Genetic Basis and Simulated Breeding Strategies for Enhancing Soybean Seed Protein Content Across Multiple Environments - Xu Sun; Bo Hu; Wen-Xia Li; Hai-Long Ning (Plants, 2025)
Soybeans are a primary source of plant-based protein, with seeds containing approximately 40% protein—a key quality trait. Selecting superior hybrid combinations and managing progeny effectively are crucial for developing high-protein soybean varieties. Using a recombinant inbred line population (RIL3613) derived from Dongnong L13 × Heihe 36 and its previously constructed high-density genetic linkage map, QTLs and QTL × environment interactions (QEIs) associated with seed protein content (SPC) were identified through the bi-parental population (BIP) model and multi-environment trials (MET) model in QTL IciMapping v4.2. Candidate genes were then predicted via sequence alignment and haplotype analysis between the parents. Finally, simulated breeding was conducted using the B4L function in the In Silico Breeding (ISB) module of the Blib platform to determine optimal breeding strategies across diverse environments. The analysis identified 19 QTLs associated with SPC and 97 QEIs linked to SPC. These QTLs collectively explained 84.442% of the phenotypic variance, with four QTLs exhibiting significant contributions. A key candidate gene, Glyma.12G231400, associated with soybean SPC, was predicted within the 38,995,090–39,293,825 bp interval on chromosome 12. Across 11 environments, three to six optimal breeding schemes were selected, all employing modified pedigree selection. These findings enhance our understanding of the genetic basis of soybean protein formation and provide technological support for molecular breeding for seed quality improvement.