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• W2979796720 abstract "Abstract 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. We implement our approach in a detailed RNASeq profiling of sustained TNF stimulation of mouse synovial fibroblasts. Bipartite network analysis suggests that the cytokine response set by TNF, progresses through two distinct transitions. An early generalization of the inflammatory response, marked by an increase in related functions and high connectivity of corresponding genomic loci, that is followed by a late shutdown of immune functions and the redistribution of expression to developmental and cell adhesion pathways and distinct chromosomal regions. Our results suggest that the incorporation of topological information may provide additional insights in the underlying topological constraints that are shaping gene expression." @default.
• W2979796720 created "2019-10-18" @default.
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• W2979796720 date "2019-10-15" @default.
• W2979796720 modified "2023-09-27" @default.
• W2979796720 title "Monitoring the prolonged TNF stimulation in space and time with topological-functional networks" @default.
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• W2979796720 doi "https://doi.org/10.1101/803817" @default.
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