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Yin and Yang of disease genes and death genes between reciprocally scale-free biological networks

机译:相互无尺度的生物网络之间的疾病基因和死亡基因的阴阳

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摘要

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.
机译:生物网络通常会显示无标度拓扑,其节点度遵循幂律分布。致死基因倾向于形成功能性枢纽,而非致死疾病基因位于外围。但是,一维分析是有缺陷的。我们创建并研究了两个不同的无标度网络;蛋白质-蛋白质相互作用(PPI)和微扰敏感性网络(PSN)。这两个网络的中心都表现出较低的分子进化速率(P <8×10 −12 ,P <2×10 −4 )和高密码子适应指数(P <2×10 −16 ,P <2×10 −8 ),表明两个轮毂均在较高的进化选择性压力下形成。此外,PPI和PSN的拓扑结构成反比:PPI的集线器往往位于PSN的外围,反之亦然。 PPI集线器高度富含致死基因,但不包含疾病基因,而PSN集线器高度富含致病基因和药物靶标,但不具有致死基因。 PPI中枢基因富含必需的细胞过程,但PSN中枢基因富含环境相互作用过程,具有更多的TATA框和转录因子结合位点。结论是,生物系统可以通过统一看似彼此相反但在死亡和疾病之间协同工作的两个相反的无标度网络来平衡内部生长信号和外部压力信号。

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