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.

中文翻译：

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菠菜草酸盐含量的基因组见解：全基因组关联研究和基因组预测方法


菠菜中的草酸盐含量是一个重要的特征，因为它与人类健康相关。了解其遗传基础可以促进草酸盐水平降低的菠菜品种的开发。为了了解遗传决定因素，由 288 个菠菜种质组成的多样化小组对草酸盐含量进行了彻底的表型分析，并进行了全基因组重新测序，产生了包含 14 386 个单核苷酸多态性 (SNP) 的综合数据集。利用该数据集，我们进行了全基因组关联研究 (GWAS)，以确定与草酸盐含量相关的值得注意的 SNP。此外，我们通过交叉预测采用基因组预测 (GP)，利用五个 GP 模型来评估草酸盐含量的基因组估计育种值 (GEBV)。观察到的正态分布和草酸盐含量的广泛范围（超过 600.0 mg·100 g−1）强调了该性状的复杂性和数量性质，可能受到多个基因的影响。此外，我们的分析揭示了明显的分层，将人口划分为四个可辨别的亚群。此外，在 GAPIT 3 和 TASSEL 5 中采用五个模型的 GWAS 分析揭示了与草酸盐含量相关的 9 个重要的 SNP（1 号染色体上的 4 个 SNP 和 5 号染色体上的 5 个 SNP）。这些位点表现出与六个候选基因的关联，这可能对草酸盐含量调节有潜在的贡献。值得注意的是，我们的 GP 模型表现出显着的预测能力，GEBV 估计的平均准确度高达 0.51。 GWAS 和 GP 方法的结合提供了对菠菜草酸含量遗传基础的全面理解。 这些发现为开发针对草酸水平进行优化的菠菜品种和杂交种提供了一条有希望的途径，从而促进消费者的健康。