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Quantitative trait loci (QTL) may explain only a small portion of the phenotypic variation of a trait, limiting their use in breeding programs. This study assessed the effectiveness of marker-assisted selection (MAS) in the F2 population under Asian soybean rust (ASR) pressure for identifying promising F2:5 progenies, even when QTL only explain a small proportion of the phenotypic variation. In addition, we identified SNPs which influence the predictive ability of genomic selection (GS) models to assess whether MAS may be a suitable approach for selecting superior progenies. Evaluated traits included seed yield (SY), days to maturity (DM), days to flowering (DF), plant height (PH), and 50-seed weight (50SW). QTL were identified via simple interval mapping, and genomic predictions were generated using G-BLUP. Models including SNPs associated with QTL on chromosomes 6 and 16 performed as well as or better than genome-wide SNP-based models, indicating that MAS may be a suitable approach. Chromosome 6 was more strongly associated with SY, DM, DF, and PH, while chromosome 16 was associated with 50SW. The CC (EMB-235706-CT on chromosome 6) and AA (EMB-227730-AG on chromosome 16) genotypes in the F2 population showed higher SY and 50SW in F2:5, along with reduced DM, DF, and PH, particularly in the presence of major-effect genomic regions, despite some QTL explaining less than 30% of phenotypic variation. These findings support the development of soybean cultivars with improved agronomic performance for managing ASR.
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Carvalho et al. (2026) studied this question.
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