ArticleInternational journal of molecular sciences2025
Genome-Wide Association Study and Genomic Prediction of Soybean Mosaic Virus Resistance.
Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- GWAS and genomic prediction for resistance to soybean mosaic virus strain SC7.BMC plant biology · 2026Article
- Dissection of local haplotype diversity at soybean rust loci reveals resistance-associated and context-dependent variation patterns in diverse germplasm.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- Molecular characterization and fertilizer optimization in soybean to maximize productivity and minimize environmental impact.Scientific reports · 2025Article
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Authors and funding
9 authors.
Funding
Abstract
Soybean mosaic virus (SMV), a pathogen responsible for inducing leaf mosaic or necrosis symptoms, significantly compromises soybean seed yield and quality. According to the classification system in the United States, SMV is categorized into seven distinct strains (G1 to G7). In this study, we performed a genome-wide association study (GWAS) in GAPIT3 using four analytical models (MLM, MLMM, FarmCPU, and BLINK) on 218 soybean accessions. We identified 22 SNPs significantly associated with G1 resistance across chromosomes 1, 2, 3, 12, 13, 17, and 18. Notably, a major quantitative trait locus (QTL) spanning 873 kb (29.85-30.73 Mb) on chromosome 13 exhibited strong association with SMV G1 resistance, including the four key SNP markers: Gm13_29459954_ss715614803, Gm13_29751552_ss715614847, Gm13_30293949_ss715614951, and Gm13_30724301_ss715615024. Within this QTL, four candidate genes were identified:
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