抄録
Peanut (Arachis hypogaea L.) is a globally important oilseed crop, and its oil content, as a key trait determining yield and economic value, has long been a central focus of genetic research and breeding improvement. In recent years, with the advancement of genome-wide association studies (GWAS) and quantitative trait locus (QTL) mapping, significant progress has been achieved in elucidating the genetic basis of peanut oil content. GWAS identifies single-nucleotide polymorphism (SNP) markers closely associated with oil content by analyzing large-scale genotype and phenotype data from natural populations, while QTL mapping reveals key genomic regions controlling oil content through the construction of genetic populations and genome scanning. The integration of GWAS and QTL mapping enhances the resolution of gene discovery for oil content and provides strong support for marker-assisted selection (MAS). This paper reviews the current applications of GWAS and QTL mapping in peanut oil content research, elaborating on their technical principles, research progress, and combined strategies. By integrating multi-omics data and genomic big data analysis, key regulatory networks in lipid metabolism pathways have been uncovered. Furthermore, the challenges of current research are discussed, along with prospects for the genetic improvement of oil content in peanuts. Overall, this study aims to provide a theoretical basis and technical guidance for enhancing peanut oil content and achieving precision breeding through a comprehensive analysis of GWAS and QTL mapping applications.
