Network-Based Discovery of Brassinosteroid Regulation of Plant Growth and Stress Responses in Arabidopsis

基于网络的油菜素类固醇调节拟南芥植物生长和应激反应的发现

• 批准号: 1818160
• 负责人: Yanhai Yin
• 金额: $ 90万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1818160&HistoricalAwards=false
• 关键词: Network; Based; Discovery; Brassinosteroid; Regulation

Plant steroid hormones called Brassinosteroids (BRs) signal to regulate plant growth, development and response environmental stresses. However, our understanding of how this steroid hormone controls thousands of genes to regulate these processes is incomplete. The project will generate and use multiple large-scale datasets to model how genes are controlled to govern BR-regulated growth and drought responses. BR pathways are well conserved among Arabidopsis and crop plants such as maize, rice and other crops, so the knowledge obtained from the proposed studies can be used to design strategies to optimize plant growth and crop production under drought conditions. Moreover, the project provides excellent training opportunities for graduate students and postdoctoral associates in modern plant biology. The investigators will also achieve societally relevant outcomes by providing training opportunities to underrepresented undergraduates through the George Washington Carver Internship program as well as engaging high school and community college teachers via summer internships. Through this partnership with teachers a learning module on BR-regulation of plant growth will be developed for high-school and community college students. Furthermore, unpublished data from the proposed studies will be incorporated into an upper level undergraduate course on functional genomics, systems, and network biology, freeing students to generate their own hypotheses during a group project rather than simply reproducing published work. Finally, the investigators will provide resources to the research community by organizing a workshop on plant phenomics, proteomics and computational modeling approaches and by making the data generated publicly accessible through publications and the Principal Investigator's laboratory website.Molecular genetic studies in Arabidopsis have greatly advanced our understanding of the BR signaling pathway. BRs signal to regulate BES1/BZR1 family transcription factors (TFs), hundreds of BR-Related Transcription Factors (BR-TFs) and thousands of target genes. Although numerous BR-TFs have been identified, the transcriptional complexes that allow BES1/BZR1 and these BR-TFs to regulate the large number of BR-responsive genes have not been characterized. In addition, modeling of BR networks has proven to be a powerful approach to understand how BES1 directs a network controlling thousands of BR responsive genes. However, previously constructed BR networks have only considered transcription, overlooking important regulation at the post-transcriptional and post-translational level. The project will use an integrated genetics, genomics, and proteomics approach to establish and experimentally test a comprehensive Arabidopsis Gene Regulatory Network (GRN) governing BR-regulated growth and drought responses. By combining cutting-edge proteomics with advanced predictive modeling the project will generate a comprehensive view of BR-mediated transcriptional regulation and allow for the identification of novel factors involved in BR responses. First, investigators will uncover the components and functions of BR transcription factor complexes by examining the role of two novel BR-TFs. These two BR-TFs interact with BES1, a master regulator of the BR pathway, as well as a large number of other BR-TFs, likely forming large transcriptional complexes to control the expression of BR target genes. Second, investigators will generate BR transcriptome, proteome, and phosphoproteome datasets that are a prerequisite for a novel approach pioneered by the Co-Principal Investigator to construct GRNs based on these combined omics data. These combined networks have increased predictive ability compared to networks based only on transcriptional data and will provide a vital resource, allowing for a more complete understanding of the transcriptional program through which BRs control plant growth and stress responses.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

