Identification of Candidate Genes Related to SPAD Value Using Multi-Year Phenotypic Data in Rice Germplasms by Genome-Wide Association Study (GWAS)

This study aimed to identify candidate genes associated with chlorophyll content in rice via genome-wide association studies (GWAS) and to develop molecular markers for the selection of genetic resources and breeding lines exhibiting high chlorophyll content. Measurement of the Soil and Plant Analysis Development (SPAD) values, indicative of chlorophyll content and photosynthetic potential, were measured in 198 rice genetic resources across three years under consistent nitrogen conditions. Nitrogen fertilizer (as urea) was applied at a rate of 90 kg N ha−1. After analyzing the multi-year SPAD data, genetic resources with the coefficient of variation (CV) value exceeding 20% were excluded, and the remaining 175 accessions were used for subsequent analyses. Population structure analysis using the principal component analysis (PCA) and phylogenetic methods confirmed clear genetic differentiation, supporting the reliability of the GWAS. A GWAS using 289,569 SNPs identified 17 significant loci, among which four quantitative trait loci (QTLs)—qSV3-1, qSV3-2, qSV6, and qSV7—explained over 20% of phenotypic variance. Analysis of their additive effects revealed distinct SPAD distributions among QTL combination groups, with accessions harboring all four QTLs exhibiting the highest values. Candidate gene analysis within ± 200 kb of lead SNPs identified Os03g079100 (OsUCL8), involved in photosynthesis, near qSV3-2. A derived cleaved amplified polymorphic sequence (dCAPS) marker was developed to differentiate alleles at this locus and validated via restriction digestion. These results provide key genetic insights into chlorophyll accumulation and offer molecular markers for breeding high-yielding rice cultivars with enhanced chlorophyll content. The results of this study are expected to contribute to the development of sustainable rice varieties by utilizing the developed markers and identified candidate genes to increase SPAD values, thereby enhancing nitrogen use efficiency, improving photosynthetic capacity, and ultimately increasing rice productivity.