Rubinstein Amir, Gurevich Vyacheslav, Kasulin-Boneh Zohar, Pnueli Lilach, Kassir Yona, Pinter Ron Y
Department of Computer Science, Technion-Israel Institute of Technology, Haifa 32000, Israel.
Proc Natl Acad Sci U S A. 2007 Apr 10;104(15):6241-6. doi: 10.1073/pnas.0611168104. Epub 2007 Mar 30.
Modeling and analysis of genetic regulatory networks is essential both for better understanding their dynamic behavior and for elucidating and refining open issues. We hereby present a discrete computational model that effectively describes the transient and sequential expression of a network of genes in a representative developmental pathway. Our model system is a transcriptional cascade that includes positive and negative feedback loops directing the initiation and progression through meiosis in budding yeast. The computational model allows qualitative analysis of the transcription of early meiosis-specific genes, specifically, Ime2 and their master activator, Ime1. The simulations demonstrate a robust transcriptional behavior with respect to the initial levels of Ime1 and Ime2. The computational results were verified experimentally by deleting various genes and by changing initial conditions. The model has a strong predictive aspect, and it provides insights into how to distinguish among and reason about alternative hypotheses concerning the mode by which negative regulation through Ime1 and Ime2 is accomplished. Some predictions were validated experimentally, for instance, showing that the decline in the transcription of IME1 depends on Rpd3, which is recruited by Ime1 to its promoter. Finally, this general model promotes the analysis of systems that are devoid of consistent quantitative data, as is often the case, and it can be easily adapted to other developmental pathways.
基因调控网络的建模与分析对于更好地理解其动态行为以及阐明和完善未解决问题至关重要。我们在此提出一种离散计算模型，该模型能有效描述代表性发育途径中基因网络的瞬时和顺序表达。我们的模型系统是一个转录级联反应，其中包括正负反馈回路，这些回路指导芽殖酵母减数分裂的起始和进程。该计算模型允许对早期减数分裂特异性基因（特别是Ime2）及其主激活因子Ime1的转录进行定性分析。模拟结果表明，相对于Ime1和Ime2的初始水平，转录行为具有稳健性。通过删除各种基因和改变初始条件，对计算结果进行了实验验证。该模型具有很强的预测性，它为如何区分和推理关于通过Ime1和Ime2进行负调控的方式的替代假设提供了见解。一些预测已通过实验得到验证，例如，表明IME1转录的下降取决于Rpd3，Rpd3由Ime1招募到其启动子。最后，这个通用模型促进了对缺乏一致定量数据的系统的分析，这种情况经常出现，并且它可以很容易地适应其他发育途径。
