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

MicroRNAs是一种短的RNA分子(~20到24个核苷酸)，其功能是调节动植物中基因表达的水平。MicroRNAs的靶标在许多关键的细胞过程中发挥作用，包括发育、生物和非生物应激反应。在农作物中，microRNAs已经显示出支持对肥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一致地跨基因组编目和跟踪microRNA基因是至关重要的。这需要统一和严格地分配识别符，定期重新评估和使用最新标准进行筛选，以及社区投入。至关重要的是，不同的出版物和数据库对特定的microRNA使用相同的名称，不同物种中的同源物理想情况下应该得到一致的名称。自2004年以来，为microRNA命名和质量控制建立了一个单一的中央登记处，以命名和编目microRNA：miRBase。MiRBase在当前的大数据时代面临挑战。特别是，新的microRNAs的注册目前依赖于耗时的人工管理。廉价的基因组和小RNA测序大大提高了microRNAs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，需要快速注册新的microRNAs，并评估现有的注释和新的注释。唐纳德·丹福斯植物科学中心、美国宾夕法尼亚州立大学和英国曼彻斯特大学的这一合作项目将为miRBase开发一个自主和自动化的microRNA注册系统。这将与miRBase命名协议集成在一起，并增加额外的质量控制。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、管理和发布新批注，该项目将消除当前对维护miRBase所需的耗时的手动批注的依赖。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，以注释来自植物小RNA深度测序数据集的高置信度microRNA。该项目将开发一条管道，自动为用户从这些深层数据集生成的新植物microRNA注释分配一致的基因名称。该项目将在miRBase基础设施中加入新的接口，以接受和显示用户提交的新的microRNA数据，并为用户提供更多可视化数据的选择。该项目的一个成果是培训研究人员进行生物大数据分析和全栈网络开发--这些技能集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相结合，并将以扩大代表不足群体的参与的计划为基础。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。

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.