Identification, Discovery, and Public Archiving of RNA Structural Motifs

RNA 结构基序的鉴定、发现和公共存档

• 批准号: 8348532
• 负责人: Shaojie Zhang
• 金额: $ 16.92万
• 依托单位: UNIVERSITY OF CENTRAL FLORIDA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8348532
• 关键词: Accounting; Achievement; Adopted; Algorithms; Architecture; Archives; Base Pairing; Biological; Biological Process; Biomedical Research; Catalysis; Characteristics; Classification; Cluster Analysis; Communities; Computing Methodologies; Data Set; Databases; Development; Disease; Dyskeratosis Congenita; Electrostatics; Family; Functional RNA; Functional disorder; Gene Expression Regulation; Goals; Human; Hydrogen Bonding; Internet; Investigation; Lead; Length; Life; Magnetism; Measurement; Physiological; Play; Prader-Willi Syndrome; Protein Binding; Proteins; RNA; RNA Folding; RNA Splicing; RNA analysis; Recruitment Activity; Recurrence; Reporting; Research; Resources; Role; Small Nucleolar RNA; Structure; Work; base; biological systems; computerized tools; design; expectation; flexibility; improved; innovation; interest; loss of function; novel; prevent; success; tool; treatment strategy; user-friendly

DESCRIPTION (provided by applicant): The non-coding RNAs play many functional roles in biological processes, such as catalysis, gene expression regulation and RNA splicing. The various roles played by non-coding RNA are determined by their character- istic structure. RNA structural motifs are recurrent structural components in the non-coding RNAs. The RNA structural motifs have conserved structures, and therefore, have conserved biological or structural functions. For instance, the kink-turn motif is found in different kinds of non-coding RNAs and all of them are responsible for protein binding activities. The alternation of their structures will result in loss-of-function of the RNA structural motif, and in some cases severe diseases. For example, the destruction of kink-turn motif in small nucleolar RNA (snoRNA) will prevent it from recruiting the L7Ae protein, and thus lead to Dyskeratosis congenita and Prader-Willi syndrome. Therefore, the study of RNA structural motif will help us to elucidate the mechanisms of many diseases and lead to the development of novel treatment strategies. Currently, the essential RNA struc- tural motif research includes the following problems: 1) identifying all occurrences of the given motif (search), 2), classifying known motif instances based on their structures and functionalities (classification), and 3) defin- ing novel RNA structural motif families (de novo discovery). In this proposal, we aim at devising a suite of computational methods to solve these three problems. First, we will develop a new computational search tool which will, in addition to 3D geometry, take into account base pairing (hydrogen bonding forces) and base stack- ing (magnetic and electrostatic forces) information. Most of the existing RNA structural motif search tools show limitations in detecting motif instances with flexible geometry. The inclusion of base pairing and base stacking will resolve this issue. Second, we will develop a novel clustering strategy to solve the classification and de novo discovery problems simultaneously. Existing clustering strategies adopt length-dependent structural alignment score (which indicates the structural similarity between two candidate motif instances) as the distance measure- ment, and apply hierarchical clustering algorithm to identify closely related motif clusters. We plan to include a statistical framework that can normalize the alignment score, and thus resolve this issue. In addition, instead of hierarchical clustering algorithm, we will adopt clique-finding algorithm in our clustering strategy, so as to make it applicable to large data sets. We will examine the resulting clusters and compare them with known motifs, and then suggest novel RNA structural motif families. With the achievement of these two goals, we propose to build a database for archiving motif instances identified by our new search tool. Finally, we will report potential novel RNA structural motif families and encourage experimental investigation of their functionalities. We expect that the proposed work will lead to better understanding of the RNA structural motifs, and significantly promote biomedical research. PUBLIC HEALTH RELEVANCE: RNA structural motifs are components in non-coding RNAs, which play catalytic, regulatory and other important roles in many biological processes. The dysfunction of RNA structural motif will result in physiological disorders and cause diseases (such as Dyskeratosis congenita and Prader-Willi syndrome). We plan to devise a suite of computational methods for RNA structural motif search, classification, and discovery, so as to elucidate the mechanisms of RNA structural motif related diseases and push forward the development of their treatment strategies.

描述（由申请人提供）：非编码RNA在生物学过程中起许多功能作用，例如催化，基因表达调节和RNA剪接。非编码RNA扮演的各种角色取决于其特征结构。 RNA结构基序是非编码RNA中的复发结构成分。 RNA结构基序具有保守的结构，因此具有保守的生物学或结构功能。例如，扭结基序是在不同种类的非编码RNA中发现的，所有这些基序都是负责蛋白质结合活性的原因。它们的结构的交替将导致RNA结构基序的功能丧失，在某些情况下，严重的疾病。例如，在小核仁RNA（SNORNA）中扭结基序的破坏将阻止其募集L7AE蛋白，从而导致鼻脑炎症性疾病和prader-Willi综合征。因此，对RNA结构基序的研究将有助于我们阐明许多疾病的机制并导致新的治疗策略的发展。当前，必需的RNA结构基序研究包括以下问题：1）确定给定基序的所有发生（搜索），2），根据其结构和功能（分类）和3）定义新的RNA结构基序家族（DE Novo Discovery）对已知的基序实例进行分类。在此提案中，我们旨在设计一套计算方法来解决这三个问题。首先，我们将开发一个新的计算搜索工具，除3D几何形状外，还将考虑基础配对（氢键力）和基本堆叠（磁性和静电力）信息。大多数现有的RNA结构图案搜索工具在检测具有柔性几何形状的图案实例时都显示出局限性。包括基础配对和基础堆叠将解决此问题。其次，我们将制定一种新颖的聚类策略，以同时解决分类和从头发现问题。现有的聚类策略采用长度依赖性的结构对准评分（表明两个候选基序实例之间的结构相似性）作为距离测量值，并应用层次聚类算法来识别紧密相关的基序群集。我们计划包括一个统计框架，该框架可以使对齐得分正常化，从而解决此问题。此外，我们将在聚类策略中采用集团找到算法，而不是分层聚类算法，以使其适用于大型数据集。我们将检查所得的簇，并将它们与已知的基序进行比较，然后建议新的RNA结构基序家族。随着这两个目标的实现，我们建议构建一个数据库，以归档新搜索工具确定的图案实例。最后，我们将报告潜在的新型RNA结构基序家族，并鼓励对其功能进行实验研究。我们预计拟议的工作将使人们更好地了解RNA结构基序，并显着促进生物医学研究。 公共卫生相关性：RNA结构基序是非编码RNA中的组成部分，在许多生物过程中起催化，调节性和其他重要作用。 RNA结构基序的功能障碍将导致生理疾病并引起疾病（例如兴奋性脑膜炎和普拉德 - 威利综合征）。我们计划设计一套用于RNA结构图案搜索，分类和发现的计算方法，以阐明RNA结构基序相关疾病的机制并推动其治疗策略的发展。