RNA 3D Motif Search, Atlas, and Prediction from Sequence

描述（由申请人提供）：我们提出通过提供将3D RNA结构与序列和其他实验数据整合的改进方法，使实验三维RNA结构数据的增长体对生物医学研究人员更有用。本项目开发的新的标注工具和服务将被整合到核酸数据库（NDB）中，为项目成果的传播提供一个平台。预期的好处包括：1)从序列中预测功能性RNA基序的三维结构；2)在基因组中搜索非编码RNA基因；3)改善同源RNA序列的比对。我们将注意力集中在反复出现的模块化RNA 3D基序上，这些基序出现在各种各样的结构化RNA分子中，并赋予RNA独特的3D形状。这包括发夹环，内部环，结环，和三级相互作用的图案。我们将开发系统的方法来识别、分类和命名反复出现的RNA 3D基序，并定义搜索标准，以可靠地找到3D结构中每个基序的实例。将建立一个注释程序，以便在新的结构中快速识别新的基序，并与RNA本体联盟的其他成员合作审查。所有的实验RNA 3D结构将用基序列表进行注释。将创建一个Motif图集，以使有关结构中的3D Motif实例的信息提供给用户。这个包含基序注释的新图谱将被添加到核酸数据库（NDB）中，这是一个包含含有大分子的核酸结构和功能注释的网络资源。将开发一个更新程序，当PDB存档中出现新的RNA结构时，motif数据和Atlas条目将自动添加到NDB中。我们将扩展NDB的查询功能，为用户提供使用多种标准搜索NDB中RNA基序的工具，并将搜索结果与实验置信度测量相结合。我们将保持基序和碱基配对相互作用发生的统计数据，结合实验置信度措施，并将这些数据作为改进和验证工具的资源。Motif Atlas中的每个条目将包括Motif所有实例的结构比对，以揭示每个Motif的序列变体，包括插入和删除的模式。这些数据将与沃森-克里克和非沃森-克里克碱基对的统计共变数据以及碱基堆叠和碱基-骨干相互作用的统计数据相结合，以开发每个模块化RNA 3D基序序列变异性的概率模型。这些模型将用于部署一个基于网络的工具，用户可以从motif Atlas中找到与他们提交的发夹、内部或连接环序列最匹配的3D motif。

DESCRIPTION (provided by applicant): We propose to make the growing body of experimental three-dimensional (3D) RNA structure data more useful to biomedical researchers by providing improved methods to integrate 3D RNA structure with sequence and other experimental data. New annotation tools and services developed in this project will be integrated into the Nucleic Acid Database (NDB) which will provide a platform for disseminating project results. Among the expected benefits are better methods for 1) predicting 3D structures of functional RNA motifs from sequence, 2) searching for non-coding RNA genes in genomes, and 3) improving alignments of homologous RNA sequences. We focus attention on recurrent, modular RNA 3D motifs, which occur in a wide variety of structured RNA molecules, and which give RNA its distinctive 3D shape. This includes hairpin loops, internal loops, junction loops, and tertiary interaction motifs. We will develop systematic methods to identify, classify, and name recurrent RNA 3D motifs and to define search criteria to reliably find instances of each motif in 3D structures. An annotation procedure will be established so that new motifs are rapidly identified in new structures and vetted in collaboration with other members of the RNA Ontology Consortium. All experimental RNA 3D structures will be annotated with lists of motifs. A Motif Atlas will be created to make information about 3D motif instances in structures available to users. This new Atlas containing the annotation of motifs will be added to the Nucleic Acid Database (NDB), a web resource containing structural and functional annotation of nucleic acid containing macromolecules. An update procedure will be developed such that motif data and Atlas entries will automatically be added to the NDB as new RNA structures become available in the PDB archive. We will extend the query capabilities of the NDB with tools for users to search the NDB for RNA motifs using multiple criteria and to integrate search results with experimental confidence measures. We will maintain statistics on the occurrences of motifs and base pairing interactions, incorporating experimental confidence measures, and make these data available as a resource for refinement and validation tools. Each entry in the Motif Atlas will include a structural alignment of all instances of the motif to reveal sequence variants for each motif, including patterns of insertions and deletions. These data will be combined with statistical covariation data for Watson-Crick and non-Watson-Crick basepairs and statistical data for base-stacking and base- backbone interactions to develop probabilistic models for the sequence variability of each modular RNA 3D motif. These models will be used to deploy a web-based tool for users to find the 3D motif from the Motif Atlas which best matches the sequences of hairpin, internal, or junction loops that they submit. PUBLIC HEALTH RELEVANCE: Recent work shows that most of the human genome is transcribed, most of the produced RNA is non-protein coding, and a large fraction of it is critical for human reproduction, growth, and development. This proposal aims to make the growing body of experimental three-dimensional (3D) RNA structure data more useful to the biomedical research community by providing improved methods to integrate 3D RNA structure with sequence and other experimental data.