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Background <p>Developing peanut varieties with high oleic acid content (OAC) and superior yield is critical for meeting global nutritional and economic demands. To address this, our study integrated marker-assisted breeding with genomic selection (GS), creating an efficient breeding framework. Using a diverse natural population of 169 accessions, we conducted genome-wide association studies (GWAS) and GS analyses to identify Tag single nucleotide polymorphisms (SNPs) associated with OAC and develop a robust yield prediction model.</p> Results <p>Phenotypic analysis indicated continuous variation in both OAC and productivity, with broad-sense heritability estimates of 0.9634 and 0.4535, respectively. Only a weak correlation was observed between these two traits. Whole-genome resequencing at approximately 10 × coverage identified 608,809 SNPs. GWAS revealed 32 significant loci associated with OAC, predominantly located on chromosomes 9 and 19, explaining 17.65–26.23% of the phenotypic variation. These loci were grouped into three distinct haplotype blocks, from which three core Tag SNPs (Arahy.9_113845844, Arahy.9_114322963, Arahy.19_154509990) were validated by regression and boxplot analyses. The GS model, developed using a genomic relationship matrix, yielded an additive genetic variance of 0.8626, a residual variance of 1.6915, a heritability estimate of 0.3377 for yield, with a prediction accuracy of 0.58. Validation in the candidate population showed optimal breeding efficiency at a 30% selection intensity using genomic estimated breeding values.</p> Conclusions <p>The identified Tag SNPs provides a framework for efficient early-generation selection for OAC, while GS predictions facilitate advanced-generation yield optimization. Our results suggest that this integrated strategy has the potential to improve both quality and yield traits, offering a framework for more efficient breeding of peanut varieties with enhanced OAC and productivity.</p>

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A breeding strategy for high-oleic acid content and high-yield peanut using Tag SNPs and genomic selection

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月11日

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  • Minjie Guo,
  • Jianli Miao,
  • Yang Li,
  • Junhua Yin,
  • Peiyun Wang,
  • Feng Luo,
  • Shaowei Li,
  • Junping Hu,
  • Wenhao Liu,
  • Taorui Zhang,
  • Li Ren,
  • Li Deng

摘要

Background

Developing peanut varieties with high oleic acid content (OAC) and superior yield is critical for meeting global nutritional and economic demands. To address this, our study integrated marker-assisted breeding with genomic selection (GS), creating an efficient breeding framework. Using a diverse natural population of 169 accessions, we conducted genome-wide association studies (GWAS) and GS analyses to identify Tag single nucleotide polymorphisms (SNPs) associated with OAC and develop a robust yield prediction model.

Results

Phenotypic analysis indicated continuous variation in both OAC and productivity, with broad-sense heritability estimates of 0.9634 and 0.4535, respectively. Only a weak correlation was observed between these two traits. Whole-genome resequencing at approximately 10 × coverage identified 608,809 SNPs. GWAS revealed 32 significant loci associated with OAC, predominantly located on chromosomes 9 and 19, explaining 17.65–26.23% of the phenotypic variation. These loci were grouped into three distinct haplotype blocks, from which three core Tag SNPs (Arahy.9_113845844, Arahy.9_114322963, Arahy.19_154509990) were validated by regression and boxplot analyses. The GS model, developed using a genomic relationship matrix, yielded an additive genetic variance of 0.8626, a residual variance of 1.6915, a heritability estimate of 0.3377 for yield, with a prediction accuracy of 0.58. Validation in the candidate population showed optimal breeding efficiency at a 30% selection intensity using genomic estimated breeding values.

Conclusions

The identified Tag SNPs provides a framework for efficient early-generation selection for OAC, while GS predictions facilitate advanced-generation yield optimization. Our results suggest that this integrated strategy has the potential to improve both quality and yield traits, offering a framework for more efficient breeding of peanut varieties with enhanced OAC and productivity.