Grigolon2018 - Responses to auxin signals
Ontology highlight
ABSTRACT:
SUBMITTER: 
Ahmad Zyoud
PROVIDER: MODEL2003060002 | BioModels | 2022-05-10
REPOSITORIES: BioModels
Publications
Responses to auxin signals: an operating principle for dynamical sensitivity yet high resilience.
Grigolon S S Bravi B B Martin O C OC
Royal Society open science 20180124 1
Plants depend on the signalling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signalling network involves a negative feedback on Aux/IAA proteins which mediate the influence of auxin (the <i>signal</i>) on the auxin response factor (ARF) transcription factors (the <i>drivers</i> of the response). To probe the role of this feedback, we consider alternative <i>in silico</i> signalling networks implementing different o ...[more]
Similar Datasets
Project description:Plants depend on the signalling of the phytohormone auxin for their development and for responding to environmental perturbations. The associated biomolecular signalling network involves a negative feedback on Aux/IAA proteins which mediate the influence of auxin (the signal) on the auxin response factor (ARF) transcription factors (the drivers of the response). To probe the role of this feedback, we consider alternative in silico signalling networks implementing different operating principles. By a comparative analysis, we find that the presence of a negative feedback allows the system to have a far larger sensitivity in its dynamical response to auxin and that this sensitivity does not prevent the system from being highly resilient. Given this insight, we build a new biomolecular signalling model for quantitatively describing such Aux/IAA and ARF responses.
2021-09-19 | BIOMD0000000927 | BioModels
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
,
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.
For more information see the terms of use
.
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.
2011-04-01 | BIOMD0000000352 | BioModels
Project description:We used a next-generation sequencing approach, Illumina Digital Gene Expression (DGE) technology, to Genome-wide profiling of gene expression during cotton SE. As a result, 5,076 differentially expressed genes were identified during cotton SE. Expression profile and functional assignments of these genes indicated significant transcriptional complexity during this process. Transcription factor-encoding genes were found to be differentially regulated during SE. The complex pathways of auxin abundance, transport and response with differentially regulated genes revealed that the auxin-related transcripts belonged to IAA biosynthesis, indole-3-butyric acid (IBA) metabolism, IAA conjugate metabolism, auxin transport, auxin-responsive protein / indoleacetic acid-induced protein (Aux/IAA), auxin response factor (ARF), small auxin-up RNA (SAUR), Aux/IAA degradation, and other auxin-related proteins, which allow an intricate system of auxin utilization to achieve multiple purposes in SE. Quantitative real-time PCR (qRT-PCR) was performed on selected genes with different expression patterns and functional assignments were made to demonstrate the utility of RNA-Seq for gene expression profiles during cotton SE. We report here the first comprehensive analysis of transcriptome dynamics that may serve as a gene expression profile blueprint in cotton SE. Our main goal was to adapt the RNA-Seq technology to this notable development process and to analyse the gene expression profile. Complex auxin signalling pathway and transcription regulation were highlighted. Together with biochemical and histological approaches, this study provides comprehensive gene expression data sets for cotton SE that serve as an important platform resource for further functional studies in plant embryogenesis. differential gene expression analysis at 9 time-points/stages during somatic embryogenesis in cotton by deep sequencing, using Illumina GAIIx.
2012-05-31 | E-GEOD-38209 | biostudies-arrayexpress
Project description:This model is from the article:
The auxin signalling network translates dynamic input into robust patterning at the shoo
t 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
,
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 netwo
rk of over 50 potentially interacting transcriptional activators and repressors, the auxin response fac
tors (ARFs) and Aux/IAAs. Here, we perform a large-scale analysis of the Aux/IAA-ARF pathway in the sho
ot apex of Arabidopsis, where dynamic auxin-based patterning controls organogenesis. A comprehensive ex
pression map and full interactome uncovered an unexpectedly simple distribution and structure of this p
athway 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 predic
tions using a novel auxin signalling sensor that reports input into the signalling pathway, in conjunct
ion 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 3 of the supplementary material of the reference article has been reproduced here. Time evolution of all the variables in the model are plotted, under the influence of a step input of auxin level (auxin=5, when time>1000; 0.11, otherwise). 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.
