Since 1999, The Arabidopsis Information Resource (www.arabidopsis.org) has been curating data about the Arabidopsis thaliana genome. Its primary focus is integrating experimental gene function information from the peer-reviewed literature and codifying it as controlled vocabulary annotations. Our goal is to produce a ‘gold standard’ functional annotation set that reflects the current state of knowledge about the Arabidopsis genome. At the same time, the resource serves as a nexus for community-based collaborations aimed at improving data quality, access and reuse. For the past decade, our work has been made possible by subscriptions from our global user base. This update covers our ongoing biocuration work, some of our modernization efforts that contribute to the first major infrastructure overhaul since 2011, the introduction of JBrowse2, and the resource’s role in community activities such as organizing the structural reannotation of the genome. For gene function assessment, we used Gene Ontology annotations as a metric to evaluate: (1) what is currently known about Arabidopsis gene function, and (2) the set of ‘unknown’ genes. Currently, 74% of the proteome has been annotated to at least one Gene Ontology term. Of those loci, half have experimental support for at least one of the following aspects: molecular function, biological process, or cellular component. Our work sheds light on the genes for which we have not yet identified any published experimental data and have no functional annotation. Drawing attention to these unknown genes highlights knowledge gaps and potential sources of novel discoveries. Article Summary The Arabidopsis Information Resource (TAIR, www.arabidopsis.org) is a comprehensive website about Arabidopsis thaliana, a small plant that’s very easy to grow and analyze in the laboratory and is used to understand how many other plants function. We share our progress in data collection and organization, website and tool improvement, and our involvement in community projects.

The Arabidopsis Information Resource in 2024

Over the last several decades, there has been rapid growth in the number and scope of agricultural genetics, genomics and breeding (GGB) databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, conducted a survey to assess the status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data sharing practices by AgBioData databases are in a healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that ontology use has not substantially changed since a similar survey was conducted in 2017. We recommend 1) providing training for database personnel in specific data sharing techniques, as well as in ontology use; 2) further study on what metadata is shared, and how well it is shared among databases; 3) promoting an understanding of data sharing and ontologies in the stakeholder community; 4) improving data sharing and ontologies for specific phenotypic data types and formats; and 5) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means.

pdf/data-sharing-and-ontology-use-among-agricultural-genetics-3x3pz453.pdf

Data sharing and ontology use among agricultural genetics, genomics, and breeding databases and resources of the AgBioData Consortium

The GFF3 format is a common, flexible tab-delimited format representing the structure and function of genes or other mapped features (https://github.com/The-SequenceOntology/Specifications/blob/master/gff3.md). However, with increasing re-use of annotation data, this flexibility has become an obstacle for standardized downstream processing. Common software packages that export annotations in GFF3 format model the same data and metadata in different notations, which puts the burden on end-users to interpret the data model. The AgBioData consortium is a group of genomics, genetics and breeding databases and partners working towards shared practices and standards. Providing concrete guidelines for generating GFF3, and creating a standard representation of the most common biological data types would provide a major increase in efficiency for AgBioData databases and the genomics research community that use the GFF3 format in their daily operations. The AgBioData GFF3 working group has developed recommendations to solve common problems in the GFF3 format. We suggest improvements for each of the GFF3 fields, as well as the special cases of modeling functional annotations, and standard protein-coding genes. We welcome further discussion of these recommendations. We request the genomics and bioinformatics community to utilize the github repository (https://github.com/NALi5K/AgBioData_GFF3_recommendation) to provide feedback via issues or pull requests.

pdf/recommendations-for-extending-the-gff3-specification-for-1vv8d12q.pdf

Recommendations for extending the GFF3 specification for improved interoperability of genomic data

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Recommendations for extending the GFF3 specification for improved interoperability of genomic data