Genomic insights into oxalate content in spinach: A genome-wide association study and genomic prediction approach

Abstract

Oxalate content in spinach is a key trait of interest due to its relevance to human health. Understanding the genetic basis of it can facilitate the development of spinach varieties with reduced oxalate levels. In pursuit of understanding the genetic determinants, a diverse panel comprising 288 spinach accessions underwent thorough phenotyping of oxalate content and were subjected to whole-genome resequencing, resulting in a comprehensive dataset encompassing 14 386 single-nucleotide polymorphisms (SNPs). Leveraging this dataset, we conducted a genome-wide association study (GWAS) to identify noteworthy SNPs associated with oxalate content. Furthermore, we employed genomic prediction (GP) via cross-prediction, utilizing five GP models, to assess genomic estimated breeding values (GEBVs) for oxalate content. The observed normal distribution and the wide range of oxalate content, exceeding 600.0 mg · 100 g−1, underscore the complex and quantitative nature of this trait, likely influenced by multiple genes. Additionally, our analysis revealed distinct stratification, delineating the population into four discernible subpopulations. Furthermore, GWAS analysis employing five models in GAPIT 3 and TASSEL 5 unveiled nine significant SNPs (four SNPs on chromosome 1 and five on chromosome 5) associated with oxalate content. These loci exhibited associations with six candidate genes, which might have potential contribution to oxalate content regulation. Remarkably, our GP models exhibited notable predictive abilities, yielding average accuracies of up to 0.51 for GEBV estimation. The integration of GWAS and GP approaches offers a holistic comprehension of the genetic underpinnings of oxalate content in spinach. These findings offered a promising avenue for the development of spinach cultivars and hybrids optimized for oxalate levels, promoting consumer health.