Legume Genomics and Genetics 2026, Vol.17, No.1, 49-67 http://cropscipublisher.com/index.php/lgg 52 because of their high polymorphic information content, codominant inheritance, and relatively uniform distribution across the genome, enabling reliable assessment of relatedness, clustering of accessions, and alignment with pedigree information. More recently, high-density SNP genotyping and genotyping-by-sequencing platforms have allowed genome-wide diversity analysis in large panels, supporting robust population structure inference (STRUCTURE, PCA, PCoA, DAPC), AMOVA, and identification of genetically distinct or redundant accessions for breeding and conservation (Chander et al., 2021). 2.3 Progress in the application of SNP technology in soybean diversity research The application of SNP technology has markedly advanced the resolution and scale of soybean diversity and population structure studies. Genotyping-by-sequencing (GBS) and diversity array technology (DArTseq) have been used to generate tens of thousands of SNPs across the 20 soybean chromosomes, producing high-density datasets for panels ranging from fewer than 100 to several hundred accessions (Fu et al., 2021). These approaches have revealed that most genetic variation typically resides within rather than among soybean populations, even in regionally focused collections, and have enabled the detection of distinct genetic clusters associated with breeding histories, adaptation zones and, in some cases, seed quality traits such as seed longevity (Shaibu et al., 2021). GBS-based SNP datasets also feed into genome-wide association and QTL mapping efforts, linking diversity patterns to complex traits, while highlighting the potential of selected accessions as donors of favorable alleles. Parallel development of fixed SNP arrays and nested marker panels has further expanded SNP applications in germplasm research. Arrays such as Axiom® SoyaSNP, SoySNP50K, SoySNP6K, and higher-density platforms like SoySNP618K provide reproducible, genome-wide SNP coverage suitable for evaluating entire national and international collections, detecting redundant accessions, and constructing high-resolution haplotype maps (Zatybekov et al., 2025). Reduced, cost-effective panels (SoySNP3K, SoySNP1K, and targeted GBTS panels of 10–40K SNPs) are now widely used for routine germplasm characterization, diversity analysis, and parent selection in breeding programs (Song et al., 2024). Whole-genome resequencing of thousands of accessions has also yielded comprehensive SNP datasets that distinguish wild and cultivated gene pools, identify large-effect mutations in agronomically important genes, and support development of diagnostic marker sets tailored for germplasm evaluation and reverse genetics (Zatybekov et al., 2025). Collectively, these advances have made SNP technology the backbone of contemporary soybean diversity research, enabling integrative analyses that connect global germplasm structure with breeding history and future improvement strategies (Figure 1). Figure 1 Global soybean germplasm resources and diversity conservation
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