ArticleFrontiers in plant science2025
Integrating linkage mapping and GWAS reveals novel genetic architecture of seed weight in soybean (
Article in Frontiers in plant science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Genome-wide signatures of selection and genetic diversity reveal the impact of modern breeding on Brazilian soybean.Molecular breeding : new strategies in plant improvement · 2026Article
- Integrative haplotype and SNP-based GWAS supports the identification of stable genomic loci controlling yield-related traits in soybean.Frontiers in plant science · 2026Article
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10 authors.
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Abstract
Objective: Seed weight is a key factor in soybean yield and value, but its genetic basis and environmental stability are not fully understood. Despite many QTL studies, there's a lack of integration between bi-parental linkage mapping and diverse germplasm association analysis. We hypothesized that combining high-resolution QTL mapping in recombinant inbred lines with GWAS in natural populations could identify both population-specific and broadly segregating seed weight loci, aiding in candidate gene discovery for breeding. Methods: We integrated biparental QTL mapping with genome-wide association studies (GWAS) to comprehensively dissect the genetics of hundred-seed weight (HSW). A recombinant inbred line population of 325 F Results: QTL mapping identified 11 significant loci explaining 2.47-8.59% of phenotypic variance, with broad-sense heritability of 0.78. The major-effect QTL Novelty and conclusions: This first integrated QTL-GWAS analysis for soybean seed weight reveals both major-effect loci and polygenic architecture, providing validated molecular markers and candidate genes for breeding programs targeting yield improvement.
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