review · Database
Expanding genotype and phenotype datasets are crucial for identifying genetic markers, understanding gene function, and advancing crop breeding for agricultural sustainability. However, integrating disparate data from diverse sources remains a primary obstacle to effective use. A working group formed under the AgBioData Consortium reviewed existing repositories, databases, metadata annotations, and tools supporting plant genomic research between 2021 and 2022. The review identified key challenges across data archiving, analysis, and visualization. To address these gaps, the initiative recommends developing standardised community formats for metadata and data annotation, securing dedicated resources for biocuration, and expanding infrastructural support. Furthermore, new analytical and visual tools are needed to link genotype and phenotype data directly. These improvements aim to support knowledge synthesis and translational research across plant genomics, with relevant parallels likely extending to livestock and animal research.
Modern agricultural research relies on massive genetic and physical datasets to improve crops and protect food security. Without unified standards and tools to connect diverse databases, valuable research remains fragmented. Standardising these data systems enables scientists to more easily identify beneficial plant traits, share findings globally, and translate basic genetic discoveries into resilient, higher-yielding crops.
This work represents foundational data infrastructure and standards development rather than a commercial product. If adopted, standardised repositories and integration tools could support commercial crop breeders and agricultural biotechnology firms in accelerating genomic selection and trait discovery. However, the work currently outlines early-stage community recommendations, meaning functional commercial tools or standardised data services remain dependent on further collaborative software development and implementation.
AI-generated from the published abstract. Always read the original work before citing.
Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.1093/database/baad088
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.
