Genome‐wide association and genomic prediction of anthracnose ( <i>Colletotrichum dematium</i> ) resistance in spinach

Anthracnose, caused by Colletotrichum dematium, has emerged as a major foliar disease that threatens spinach (Spinacia oleracea L.) production. In this study, a diverse panel of 266 accessions was evaluated under field conditions to dissect the genetic architecture of anthracnose resistance. Substantial phenotypic variation was observed, with disease severity indices (DSIs) ranging from 1 (highly resistant) to 10 (highly susceptible). A total of 20 accessions showed moderate to high resistance (DSI ≤ 4), representing valuable resistance sources. A genome-wide association study (GWAS) identified 20 significant single-nucleotide polymorphisms (SNPs). The most consistent marker (SOVchr3_19667279) explained up to 66.8% of phenotypic variance, and several associated SNPs were located within or near putative defense-related genes. Genomic prediction (GP) using multiple models demonstrated that predictive accuracy increased when a set with more SNPs was used. The genomic best linear unbiased prediction model achieved the highest accuracy (r = 0.92), while the Bayesian ridge regression model attained the best predictive accuracy (r = 0.51) when using 20 GWAS-derived SNPs, highlighting the value of integrating association mapping with prediction approaches. Cross-population prediction performed well (r = 0.58-0.71), whereas across-population prediction showed reduced accuracy (r = 0.10-0.14), indicating the influence of genetic background on model transferability. This integrative genomic study provides novel insights into the genetic basis of anthracnose resistance in spinach and demonstrates the potential of GWAS and GP in accelerating resistance breeding.