Structural, Functional, and Evolutionary Analysis of Long Non-coding RNAs in Control of Stress Response and the Epigenome in Diverse Plant Species

长非编码 RNA 在不同植物物种中控制应激反应和表观基因组的结构、功能和进化分析

• 批准号: 1444490
• 负责人: Brian Gregory
• 金额: $ 256.13万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1444490&HistoricalAwards=false
• 关键词: Structural; Functional; Evolutionary; Analysis; Long

PI: Brian D. Gregory (University of Pennsylvania)Co-PIs: Eric Lyons and Mark Beilstein (University of Arizona) Long non-coding RNAs (lncRNAs) are an emerging class of molecules gaining attention for their roles in various biological processes. lncRNAs are defined by the fact that they do not code for proteins and are therefore not mRNAs. In addition, they do not fit into other well-defined small silencing RNA-producing categories such as small interfering RNAs (siRNA) and microRNAs (miRNAs). Despite the importance of lncRNAs in development, epigenetic modification, and stress responses, there is still much to be learned about their structure, protein interactions, and functions, especially in model and crop plant species. This project will address this significant gap using a combination of genomic, evolutionary, and bioinformatics approaches. It is anticipated that the data, web-accessible genome analytical tools, and data management systems developed by the project will provide novel insights into plant gene expression regulation by lncRNAs, and provide important new findings and resources for studies focused on the improvement of numerous crop and genetic model plants. With regard to outreach and training, this project will provide interdisciplinary research training in RNA biology, computational science and evolutionary biology for students and postdoctoral associates. In addition, the project will develop an interdisciplinary course entitled "Applied Concepts in RNA Biology" that will leverage large-scale computing and datasets to understand various aspects of the role of RNA in biological systems. This project-based course will teach the fundamentals of RNA biology, next-generation sequencing techniques, distributed and high performance computing, data-intensive science, and collaborative research techniques that will be used in student-driven research projects. The course will be taught simultaneously at the University of Pennsylvania and the University of Arizona, with two-way audio/video conferencing and lecture topics alternatively taught at each site. All project outcomes will be made readily accessible to the broader research community through a project website (https://genomevolution.org/wiki/index.php/EPIC-CoGe_Tutorial), the iPlant Collaborative and long-term repositories such as GenBank and the Short Read Archive (SRA). This project is uniquely positioned to provide insights into the structure and function of lncRNAs, and their interaction with specific epigenomic regulatory modifications in the genome. The specific goals of the project are to define a subset of lncRNAs that are important for proper gene regulation in both normal development and stress response. Specifically, the project will focus on identifying and functionally characterizing those lncRNAs that are (1) nuclear, (2) highly structured, (3) stress responsive, (4) protein bound, and (5) evolutionary conserved in genetic models (Eutrema salsugineum and Arabidopsis thaliana) and in crop species (Camelina sativa, Brassica rapa, Zea mays, and Sorghum bicolor), focusing on their roles in stress adaptation. Finally, the project will expand EPIC-CoGe, a central repository for plant epigenomics data across all species, with advanced data integration, visualization, and analysis tools to allow for the integration of functional genomics data to provide new insight into genome-wide epigenomic interactions.

PI：Brian D. Gregory（宾夕法尼亚大学）Co-Pis：Eric Lyons和Mark Beilstein（亚利桑那大学）长的非编码RNA（LNCRNA）是一类新兴的分子类别，因为它们在各种生物学过程中的作用而引起了人们的关注。 LNCRNA的定义是因为它们不为蛋白质编码，因此不是mRNA。此外，它们不适合其他定义明确的小沉默RNA产生类别，例如小型干扰RNA（siRNA）和microRNA（miRNA）。尽管LNCRNA在发育，表观遗传修饰和压力反应中的重要性，但关于它们的结构，蛋白质相互作用和功能，尤其是在模型和作物植物物种中仍然有很多了解。该项目将通过基因组，进化和生物信息学方法的结合来解决这一重大差距。可以预见，该项目开发的数据，可访问的基因组分析工具以及数据管理系统将为LNCRNA提供对植物基因表达调节的新见解，并为研究的研究提供了重要的新发现和资源。关于宣传和培训，该项目将为学生和博士后同伴提供RNA生物学，计算科学和进化生物学的跨学科研究培训。 此外，该项目将开发一个标题为“ RNA生物学中应用概念”的跨学科课程，该课程将利用大规模计算和数据集来了解RNA在生物系统中的作用的各个方面。 该基于项目的课程将教授RNA生物学，下一代测序技术，分布式和高性能计算，数据密集型科学以及将用于学生驱动的研究项目的协作研究技术。该课程将在宾夕法尼亚大学和亚利桑那大学同时教授，并在每个站点上都有双向音频/视频会议和讲座主题。通过项目网站（https://genomevolution.org/wiki/index.php/epic-coge_tutorial），iPlant的协作和长期存储库，例如GenBank和Short Brade Archive（SRA），将使更广泛的研究社区易于访问所有项目成果。 该项目是独特的定位，可以提供有关LNCRNA的结构和功能的见解，以及它们与基因组中特定表观基因组调节修饰的相互作用。该项目的具体目标是定义LNCRNA的子集，对于正常发育和压力反应中的适当基因调节很重要。 Specifically, the project will focus on identifying and functionally characterizing those lncRNAs that are (1) nuclear, (2) highly structured, (3) stress responsive, (4) protein bound, and (5) evolutionary conserved in genetic models (Eutrema salsugineum and Arabidopsis thaliana) and in crop species (Camelina sativa, Brassica rapa, Zea mays, and Sorghum bicolor), focusing on它们在压力适应中的作用。最后，该项目将扩大所有物种中植物表观基因组学数据的中央存储库，具有先进的数据集成，可视化和分析工具，以允许功能基因组学数据的整合，以提供对全基因组表观基因组相互作用的新见解。