Federated Plant Database Initiative for the Legumes

PI: David Fernandez-Baca（爱荷华州立大学）CoPIs: Steven B. Cannon （USDA-ARS/爱荷华州立大学），Christopher D. Town （J. Craig Venter研究所），Andrew D. Farmer（国家基因组资源中心）和Jeremy DeBarry（亚利桑那大学）。高级人员：Ethalinda K.S. Cannon（爱荷华州立大学）豆类在粮食安全以及世界上几乎所有的种植系统中都发挥着核心作用。在栽培植物中，豆科植物，如豆类、豌豆和小扁豆，在固定大气氮的能力方面是独一无二的，这些氮被转化为可溶解的有机形式，可以通过与土壤细菌的共生被植物吸收。大约33%的营养氮来自豆类，豆类是大多数发展中国家最重要的蛋白质来源。许多豆类作物的基因组资源已经或正在开发中，但是这些数据资源的碎片性限制了研究人员利用在一个物种中产生的信息来推断另一个物种的功能或识别候选基因的能力。该项目的总体目标是通过为“豆类联盟”（LF）开发软件和方法来解决这一缺陷，该联盟由不同的、独立资助的、地理上分散的基因组数据门户（gdp）组成。LF将促进对广泛豆类物种的基因组、遗传和表型信息的利用，使研究人员和育种者能够充分利用目前在gdp中可用的数据。该项目将为不同背景、不同教育水平的学生提供研究培训机会。在外延方面，该项目将通过在国家和国际会议上的演讲和研讨会，以及通过向社区提供描述项目目标、实施方法和进度报告的中央门户网站，积极参与豆类数据提供者社区。跨作物和模式植物的数据收集速度急剧增加。大多数作物品种既存在数据管理问题，也存在获取遗传“大数据”的巨大机会。该项目的目标是开发豆类数据库的联合模型，促进跨大范围豆类物种的数据交换，以实现跨物种翻译基因组学，并调整现有的一套生物信息管理开源工具，这将为面向项目的数据管理提供一个框架，使其能够长期集成和广泛使用。具体目标是：1)。采用并移植目前在每个定制框架中管理的数据到一组集成良好的开源模型生物数据库工具中；定义数据格式、元数据标准、数据交换和Web服务协议，以促进以物种为中心的数据库在不同层次之间的通信；3)。3)利用其他重要特征的orthology， synsyny和mapping来整合跨豆科植物物种的遗传，基因组和表型数据，从而能够识别重要性状的共同分子碱基，并实现跨数据库项目的遍历；提高生物数据库项目收集和管理复杂表型数据的能力，使用本体，受控词汇表和定义良好的协议和模式；5)。通过实现一个通用的、开放的、虚拟化的数据存储库，实现跨站点的数据交换，实现数据集、标准化元数据的稳定、长期归档，以及用于归档、搜索和访问来自联邦gdp的数据集的健壮方法，从而促进高效的数据交换。预计LF将为一个被广泛接受的开源技术堆栈提供一个模型，可以被资源或技术专长有限的其他研究社区采用。所有数据将通过项目网站和相关的gdp免费提供给公众，包括但不限于MedicagoGenome （http://medicagogenome.org）、SoyBase （http://soybase.org）、PeanutBase （http://peanutbase.org）和豆类信息系统（http://legumeinfo.org）。

PI: David Fernandez-Baca (Iowa State University) CoPIs: Steven B. Cannon (USDA-ARS/Iowa State University), Christopher D. Town (J. Craig Venter Institute), Andrew D. Farmer (National Center for Genome Resources) and Jeremy DeBarry (University of Arizona). Senior Personnel: Ethalinda K.S. Cannon (Iowa State University) Legumes play a central role in food security and nearly every cropping system worldwide. Among cultivated plants, legumes such as beans, peas and lentils are unique in their ability to fix atmospheric nitrogen which is converted into a soluble organic form that can be taken up by plants through symbiosis with a soil bacterium. Approximately 33% of all nutritional nitrogen comes from legumes which are the most important source of protein in most developing countries. Genomic resources have been or are being developed for many legume crops, but the fragmented nature of these data resources limits the ability of researchers to leverage information generated in one species to infer function or identify candidate genes in another species. The overarching goal of this project is to address this deficiency by developing software and methods for a "Legume Federation" (LF) of diverse, independently funded and geographically separated genomic data portals (GDPs). The LF will facilitate utilization of genomic, genetic and phenotypic information across a wide range of legume species that will allow researchers and breeders to take full advantage of the data that are currently available at the GDPs. The project will provide research training opportunities for students from diverse backgrounds at different educational levels. In the context of outreach, the project will pro-actively engage the community of legume data providers through presentations and workshops at national and international meetings as well as through a central web portal that will provide information describing project goals, methods of implementation and progress reports to the community. The pace of data collection across crop and model plants has increased dramatically. Most crop species have both a data management problem and great opportunities to access genetic "big data". The objectives of this project are to develop a federation model for legume databases, to facilitate data exchange across a wide range of legume species to enable cross-species translational genomics, and to adapt an existing set of open-source tools for biological information management that will provide a framework for project-oriented data management enabling both long-term integration and widespread use. The specific goals are to: 1). Adopt and port the data currently managed in each of the custom frameworks into a set of well-integrated, open source model organism database tools;2). Define data formats, metadata standards, data exchange and Web service protocols to facilitate communications between species-centric databases at various levels; 3). Utilize orthology, synteny, and mappings of other significant features to integrate genetic, genomic, and phenotypic data across legume species, to enable identification of common molecular bases for important traits and enable traversal across database projects;4). Improve the capacity of organism database projects to collect and manage complex phenotype data using ontologies, controlled vocabularies and well-defined protocols and schemas; and, 5). Facilitate productive data exchange by implementing a common, open, virtualized Data Repository for data exchange across sites and for stable, long-term archiving of data sets, standardized metadata, and robust methods for archiving, searching, and accessing data sets from federated GDPs. It is anticipated that the LF will provide a model for a well-accepted open-source technology stack that can be adopted by other research communities that have limited resources or technical expertise. All data will be freely available to the general public through the project web site and through the associated GDPs that include but are not limited to MedicagoGenome (http://medicagogenome.org), SoyBase (http://soybase.org), PeanutBase (http://peanutbase.org), and the Legume Information System (http://legumeinfo.org).