Department of Computer Science, Rice University, Houston, TX 77251, USA.
Proc Natl Acad Sci U S A. 2013 May 7;110(19):7754-9. doi: 10.1073/pnas.1217630110. Epub 2013 Apr 22.
Cis-regulatory networks (CRNs) play a central role in cellular decision making. Like every other biological system, CRNs undergo evolution, which shapes their properties by a combination of adaptive and nonadaptive evolutionary forces. Teasing apart these forces is an important step toward functional analyses of the different components of CRNs, designing regulatory perturbation experiments, and constructing synthetic networks. Although tests of neutrality and selection based on molecular sequence data exist, no such tests are currently available based on CRNs. In this work, we present a unique genotype model of CRNs that is grounded in a genomic context and demonstrate its use in identifying portions of the CRN with properties explainable by neutral evolutionary forces at the system, subsystem, and operon levels. We leverage our model against experimentally derived data from Escherichia coli. The results of this analysis show statistically significant and substantial neutral trends in properties previously identified as adaptive in origin--degree distribution, clustering coefficient, and motifs--within the E. coli CRN. Our model captures the tightly coupled genome-interactome of an organism and enables analyses of how evolutionary events acting at the genome level, such as mutation, and at the population level, such as genetic drift, give rise to neutral patterns that we can quantify in CRNs.
顺式调控网络 (CRN) 在细胞决策中起着核心作用。与其他生物系统一样，CRN 经历了进化，通过适应性和非适应性进化力量的结合来塑造其特性。剖析这些力量是对 CRN 的不同组成部分进行功能分析、设计调控扰动实验以及构建合成网络的重要步骤。尽管存在基于分子序列数据的中性和选择测试，但目前尚无基于 CRN 的此类测试。在这项工作中，我们提出了一个独特的基于基因组背景的 CRN 基因型模型，并展示了如何在系统、子系统和操纵子水平上使用该模型来识别 CRN 的部分具有中性进化力量可解释的特性。我们利用我们的模型对抗大肠杆菌的实验衍生数据。该分析的结果表明，在大肠杆菌 CRN 中，先前被确定为起源于适应性的特性——度分布、聚类系数和基序——存在统计学上显著且大量的中性趋势。我们的模型捕获了生物体的紧密耦合的基因组-相互作用组，并能够分析在基因组水平（如突变）和种群水平（如遗传漂变）发生的进化事件如何产生我们可以在 CRN 中量化的中性模式。
