Integrating Linkage Mapping and GWAS Reveals Novel Genetic Architecture of Seed Weight in Soybean (Glycine max L.)

Chunlei Zhang¹Huilong Hong²Rongqiang Yuan¹Kezhen Zhao¹Bire Zha¹Sobhi F Lamlom^1,3Xiaoyu Xi¹Honglei Ren^1*Qiu Lijuan²Jiajun Wang¹

• ¹Soybean Research Institute, Heilongjiang Academy of Agricultural Sciences, Harbin, China
• ²Chinese Academy of Agricultural Sciences Institute of Crop Sciences, Beijing, China
• ³Alexandria University Faculty of Agriculture Sababasha, Alexandria, Egypt

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 F₂:₅ lines from Qihuang 34 × Dongsheng 16 was phenotyped across three environments and genotyped using SLAF-seq, generating a high-density genetic map with 6,297 SNP markers spanning 2,945.26 cM (0.47 cM resolution). Simultaneously, 348 diverse soybean accessions underwent whole-genome resequencing (10× coverage), yielding 1,882,531 SNPs for association analysis across two years. 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 qHSW-19-4 (44.84-44.85 Mb, LOD = 9.72) demonstrated unprecedented 11.4 kb mapping precision. GWAS independently detected six genome-wide significant associations (P < 1 × 10⁻⁸), including a stable chromosome 19 peak at 45.28 Mb (P = 2.06 × 10⁻²³) explaining 15.3-18.7% of variance. Remarkably, this GWAS signal co-localized within 580 kb of qHSW-19-4, providing robust cross-population validation of chromosome 19 as a major seed weight regulatory region. Functional analysis of 44 candidate genes, validated by quantitative RT-PCR across seed developmental stages, identified four high-priority candidates: Glyma.19G195400 (cell wall invertase, 2.7-fold upregulation in large-seeded parent, r = 0.68 with HSW), Glyma.19G194300 (PEBP/Dt1 family protein), Glyma.19G193400 (bZIP transcription factor), and Glyma.06G095100 (Myb DNA-binding domain). 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.