Advancing Rice Resilience to Heat Stress: Insights from CRISPR/Cas9 Genome Editing
Year: 2026
Type: article
Abstract: Heat stress during reproductive stages remains one of the most critical constraints to rice yield and grain quality, yet progress in developing heat-resilient cultivars is slowed by the complex, polygenic nature of thermotolerance and lengthy breeding cycles. Despite incremental gains through conventional breeding, high temperatures above 35 °C continue to cause severe yield losses, spikelet sterility, and quality deterioration. The emergence of CRISPR/Cas genome editing offers a precise and efficient platform to dissect heat-stress mechanisms and accelerate the development of heat-tolerant rice. Recent CRISPR/Cas9 studies have validated and edited key genes involved in calcium signaling, hormone pathways, reproductive processes, photosynthesis, reactive oxygen species homeostasis, and transcriptional regulation, such as OsCNGC14/16 , OsNCED1 , OsSPL7 , and OsHSP60-3b . Beyond stress resilience, genome editing has improved major yield components, including grain size, panicle architecture, and spikelet number, through targets such as GS3, GW3 , Gn1a , and OsSPL16 , achieving 28%–40% increases in grain weight and 15%–25% improvements in panicle traits, alongside enhanced grain quality attributes. Remaining challenges, including off-target effects, genotype dependence, limited field validation, and regulatory constraints, are being addressed through high-fidelity Cas variants, optimized sgRNA design, DNA-free editing, and integration with genomic selection and speed breeding. This review synthesizes advances in heat-stress biology and CRISPR/Cas applications in rice, and highlights future opportunities in base and prime editing, transcriptional reprogramming, multiplex genome engineering, and field deployment.
Source: Rice Science
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
SDG: Zero hunger
Open Access status: diamond
Funder: Rural Development Administration
Award: G4833226102
OpenAlex ID: W7128923628
