Marker-Assisted Identification of Quantitative Trait Loci (QTLs) Associated with Yield and Stress Tolerance in Rice

Abstract

Rice production must increase by 70–100% by 2050 to meet global food demands amid climate challenges and yield stagnation. This review synthesizes marker-assisted approaches for identifying quantitative trait loci (QTLs) governing grain yield and abiotic/biotic stress tolerance in rice (Oryza sativa L.). Key yield components panicle number, grains per panicle (GNPP), and thousand-grain weight (TGW) are dissected through biparental mapping, genome-wide association studies (GWAS), and meta-QTL analyses, revealing major loci such as GS3 (negative regulator of grain length), GW2 (ubiquitin ligase enhancing width/weight), and qPE9-1 (panicle architecture). For stress tolerance, prominent QTLs include qDTY1.1/qDTY2.1 (drought yield), Saltol (salinity tolerance via Na+ exclusion), Sub1 (submergence via ethylene signaling), and Pi-ta/Pi9 (blast resistance). Integration via marker-assisted selection (MAS) and backcrossing (MABC) has enabled pyramiding (e.g., Sub1 + Saltol), yielding resilient varieties with 20–50% improved performance under stress. High-density SNP markers and multi-parent populations (e.g., MAGIC) enhance precision, accelerating breeding cycles by 50%. This genomics-driven strategy offers a blueprint for sustainable rice improvement, mitigating environmental risks and boosting productivity in vulnerable agro-ecosystems.