Discovery of Gene Regulatory Networks Controlling Cell Cycle Exit in Drosophila,

摘要 终末细胞分化通常伴随着增殖的停止和细胞的永久退出 周期这些过程之间协调的丧失可导致异常的组织发育， 肿瘤发生尽管其重要性，很少有人知道细胞周期退出和终末分化是如何进行的。 协调一致。一种假说得到了细胞培养、小鼠和昆虫研究的支持， 触发分化的细胞外信号也控制关键细胞周期调节因子的表达。然而，在这方面， 这些调控因子的特性以及连接细胞外分化信号的遗传调控网络 与细胞周期相关的基因仍然是未知的。目的：鉴定连接终末细胞的基因调控网络， 分化与细胞周期退出体内，这个合作试点项目之间的埃德加博士在FHCRC和博士。 NMSU的Song提出通过离散动态系统将联合收割机与一种新的系统生物学方法结合起来 具有高通量时间基因表达的模型和成功模型中的反向遗传学研究 黑腹果蝇Drosophila melanogaster这些模型将使人们能够预测基因网络， 细胞外信号与细胞周期机制。这些模型将通过实验进行测试和探索， vivo.该项目有三个具体目标： 目标1。推进从全基因组生成离散动态系统模型的方法和软件 时间基因表达将使用果蝇翅膀的微阵列数据。 目标2.通过计算机模拟遗传扰动并比较预测变化来测试建模方法 基因表达的变化与体内实验观察到的变化之间的关系。 目标3。利用建模方法预测新的基因调控网络与细胞周期的融合 在分化过程中进行控制，并在体内实验探索和验证预测的网络。 重要的是，这些目标是高度迭代的，将导致国际社会之间的密切整合与合作。 FHCRC的体内实验和NMSU的计算机模拟。这些调查最终将提供 关于发育信号如何与细胞周期相互作用以确保细胞周期退出的信息， 终末分化此外，还提供了一种功能强大且广泛适用的计算方法来阐明 将建立基因调控网络。

ABSTRACT Terminal cellular differentiation is often coupled with a halt in proliferation and permanent exit from the cell cycle. A loss of coordination between these processes can lead to aberrant tissue development and tumorigenesis. Despite its importance, little is known about how cell cycle exit and terminal differentiation are coordinated. One hypothesis, supported by studies in cell culture, mice and insects, suggests that the extracellular signals that trigger differentiation also control the expression of key cell cycle regulators. However, the identities of these regulators and the genetic regulatory networks linking extracellular differentiation signals with cell cycle genes remain largely unknown. To identify the gene regulatory networks linking terminal differentiation with cell cycle exit in vivo, this collaborative pilot project between Dr. Edgar at FHCRC and Dr. Song at NMSU proposes to combine a novel systems biology approach through discrete dynamic system models with high throughput temporal gene expression and reverse genetics studies in the successful model organism, Drosophila melanogaster. These models will allow one to predict genetic networks that connect extracellular signals with the cell cycle machinery. The models will be tested and explored by experiments in vivo. This project has three specific aims: Aim 1. To advance the methodology and software to generate discrete dynamic system models from genomewide temporal gene expression. Microarray data from Drosophila wings will be used. Aim 2. To test the modeling approach by genetic perturbations in silico and comparing the predicted changes in gene expression to the changes experimentally observed in vivo. Aim 3. To use the modeling approach to predict new genetic regulatory networks converging on cell cycle control during differentiation, and experimentally explore and validate the predicted networks in vivo. Importantly, the aims are highly iterative and will lead to a close integration and cooperation between the in vivo experiments at FHCRC and in silico modeling at NMSU. These investigations will ultimately provide information about how developmental signals interface with the cell cycle to ensure cell cycle exit upon terminal differentiation. In addition, a powerful and widely applicable computational approach to elucidating gene regulatory networks will be developed.