Comparative Analysis of GWAS Models for Cation Exchange Capacity in Oat (Avena sativa L.)

Cation exchange capacity (CEC) is an important trait related to soil fertility and nutrient retention used for breeding in agricultural forage crops. However, its genetic background in oat (Avena sativa L.) remains poorly understood. In this study, four genome-wide association study (GWAS) models—Mixed Linear Model (MLM), FarmCPU, BLINK, and BayesCπ—were considered to identify SNPs associated with CEC based on publicly available genotypic and phenotypic data. Principal component analysis (PCA) was performed to account for population structure, and the models were compared in terms of the number of significant SNPs, their overlap, and visualizations (Manhattan and QQ plots). The results showed that FarmCPU provided the highest detection power, MLM the highest stringency, BLINK demonstrated the highest analysis speed, and BayesCπ allowed to accurately estimate SNP effects and explained variance. The obtained results provide a comparative view of the performance of GWAS models in studying complex agronomic traits and confirm the need to select the method for specific breeding tasks of oats and other agricultural plants in general.