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S. Abugalieva

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Open access Sep 2026

Multi-Season Multi-Model GWAS Prioritizes Stable Genomic Loci and Candidate Genes for Six Agronomic Traits in Soybean Under Conditions in Southeastern Kazakhstan

Reliable identification of genomic regions controlling complex agronomic traits across variable growing seasons remains a major challenge in soybean genetics and breeding. Here, a diverse panel of 252 soybean accessions was evaluated over six consecutive growing seasons (2018–2023) for flowering time, maturity, plant height, number of seeds per plant, seed yield per plant, and thousand-seed weight. Whole-genome resequencing and variant filtering yielded 2,019,772 high-quality SNPs, and association signals were evaluated using Inclusive Integrative Input Multiple-locus Random-SNP-effect Mixed Linear Model (IIIVmrMLM), Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK), and Multi-Locus Mixed Model (MLMM) together with linkage disequilibrium (LD)-based locus consolidation. Cross-model prioritization retained 21 high-confidence loci supported by all three GWAS models and distributed across 10 chromosomes. Among the identified loci, 18 overlapped or co-localized with previously reported SoyBase genes and QTLs, whereas three (q.VER2.13-1, q.YP.01-1, and q.TSW.15-1) showed no positional overlap with known genes and QTLs and were therefore considered presumably novel. These three loci were associated with flowering time, yield per plant, and thousand-seed weight, accounting for 1.60%, 2.13%, and 5.53% of phenotypic variation, respectively. Ten loci co-localized with genomic regions containing established soybean regulators, including E2, E3, GmDt2, and POWR1, support the biological plausibility of the association results. Integration of genomic position, functional annotation, and tissue-expression evidence prioritized 112 candidate genes across 18 loci. These findings provide a focused set of genomic loci and candidate genes for independent validation and further investigation of the genetic basis of soybean adaptation and yield formation under variable continental growing conditions.

A. Zatybekov, Y. Genievskaya, C. Fang et al. · Plants · 0 citations

Open access Aug 2026

Genome-Wide Characterization of Genetic Diversity and Population Structure in a Kazakhstani Two-Row Spring Barley Breeding Panel

Barley (Hordeum vulgare L.) is a major cereal in Kazakhstan, where diverse breeding material supports crop improvement. We characterized 86 two-row spring barley accessions from six breeding organizations using the Illumina Infinium 50K Barley SNP Array. Analysis of 29,920 high-quality SNPs revealed moderate diversity (He = 0.346, PIC = 0.278, Shannon = 0.752), with 80.84% of molecular variation occurring within and 19.16% among breeding organizations. A minor allele frequency-free (MAF-free) analysis showed that 95.61% of marker–allele combinations at polymorphic loci were shared by at least two organizations. Although PCA, kinship, and neighbor-joining analyses indicated extensive overlap, discriminant analysis of principal components (DAPC) cluster membership was significantly associated with breeding origin (χ2 = 106.38, Monte Carlo p = 1 × 10–5; bias-corrected Cramér’s V = 0.513), demonstrating substantial but incomplete differentiation among breeding programs. Phenotypic differentiation was evaluated using environment-adjusted genotype BLUPs. All seven traits differed significantly among five DAPC clusters. In a reduced six-trait linear discriminant analysis (LDA) excluding vegetation period, LD1 was associated most strongly with number of kernels per spike, followed by heading time, spike length, and heading-to-maturity time. Leave-one-out cross-validation (LOOCV) accuracy was 36.47%, exceeding the permutation mean of 19.83% but indicating considerable phenotypic overlap. The examined materials therefore constitute a diverse, interconnected breeding panel that may support germplasm management and parent selection and provide a genomic and phenotypic framework for future GWAS, genomic selection, and targeted validation of molecular markers within the represented collections.

Y. Genievskaya, V. Chudinov, G. Sereda et al. · International Journal of Mol... · 0 citations