Reconstructing Regulation Networks of Meiosis in Silico

在计算机中重建减数分裂的调控网络

• 批准号: 6967222
• 负责人: Wei Wang
• 金额: $ 33.66万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-07-01 至 2010-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6967222
• 关键词: Saccharomyces; binding sites; bioinformatics; chromatin immunoprecipitation; developmental genetics; fungal genetics; gene expression; genetic regulation; genetic transcription; mathematical model; meiosis; method development; microarray technology; northern blottings; polymerase chain reaction; sporogenesis; transcription factor

DESCRIPTION (provided by applicant): In the post-genome era, it is critical to organize genes and proteins into functional biological networks. Our long-term goal is to dissect the transcriptional regulatory networks that regulate every biological process in the cell, understand the regulatory mechanisms, and discover fundamental principles that govern the evolution of these networks. The focus of this proposal is to develop new bioinformatics methods for reconstructing the transcriptional network regulating yeast sporulation, which consists of meiosis and spore morphogenesis, by integrating genomic data from different sources. These methods are uniquely appropriate for identifying combinatorial regulation of transcription factors particularly those transient ones and thus revealing the dynamic realization of the underlying network. The proposed research will contribute significantly to our understanding of yeast sporulation and may shed light on understanding meiosis in higher organisms. The bioinformatics methods developed and validated in the proposed study can also serve as a good starting point to develop equivalent tools for higher organisms. The specific hypothesis behind the proposed research is that not all important transcriptional regulators of yeast sporulation have been identified, and many network links that determine regulatory logic are still missing. The specific aims are: 1. develop a new bioinformatics method to accurately construct transcription modules (defined to consist of a TF, its binding site and its target genes) using gene expression, transcription factor binding and sequence motif information; 2. construct transcription modules of budding yeast sporulation using the above algorithm, discover combinatorial regulation and determine transcriptional network of yeast sporulation by assembling these modules; 3. predict transcription modules and network topologies of sporulation in the 6 newly sequenced yeast genomes based on the network of budding yeast.

描述（由申请人提供）：在后基因组时代，将基因和蛋白质组织成功能性生物网络至关重要。我们的长期目标是剖析调节细胞中每个生物过程的转录调节网络，了解调节机制，并发现控制这些网络进化的基本原理。该提案的重点是开发新的生物信息学方法，通过整合不同来源的基因组数据来重建调节酵母孢子形成的转录网络，其中包括减数分裂和孢子形态发生。这些方法特别适合识别转录因子的组合调节，特别是那些瞬时转录因子，从而揭示底层网络的动态实现。拟议的研究将极大地促进我们对酵母孢子形成的理解，并可能有助于理解高等生物的减数分裂。在拟议的研究中开发和验证的生物信息学方法也可以作为开发高等生物等效工具的良好起点。 这项研究背后的具体假设是，并非酵母孢子形成的所有重要转录调节因子都已被识别，并且许多决定调节逻辑的网络链接仍然缺失。具体目标是：1.开发一种新的生物信息学方法，利用基因表达、转录因子结合和序列基序信息准确构建转录模块（定义为由转录因子、其结合位点和靶基因组成）； 2.利用上述算法构建出芽酵母孢子形成的转录模块，通过组装这些模块发现组合调控并确定酵母孢子形成的转录网络； 3.基于芽殖酵母网络预测6个新测序的酵母基因组中孢子形成的转录模块和网络拓扑。