Monitoring the prolonged TNF stimulation in space and time with topological-functional networks
datasetposted on 03.12.2019 by Christoforos Nikolaou
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In this work we monitor the prolonged TNF stimulation of mouse synovial fibroblasts in space and time through a combination of functional and topological analyses. We introduce a novel concept in the form of bipartite functional/positional networks that capture the interaction between genome organization and the functional footprint of a given regulatory program. By implementing this approach in a time-dependent gene expression experiment we are able to dissect the complex cellular response to a cytokine trigger. We treated synovial fibroblasts in culture for 1, 3, 6, 24 hours to a final point of 7 days with TNF. Control cultures that were grown for the same period without TNF were used as controls. RNA was extracted and RNASeq was performed on a Solexa NextSeq Platform in triplicates. Mapping was performed with BowTie and differential expression was calculated with Cufflinks/CuffDiff (Langmead and Salzberg, 2012; Trapnell et al., 2012;). The differential expression files were used for analysis with abs(log 2 (FC)) <= 1 AND p-value <= 0.05 as a cutoff threshold to select significantly differentially expressed genes. The files used as input for all the analyses described bellow were files of diff format, containing the fields of: gene_name, chromosome, start coordinates, end coordinates, log 2 (FC), p-value. A total of >1500 were found to be differentially expressed in at least one timepoint. They were clustered in 8 groups depending on their relative gene expression in time. Functional analysis was performed with gProfiler for each of the 8 clusters. We analyzed gene expression in linear genomic space through an implementation of the "breakpoints" R function, which uses a Chow test to define significant differences between adjacent linear models in time series data. We used differential gene expression as the time series data and defined sets of ~300 domains of consistent gene expression in each time point, which we termed Domains of Focal Deregulation. We then selected a subset of DFDs from each timepoint on the basis of high/low mean scores of differential expression as the most prominent in terms of gene deregulation and created bipartite positional/functional bipartite networks through a functional enrichment analysis of the genes contained in each DFD. Comparison of the bipartite networks monitors the progression of TNF stimulation, which appears to take place through two distinct transition points. A first, at 3h with a large expansion of inflammatory and immune-related functions and second, at 24h which is marked by immune-related functions being shut down and replaced by pathways associated with development and cell adhesion.