Adoption of Standard Reference SNP Identifiers in Agricultural Genomics for Interoperability and Data Reuse

Agricultural research has long faced challenges with data sharing, often relying on informal networks and requiring significant effort to clean and harmonize data. This hampers collaboration and limits data reuse. While FAIR (Findable, Accessible, Interoperable, and Reusable) principles are widely adopted in biomedical research, their uptake in agricultural genomics has lagged. The AgBioData Standards for Genetic Variation Working Group aims to close this gap by promoting FAIR data practices. We surveyed current standards for managing agricultural genetic variation and recommend adopting reference SNP identifiers (rsIDs) as a key step. We present examples from crop research communities with varying data maturity, including those without reference assemblies. Milestones include introducing nearly 220 million rsIDs to Gramene and pangenome databases, projecting rsIDs from reference to pangenome varieties in sorghum and maize, and developing an agricultural FAIR guide for rsID adoption. Better coordination among data producers, repositories, and breeding platforms is essential to improve interoperability, consistency, and accelerate genetic variant discovery for crop trait improvement.

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Publication Details

Journal
Scientific Data
Published
2026-04-16
DOI
https://doi.org/10.1038/s41597-026-07208-0
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
0.00

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article

Adoption of Standard Reference SNP Identifiers in Agricultural Genomics for Interoperability and Data Reuse

Tao-Ho Chang, Nicholas P. Gladman, Sebastian Beier, Timothée Cezard et al.
Scientific Data
Research Data Management Practices
article

Adoption of Standard Reference SNP Identifiers in Agricultural Genomics for Interoperability and Data Reuse

Tao-Ho Chang, Nicholas P. Gladman, Sebastian Beier, Timothée Cezard, Jill M. Bushakra, Taner Z. Sen, Nahla Bassil, Sonia Balyan, Sharon Wei, Doreen Ware, Irene Cobo-Simón, Moira J. Sheehan, Raja Sekhar Nandety, Marcela K. Tello-Ruiz, Christine G. Elsik, Melanie Harrison, Jodi Humann, Rex Nelson, Vivek Kumar, Sarah Dyer, Carson Andorf, Catherine Kim, Andrew Olson, Kapeel Chogule
article en

Abstract

Agricultural research has long faced challenges with data sharing, often relying on informal networks and requiring significant effort to clean and harmonize data. This hampers collaboration and limits data reuse. While FAIR (Findable, Accessible, Interoperable, and Reusable) principles are widely adopted in biomedical research, their uptake in agricultural genomics has lagged. The AgBioData Standards for Genetic Variation Working Group aims to close this gap by promoting FAIR data practices. We surveyed current standards for managing agricultural genetic variation and recommend adopting reference SNP identifiers (rsIDs) as a key step. We present examples from crop research communities with varying data maturity, including those without reference assemblies. Milestones include introducing nearly 220 million rsIDs to Gramene and pangenome databases, projecting rsIDs from reference to pangenome varieties in sorghum and maize, and developing an agricultural FAIR guide for rsID adoption. Better coordination among data producers, repositories, and breeding platforms is essential to improve interoperability, consistency, and accelerate genetic variant discovery for crop trait improvement.

Scientific Data
European Bioinformatics Institute (GB), Agricultural Research Service (US), National Chung Hsing University (TW), Forschungszentrum Jülich (DE), Iowa State University (US), Cornell University (US), Cold Spring Harbor Laboratory (US), Regional Centre for Biotechnology (IN), Centro de Excelência em Bioinformática (BR), National Clonal Germplasm Repository (US), Institute of Flight (US), National Research Council (LK), Western Regional Research Center (US), Edward T. Schafer Agricultural Research Center (US), Washington State University (US), University of Missouri (US), Ithaca College (US)
National Science Foundation, Wellcome, European Bioinformatics Institute, Agricultural Research Service
Zero hunger
Openalex Percentile: Top 16%
Research Data Management Practices
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