Location: Corn Insects and Crop Genetics Research
2018 Annual Report
Objectives
Objective 1: Accelerate maize trait analysis, germplasm analysis, genetic studies, and breeding through stewardship of maize genomes, genetic data, genotype data, and phenotype data.
Objective 2: Develop an infrastructure to curate, integrate, query, and visualize the genetic, genomic, and phenotypic relationships in maize germplasm.
Objective 3: Identify and curate key datasets for benchmarking genomic discovery tools for the functional annotation of maize genomes, for agronomic trait analyses, for breeding (including genome editing), and for improving database interoperability.
Objective 4: Provide community support services, training and documentation, meeting coordination, support for community elections and surveys, and support for the crop genome database community.
Objective 5: Collaborate with database developers and plant researchers to develop improved methods and mechanisms for open, standardized data and knowledge exchange to enhance database utility and interoperability.
Approach
The Maize Genetics and Genomics Database (MaizeGDB – http://www.maizegdb.org) is the model organism database for maize. MaizeGDB’s overall aim is to provide long-term storage, support, and stability to the maize research community’s data and to provide informatics services for access, integration, visualization, and knowledge discovery. The MaizeGDB website, database, and underlying resources allow plant researchers to understand basic plant biology, make genetic enhancement, facilitate breeding efforts, and translate those findings into products that increase crop quality and production. To accelerate research and breeding progress, generated data must be made freely and easily accessible. Curation of high-quality and high-impact datasets has been the foundation of the MaizeGDB project since its inception over 25 years ago. MaizeGDB serves as a two-way conduit for getting maize research data to and from our stakeholders. The maize research community uses data at MaizeGDB to facilitate their research, and in return, their published data gets curated at MaizeGDB. The information and data provided at MaizeGDB and facilitated through outreach has directly been used in research that has had broad commercial, social, and academic impacts. The MaizeGDB team will make accessible high-quality, actively curated and reliable genetic, genomic, and phenotypic description datasets. At the root of high-quality genome annotation lies well-supported assemblies and annotations. For this reason, we focus our efforts on benefitting researchers by developing a system to ensure long-term stewardship of both a representative reference genome sequence assembly with associated structural and functional annotations as well as additional reference-quality genomes that help represent the diversity of maize. In addition, we will enable researchers to access data in a customized and flexible manner by deploying tools that enable direct interaction with the MaizeGDB database. Continued efforts to engage in education, outreach, and organizational needs of the maize research community will involve the creation and deployment of video and one-on-one tutorials, updating maize Cooperators on developments of interest to the community, and supporting the information technology needs of the Maize Genetics Executive Committee and Annual Maize Genetics Conference Steering Committee.
Progress Report
ARS scientists working on the Maize Genetics and Genomics Database (MaizeGDB) in Ames, Iowa continue to provide tools and resources that make the maize genome sequence useful for investigative research and crop improvement. Genome sequences served include the latest version of the B73 representative genome, a long-established maize inbred line that was used as a founder of many public and private breeding programs, and 10 additional recently released maize genome assemblies. Genotype data for thousands of various other lines and individuals that represent the broad diversity represented by the Zea genus (i.e., maize and its near relatives) are also made available. MaizeGDB focuses on curating high-quality, high-impact data sets for the maize research community. The work accomplished during the first four months of the project plan was focused on developing plans, prioritizing curation and development efforts, and communicating future work with our stakeholders. Plans have been developed to: curate genotype by environment data, host additional maize genome assemblies, integrate genomics, genetics, and phenotype data, and update infrastructure for computation, storage, back-ups, and disaster recovery. MaizeGDB has updated the genome assembly/annotation status page to reflect which genomes are available and added text to encourage community-driven improvements to the assemblies and annotations. Work carried out by the MaizeGDB team has resulted in improved communication among maize researchers worldwide, increased ability to document the results of experiments, and increased availability of information relative to high impact research.
Accomplishments
1. MaizeGDB has improved tools and resources to support multiple maize genomes and to provide better access to data. In addition to the maize reference genome (B73), a long-established maize inbred line that was used as a founder of many public and private breeding programs, several additional reference-quality genomes are now available to the research community. ARS researchers and Iowa State University personnel from Ames, Iowa have continued to provide tools and resources to support these genome assemblies including ways to visually explore the genomes, search based on sequence similarity, visualize variation across lines, view pedigree information, integrate phenotype images, collect assembly and annotation errors, explore curated genomic and genetic data, and download standardized data. Recent focus on data curation has been to identify and curate key datasets for benchmarking genomic discovery tools for the functional annotation of maize genomes, for agronomic trait analyses, for breeding, and for improving database interoperability. The MaizeGDB resource provides long-term storage, support, and stability to the maize research community’s data and provides informatics services for access, integration, and knowledge discovery.
