Ksouri Najla, Sánchez Gerardo, Font I Forcada Carolina, Contreras-Moreira Bruno, Gogorcena Yolanda
Group of Genomics of Fruit Trees and Grapevine, Department of Pomology, Estación Experimental de Aula Dei-Consejo Superior de Investigaciones Científicas, Avenida de Montañana 1005, 50059, Zaragoza, Spain.
Biotechnology Lab, Estación Experimental Agropecuaria (EEA) San Pedro, INTA, Ruta N°9 Km 170, B2930, San Pedro, Argentina.
Plant Methods. 2025 Jul 22;21(1):101. doi: 10.1186/s13007-025-01415-3.
Improving peach cultivars with superior traits is a primary objective of breeding initiatives. In this study, we aimed to elucidate the genetic basis of key agronomic and fruit-related traits using a reproducible ddRAD-seq protocol applied to a discovery panel of 90 peach accessions. Our customized workflow (available at https://github.com/najlaksouri/GWAS-Workflow ) integrates three variant callers and tests up to seven models to perform a robust genome-wide association analysis (GWAS). This approach produced 13,045 high-confidence SNPs and identified Blink as the most suitable model, effectively balancing false positive and negative associations. A total of 16 significant associations signals were unveiled for six highly heritable traits (H > 0.5), including harvest date, fruit weight, flesh firmness, contents of flavonoids, anthocyanins and sorbitol. By assessing the allelic effect of significant markers on phenotypic attributes, nine SNP alleles were deemed favorable. Notably, a promising marker (SNC_034014.1_7012470) demonstrated simultaneous association with harvest date and fruit firmness, displaying a positive allelic effect on both traits. We anticipate that this marker can serve as a good predictor of firmer varieties. Candidate causal genes were shortlisted when fulfilling the following criteria: (i) position within the linkage disequilibrium block, (ii) functional annotation and (iii) expression pattern. A comprehensive bibliographic review of previously reported QTLs mapping nearby the associated markers allowed us to benchmark the accuracy of our approach. Despite the moderate germplasm size, ddRAD-seq allowed us to produce an accurate representation of the peach genome, resulting in SNP markers suitable for empirical association studies. Together with candidate genes, they lay the foundation for further genetic dissection of peach key traits.
培育具有优良性状的桃品种是育种工作的首要目标。在本研究中，我们旨在通过将可重复的ddRAD-seq方案应用于由90份桃种质组成的发现群体，阐明关键农艺性状和果实相关性状的遗传基础。我们定制的工作流程（可在https://github.com/najlaksouri/GWAS-Workflow获取）整合了三种变异检测工具，并测试多达七种模型，以进行稳健的全基因组关联分析（GWAS）。这种方法产生了13,045个高可信度单核苷酸多态性（SNP），并确定Blink为最合适的模型，有效平衡了假阳性和阴性关联。共揭示了六个高遗传力性状（H>0.5）的16个显著关联信号，包括采收期、果实重量、果肉硬度、黄酮类化合物、花青素和山梨醇含量。通过评估显著标记对表型属性的等位基因效应，九个SNP等位基因被认为是有利的。值得注意的是，一个有前景的标记（SNC_034014.1_7012470）显示与采收期和果实硬度同时关联，对这两个性状均表现出正等位基因效应。我们预计该标记可作为较硬品种的良好预测指标。当满足以下标准时，将候选因果基因列入候选名单：（i）位于连锁不平衡区域内；（ii）功能注释；（iii）表达模式。对先前报道的与相关标记附近的数量性状位点（QTL）进行全面的文献综述，使我们能够评估我们方法的准确性。尽管种质规模适中，但ddRAD-seq使我们能够准确呈现桃基因组，产生适用于实证关联研究的SNP标记。它们与候选基因一起，为进一步对桃关键性状进行遗传剖析奠定了基础。
