Éditeur(s) : HAL CCSD
Résumé : International audience
The study of complex biological processes requires to forgo simplified models for extensive ones. Yet, these models' size and complexity place them beyond understanding. Their analysis requires new methods for identifying general patterns. The Transforming Growth Factor TGF-β is a multifunctional cytokine that regulates mammalian cell development , differentiation, and homeostasis. Depending on the context, it can play the antagonistic roles of growth inhibitor or of tumor promoter. Its context-dependent pleiotropic nature is associated with complex sig-naling pathways. The most comprehensive model of TGF-β-dependent signaling is composed of 15,934 chains of reactions (trajectories) linking TGF-β to at least one of its 159 target genes. Identifying functional patterns in such a network requires new automated methods. This article presents a framework for identifying groups of similar trajec-tories composed of the same molecules using an exhaustive and without prior assumptions approach. First, the trajectories were clustered using the Relevant Set Correlation model, a shared nearest-neighbors clustering method. Five groups of trajectories were identified. Second, for each cluster the over-represented molecules were determined by scoring the frequency of each molecule implicated in trajectories. Third, Gene set enrichment analysis on the clusters of trajectories revealed some specific TGF-β-dependent biological processes, with different clusters associated to the antagonists roles of TGF-β. This confirms that our approach yields biologically-relevant results. We developed a web interface that facilitates graph visualization and analysis. Our clustering-based method is suitable for identifying families of functionally-similar trajectories in the TGF-β signaling network. It can be generalized to explore any large-scale biological pathways.
CMSB 2017 - 15th International Conference on Computational Methods in Systems Biology
Darmstadt, France

hal-01559249
https://hal.archives-ouvertes.fr/hal-01559249
https://hal.archives-ouvertes.fr/hal-01559249/document
https://hal.archives-ouvertes.fr/hal-01559249/file/JeanCoquet_CMSB.pdf

Éditeur(s) : HAL CCSD American Society for Microbiology
Résumé : International audience
: Estradiol signaling is ideally suited for analyzing molecular and functional linkages between the different layers of information directing transcriptional regulations: DNA sequence, chromatin modifications and the spatial organization of the genome. Hence, estrogen receptor (ER) can bind at a distance from its target genes and engages timely and spatially coordinated processes to regulate their expression. In the context of the coordinated regulations of co-linear genes, identifying which ER binding sites (ERBSs) regulate a given gene still remains a challenging question. Here, we investigated the coordination of such regulatory events at a 2 Mb genomic locus containing the estrogen-sensitive TFF cluster of genes in breast cancer cells. We demonstrated that this locus exhibits a hormone and cohesin-dependent reduction in the plasticity of its three-dimensional organization that allows multiple ERBSs to be dynamically brought to the vicinity of estrogen-sensitive genes. Additionally, by using triplex forming oligonucleotides, we could precisely document the functional links between ER engagement at given ERBSs and the regulation of particular genes. Hence, our data evidence a formerly suggested cooperation of enhancers towards gene regulations, and also show that redundancy between ERBSs can occur.
ISSN: 0270-7306

hal-00984591
https://hal-univ-rennes1.archives-ouvertes.fr/hal-00984591
https://hal-univ-rennes1.archives-ouvertes.fr/hal-00984591/document
https://hal-univ-rennes1.archives-ouvertes.fr/hal-00984591/file/Mol._Cell._Biol.-2014-Quintin-MCB.00918-13.pdf
DOI : 10.1128/MCB.00918-13