Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network.
Position Matters: Network Centrality Considerably Impacts Rates of Protein Evolution in the Human Protein-Protein Interaction Network.
复制标题
位置问题：网络中心性大大影响了人类蛋白质 - 蛋白质相互作用网络中蛋白质进化的速率。
DOI：
10.1093/gbe/evx117
复制
发表时间：
2017-06-01
影响因子：
3.3
通讯作者：
Chakraborty S
中科院分区：
文献类型：
--
作者：
Alvarez-Ponce D;Feyertag F;Chakraborty S
任何生物体的蛋白质都以不同的速度进化。已经确定了一长串影响蛋白质进化速率的因素。然而，每个因素在决定蛋白质进化速率方面的相对重要性仍然没有得到解决。流行的观点是，进化速率主要由基因表达决定，而其他因素，如网络中心性，只有一个边际效应，如果有的话。然而，这一观点主要是基于酵母的分析，准确测量蛋白质进化速率决定因素的重要性是复杂的，因为不同的因素往往相互关联，并且可用的功能基因组学数据集质量相对较差。在这里，我们使用相关性，偏相关性和主成分回归分析来衡量几个因素的贡献，人类蛋白质的进化速率的变化。为此，我们分析了整个人类蛋白质-蛋白质相互作用数据集和人类信号转导网络-一个非常高质量的网络数据集，通过手动策展获得，预计几乎没有假阳性。与流行的观点相反，我们观察到网络中心性（以物理和非物理相互作用的数量，介数和紧密度来衡量）对蛋白质进化的速度有相当大的影响。令人惊讶的是，根据一些分析，中心性对蛋白质进化速率的影响似乎与基因表达的影响相当，甚至上级。我们的观察结果似乎独立于潜在的混杂因素和interactomic数据集的局限性（偏差和错误）。
The proteins of any organism evolve at disparate rates. A long list of factors affecting rates of protein evolution have been identified. However, the relative importance of each factor in determining rates of protein evolution remains unresolved. The prevailing view is that evolutionary rates are dominantly determined by gene expression, and that other factors such as network centrality have only a marginal effect, if any. However, this view is largely based on analyses in yeasts, and accurately measuring the importance of the determinants of rates of protein evolution is complicated by the fact that the different factors are often correlated with each other, and by the relatively poor quality of available functional genomics data sets. Here, we use correlation, partial correlation and principal component regression analyses to measure the contributions of several factors to the variability of the rates of evolution of human proteins. For this purpose, we analyzed the entire human protein–protein interaction data set and the human signal transduction network—a network data set of exceptionally high quality, obtained by manual curation, which is expected to be virtually free from false positives. In contrast with the prevailing view, we observe that network centrality (measured as the number of physical and nonphysical interactions, betweenness, and closeness) has a considerable impact on rates of protein evolution. Surprisingly, the impact of centrality on rates of protein evolution seems to be comparable, or even superior according to some analyses, to that of gene expression. Our observations seem to be independent of potentially confounding factors and from the limitations (biases and errors) of interactomic data sets.
登录
查看更多内容
影响因子：
3.4
作者：
Bloom JD;Adami C
通讯作者：
Adami C
影响因子：
4.3
作者：
Batada NN;Hurst LD;Tyers M
通讯作者：
Tyers M
影响因子：
14.9
作者：
Chen WH;Minguez P;Lercher MJ;Bork P
通讯作者：
Bork P
影响因子：
--
作者：
Cui Q;Purisima EO;Wang E
通讯作者：
Wang E
影响因子：
10.7
作者：
Drummond, DA;Raval, A;Wilke, CO
通讯作者：
Wilke, CO