Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management

Area of Science:

• Agricultural Science
• Genetics
• Biotechnology

Background:

• Rice (Oryza sativa) is a vital global staple crop, essential for feeding nearly half the world's population.
• Abiotic and biotic stresses significantly threaten rice quality and yield, posing challenges to global food security.
• Improving rice is critical to meet the demands of an increasing world population.

Purpose of the Study:

• To review the application of multi-omics technologies in understanding and improving desirable rice traits.
• To provide an overview of omics applications for rice yield enhancement and stress management.
• To describe relevant data science databases for analyzing big data in rice research.

Main Methods:

• Comprehensive utilization of 'omics' techniques, including genomics, transcriptomics, proteomics, and metabolomics.
• Exploration of genetic resources for trait development through advanced omics platforms.
• Review of multi-omics technologies for basic and applied research in rice.

Main Results:

• Omics disciplines have significantly advanced the understanding of regulatory mechanisms and cellular processes in rice.
• These technologies facilitate the identification of genetic resources for improving rice traits under various conditions.
• Multi-omics approaches offer new strategies for enhancing rice yield and resilience to environmental stresses.

Conclusions:

• Multi-omics technologies provide a powerful framework for deciphering the complexities of rice genetics and physiology.
• The application of omics is essential for achieving desired improvements in rice traits, particularly yield and stress tolerance.
• Data science tools and databases are crucial for managing and analyzing the large datasets generated by omics studies in rice.