Collaborative Research: BBSRC-NSF/BIO: An autonomous registry system for plant microRNAs

MicroRNA是短RNA分子（约20至24个核苷酸），其功能是调节动物和植物的基因表达水平。microRNA的靶标在许多关键的细胞过程中发挥作用，包括发育、生物和非生物胁迫反应。在作物中，microRNA已被证明具有支持对生育力和产量重要的表型的作用，从而有助于粮食安全和农业经济。与基因组的所有特征一样，使用适当的基因名称在基因组中一致地对microRNA基因进行编目和跟踪至关重要。这就需要统一和严格地指定标识符，使用最新标准进行定期重新评估和筛选，以及社区的投入。不同的出版物和数据库对特定的microRNA使用相同的名称是至关重要的，并且不同物种中的同源物最好使用一致的名称。自2004年以来，已经存在一个用于microRNA命名和质量控制的单一中央注册表，用于命名和分类microRNA：miRBase。miRBase在当前的“大数据”时代面临挑战。特别是，新microRNA的注册目前依赖于耗时的手动管理。基因组和小RNA的廉价测序大大提高了microRNA的发现率，超过了miRBase手动管理新条目的能力。然而，对单一可信资源的需求比以往任何时候都更加迫切，以快速注册新的microRNA，并评估现有的注释和新的注释。唐纳德·丹佛斯植物科学中心和美国宾夕法尼亚州立大学以及英国曼彻斯特大学之间的这个合作项目将为miRbase开发一个自主和自动化的microRNA注册系统。这将与miRBase命名协议集成，并添加额外的质量控制。该项目将解决小RNA领域持续增长的一个关键问题，特别是在植物中。通过自动提交、管理和发布新注释，该项目将消除目前对耗时的手动注释的依赖，以维护miRBase。这将使miRBase能够继续催化生物学所有领域的基础发现。因此，该项目将建立在现有工具的基础上，从植物小RNA深度测序数据集中注释高置信度的microRNA。该项目将开发一个管道，自动将一致的基因名称分配给用户从这些深度数据集中生成的新型植物microRNA注释。该项目将在miRBase基础设施中引入新的接口，以接受和显示用户提交的新microRNA数据，并为用户提供更多可视化数据的选择。该项目的一项产出是培训研究人员分析生物大数据和全栈网络开发-这些技能在科学和其他领域都有很高的需求。该项目还将把研究与本科教育结合起来，并将建立在扩大代表性不足群体参与的项目基础上。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

MicroRNAs are short RNA molecules (~20 to 24 nucleotides) that function to regulate levels of gene expression in animals and plants. The targets of microRNAs function in many key cellular processes, including development, biotic and abiotic stress responses. In crop plants, microRNAs have demonstrated roles supporting phenotypes important for fertility and yield, and thus contribute to food security and the agricultural economy. As with all features of genomes, cataloging and tracking microRNA genes consistently and across genomes using appropriate gene names is crucial. This requires uniform and rigorous assignment of identifiers, periodic reassessment and screening using the latest criteria, and community input. It is crucial that different publications and databases use the same name for a particular microRNA, and homologs in different species should ideally receive consistent names. A single, central registry for microRNA nomenclature and quality control has existed since 2004 to name and catalogue microRNAs: miRBase. miRBase faces challenges in the current era of 'big data'. In particular, registration of new microRNAs currently relies on time-consuming, manual curation. Inexpensive sequencing of genomes and small RNAs has massively increased the discovery rate of microRNAs, exceeding the capacity of miRBase for manual curation of new entries. Yet the need for a single trusted resource is more acute than ever, for rapid registration of new microRNAs, and to assess both existing annotations and new. This collaborative project between the Donald Danforth Plant Science Center and Pennsylvania State University in the US and the University of Manchester in the UK will develop an autonomous and automated microRNA registry system for miRbase. This will be integrated with miRBase naming protocols and adding additional quality controls. The project will resolve a critical problem for the continued growth of the small RNA field, particularly in plants. By automating submission, curation, and release of new annotations, this project will eliminate the current reliance on time-consuming manual annotations to maintain miRBase. This will allow miRBase to continue to catalyze fundamental discoveries in all areas of biology. The project will thus build on existing tools to annotate high-confidence microRNAs from plant small RNA deep sequencing datasets. The project will develop a pipeline to automatically assign consistent gene names to novel plant microRNA annotations generated by users from these deep datasets. And the project will incorporate new interfaces into the miRBase infrastructure to accept and display user submissions of novel microRNA data, and to expand options for users to visualize data. An output of the project is training researchers in the analysis of biological big data and full stack web development -- skill sets in high demand across the sciences and beyond. The project will also integrate research with undergraduate education, and it will build on programs to broaden participation by under-represented groups.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.