Computational Analysis of Retinal Regulatory Interactions: structure and dynamics

描述（由申请人提供）：对视网膜调控网络的理解有助于阐明视网膜发育和视网膜疾病的分子基础。虽然视网膜调控因子和元件的知识已经取得了进展，并已确定与视网膜疾病相关的几个转录因子（TF）突变，视网膜调控网络的整体理解仍然是相当有限的。我们的长期目标是了解视网膜调控网络的结构和动力学。为此，我们在这里提出了一种计算方法来预测蛋白质-DNA和蛋白质-蛋白质相互作用相关的视网膜调节，通过整合现有的知识和各种数据集从高通量实验。我们还建议验证实验的预测。我们不仅对静态相互作用的预测感兴趣，而且对相互作用的条件依赖性转录活性也感兴趣。为了实现我们的目标，我们有四个具体的目标：（1）识别视网膜相关的顺式调控元件及其调控靶点，（2）确定协同调控视网膜相关基因的相互作用转录因子，（3）表征视网膜调控网络的动力学，以及（4）生物信息学预测的实验验证。除了视网膜疾病的调查，在这个建议中开发的计算程序也应该是广泛的社区普遍有用。

DESCRIPTION (provided by applicant): An understanding of retinal regulatory networks can help elucidate the molecular basis of retinal development and retinal diseases. Although gains in knowledge about retinal regulatory factors and elements have been made and several transcription factor (TF) mutations associated with retinal disease have been identified, overall understanding of retinal regulatory networks is still rather limited. Our long-term goal is to attain understanding of the structure and dynamics of retinal regulatory networks. To that end, we here propose a computational approach to predict protein-DNA and protein-protein interactions related to the retinal regulation by integrating current knowledge and a variety of data sets from high-throughput experiments. We also propose to verify the prediction experimentally. We are interested not only in the prediction of static interactions, but also in the condition-dependent transcriptional activity of interactions. To achieve our objective, we have four Specific Aims: (1) identification of retina-related cis-regulatory elements and their regulatory targets, (2) determination of interacting transcription factors that co-regulate retina-related genes, (3) characterization of the dynamics of the retinal regulatory networks, and (4) experimental verification of bioinformatics predictions. Beyond investigation of retinal disease, the computational programs developed in this proposal should also be generally useful for a broad community.