Institute for Computer Science, Heinrich-Heine-University, Düsseldorf, Germany.
PLoS One. 2011 Apr 12;6(4):e18288. doi: 10.1371/journal.pone.0018288.
Interacting proteins may often experience similar selection pressures. Thus, we may expect that neighbouring proteins in biological interaction networks evolve at similar rates. This has been previously shown for protein-protein interaction networks. Similarly, we find correlated rates of evolution of neighbours in networks based on co-expression, metabolism, and synthetic lethal genetic interactions. While the correlations are statistically significant, their magnitude is small, with network effects explaining only between 2% and 7% of the variation. The strongest known predictor of the rate of protein evolution remains expression level. We confirmed the previous observation that similar expression levels of neighbours indeed explain their similar evolution rates in protein-protein networks, and showed that the same is true for metabolic networks. In co-expression and synthetic lethal genetic interaction networks, however, neighbouring genes still show somewhat similar evolutionary rates even after simultaneously controlling for expression level, gene essentiality and gene length. Thus, similar expression levels and related functions (as inferred from co-expression and synthetic lethal interactions) seem to explain correlated evolutionary rates of network neighbours across all currently available types of biological networks.
相互作用的蛋白质通常可能经历相似的选择压力。因此，我们可以预期生物相互作用网络中的邻近蛋白质以相似的速度进化。这在蛋白质-蛋白质相互作用网络中已经得到了证明。同样，我们在基于共表达、代谢和合成致死遗传相互作用的网络中发现了相邻蛋白质进化速率的相关性。虽然相关性在统计学上是显著的，但它们的幅度很小，网络效应仅解释了变异的 2%到 7%。已知最强的蛋白质进化速率预测因子仍然是表达水平。我们证实了之前的观察结果，即邻近蛋白质的相似表达水平确实可以解释它们在蛋白质-蛋白质网络中的相似进化速率，并且在代谢网络中也是如此。然而，在共表达和合成致死遗传相互作用网络中，即使同时控制表达水平、基因必需性和基因长度，相邻基因的进化速率仍然有些相似。因此，相似的表达水平和相关功能（从共表达和合成致死相互作用中推断）似乎可以解释所有现有类型的生物网络中网络邻居的相关进化速率。
