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Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks

Genes in linear proximity often share regulatory inputs, expression and evolutionary patterns, even in complex eukaryote genomes with extensive intergenic sequences. Gene regulation, on the other hand, is effected through the co-ordinated activation (or suppression) of genes participating in common...

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Autores principales: Mavropoulos Papoudas, Stylianos, Papanikolaou, Nikolaos, Nikolaou, Christoforos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6994266/
https://www.ncbi.nlm.nih.gov/pubmed/32021663
http://dx.doi.org/10.1016/j.csbj.2020.01.001
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author Mavropoulos Papoudas, Stylianos
Papanikolaou, Nikolaos
Nikolaou, Christoforos
author_facet Mavropoulos Papoudas, Stylianos
Papanikolaou, Nikolaos
Nikolaou, Christoforos
author_sort Mavropoulos Papoudas, Stylianos
collection PubMed
description Genes in linear proximity often share regulatory inputs, expression and evolutionary patterns, even in complex eukaryote genomes with extensive intergenic sequences. Gene regulation, on the other hand, is effected through the co-ordinated activation (or suppression) of genes participating in common biological pathways, which are often transcribed from distant loci. Existing approaches for the study of gene expression focus on the functional aspect, taking positional constraints into account only marginally. In this work we propose a novel concept for the study of gene expression, through the combination of topological and functional information into bipartite networks. Starting from genome-wide expression profiles, we define extended chromosomal regions with consistent patterns of differential gene expression and then associate these domains with enriched functional pathways. By analyzing the resulting networks in terms of size, connectivity and modularity we can draw conclusions on the way genome organization may underlie the gene regulation program. Implementation of this approach in a detailed RNASeq profiling of sustained Tnf stimulation of mouse synovial fibroblasts, allowed us to identify unexpected regulatory changes taking place in the cells after 24 h of stimulation. Bipartite network analysis suggests that the cytokine response set by Tnf, progresses through two distinct transitions. An early generalization of the inflammatory response, that is followed by a late shutdown of immune-related functions and the redistribution of expression to developmental and cell adhesion pathways and distinct chromosomal regions. We show that the incorporation of topological information may provide additional insights in the complex propagation of Tnf activation.
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spelling pubmed-69942662020-02-04 Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks Mavropoulos Papoudas, Stylianos Papanikolaou, Nikolaos Nikolaou, Christoforos Comput Struct Biotechnol J Research Article Genes in linear proximity often share regulatory inputs, expression and evolutionary patterns, even in complex eukaryote genomes with extensive intergenic sequences. Gene regulation, on the other hand, is effected through the co-ordinated activation (or suppression) of genes participating in common biological pathways, which are often transcribed from distant loci. Existing approaches for the study of gene expression focus on the functional aspect, taking positional constraints into account only marginally. In this work we propose a novel concept for the study of gene expression, through the combination of topological and functional information into bipartite networks. Starting from genome-wide expression profiles, we define extended chromosomal regions with consistent patterns of differential gene expression and then associate these domains with enriched functional pathways. By analyzing the resulting networks in terms of size, connectivity and modularity we can draw conclusions on the way genome organization may underlie the gene regulation program. Implementation of this approach in a detailed RNASeq profiling of sustained Tnf stimulation of mouse synovial fibroblasts, allowed us to identify unexpected regulatory changes taking place in the cells after 24 h of stimulation. Bipartite network analysis suggests that the cytokine response set by Tnf, progresses through two distinct transitions. An early generalization of the inflammatory response, that is followed by a late shutdown of immune-related functions and the redistribution of expression to developmental and cell adhesion pathways and distinct chromosomal regions. We show that the incorporation of topological information may provide additional insights in the complex propagation of Tnf activation. Research Network of Computational and Structural Biotechnology 2020-01-18 /pmc/articles/PMC6994266/ /pubmed/32021663 http://dx.doi.org/10.1016/j.csbj.2020.01.001 Text en © 2020 The Authors. Published by Elsevier B.V. on behalf of Research Network of Computational and Structural Biotechnology. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Mavropoulos Papoudas, Stylianos
Papanikolaou, Nikolaos
Nikolaou, Christoforos
Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks
title Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks
title_full Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks
title_fullStr Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks
title_full_unstemmed Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks
title_short Monitoring the prolonged Tnf stimulation in space and time with topological-functional networks
title_sort monitoring the prolonged tnf stimulation in space and time with topological-functional networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6994266/
https://www.ncbi.nlm.nih.gov/pubmed/32021663
http://dx.doi.org/10.1016/j.csbj.2020.01.001
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