Department of Plant Sciences, North Dakota State University, Fargo, ND, 58108, USA.
Department of Plant Pathology, North Dakota State University, Fargo, ND, 58108, USA.
Theor Appl Genet. 2022 Jun;135(6):2167-2184. doi: 10.1007/s00122-022-04104-0. Epub 2022 May 6.
GWAS detected ninety-eight significant SNPs associated with Sclerotinia sclerotiorum resistance. Six statistical models resulted in medium to high predictive ability, depending on trait, indicating potential of genomic prediction for disease resistance breeding. The lack of complete host resistance and a complex resistance inheritance nature between rapeseed/canola and Sclerotinia sclerotiorum often limits the development of functional molecular markers that enable breeding for sclerotinia stem rot (SSR) resistance. However, genomics-assisted selection has the potential to accelerate the breeding for SSR resistance. Therefore, genome-wide association (GWA) mapping and genomic prediction (GP) were performed using a diverse panel of 337 rapeseed/canola genotypes. Three-week-old seedlings were screened using the petiole inoculation technique (PIT). Days to wilt (DW) up to 2 weeks and lesion phenotypes (LP) at 3, 4, and 7 days post-inoculation (dpi) were recorded. A strong correlation (r = - 0.90) between DW and LP_4dpi implied that a single time point scoring at four days could be used as a proxy trait. GWA analyses using single-locus (SL) and multi-locus (ML) models identified a total of 41, and 208 significantly associated SNPs, respectively. Out of these, ninety-eight SNPs were identified by a combination of the SL model and any of the ML models, at least two ML models, or two traits. These SNPs explained 1.25-12.22% of the phenotypic variance and considered as significant, could be associated with SSR resistance. Eighty-three candidate genes with a function in disease resistance were associated with the significant SNPs. Six GP models resulted in moderate to high (0.42-0.67) predictive ability depending on SSR resistance traits. The resistant genotypes and significant SNPs will serve as valuable resources for future SSR resistance breeding. Our results also highlight the potential of genomic selection to improve rapeseed/canola breeding for SSR resistance.
GWAS 检测到与核盘菌抗性相关的 98 个显著 SNPs。六种统计模型根据性状表现出中等至高度的预测能力，表明基因组预测在抗病性育种方面具有潜力。油菜/芥蓝与核盘菌之间缺乏完全的寄主抗性和复杂的抗性遗传性质，常常限制了功能分子标记的开发，这些标记可用于选育抗核盘菌茎腐病（SSR）。然而，基于基因组的选择有可能加速 SSR 抗性的选育。因此，使用 337 个油菜/芥蓝基因型的多样化群体进行了全基因组关联（GWA）图谱绘制和基因组预测（GP）。使用叶柄接种技术（PIT）对 3 周龄的幼苗进行筛选。记录 DW 至 2 周和 LP_4dpi 的发病症状（LP）。DW 和 LP_4dpi 之间存在很强的相关性（r=-0.90），这意味着可以使用单点 4 天的评分作为替代性状。使用单基因座（SL）和多基因座（ML）模型进行 GWA 分析，分别鉴定出 41 个和 208 个显著相关的 SNP。其中，98 个 SNP 是通过 SL 模型和任何一个 ML 模型、至少两个 ML 模型或两个性状的组合确定的。这些 SNP 解释了 1.25-12.22%的表型方差，被认为是与 SSR 抗性相关的显著 SNP。与显著 SNP 相关的 83 个候选基因具有抗病功能。6 个 GP 模型根据 SSR 抗性性状表现出中等至高度（0.42-0.67）的预测能力。抗性基因型和显著 SNP 将成为未来 SSR 抗性育种的有价值资源。我们的研究结果还突出了基因组选择在提高油菜/芥蓝 SSR 抗性育种方面的潜力。
