Federated Plant Database Initiative for the Legumes

Iowa State University, Ames IA

Investigators

Abstract

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).