Location: Plant, Soil and Nutrition Research
Title: GramenePlants: Advancing Plant Pan-Genome Resources for an AI-Ready FutureAuthor
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Gladman, Nicholas |
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OLSON, ANDREW - Cold Spring Harbor Laboratory |
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KUMARI, SUNITA - Cold Spring Harbor Laboratory |
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WEI, XUEHONG - Cold Spring Harbor Laboratory |
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CHOUGULE, KAPEEL - Cold Spring Harbor Laboratory |
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LU, ZHENYUAN - Cold Spring Harbor Laboratory |
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VAN BUREN, PETER - Cold Spring Harbor Laboratory |
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OLSON, AUDRA - Cold Spring Harbor Laboratory |
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KIM, SUYUN - Cold Spring Harbor Laboratory |
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Ware, Doreen |
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BRAYNEN, JANEEN - Cold Spring Harbor Laboratory |
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Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 6/15/2026 Publication Date: 6/15/2026 Citation: Gladman, N.P., Olson, A., Kumari, S., Wei, X., Chougule, K., Lu, Z., Van Buren, P., Olson, A., Kim, S., Ware, D., Braynen, J. 2026. GramenePlants: Advancing Plant Pan-Genome Resources for an AI-Ready Future. Meeting Abstract. National Association for Plant Breeding (NAPB) annual meeting. Interpretive Summary: Technical Abstract: Since 2001, Gramene has supported comparative plant genomics, genetics, breeding, and evolution. With a global user base, it provides integrated access to genome annotations, variation, pathways, regulatory networks, and expression data across coordinated platforms. Rebranded as GramenePlants, Release 69 includes 233 reference genomes, curated pathways for 139 species, and extensive variation data. Recent updates add expression visualization tools, a literature-curated gene function catalog, and large-scale phenomics data for trait discovery. The enhanced Germplasm tab links loss-of-function alleles to public germplasm repositories. Crop pan-genome resources—including GrameneMaize, GrameneOryza, GrameneGrapevine, and SorghumBase—enable exploration of structural and presence/absence variation. Integration of standard SNP identifiers (rsIDs) and collaborations with the US National Plant Germplasm System (NPGS) and Breeding Insight have created useful database resources as well as community products in addition to enhancing reproducibility and alignment with FAIR data principles. Looking forward, Gramene supports the community through FAIR data training and by developing next-generation AI tools, including a Model Context Protocol (MCP) server to make integrated gene search data accessible to AI agents. A core strategic priority is making all integrated data ‘AI-ready’ to empower researchers and breeders to leverage advanced analytics for predictive biology. Together, GramenePlants and its crop-specific portals provide a scalable, community-driven infrastructure for advancing plant genomics research into the era of artificial intelligence. |
