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Obtaining High-Quality Transcriptome Data from Cereal Seeds by a Modified Method for Gene Expression Profiling
Published on: May 21, 2020
Genome-Wide Characterization of Genetic Diversity and Population Structure in a Kazakhstani Two-Row Spring Barley
Yuliya Genievskaya1, Vladimir Chudinov2, Grigoriy Sereda3
1Institute of Plant Biology and Biotechnology, Almaty 050040, Kazakhstan.
Abstract:
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.
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