A breeding strategy for high-oleic acid content and high-yield peanut using Tag SNPs and genomic selection.
- 2026-04-11
- BMC plant biology 26(1)
- Minjie Guo
- Jianli Miao
- Yang Li
- Junhua Yin
- Peiyun Wang
- Feng Luo
- Shaowei Li
- Junping Hu
- Wenhao Liu
- Taorui Zhang
- Li Ren
- Li Deng
- PubMed: 41965514
- DOI: 10.1186/s12870-026-08473-2
Study Design
- Population
- 169 peanut accessions
- Methods
- Integrated marker-assisted breeding with genomic selection; genome-wide association studies (GWAS) and genomic selection (GS) analyses
- Funding
- Unclear
Abstract
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.
Supplementary Information: The online version contains supplementary material available at 10.1186/s12870-026-08473-2.
Keywords: Breeding; Genome-wide association study (GWAS); Genomic selection; High yield; High-oleic; Peanut; Tag SNPs.