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

Abstract : 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.
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Jonathan Legrand, Jean-Benoist Leger, Stephane Robin, Teva Vernoux, Yann Guédon. Modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network. BMC Systems Biology, BioMed Central, 2016, 10 (22), pp.17. ⟨10.1186/s12918-016-0254-7⟩. ⟨hal-01361020⟩

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