# Deciphering Pesticide Stress Responses in Rice Through Integrated Multi-Omic Assessment

## TL;DR

This paper reviews how multi-omic technologies help understand rice's response to pesticide stress and suggests ways to improve rice resilience.

## Contribution

The paper provides a comprehensive synthesis of rice-specific omic evidence related to pesticide stress responses.

## Key findings

- Omic studies reveal pesticide-induced activation of detoxification enzymes and transporters in rice.
- Multi-omic integration helps connect gene regulation, protein activity, and metabolic changes under pesticide stress.
- Challenges remain in interpreting complex datasets and translating findings to real agricultural settings.

## Abstract

Pesticides are widely used in rice cultivation for pest control to guarantee crop productivity. Intensive use of these chemicals causes harmful effects on rice plants, such as physiological and biochemical stress responses. Such stress is often expressed as oxidative damage, disruption of metabolic balance, and a reduction in plant resilience to environmental challenges. In recent years, omic technologies (such as transcriptomics, epigenomics, proteomics, and metabolomics) have contributed to identifying molecular pathways affected by pesticide exposure. However, no comprehensive synthesis of rice-specific omic evidence currently exists, limiting translational applications. These omic studies revealed activation of detoxification-related enzymes and transporters, alongside changes in antioxidant defenses, hormone-mediated signaling, and membrane remodeling. This review presents current omic-based approaches used to investigate pesticide-induced stress in rice. It focuses on molecular responses including changes in gene expression, enzymatic detoxification, metabolic reprogramming, and stress signaling pathways. The review also highlights how multi-omic integration can contribute to a more holistic understanding of these stress responses, combining cross-layer evidence that connects gene regulation, protein activity, and metabolic remodeling. Despite these advancements, there are still challenges, particularly in the interpretation of complex datasets, the integration of multiple omic layers and the translation of results to real agricultural conditions. Finally, the review also discusses biotechnological approaches that may improve rice tolerance to pesticide exposure. In summary, the role of omic approaches to elucidate pesticide toxicity in rice and to contribute to more resilient crop production systems is critically reviewed.