Computational modeling of the regulatory network organizing the wound response in Arabidopsis thaliana.
Computational modeling of the regulatory network organizing the wound response in Arabidopsis thaliana.
复制标题
组织拟南芥伤口反应的调节网络的计算模型。
DOI：
10.1162/artl_a_00076
复制
发表时间：
2012
期刊：
影响因子：
2.6
通讯作者：
Kim JT
中科院分区：
文献类型：
--
作者：
Kim JT
植物经常受到机械冲击或昆虫的伤害，它们对伤害做出适当反应的能力对于它们的生存和繁殖成功至关重要。伤口反应由信号传导和调节网络介导。对拟南芥的分子研究已经确定COI 1基因是这个网络的核心组成部分。这些网络的当前模型定性地描述了伤口反应，但它们没有使用定量基因表达数据直接评估。我们建立了一个模型，包括使用transsys框架的关键组成部分的opsiswound响应。为了比较，我们构建了一个没有任何调节相互作用的空模型，以及通过重新连接伤口反应模型的各种替代模型。通过计算优化对所有模型进行参数化，以生成近似的合成基因表达谱。 经验数据集。我们使用各种距离测量对合成与经验数据的拟合进行评分，并使用优化后的中值距离直接定量评估伤口反应模型及其替代方案。候选模型的区分主要依赖于基因表达谱距离的测量。使用零模型来评估质量的距离措施的歧视，我们确定的相关性的对数比配置文件作为最合适的距离。我们的伤口反应模型拟合的经验数据显着优于替代模型。伤口响应模型的逐渐扰动导致拟合的相应逐渐下降。优化方法提供了对生物学相关特征的见解，例如鲁棒性。这是一个步骤，使多个交叉通路的综合研究，因此可能有助于发展我们的理解，基因组如何通知 将环境信号映射到表型性状。
Plants are frequently wounded by mechanical impact or by insects, and their ability to adequately respond to wounding is essential for their survival and reproductive success. The wound response is mediated by a signal transduction and regulatory network. Molecular studies inArabidopsishave identified theCOI1gene as a central component of this network. Current models of these networks qualitatively describe the wound response, but they are not directly assessed using quantitative gene expression data. We built a model comprising the key components of theArabidopsiswound response using thetranssysframework. For comparison, we constructed a null model that is devoid of any regulatory interactions, and various alternative models by rewiring the wound response model. All models were parametrized by computational optimization to generate synthetic gene expression profiles that approximate the empirical data set. We scored the fit of the synthetic to the empirical data with various distance measures, and used the median distance after optimization to directly and quantitatively assess the wound response model and its alternatives. Discrimination of candidate models depends substantially on the measure of gene expression profile distance. Using the null model to assess quality of the distance measures for discrimination, we identify correlation of log-ratio profiles as the most suitable distance. Our wound response model fits the empirical data significantly better than the alternative models. Gradual perturbation of the wound response model results in a corresponding gradual decline in fit. The optimization approach provides insights into biologically relevant features, such as robustness. It is a step toward enabling integrative studies of multiple cross-talking pathways, and thus may help to develop our understanding how the genome informs the mapping of environmental signals to phenotypic traits.