Zhao Tiantian, Wang Fengmin, Qi Jin, Chen Qiang, Zhu Lijuan, Liu Luping, Yan Long, Chen Yuling, Yang Chunyan, Qin Jun
Ministry of Education Key Laboratory of Molecular and Cellular Biology, Hebei Research Center of the Basic Discipline of Cell Biology, Hebei Collaboration Innovation Center for Cell Signaling and Environmental Adaptation, Hebei Key Laboratory of Molecular and Cellular Biology, College of Life Sciences, Hebei Normal University, Shijiazhuang, China.
Hebei Laboratory of Crop Genetics and Breeding, Huang-Huai-Hai Key Laboratory of Biology and Genetic Improvement of Soybean, Ministry of Agriculture and Rural Affairs, Institute of Cereal and Oil Crops, National Soybean Improvement Center Shijiazhuang Sub-Center, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, Hebei, China.
BMC Plant Biol. 2025 Jul 2;25(1):837. doi: 10.1186/s12870-025-06775-5.
Soybean (Glycine max (L.) Merr.), a global agricultural staple, faces significant threats from Soybean Mosaic Virus (SMV). Effective resistance to SMV, particularly the SC3 strain, is crucial for sustainable soybean production. This study aims to explore the genetic variability and identify loci associated with SMV SC3 resistance in soybean.
We assessed the resistance of 290 soybean accessions to the SMV SC3 strain, revealing considerable genetic variability: 19.9% exhibited high resistance, while 11.7% were highly susceptible. This diversity is a valuable asset for breeding programs targeting disease management. Deep sequencing and genome-wide association studies (GWAS) of the accession population structures identified five distinct clusters and 14 significant loci associated with resistance across chromosomes 2, 4, 7, 9, 13, 14, 17, 19, and 20. Notably, a known resistance locus on chromosome 13 and a novel locus on chromosome 4, Loci_04_7299944, were identified. The latter is linked to Glyma.04G086700, a gene encoding a leucine-rich repeat protein kinase integral to pathogen recognition and resistance, showing three distinct haplotypes correlated with varying resistance levels, governed by specific allelic variations at certain SNP sites. Our genomic prediction models demonstrated that expanding SNP feature sets generally improved prediction accuracy, especially with the Top 100 set, although adding more than 8000 SNPs introduced diminishing returns and potential noise. Fourteen effective SNP loci were identified as pivotal for accurately predicting the genetic architecture of complex traits related to SMV resistance.
Our findings underscore the importance of selecting SNPs closely linked to phenotypic traits to refine prediction accuracy in genomic selection models. The identified loci, particularly Glyma.04G086700, provide a foundation for further exploration of genetic mechanisms underlying SMV SC3 resistance. These insights can guide future enhancements in soybean breeding strategies to combat SMV effectively.
大豆（Glycine max (L.) Merr.）作为全球重要的农作物，面临着来自大豆花叶病毒（SMV）的重大威胁。对SMV，尤其是SC3株系的有效抗性，对大豆的可持续生产至关重要。本研究旨在探索大豆中与SMV SC3抗性相关的遗传变异性并鉴定相关位点。
我们评估了290份大豆种质对SMV SC3株系的抗性，发现存在显著的遗传变异性：19.9%表现出高抗性，而11.7%高度感病。这种多样性对于以病害管理为目标的育种计划来说是一项宝贵资产。对种质群体结构进行深度测序和全基因组关联研究（GWAS），确定了五个不同的聚类以及位于第2、4、7、9、13、14、17、19和20号染色体上与抗性相关的14个显著位点。值得注意的是，鉴定出了位于13号染色体上的一个已知抗性位点以及位于4号染色体上的一个新位点Loci_04_7299944。后者与Glyma.04G086700相关，该基因编码一种富含亮氨酸重复序列的蛋白激酶，对病原体识别和抗性至关重要，显示出三种不同的单倍型，与不同的抗性水平相关，由某些SNP位点的特定等位基因变异决定。我们的基因组预测模型表明，扩展SNP特征集通常会提高预测准确性，尤其是使用前100个SNP集时，不过添加超过8000个SNP会带来收益递减和潜在噪声。确定了14个有效的SNP位点对于准确预测与SMV抗性相关的复杂性状的遗传结构至关重要。
我们的研究结果强调了选择与表型性状紧密连锁的SNP以提高基因组选择模型预测准确性的重要性。鉴定出的位点，特别是Glyma.04G086700，为进一步探索SMV SC3抗性的遗传机制奠定了基础。这些见解可为未来改进大豆育种策略以有效对抗SMV提供指导。
