Kozlov Konstantin, Gursky Vitaly, Kulakovskiy Ivan, Samsonova Maria
BMC Genomics. 2014;15 Suppl 12(Suppl 12):S6. doi: 10.1186/1471-2164-15-S12-S6. Epub 2014 Dec 19.
The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency.
We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded.
The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3) functional important sites are not exclusively located in cis-regulatory elements, but are rather dispersed through regulatory region. It is of importance that some of the sites with high functional impact in hb, Kr and kni regulatory regions coincide with strong sites annotated and verified in Dnase I footprint assays.
转录调控的详细分析对于理解生物学过程至关重要。果蝇中的间隙基因网络在研究转录调控机制的研究中引起了极大的兴趣。它实现了体节基因网络的最上游调控层。与该系统的遗传学相比，参与间隙基因调控的分子机制的知识还远不完整。数学建模超越了遗传学和分子方法所获得的见解。它使我们能够在计算机上重建野生型基因表达模式，推断潜在的调控机制并证明其充分性。
我们开发了一个新模型，该模型使用详细的基于DNA的信息以及不同时间点的空间转录因子浓度数据，对间隙基因调控系统进行了动态描述。我们表明，该模型能够正确地再现野生型胚胎中的间隙基因表达模式，并能够预测Kr突变体和四种报告构建体中的间隙表达模式。我们使用四重交叉验证测试并拟合随机数据集来验证模型并证明其在数据描述中的充分性。可识别性分析表明，大多数模型参数都可以很好地识别。我们重建了间隙基因网络拓扑，并研究了单个转录因子结合位点对模型输出的影响。我们通过计算位点调控权重来衡量这种影响，该权重是所有注释位点集与排除感兴趣位点的集的残差平方和误差之间的归一化差异。
重建的间隙基因网络拓扑与先前的建模结果和文献数据一致。我们表明：1）转录因子结合位点的调控权重与其PWM评分的相关性非常弱；2）调控权重低的位点对模型输出很重要；3）功能重要位点并非仅位于顺式调控元件中，而是分散在调控区域中。重要的是，在hb、Kr和kni调控区域中一些具有高功能影响的位点与在Dnase I足迹分析中注释和验证的强位点一致。
