Abstract
Analysis of the topology of transcriptional regulatory networks (TRNs) is an effective way to study the regulatory interactions between the transcription factors (TFs) and the target genes. TRNs are characterized by the abundance of motifs such as feed forward loops (FFLs), which contribute to their structural and functional properties. In this paper, we focus on the role of motifs (specifically, FFLs) in signal propagation in TRNs and the organization of the TRN topology with FFLs as building blocks. To this end, we classify nodes participating in FFLs (termed motif central nodes) into three distinct roles (namely, roles A, B and C), and contrast them with TRN nodes having high connectivity on the basis of their potential for information dissemination, using metrics such as network efficiency, path enumeration, epidemic models and standard graph centrality measures. We also present the notion of a three tier architecture and how it can help study the structural properties of TRN based on connectivity and clustering tendency of motif central nodes. Finally, we motivate the potential implication of the structural properties of motif centrality in design of efficient protocols of information routing in communication networks as well as their functional properties in global regulation and stress response to study specific disease conditions and identification of drug targets.
Highlights
Analysis of the topology of transcriptional regulatory networks (TRNs) is an effective way to study the regulatory interactions between the transcription factors (TFs) and the target genes
We have earlier explored the role of motifs in topological robustness of E. coli and S.cerevisiae TRNs; here we showed that feed forward loops (FFLs) motifs render robustness to TRNs by creating multiple independent communication pathways, which may be utilized to design of fault-tolerant and energy-efficient dynamic communication network topologies[25,26]
We measure the communication efficiency rendered by FFL motifs in TRNs (1) in terms of the number of directed paths created as a result of the direct link and indirect path present in each FFL and (2) using the Susceptible-Infected-Recovered (SIR) epidemic model to gauge the diffusion of information across each TRN over time when FFL motifs are activated as initial carriers of the infection
Summary
Consider a simple n– node directed graph. There are two possible consequences of knocking off the direct link from any node u to w: (a) w becomes unreachable from u, or (b) the shortest path length l (where 2 ≤ l ≤ n − 1) from u to w increases, which commensurately hampers how quickly information propagates from the source to the destination node. We hypothesize that cascades of FFLs should make TRNs resilient by minimizing the increase in shortest path length due to node and link failures
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