Lipidomics reveals associations between rice quality traits
College of Science
Introduction: Lipids are a diverse group of macromolecules that occur in rice grains and are known to impact rice grain properties. Identifying the relationships between specific lipids and traits of quality is important to improve varietal selection for high quality rice.
Objectives: Using untargeted lipidomics, this study aims to understand the role of lipids on different traits of quality by identifying the genotypic effect of lipids and their impact on traits of cooking and eating quality of a rice mapping population.
Methods: Lipids from milled rice grains of three sets of rice samples were screened by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) in the positive ionisation mode. Lipid features were putatively identified using analytical standards and online databases. Multivariate statistics were carried out to identify the lipid profile of varieties across three experiments. Correlation analysis was carried out between lipid features and 12 quality traits across a rice mapping population that segregates for grain physical and texture-associated traits.
Results: Thousands of features in rice grain lipids were detected, and were grouped into six categories—fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids and prenol lipids. A strong genotypic basis for the lipid profile was observed among the four varieties grown under five nitrogen treatments. Clear differentiation in lipid profiles between waxy and non-waxy rice was observed. Strong correlations were observed for putative lipids that form the amylose–lipid complex and with amylose content and viscosity parameters.
Conclusions: This study demonstrates the strength of untargeted lipidomics in putatively determining features that differentiate varieties from each other, and reveals the role of specific lipids on the physical and textural quality of rice.
Digitial Object Identifier (DOI)
Concepcion, J. T., Calingacion, M. N., Garson, M. J., & Fitzgerald, M. A. (2020). Lipidomics reveals associations between rice quality traits. Metabolomics, 16 (54), 1-16. https://doi.org/10.1007/s11306-020-01670-6