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Updated: Jun 6, 2026

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
Published on: October 19, 2021
Patterns of human gene expression variance show strong associations with signaling network hierarchy
Kakajan Komurov1, Prahlad T Ram
1Department of Systems Biology, The University of Texas MD Anderson Cancer Center, 7435 Fannin St, Houston, TX 77054, USA. kkomurov@mdanderson.org
Background:
Understanding organizational principles of cellular networks is one of the central goals of systems biology. Although much has been learnt about gene expression programs under specific conditions, global patterns of expressional variation (EV) of genes and their relationship to cellular functions and physiological responses is poorly understood.
Results:
To understand global principles of relationship between transcriptional regulation of human genes and their functions, we have leveraged large-scale datasets of human gene expression measurements across a wide spectrum of cell conditions. We report that human genes are highly diverse in terms of their EV; while some genes have highly variable expression pattern, some seem to be relatively ubiquitously expressed across a wide range of conditions. The wide spectrum of gene EV strongly correlates with the positioning of proteins within the signaling network hierarchy, such that, secreted extracellular receptor ligands and membrane receptors have the highest EV, and intracellular signaling proteins have the lowest EV in the genome. Our analysis shows that this pattern of EV reflects functional centrality: proteins with highly specific signaling functions are modulated more frequently than those with highly central functions in the network, which is also consistent with previous studies on tissue-specific gene expression. Interestingly, these patterns of EV along the signaling network hierarchy have significant correlations with promoter architectures of respective genes.
Conclusion:
Our analyses suggest a generic systems level mechanism of regulation of the cellular signaling network at the transcriptional level.
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