ArticlePLoS computational biology2014
Phenotypic robustness and the assortativity signature of human transcription factor networks.
Article in PLoS computational biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Identifying transcription factors with cell-type specific DNA binding signatures.BMC genomics · 2024Article
- Systems biology in hepatology: approaches and applications.Nature reviews. Gastroenterology & hepatology · 2018Review
- TCSBN: a database of tissue and cancer specific biological networks.Nucleic acids research · 2018Article
- Tracking Cancer Genetic Evolution using OncoTrack.Scientific reports · 2016Article
- Integrated Network Analysis Reveals an Association between Plasma Mannose Levels and Insulin Resistance.Cell metabolism · 2016Article
- Mechanisms of mutational robustness in transcriptional regulation.Frontiers in genetics · 2015Review
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3 authors.
Funding
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.
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