Neutral evolution of mutational robustness
Neutral evolution of mutational robustness
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DOI：
10.1073/pnas.96.17.9716
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发表时间：
1999-08-17
影响因子：
11.1
通讯作者：
Huynen, M
中科院分区：
文献类型：
--
作者：
van Nimwegen, E;Crutchfield, JP;Huynen, M
引入并分析了中性选择基因网络中群体进化的一般模型，证明了群体在神经网络上的极限分布完全由网络拓扑结构决定，由网络邻接矩阵的主特征向量给出，并且每个个体的中性突变邻居数由矩阵谱半径给出，这些结果量化了群体进化的突变稳健性--表型对突变的不敏感性--从而减少遗传负荷的程度。由于平均中立性与进化参数无关--例如突变率、种群大小和选择优势--人们可以通过使用来自体外或体内进化的简单种群数据来推断神经网络拓扑的全局统计。在RNA二级结构的中性网络上进化的种群与我们的理论预测显示出很好的一致性。
We introduce and analyze a general model of a population evolving ol er a network of selectively neutral genotypes, We show that the population's limit distribution on the neutral network is solely determined by the network topology and given by the principal eigenvector of the network's adjacency matrix, Moreover, the average number of neutral mutant neighbors per individual is given by the matrix spectral radius, These results quantify the extent to which populations evolve mutational robustness-the insensitivity of the phenotype to mutations-and thus reduce genetic load. Because the average neutrality is independent of evolutionary parameters-such as mutation rate, population size, and selective advantage-one can infer global statistics of neutral network topology by using simple population data available from in vitro or in vivo evolution. Populations evolving on neutral networks of RNA secondary structures show excellent agreement with our theoretical predictions.