Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks.
Biological networks often show a scale-free topology with node degree following a power-law distribution. Lethal genes tend to form functional hubs, whereas non-lethal disease genes are located at the periphery. Uni-dimensional analyses, however, are flawed. We created and investigated two distinct scale-free networks; a protein-protein interaction (PPI) and a perturbation sensitivity network (PSN). The hubs of both networks exhibit a low molecular evolutionary rate (P < 8 × 10(-12), P < 2 × 10(-4)) and a high codon adaptation index (P < 2 × 10(-16), P < 2 × 10(-8)), indicating that both hubs have been shaped under high evolutionary selective pressure. Moreover, the topologies of PPI and PSN are inversely proportional: hubs of PPI tend to be located at the periphery of PSN and vice versa. PPI hubs are highly enriched with lethal genes but not with disease genes, whereas PSN hubs are highly enriched with disease genes and drug targets but not with lethal genes. PPI hub genes are enriched with essential cellular processes, but PSN hub genes are enriched with environmental interaction processes, having more TATA boxes and transcription factor binding sites. It is concluded that biological systems may balance internal growth signaling and external stress signaling by unifying the two opposite scale-free networks that are seemingly opposite to each other but work in concert between death and disease.
Division of Biomedical Informatics, Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110799, Korea, College of Medicine, CHA General Hospital, CHA University, Seoul 135081, Korea and Systems Biomedical Informatics Research Center, Seoul National University, Seoul 110799, Korea.
Hyun Wook
HW
Han
Jung Hun
JH
Ohn
Jisook
J
Moon
Ju Han
JH
Kim
D001665:Binding Sites; D004194:Disease / Q000235:genetics*; D019143:Evolution, Molecular; D005796:Genes; D005804:Genes, Lethal; D008954:Models, Biological; D058977:Molecular Sequence Annotation; D025941:Protein Interaction Mapping; D012441:Saccharomyces cerevisiae / Q000235:genetics; D016385:TATA Box; D014157:Transcription Factors / Q000378:metabolism
D014157:Transcription Factors