A Multi-OmicApproach to Reveal the Effect of Low-Level Gamma Radiation on Rice Seeds

Significance of the Topic

The exposure of rice seeds to low-level gamma radiation poses potential risks to agricultural productivity and food safety. A multi-omic approach combining transcriptome and metabolome analysis allows for comprehensive characterization of biological responses at molecular levels. Such insights are critical for developing biomarkers of radiation exposure and enhancing crop resilience under environmental stress.

Objectives and Study Overview

The study aimed to:

• Assess the molecular effects of chronic low-level gamma radiation on rice seeds from a contaminated field in Fukushima Prefecture
• Integrate transcriptomic and metabolomic datasets to identify overlapping stress-response pathways
• Validate key gene expression changes using quantitative RT-PCR

Methodology and Instrumentation

Rice seeds from contaminated and control sites were processed for parallel omics analyses.
Methodology steps included:

• RNA extraction via CTAB/phenol–chloroform and column kit, quality assessed on Agilent 2100 Bioanalyzer
• Transcript profiling using Agilent 4×44k microarrays, data analysis in GeneSpring 13.1 with moderated t-test and pathway mapping
• Metabolite extraction by chloroform:methanol:water biphasic method, derivatization with d27 myristic acid
• GC/Q-TOF analysis on Agilent 7200 series and Fiehn GC/MS library matching in MassHunter Unknown Analysis
• LC/Q-TOF analysis using Agilent 1290 Infinity coupled to 6550 Q-TOF, data processed with MassHunter Profinder and GeneSpring MPP
• qRT-PCR validation on Agilent Real Time PCR System

Key Results and Discussion

A total of 2,331 genes and 383 metabolites were significantly altered under radiation exposure. Combined multi-omic analysis revealed:

• Enrichment of phenylpropanoid biosynthesis, fatty acid metabolism, antioxidant defense, carbon fixation and glutathione pathways
• Reciprocal regulation in upstream and downstream pathway entities, exemplified by down-regulation of L-arginine and L-methionine versus up-regulation of D-proline, L-alanine and raffinose
• Consistent gene–metabolite signatures indicating coordinated stress response mechanisms

Benefits and Practical Applications

• Identification of potential radio markers for monitoring seed exposure to ionizing radiation
• Enhanced understanding of plant defense strategies against environmental stressors
• Framework for integrating multi-omic platforms in agricultural research and quality control

Future Trends and Potential Applications

Continued development of integrated omic workflows and advanced bioinformatics will enable:

• Discovery of robust biomarkers for crop health and environmental monitoring
• Application of machine learning to predict stress resilience traits
• Extension of multi-omic analyses to other plant species and stress conditions for precision agriculture

Conclusion

This multi-omic investigation demonstrates that low-level gamma radiation induces a coordinated molecular defense in rice seeds. The combined transcriptomic and metabolomic profiling approach effectively elucidates stress response pathways and offers novel biomarkers for radiation exposure.

Reference

1. Hayashi G; et al. Unraveling low-level gamma radiation-responsive changes in expression of early and late genes in leaves of rice seedlings at Iitate village, Fukushima. Journal of Heredity. 2014;105:723–738.