Protein networks, pleiotropy and the evolution of senescence
Protein networks, pleiotropy and the evolution of senescence
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DOI：
10.1098/rspb.2004.2732
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发表时间：
2004-06-22
影响因子：
4.7
通讯作者：
Promislow, DEL
中科院分区：
文献类型：
--
作者：
Promislow, DEL
酵母蛋白相互作用网络中蛋白质之间的相互作用或连通性的数量遵循幂律。我比较了与衰老和其他五个特征相关的酵母蛋白子集的连接模式。我发现与衰老相关的蛋白质的连通性比偶然预期的要高得多，这种模式在大多数其他数据集中都没有看到。即使在控制了其他与连接相关的因素（如细胞内蛋白质表达的定位）的情况下，这种模式仍然成立。我认为这些观察结果与衰老进化的拮抗多效性理论是一致的。为了进一步支持这一论点，我发现蛋白质的连通性与其影响的性状数量或其多效性程度呈正相关，并进一步表明与衰老相关的蛋白质的平均多效性程度最大。我用一个简单的数学模型来解释这些结果，该模型结合了衰老进化的拮抗多效性理论假设和网络拓扑数据。这些发现整合了衰老的分子和进化模型，应该有助于寻找新的衰老基因。
The number of interactions, or connectivity, among proteins in the yeast protein interaction network follows a power law. I compare patterns of connectivity for subsets of yeast proteins associated with senescence and with five other traits. I find that proteins associated with ageing have significantly higher connectivity than expected by chance, a pattern not seen for most other datasets. The pattern holds even when controlling for other factors also associated with connectivity, such as localization of protein expression within the cell. I suggest that these observations are consistent with the antagonistic pleiotropy theory for the evolution of senescence. In further support of this argument, I find that a protein's connectivity is positively correlated with the number of traits it influences or its degree of pleiotropy, and further show that the average degree of pleiotropy is greatest for proteins associated with senescence. I explain these results with a simple mathematical model combining assumptions of the antagonistic pleiotropy theory for the evolution of senescence with data on network topology. These findings integrate molecular and evolutionary models of senescence, and should aid in the search for new ageing genes.