ArticleBMC plant biology2026
GWAS and genomic prediction for resistance to soybean mosaic virus strain SC7.
Article in BMC plant biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND SOYBEAN MOSAIC VIRUS (SMV): Represents one of the most prevalent and destructive diseases affecting major soybean-producing regions, significantly impacting both soybean yield and quality. This study aimed to investigate the variation in soybean resistance to the SMV SC7 strain, identify the associated resistance loci, and predict potential candidate genes.
resultsThe study investigated a collection of 290 soybean germplasm materials, distinguished by their extensive genetic diversity. Inoculation with the SMV SC7 strain for resistance identification revealed that 18.2% of the materials exhibited high resistance (HR), while 6.8% displayed high susceptibility (HS). Based on four models for GWAS analysis, five significant single nucleotide polymorphisms (SNPs) associated with SMV resistance were identified on chromosomes 11, 13(two SNPs), 16, and 17. Two known resistance loci reconfirmed on chromosome 13. Furthermore, the loci Chr11_27826328, Chr16_34392503, and Chr17_18822285 were located on chromosomes 11, 16, and 17, respectively. A candidate gene related to SMV resistance, Glyma.16g182700, has been identified on chromosome 16. Haplotype analysis of this gene demonstrated significant differences in SMV resistance between materials containing Hap1 and those possessing Hap2. Compared to random SNPs, the 100 GWAS-significant markers yielded higher genomic prediction accuracy. And a plateau in accuracy was reached at approximately 6000 markers.
conclusionsThis study reveals the genetic architecture underlying soybean resistance to the SMV SC7 strain, identifies a key candidate gene, and enhances the accuracy of GS by incorporating significant SNPs. These findings provide valuable resources for marker-assisted selection and the genetic improvement of SMV-resistant soybean varieties.
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