For more information see the terms of use
.
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.
2011-04-01 | BIOMD0000000351 | BioModels
Project description:Auxin is a drug-like small molecule and morphogen that triggers the formation of SCFTIR1/AFB-AUX/IAA co-receptor complexes leading to ubiquitylation and proteasome-dependent degradation of AUX/IAA transcriptional repressors in plants. Here, we systematically dissect auxin sensing by SCFTIR1-IAA6 and SCFTIR1-IAA19 co-receptor complexes, and assess IAA6/IAA19 ubiquitylation in vitro and IAA6/IAA19 degradation in vivo. TIR1-IAA19 and TIR1-IAA6 interactions form co-receptors with different affinities, which specify ubiquitylation and turnover rate of the AUX/IAA. We demonstrate lysine ubiquitylation in IAA6/IAA19 and propose this ubiquitylation signature to be a consequence of auxin-mediated SCFTIR1-AUX/IAA interactions. We present evidence for an evolving AUX/IAA repertoire, typified by the IAA6/IAA19 ohnologs, that contributes differentially to auxin sensing. We postulate that AUX/IAAs have emerged as a versatility toolbox for auxin-modulated transcriptional control, as the gamut of AUX/IAA destruction kinetics enables fine-tuning of transcriptional auxin response and contributes to the complexity of hormone signaling.
2017-06-14 | PXD004027 | Pride
Project description:Somatic embryogenesis (SE) is a useful biotechnological tool to study the morpho-physiological, biochemical and molecular processes during the development of Coffea canephora. Plant growth regulators (PGR) play a key role during cell differentiation in SE. The Auxin-response-factor (ARF) and Auxin/Indole-3-acetic acid (Aux/IAA) are fundamental components involved in the signaling of the IAA. The IAA signaling pathway activates or represses the expression of genes responsive to auxins during the embryogenic transition of the somatic cells. The growing development of new generation sequencing technologies (NGS), as well as bioinformatics tools, has allowed us to broaden the landscape of SE study of various plant species and identify the genes directly involved. Analysis of transcriptome expression profiles of the C. canephora genome and the identification of a particular set of differentially expressed genes (DEG) during SE are described in this study. A total of eight ARF and seven Aux/IAA differentially expressed genes were identified during the different stages of the SE induction process. The quantitative expression analysis showed that ARF18 and ARF5 genes are highly expressed after 21 days of the SE induction, while Aux/IAA7 and Aux/IAA12 genes are repressed. The results of this study allow to have a better understanding of the genes involved in auxin signaling pathway as well as their expression profiles during the SE process.
2019-04-03 | GSE128888 | GEO
Project description:Rose (Rosa hybrida L.) is a major cut flowers in the world. Studying the molecular mechanism of auxin regulation in growth is of great significance for enhancing the understanding of the growth and development processes of rose and informing accurate exogenous auxin application in rose production. However, the response mechanism of rose to miRNA-mediated auxin signal transduction is unclear. In this study, rose plants were treated with IAA, and 75 known miRNAs and 168 novel miRNAs were identified by small RNA sequencing. Among them, 19 known miRNAs and 42 miRNAs were differentially expressed. Many differential miRNAs demonstrated staged responses to auxin treatment. The targeted relationship between miRNA and key transcription factors regulated by auxin in rose was analyzed, and the target genes in the ARF family and AUX/IAA family were screened. By using quantitative real-time PCR(qRT-PCR) to verify the expression patterns of the miRNA regulating the auxin signal transduction pathway and its target gene, we found that miR156a, miR160a, miR164a, miR167d, miR396b-3p, novel_miR_189, novel_miR_74, novel_miR_8, and novel_miR_207 interacted negatively with the ARF family, and miR390a-3p and novel_miR_101 interacted negatively with the AUX/IAA family. These results provide a theoretical basis for further studies on the auxin regulatory mechanisms in rose.
