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The variety and quantity of data being produced by biological research has grown dramatically in recent years, resulting in an expansion of our understanding of biological systems. However, this abundance of data has brought new challenges, especially in curation. The role of biocurators is in part to filter research outcomes as they are generated, not only so that information is formatted and consolidated into locations that can provide long-term data sustainability, but also to ensure that the relevant data that was captured is reliable, reusable, and accessible. In many ways, biocuration lies somewhere between an art and a science. At GrainGenes ( https://wheat.pw.usda.gov;https://graingenes.org ), a long-time, stably-funded centralized repository for data about wheat, barley, rye, oat, and other small grains, curators have implemented a workflow for locating, parsing, and uploading new data so that the most important, peer-reviewed, high-quality research is available to users as quickly as possible with rich links to past research outcomes. In this report, we illustrate the principles and practical considerations of curation that we follow at GrainGenes with three case studies for curating a gene, a quantitative trait locus (QTL), and genomic elements. These examples demonstrate how our work allows users, i.e., small grains geneticists and breeders, to harness high-quality small grains data at GrainGenes to help them develop plants with enhanced agronomic traits.

GrainGenes (https://wheat.pw.usda.gov or https://graingenes.org) is an international centralized repository for curated, peer-reviewed datasets useful to researchers working on wheat, barley, rye and oat. GrainGenes manages genomic, genetic, germplasm and phenotypic datasets through a dynamically generated web interface for facilitated data discovery. Since 1992, GrainGenes has served geneticists and breeders in both the public and private sectors on six continents. Recently, several new datasets were curated into the database along with new tools for analysis. The GrainGenes homepage was enhanced by making it more visually intuitive and by adding links to commonly used pages. Several genome assemblies and genomic tracks are displayed through the genome browsers at GrainGenes, including the Triticum aestivum (bread wheat) cv. ‘Chinese Spring’ IWGSC RefSeq v1.0 genome assembly, the Aegilops tauschii (D genome progenitor) Aet v4.0 genome assembly, the Triticum turgidum ssp. dicoccoides (wild emmer wheat) cv. ‘Zavitan’ WEWSeq v.1.0 genome assembly, a T. aestivum (bread wheat) pangenome, the Hordeum vulgare (barley) cv. ‘Morex’ IBSC genome assembly, the Secale cereale (rye) select ‘Lo7’ assembly, a partial hexaploid Avena sativa (oat) assembly and the Triticum durum cv. ‘Svevo’ (durum wheat) RefSeq Release 1.0 assembly. New genetic maps and markers were added and can be displayed through CMAP. Quantitative trait loci, genetic maps and genes from the Wheat Gene Catalogue are indexed and linked through the Wheat Information System (WheatIS) portal. Training videos were created to help users query and reach the data they need. GSP (Genome Specific Primers) and PIECE2 (Plant Intron Exon Comparison and Evolution) tools were implemented and are available to use. As more small grains reference sequences become available, GrainGenes will play an increasingly vital role in helping researchers improve crops.

The Triticeae Toolbox (; T3) is the database schema enabling plant breeders and researchers to combine, visualize, and interrogate the wealth of phenotype and genotype data generated by the Triticeae Coordinated Agricultural Project (TCAP). T3 enables users to define specific data sets for download in formats compatible with the external tools TASSEL, Flapjack, and R; or to use by software residing on the T3 server for operations such as Genome Wide Association and Genomic Prediction. New T3 tools to assist plant breeders include a Selection Index Generator, analytical tools to compare phenotype trials using common or user-defined indices, and a histogram generator for nursery reports, with applications using the Android OS, and a Field Plot Layout Designer in development. Researchers using T3 will soon enjoy the ability to design training sets, define core germplasm sets, and perform multivariate analysis. An increased collaboration with GrainGenes and integration with the small grains reference sequence resources will place T3 in a pivotal role for on-the-fly data analysis, with instant access to the knowledge databases for wheat and barley. T3 software is available under the GNU General Public License and is freely downloadable.

For functional genomics studies, it is important to understand the dynamic expression profiles of transcribed genes in different tissues, stages of development and in response to environmental stimuli. The proliferation in the use of next-generation sequencing technologies by the plant research community has led to the accumulation of large volumes of expression data. However, analysis of these datasets is complicated by the frequent occurrence of polyploidy among economically-important crop species. In addition, processing and analyzing such large volumes of sequence data is a technical and time-consuming task, limiting their application in functional genomics studies, particularly for smaller laboratories which lack access to high-powered computing infrastructure. Wheat is a good example of a young polyploid species with three similar genomes (97 % identical among homoeologous genes), rapidly accumulating RNA-seq datasets and a large research community. We present WheatExp, an expression database and visualization tool to analyze and compare homoeologue-specific transcript profiles across a broad range of tissues from different developmental stages in polyploid wheat. Beginning with publicly-available RNA-seq datasets, we developed a pipeline to distinguish between homoeologous transcripts from annotated genes in tetraploid and hexaploid wheat. Data from multiple studies is processed and compiled into a database which can be queried either by BLAST or by searching for a known gene of interest by name or functional domain. Expression data of multiple genes can be displayed side-by-side across all expression datasets providing immediate access to a comprehensive panel of expression data for specific subsets of wheat genes. The development of a publicly accessible expression database hosted on the GrainGenes website - http://wheat.pw.usda.gov/WheatExp/ - coupled with a simple and readily-comparable visualization tool will empower the wheat research community to use RNA-seq data and to perform functional analyses of target genes. The presented expression data is homoeologue-specific allowing for the analysis of relative contributions from each genome to the overall expression of a gene, a critical consideration for breeding applications. Our approach can be expanded to other polyploid species by adjusting sequence mapping parameters according to the specific divergence of their genomes.

GrainGenes (http://wheat.pw.usda.gov) is an international database for genetic and genomic information about Triticeae species (wheat [Triticum aestivum], barley [Hordeum vulgare], rye [Secale cereale], and their wild relatives) and oat (Avena sativa) and its wild relatives. A major strength of the GrainGenes project is the interaction of the curators with database users in the research community, placing GrainGenes as both a data repository and information hub. The primary intensively curated data classes are genetic and physical maps, probes used for mapping, classical genes, quantitative trait loci, and contact information for Triticeae and oat scientists. Curation of these classes involves important contributions from the GrainGenes community, both as primary data sources and reviewers of published data. Other partially automated data classes include literature references, sequences, and links to other databases. Beyond the GrainGenes database per se, the Web site incorporates other more specific databases, informational topics, and downloadable files. For example, unique BLAST datasets of sequences applicable to Triticeae research include mapped wheat expressed sequence tags, expressed sequence tag-derived simple sequence repeats, and repetitive sequences. In 2004, the GrainGenes project migrated from the AceDB database and separate Web site to an integrated relational database and Internet resource, a major step forward in database delivery. The process of this migration and its impacts on database curation and maintenance are described, and a perspective on how a genomic database can expedite research and crop improvement is provided.