Apparent dependence of protein evolutionary rate on number of interactions is linked to biases in protein-protein interactions data sets.
Apparent dependence of protein evolutionary rate on number of interactions is linked to biases in protein-protein interactions data sets.
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DOI：
10.1186/1471-2148-3-21
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发表时间：
2003-10-02
影响因子：
3.4
通讯作者：
Adami C
中科院分区：
文献类型：
--
作者：
Bloom JD;Adami C
几项研究表明，与更多伴侣相互作用的蛋白质会更慢地进化。
我们研究了通过苏氏酿酒酵母中七种不同的高通量方法确定的相互作用集的进化速率与蛋白质 - 蛋白质相互作用的数量之间的相关性。我们表明，交互蛋白的明显趋势更慢地随着对丰富的蛋白质进行计数的偏见，控制蛋白质的丰度显着降低了观察到的相互作用与进化速率之间的相关性。尺寸解释了某些相互作用研究未能显示进化率与相互作用数量之间的相关性。
仔细分析数据支持的唯一相关性是进化速率和蛋白质丰度之间的相关性。 。
Several studies have suggested that proteins that interact with more partners evolve more slowly. The strength and validity of this association has been called into question. Here we investigate how biases in high-throughput protein–protein interaction studies could lead to a spurious correlation. We examined the correlation between evolutionary rate and the number of protein–protein interactions for sets of interactions determined by seven different high-throughput methods in Saccharomyces cerevisiae. Some methods have been shown to be biased towards counting more interactions for abundant proteins, a fact that could be important since abundant proteins are known to evolve more slowly. We show that the apparent tendency for interactive proteins to evolve more slowly varies directly with the bias towards counting more interactions for abundant proteins. Interactions studies with no bias show no correlation between evolutionary rate and the number of interactions, and the one study biased towards counting fewer interactions for abundant proteins actually suggests that interactive proteins evolve more rapidly. In all cases, controlling for protein abundance significantly decreases the observed correlation between interactions and evolutionary rate. Finally, we disprove the hypothesis that small data set size accounts for the failure of some interactions studies to show a correlation between evolutionary rate and the number of interactions. The only correlation supported by a careful analysis of the data is between evolutionary rate and protein abundance. The reported correlation between evolutionary rate and protein–protein interactions cannot be separated from the biases of some protein–protein interactions studies to count more interactions for abundant proteins.
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影响因子：
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Superti-Furga, G
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