Abstract
Many developmental, physiological, and behavioral processes depend on the precise expression of genes in space and time. Such spatiotemporal gene expression phenotypes arise from the binding of sequence-specific transcription factors (TFs) to DNA, and from the regulation of nearby genes that such binding causes. These nearby genes may themselves encode TFs, giving rise to a transcription factor network (TFN), wherein nodes represent TFs and directed edges denote regulatory interactions between TFs. Computational studies have linked several topological properties of TFNs — such as their degree distribution — with the robustness of a TFN's gene expression phenotype to genetic and environmental perturbation. Another important topological property is assortativity, which measures the tendency of nodes with similar numbers of edges to connect. In directed networks, assortativity comprises four distinct components that collectively form an assortativity signature. We know very little about how a TFN's assortativity signature affects the robustness of its gene expression phenotype to perturbation. While recent theoretical results suggest that increasing one specific component of a TFN's assortativity signature leads to increased phenotypic robustness, the biological context of this finding is currently limited because the assortativity signatures of real-world TFNs have not been characterized. It is therefore unclear whether these earlier theoretical findings are biologically relevant. Moreover, it is not known how the other three components of the assortativity signature contribute to the phenotypic robustness of TFNs. Here, we use publicly available DNaseI-seq data to measure the assortativity signatures of genome-wide TFNs in 41 distinct human cell and tissue types. We find that all TFNs share a common assortativity signature and that this signature confers phenotypic robustness to model TFNs. Lastly, we determine the extent to which each of the four components of the assortativity signature contributes to this robustness.
Highlights
Cells are capable of expressing specific subsets of their gene complement in a coordinated fashion, leading to stable gene expression phenotypes
These gene expression phenotypes are largely robust to genetic mutation, and one source of this robustness may reside in the network structure of interacting molecules that underlie genetic regulation
Theoretical work has shown that transcription factor network (TFN) models with increased assortativity exhibit increased robustness to both mutation in cisregulatory sites [21] and to gene duplication [22]. This occurs because increased assortativity may either shrink the average size of nested subgraphs within the network [21] or increase the average number of regulatory links that separate Transcription factors (TFs) [23], both of which tend to dampen the phenotypic effects of mutations. This earlier work focused exclusively on the assortativity of outgoing connections, referred to as out-out assortativity, and the findings suggest that TFNs are more robust when for some edge A ? B it is frequently the case that TFs A and B regulate a similar number of targets
Summary
Cells are capable of expressing specific subsets of their gene complement in a coordinated fashion, leading to stable gene expression phenotypes. TFs are proteins that bind DNA to regulate the expression of their target genes. Since some of the targets are themselves TFs, the resulting cross-regulation forms a transcription factor network (TFN). TFNs are responsible for metazoan developmental programs, such as the development of skeletal muscle [5] and the formation of the retina [6]. They are involved in generating oscillatory gene expression patterns, such as those that drive the cell cycle [7] and the mammalian circadian clock [8]. The topology of TFNs has been the subject of work seeking a greater understanding of how the structure of a TFN affects its function [14], and likewise how evolution may [15] or may not [16] mold its structural properties
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
