the shoot apex. A mathematical model of the Aux/IAA-ARF network predicted a strong buffering capacity along with spatial differences in auxin sensitivity. We then tested and confirmed these predictions using a novel auxin signalling sensor that reports input into the signalling pathway, in conjunction with the published DR5 transcriptional output reporter. Our results provide evidence that the auxin signalling network is essential to create robust patterns at the shoot apex. Note:
Figure 4 of the supplementary material of the reference article has been reproduced here. In this model, the fluctuations of auxin level is represented using sinux function. Time evolution of the variables AUX/IAA (I) and mRNA (R) are plotted, under the influence of fluctuations of auxin level. pi_A is varied between 0 and 2 by steps of 0.1.
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
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To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2024-09-02 | BIOMD0000000352 | BioModels