Plant metabolites are important traits for plant breeders seeking to improve nutrition and agronomic performance yet integrating selection for metabolomic traits can be limited by phenotyping expense and degree of genetic characterization, especially of uncommon metabolites. As such, developing generalizable genomic selection methods based on biochemical pathway biology for metabolites that are transferable across plant populations would benefit plant breeding programs. We tested genomic prediction accuracy for >600 metabolites measured by gas chromatography–mass spectrometry (GC-MS) and liquid chromatography–mass spectrometry (LC-MS) in oat (Avena sativa L.) seed. Using a discovery germplasm panel, we conducted metabolite genome-wide association study (mGWAS) and selected loci to use in multikernel models that encompassed metabolome-wide mGWAS results or mGWAS from specific metabolite structures or biosynthetic pathways. Metabolite kernels developed from LC-MS metabolites in the discovery panel improved prediction accuracy of LC-MS metabolite traits in the validation panel consisting of more advanced breeding lines. No approach, however, improved prediction accuracy for GC-MS metabolites. We ranked model performance by metabolite and found that metabolites with similar polarity had consistent rankings of models. Overall, testing biological rationales for developing kernels for genomic prediction across populations contributes to developing frameworks for plant breeding for metabolite traits.
|State||Published - Jun 2022|
Bibliographical noteFunding Information:
Corey D. Broeckling conducted the metabolomics extraction, measurement, and data processing at the Bioanalysis and Omics Center of the Analytical Resources Core at Colorado State University (Fort Collins, CO USA). Funding for this research was provided by the USDA - National Institute of Food and Agriculture - Agriculture and Food Research Initiative (USDA NIFA-AFRI) grant (2017-67007-26502), and the USDA Agricultural Research Service Project Number 8062-21000-045-000-D.
Corey D. Broeckling conducted the metabolomics extraction, measurement, and data processing at the Bioanalysis and Omics Center of the Analytical Resources Core at Colorado State University (Fort Collins, CO USA). Funding for this research was provided by the USDA ‐ National Institute of Food and Agriculture ‐ Agriculture and Food Research Initiative (USDA NIFA‐AFRI) grant (2017‐67007‐26502), and the USDA Agricultural Research Service Project Number 8062‐21000‐045‐000‐D.
© 2022 The Authors. The Plant Genome published by Wiley Periodicals LLC on behalf of Crop Science Society of America.
ASJC Scopus subject areas
- Agronomy and Crop Science
- Plant Science