TRTech-PGR: Identification and characterization of stress-responsive and evolutionary conserved epitranscriptomic modification sites in plant transcriptomes.

RNA是生命所必需的分子，在细胞的功能中起着多种作用。对RNA的化学修饰会影响其周转率。在植物中，由于在细胞水平上很难进行生化鉴定，人们对这些修饰的化学多样性以及它们发生的生物学背景知之甚少。这个项目的目标是使用计算方法，通过重新分析从广泛的模式和农业上重要的植物物种中获得的~1PB的公开数据，系统地识别RNA修饰。该项目将根据RNA修饰在哪里应用、生物学条件(例如，在植物发育期间、植物经历逆境时等)以及每一种植物之间的保守程度来识别和分类RNA修饰。该项目致力于培养计算机和生物学之间的接口的下一代植物科学家。本科生将在RNA修饰的鉴定和生物学验证中发挥不可或缺的作用。总而言之，该项目将通过在公共资源库中使用数据的新应用来洞察RNA修饰的生物学意义。RNA的化学修饰是多样的，发生在所有类别的RNA分子上，并且是生理上相关的。然而，RNA修饰在植物中还没有得到深入的研究。这种认识上的差距在很大程度上是由于用于测量特定RNA修饰丰度的生化分析的成本和技术困难。鉴于这些困难，已经开发了便于高通量识别和预测这些化学加成的电子方法。这项建议旨在通过以下方式解决在识别修饰和将其置于生物学背景中的挑战：1)使用大约1PB的公开可获得的RNA-SEQ数据，开发超过47种独特修饰的详尽、带注释的植物表观转录转录资源，以及2)为每一种修饰及其被发现修改的RNA提供生物学和进化背景。为了处理丰富的可公开获得的RNA-SEQ数据，并以一种将驱动假设生成的方式呈现结果信息，该项目将开发新的计算工作流程和数据可视化工具。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

RNA is an essential molecule for life, serving many roles in the functioning of cells. Chemical modifications to RNA can affect its rate of turnover. In plants, little is known about the chemical diversity of these modifications and the biological contexts in which they occur, due to the difficulties in biochemically identifying them at the cellular level. This project aims to use computational approaches to systematically identify RNA modifications by reanalyzing ~1 petabyte of publicly available data from a broad diversity of model and agriculturally important plant species. This project will identify and classify RNA modifications based on where they are applied, the biological conditions (e.g., during the development of the plant, when the plant experiences stress, etc.), and the degree to which each modification is conserved between plant species. This project is devoted to training the next generation of plant scientists at the interface between computers and biology. Undergraduate students will play an integral role in the identification and biological validation of RNA modifications. Altogether, this project will provide insight into the biological significance of RNA modifications using novel applications of data in public repositories. RNA chemical modifications are diverse, occur on all classes of RNA molecules, and are physiologically relevant. However, RNA modifications have not yet been studied in depth in plants. This gap in knowledge is in large part due to the cost and technical difficulties of the biochemical assays used to measure abundance of specific RNA modifications. In light of these difficulties, in silico methods have been developed that facilitate high-throughput identification and prediction of these chemical additions. This proposal aims to address challenges in identifying modifications and placing them into a biological context by: 1) developing an exhaustive, annotated plant epitranscriptomic resource of over 47 unique modifications using approximately 1 petabase of publicly available RNA-seq data, and 2) provide a biological and evolutionary context for each of these modifications and the RNAs they are found to modify. To process the wealth of publicly available RNA-seq data and present the resulting information in a manner that will drive hypothesis generation, this project will develop novel computational workflows and data visualization tools.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.