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Background <p>Enhancing plant adaptation to challenging climates through breeding techniques requires studying plant systems with diverse genetic architectures. Comprehensive understanding of the genetic architecture of root traits is crucial for analyzing overall plant development and incorporating these insights into crop breeding programs on challenging climate adaptation. To dissect genetic architecture of root traits in soybean, we applied genome-wide association study (GWAS) in soybean germplasm population. Phenotyping of six root-related traits was performed at two plant growth stages, V<sub>1</sub> (two-weeks growth stage) and V<sub>2</sub> (three-weeks growth stage), under hydroponic culture and GWAS was performed to identify key SNPs and genes associated with root traits.</p> Results <p>Total 58 single nucleotide polymorphisms (SNPs) associated with six root-related traits were detected for two growth stages using three GWAS models, Mixed Linear Model (MLM), the Fixed and Random Model Circulating Probability Unification (FarmCPU) and 3&#xa0;V multi-locus random-SNP-effect Mixed Linear Model (3VmrMLM). A total of 35 SNPs were detected for six root traits at V<sub>1</sub> stage, while 23 SNPs were detected for the same traits at V<sub>2</sub> stage. Quantitative trait locus (QTL) <i>qRoot10.1</i> represented by three significant SNPs, was identified for primary root length (PRL) at V<sub>1</sub> and V<sub>2</sub> stage, and for root tips (RT) at V<sub>2</sub> stage. Further, QTL <i>qRoot10.1</i> was validated for PRL and total root length (TRL) in a separate set of soybean population. Candidate gene analysis in genomic regions of 58 SNPs identified 63 candidate genes, with annotations associated with various pathways of root development. Differential gene expression analysis of the candidate gene <i>Glyma.10g273000</i> at <i>qRoot10.1</i> revealed a significant difference in expression between long-rooting and short-rooting genotypes.</p> Conclusion <p>In this study, we offer new insights into the root architecture of soybean, identifying key SNPs and genes that could be instrumental in future breeding programs aimed at developing highly efficient root systems in soybean.</p>

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Genome-wide association study for root-related traits at vegetative growth stages of soybean (Glycine max L. Merrill)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月15日

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  • Giriraj Kumawat,
  • Nisha Agrawal,
  • Rishiraj Raghuvanshi,
  • Harsha Shrivastava,
  • Shreya Verma,
  • Rucha Kavishwar,
  • Subhash Chandra,
  • Prince Choyal,
  • Shivakumar Maranna,
  • Vennampally Nataraj,
  • Mrinal K. Kuchlan,
  • Punam Kuchlan,
  • Gyanesh Kumar Satpute,
  • Milind B. Ratnaparkhe,
  • Vangala Rajesh,
  • Sanjay Gupta,
  • Ajay Kumar Singh,
  • Kunwar Harendra Singh

摘要

Background

Enhancing plant adaptation to challenging climates through breeding techniques requires studying plant systems with diverse genetic architectures. Comprehensive understanding of the genetic architecture of root traits is crucial for analyzing overall plant development and incorporating these insights into crop breeding programs on challenging climate adaptation. To dissect genetic architecture of root traits in soybean, we applied genome-wide association study (GWAS) in soybean germplasm population. Phenotyping of six root-related traits was performed at two plant growth stages, V1 (two-weeks growth stage) and V2 (three-weeks growth stage), under hydroponic culture and GWAS was performed to identify key SNPs and genes associated with root traits.

Results

Total 58 single nucleotide polymorphisms (SNPs) associated with six root-related traits were detected for two growth stages using three GWAS models, Mixed Linear Model (MLM), the Fixed and Random Model Circulating Probability Unification (FarmCPU) and 3 V multi-locus random-SNP-effect Mixed Linear Model (3VmrMLM). A total of 35 SNPs were detected for six root traits at V1 stage, while 23 SNPs were detected for the same traits at V2 stage. Quantitative trait locus (QTL) qRoot10.1 represented by three significant SNPs, was identified for primary root length (PRL) at V1 and V2 stage, and for root tips (RT) at V2 stage. Further, QTL qRoot10.1 was validated for PRL and total root length (TRL) in a separate set of soybean population. Candidate gene analysis in genomic regions of 58 SNPs identified 63 candidate genes, with annotations associated with various pathways of root development. Differential gene expression analysis of the candidate gene Glyma.10g273000 at qRoot10.1 revealed a significant difference in expression between long-rooting and short-rooting genotypes.

Conclusion

In this study, we offer new insights into the root architecture of soybean, identifying key SNPs and genes that could be instrumental in future breeding programs aimed at developing highly efficient root systems in soybean.