Federated Plant Database Initiative for the Legumes

PI：David Fernandez-Baca(爱荷华州立大学)Copis：Steven B.Cannon(美国农业部-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：爱荷华州立大学Ethalinda K.S.Canon(爱荷华州立大学)豆类在全球粮食安全和几乎所有种植制度中发挥着核心作用。在种植的植物中，豆类，如豌豆和小扁豆，其独特的能力是固定大气中的氮，这些氮被转化为一种可溶的有机形式，植物可以通过与土壤细菌的共生来吸收。大约33%的营养氮来自豆类，这是大多数发展中国家最重要的蛋白质来源。已经或正在为许多豆科作物开发基因组资源，但这些数据资源的碎片化性质限制了研究人员利用一个物种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开发软件和方法来解决这一不足，该“豆类联盟”由不同的、独立资助的和地理上分离的基因组数据门户(GDP)组成。LF将促进广泛豆科物种的基因组、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GDPS目前可用的数据。该项目将为不同教育水平的不同背景的学生提供研究培训机会。在外联方面，该项目将通过在国家和国际会议上进行介绍和举办讲习班，以及通过一个中央门户网站主动与豆类数据提供者社区接触，该门户网站将向社区提供描述项目目标、实施方法和进展报告的信息。在作物和模式植物之间收集数据的速度大大加快。大多数作物物种既有数据管理问题，又有获取遗传“大数据”的巨大机会。该项目的目标是开发豆类数据库的联邦模式，促进广泛的豆类物种之间的数据交换，以实现跨物种的翻译基因组学，并调整现有的一套用于生物信息管理的开放源码工具，这将为面向项目的数据管理提供一个框架，使其能够长期整合和广泛使用。具体目标是：1)。采用和移植目前在每个定制框架中管理的数据到一套集成良好的、开源的有机体模型数据库工具中；2)。定义数据格式、元数据标准、数据交换和网络服务协议，以促进各级以物种为中心的数据库之间的通信；3)利用正交学、共性和其他重要特征的映射来整合豆科物种的遗传、基因组和表型数据，以便能够识别重要性状的共同分子基础，并能够遍历数据库项目；4)提高生物体数据库项目使用本体、受控词汇和明确定义的协议和模式收集和管理复杂表型数据的能力；以及，5)。通过实施通用、开放、虚拟的数据存储库来实现跨站点的数据交换、稳定、长期的数据集归档、标准化的元数据以及用于归档、搜索和访问联合GDP中的数据集的可靠方法，从而促进高效的数据交换。预计LF将为资源或技术专长有限的其他研究界提供一个被广泛接受的开放源码技术堆栈的模式。所有数据将通过项目网站和相关的GDP免费向公众提供，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).