# Resistance gene against Xanthomonas oryzae pv. Oryzae (Xoo) in rice: molecular mechanisms and breeding strategies for bacterial leaf blight

## TL;DR

This paper reviews resistance genes in rice against bacterial leaf blight and explores how AI can improve breeding for disease resistance.

## Contribution

The paper integrates recent findings on resistance genes with emerging AI technologies for rice breeding.

## Key findings

- Resistance genes in rice activate immune responses against Xoo through complex molecular mechanisms.
- AI technologies offer potential to accelerate breeding of BLB-resistant rice varieties.
- Traditional breeding methods face limitations in speed and efficiency compared to AI-driven approaches.

## Abstract

Bacterial leaf blight (BLB), caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most devastating diseases threatening global rice production. In recent decades, a range of disease resistance genes have been identified in rice. These genes are involved in complex molecular mechanisms, such as the activation of immune receptors and defense signaling pathways, which trigger the plant’s immune response to combat pathogen invasion. Some of these genes have been successfully applied in molecular breeding to develop new disease-resistant varieties. However, traditional breeding methods, which rely heavily on the experience and intuition of breeders, often face limitations in speed and efficiency. With the emergence of artificial intelligence (AI) technologies, there is growing interest in using them to accelerate the breeding of disease-resistant cultivars. This review summarizes the current understanding of the molecular mechanisms underlying BLB resistance, focusing on key resistance genes and their roles in defense responses. It also explores breeding strategies aimed at enhancing resistance and evaluates the opportunities and challenges of AI tools into rice disease resistance breeding.