2024-02-24 | GSE225991 | GEO
Project description:Rose (Rosa hybrida L.) is a major cut flowers in the world. Studying the molecular mechanism of auxin regulation in growth is of great significance for enhancing the understanding of the growth and development processes of rose and informing accurate exogenous auxin application in rose production. However, the response mechanism of rose to miRNA-mediated auxin signal transduction is unclear. In this study, rose plants were treated with IAA, and 75 known miRNAs and 168 novel miRNAs were identified by small RNA sequencing. Among them, 19 known miRNAs and 42 miRNAs were differentially expressed. Many differential miRNAs demonstrated staged responses to auxin treatment. The targeted relationship between miRNA and key transcription factors regulated by auxin in rose was analyzed, and the target genes in the ARF family and AUX/IAA family were screened. By using quantitative real-time PCR(qRT-PCR) to verify the expression patterns of the miRNA regulating the auxin signal transduction pathway and its target gene, we found that miR156a, miR160a, miR164a, miR167d, miR396b-3p, novel_miR_189, novel_miR_74, novel_miR_8, and novel_miR_207 interacted negatively with the ARF family, and miR390a-3p and novel_miR_101 interacted negatively with the AUX/IAA family. These results provide a theoretical basis for further studies on the auxin regulatory mechanisms in rose.
2023-02-28 | GSE225844 | GEO
Project description:We used a next-generation sequencing approach, Illumina Digital Gene Expression (DGE) technology, to Genome-wide profiling of gene expression during cotton SE. As a result, 5,076 differentially expressed genes were identified during cotton SE. Expression profile and functional assignments of these genes indicated significant transcriptional complexity during this process. Transcription factor-encoding genes were found to be differentially regulated during SE. The complex pathways of auxin abundance, transport and response with differentially regulated genes revealed that the auxin-related transcripts belonged to IAA biosynthesis, indole-3-butyric acid (IBA) metabolism, IAA conjugate metabolism, auxin transport, auxin-responsive protein / indoleacetic acid-induced protein (Aux/IAA), auxin response factor (ARF), small auxin-up RNA (SAUR), Aux/IAA degradation, and other auxin-related proteins, which allow an intricate system of auxin utilization to achieve multiple purposes in SE. Quantitative real-time PCR (qRT-PCR) was performed on selected genes with different expression patterns and functional assignments were made to demonstrate the utility of RNA-Seq for gene expression profiles during cotton SE. We report here the first comprehensive analysis of transcriptome dynamics that may serve as a gene expression profile blueprint in cotton SE. Our main goal was to adapt the RNA-Seq technology to this notable development process and to analyse the gene expression profile. Complex auxin signalling pathway and transcription regulation were highlighted. Together with biochemical and histological approaches, this study provides comprehensive gene expression data sets for cotton SE that serve as an important platform resource for further functional studies in plant embryogenesis.
2012-05-31 | GSE38209 | GEO
Project description:ETTIN (ETT) encodes a member of the Auxin Response Factor (ARF) family of transcription factors. The gynoecia of strong ett mutants show a partial breakdown in abaxial-adaxial (internal -external) polarity, and a shift in tissue boundaries along the apico-basal axis of the gynoecium. This latter effect increases the size of the stigma, style and stipe in ett mutants at the expense of ovary tissue. Among the putative direct targets of ETT, we found several genes encoding either pectin methylesterases (PMEs) or their inhibitors. PMEs may function to increase the extensibility of the cell wall and thus contribute directly to cellular growth. The identification of genes encoding PMEs and related molecules as direct targets of ETT therefore suggests this factor to be situated near the end of a hierarchy of genetic regulation acting on growth through cell wall modification. Other putative direct targets of ETT encode two members of the Aux/IAA protein family, which have been found to negatively regulate ARFs as an inverse function of auxin concentration. ETT lacks the protein domains, present in most ARFs, that are necessary for negative regulation by Aux/IAA proteins and its own activity should not therefore be subject to regulation by auxin concentration. However, the regulation of two Aux/IAA proteins by ETT may represent an input of this protein into an auxin-regulated network involving other ARFs.
2021-03-05 | GSE14660 | GEO