ABI: Systems Bioinformatics Approaches to Modeling and Deciphering Plant Transcriptional Regulatory Networks

ABI：模拟和破译植物转录调控网络的系统生物信息学方法塞缪尔·罗伯茨诺贝尔基金会获得一笔赠款，用于研究基因组规模的转录调控网络如何控制基因表达。该项目将解决植物系统和关键调控元件中基因调控的多样性和复杂性，包括转录因子、microRNAs(MiRNAs)、反式作用小干扰RNA(ta-siRNAs)和新出现的调控元件。利用系统生物信息学方法破译植物转录调控网络的具体目标包括：1)开发图形模型来模拟和模拟植物转录调控网络；2)开发新的计算算法以从模式植物的高通量功能基因组学数据中推断大规模基因调控网络(GRN)；3)构建以激素相关调控网络为重点的拟南芥基因调控网络(AGRN)；4)构建参与豆科植物结瘤调控的豆科基因调控网络(LGRN)：紫花苜蓿、莲花和大豆；以及5)开发综合网络系统，以托管AGRN和LGRN以及支持性基因组规模的数据，以及网络发现、搜索和管理工具，作为链接到AGRN和LGRN网络服务的流行的基于Cytoscape的开源网络可视化软件的插件。整合这些系统不仅将满足植物生物学研究界和植物育种者的需求，而且最终将导致开发出更好的工程改造的重要经济作物，例如饲用豆类。这项拟议的工作是跨学科的，需要将基因组学、计算生物学和生物信息学应用于遗传学、分子和细胞生物学以及植物生理学等经典学科。通过在诺布尔基金会提供单一的培训场地，该项目将使博士后研究员、访问科学家、学生和技术人员能够获得许多对尖端生物学研究至关重要的研究技能。一个强大的学生推广计划将被利用，以最大限度地提高这个项目的教学成果。

ABI: Systems Bioinformatics Approaches to Modeling and Deciphering Plant Transcriptional Regulatory NetworksThe Samuel Roberts Noble Foundation is awarded a grant to investigate how genome scale transcriptional regulatory networks control gene expression. The project will address diversity and complexity of gene regulation in plant systems and key regulatory elements, including transcription factors, microRNAs (miRNAs), trans-acting small interfering RNAs (ta-siRNAs), and emergent regulatory elements. Using systems bioinformatics approaches to decipher plant transcriptional regulatory networks, specific aims include: 1) developing graphical models to model and simulate plant transcriptional regulatory networks; 2) developing novel computational algorithms to infer large-scale gene regulatory networks (GRNs) from high throughput functional genomics data in model plants; 3) constructing Arabidopsis Gene Regulation Networks (AGRN) focusing on hormone-related regulatory networks; 4) constructing legume gene regulatory networks (LGRN) involved in regulation of nodulation in three model legumes: Medicago truncatula, Lotus japonicus, and Glycine max; and 5) developing integrated web systems to host AGRN and LGRN along with supportive genome-scale data, and network discovery, search and curation tools as plug-ins of popular Cytoscape-based open-source network visualization software linked to AGRN and LGRN web services. Integrating these systems will not only fulfill the needs of the plant biology research community and plant breeders, but will ultimately lead to the development of better engineered economically important crops, e.g. forage legumes. The proposed work is trans-disciplinary and requires the application of genomics, computational biology, and bioinformatics to the classical disciplines of genetics, molecular and cell biology, and plant physiology. By providing a single training ground at the Noble Foundation, this project will empower postdoctoral fellows, visiting scientists, students, and technical staff to acquire many of the research skills that are essential for cutting-edge biological research. A strong student outreach program will be harnessed to maximize teaching and learning outcomes for this project.