植物甾体激素是一类调节植物生长发育和响应环境胁迫的信号物质。然而，我们对这种类固醇激素如何控制数千个基因来调节这些过程的理解是不完整的。该项目将生成并使用多个大规模数据集来模拟基因是如何被控制来管理BR调节的生长和干旱反应的。BR途径在拟南芥和作物如玉米、水稻和其他作物中很好地保守，因此从拟议的研究中获得的知识可用于设计策略以优化干旱条件下的植物生长和作物产量。此外，该项目为现代植物生物学的研究生和博士后提供了极好的培训机会。调查人员还将通过乔治华盛顿卡弗实习计划为代表性不足的本科生提供培训机会，以及通过暑期实习吸引高中和社区大学教师，从而实现与社会相关的成果。通过与教师的这种伙伴关系，将为高中和社区大学的学生开发一个关于BR调节植物生长的学习模块。此外，来自拟议研究的未发表数据将被纳入功能基因组学，系统和网络生物学的高级本科课程，使学生能够在小组项目中产生自己的假设，而不是简单地复制已发表的工作。最后，研究人员将通过组织一个关于植物表型组学、蛋白质组学和计算建模方法的研讨会，并通过出版物和首席研究员实验室网站公开获得所产生的数据，为研究界提供资源。拟南芥的分子遗传学研究极大地促进了我们对BR信号通路的理解。BR信号调节BES 1/BZR 1家族转录因子（TF）、数百种BR相关转录因子（BR-TF）和数千种靶基因。虽然已经鉴定了许多BR-TF，但是允许BES 1/BZR 1和这些BR-TF调节大量BR应答基因的转录复合物尚未被表征。此外，BR网络的建模已被证明是了解BES 1如何指导控制数千个BR响应基因的网络的有力方法。然而，以前构建的BR网络只考虑了转录，忽略了重要的调控在转录后和翻译后水平。该项目将使用整合的遗传学，基因组学和蛋白质组学方法来建立和实验测试一个全面的拟南芥基因调控网络（GRN）管理BR调节的生长和干旱反应。通过将尖端的蛋白质组学与先进的预测建模相结合，该项目将产生BR介导的转录调控的全面视图，并允许识别参与BR反应的新因子。首先，研究人员将通过研究两种新型BR-TF的作用来揭示BR转录因子复合物的组成和功能。这两种BR-TF与BR途径的主调节因子BES 1以及大量其他BR-TF相互作用，可能形成大的转录复合物以控制BR靶基因的表达。其次，研究人员将生成BR转录组，蛋白质组和磷酸化蛋白质组数据集，这是联合主要研究者开创的基于这些组合组学数据构建GRNs的新方法的先决条件。与仅基于转录数据的网络相比，这些组合网络提高了预测能力，并将提供重要的资源，使人们能够更全面地了解BR控制植物生长和胁迫反应的转录程序。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Brassinosteroid gene regulatory networks at cellular resolution in the Arabidopsis root.

• DOI: 10.1126/science.adf4721
• 发表时间: 2023-03-31
• 期刊: SCIENCE
• 影响因子: 56.9
• 作者: Nolan, Trevor M.;Vukasinovic, Nemanja;Hsu, Che-Wei;Zhang, Jingyuan;Vanhoutte, Isabelle;Shahan, Rachel;Taylor, Isaiah W.;Greenstreet, Laura;Heitz, Matthieu;Afanassiev, Anton;Wang, Ping;Szekely, Pablo;Brosnan, Aiden;Yin, Yanhai;Schiebinger, Geoffrey;Ohler, Uwe;Russinova, Eugenia;Benfey, Philip N.
• 通讯作者: Benfey, Philip N.

Redesigning green revolution trait with increased grain yield and nitrogen utilization efficiency by reducing brassinosteroid signaling in semidwarf wheat

• DOI: 10.1007/s11427-023-2401-3
• 发表时间: 2023-06
• 期刊: Science China Life Sciences
• 作者: Hongqing Guo;Yanhai Yin

Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses

干旱机器人检测 (RoAD)：油菜素类固醇和干旱反应的自动表型分析系统

• DOI: 10.1111/tpj.15401
• 发表时间: 2021
• 期刊: The Plant Journal
• 作者: Xiang, Lirong;Nolan, Trevor M.;Bao, Yin;Elmore, Mitch;Tuel, Taylor;Gai, Jingyao;Shah, Dylan;Wang, Ping;Huser, Nicole M.;Hurd, Ashley M.
• 通讯作者: Hurd, Ashley M.

The AP2/ERF Transcription Factor TINY Modulates Brassinosteroid-Regulated Plant Growth and Drought Responses in Arabidopsis

• DOI: 10.1105/tpc.18.00918
• 发表时间: 2019-08-01
• 期刊: PLANT CELL
• 影响因子: 11.6
• 作者: Xie, Zhouli;Nolan, Trevor;Yin, Yanhai
• 通讯作者: Yin, Yanhai