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Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network

BACKGROUND: Auxin is a major phytohormone involved in many developmental processes by controlling gene expression through a network of transcriptional regulators. In Arabidopsis thaliana, the auxin signalling network is made of 52 potentially interacting transcriptional regulators, activating or rep...

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Autores principales: Legrand, Jonathan, Léger, Jean-Benoist, Robin, Stéphane, Vernoux, Teva, Guédon, Yann
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4774195/
https://www.ncbi.nlm.nih.gov/pubmed/26932351
http://dx.doi.org/10.1186/s12918-016-0254-7
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author Legrand, Jonathan
Léger, Jean-Benoist
Robin, Stéphane
Vernoux, Teva
Guédon, Yann
author_facet Legrand, Jonathan
Léger, Jean-Benoist
Robin, Stéphane
Vernoux, Teva
Guédon, Yann
author_sort Legrand, Jonathan
collection PubMed
description BACKGROUND: Auxin is a major phytohormone involved in many developmental processes by controlling gene expression through a network of transcriptional regulators. In Arabidopsis thaliana, the auxin signalling network is made of 52 potentially interacting transcriptional regulators, activating or repressing gene expression. All the possible interactions were tested in two-way yeast-2-hybrid experiments. Our objective was to characterise this auxin signalling network and to quantify the influence of the dimerisation sequence dissimilarities on the interaction between transcriptional regulators. RESULTS: We applied model-based graph clustering methods relying on connectivity profiles between transcriptional regulators. Incorporating dimerisation sequence dissimilarities as explanatory variables, we modelled their influence on the auxin network topology using mixture of linear models for random graphs. Our results provide evidence that the network can be simplified into four groups, three of them being closely related to biological groups. We found that these groups behave differently, depending on their dimerisation sequence dissimilarities, and that the two dimerisation sub-domains might play different roles. CONCLUSIONS: We propose here the first pipeline of statistical methods combining yeast-2-hybrid data and protein sequence dissimilarities for analysing protein-protein interactions. We unveil using this pipeline of analysis the transcriptional regulator interaction modes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0254-7) contains supplementary material, which is available to authorized users.
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spelling pubmed-47741952016-03-03 Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network Legrand, Jonathan Léger, Jean-Benoist Robin, Stéphane Vernoux, Teva Guédon, Yann BMC Syst Biol Research Article BACKGROUND: Auxin is a major phytohormone involved in many developmental processes by controlling gene expression through a network of transcriptional regulators. In Arabidopsis thaliana, the auxin signalling network is made of 52 potentially interacting transcriptional regulators, activating or repressing gene expression. All the possible interactions were tested in two-way yeast-2-hybrid experiments. Our objective was to characterise this auxin signalling network and to quantify the influence of the dimerisation sequence dissimilarities on the interaction between transcriptional regulators. RESULTS: We applied model-based graph clustering methods relying on connectivity profiles between transcriptional regulators. Incorporating dimerisation sequence dissimilarities as explanatory variables, we modelled their influence on the auxin network topology using mixture of linear models for random graphs. Our results provide evidence that the network can be simplified into four groups, three of them being closely related to biological groups. We found that these groups behave differently, depending on their dimerisation sequence dissimilarities, and that the two dimerisation sub-domains might play different roles. CONCLUSIONS: We propose here the first pipeline of statistical methods combining yeast-2-hybrid data and protein sequence dissimilarities for analysing protein-protein interactions. We unveil using this pipeline of analysis the transcriptional regulator interaction modes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12918-016-0254-7) contains supplementary material, which is available to authorized users. BioMed Central 2016-03-01 /pmc/articles/PMC4774195/ /pubmed/26932351 http://dx.doi.org/10.1186/s12918-016-0254-7 Text en © Legrand et al. 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Legrand, Jonathan
Léger, Jean-Benoist
Robin, Stéphane
Vernoux, Teva
Guédon, Yann
Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
title Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
title_full Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
title_fullStr Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
title_full_unstemmed Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
title_short Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
title_sort modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4774195/
https://www.ncbi.nlm.nih.gov/pubmed/26932351
http://dx.doi.org/10.1186/s12918-016-0254-7
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