Coastal Research and Education Center, Clemson University, Charleston, SC.
U.S. Vegetable Laboratory, USDA-ARS, Charleston, SC 29414.
Plant Dis. 2023 Dec;107(12):3836-3842. doi: 10.1094/PDIS-02-23-0400-RE. Epub 2023 Nov 28.
Fusarium wilt caused by f. sp. () race 2 is a serious disease in watermelon and can reduce yields by 80%. Genome-wide association studies (GWAS) are a valuable tool in dissecting the genetic basis of traits. accessions ( = 120) from the USDA germplasm collection were genotyped with whole-genome resequencing, resulting in 2,126,759 single nucleotide polymorphic (SNP) markers that were utilized for GWAS. Three models were used for GWAS with the R package GAPIT. Mixed linear model (MLM) analysis did not identify any significant marker associations. FarmCPU identified four quantitative trait nucleotides (QTN) on three different chromosomes (i.e., chromosomes 1, 5, and 9), and Bayesian-information and linkage-disequilibrium iteratively nested keyway (BLINK) identified one QTN on chromosome 10 as significantly associated with race 2 resistance. FarmCPU identified four QTN that explained 60% of race 2 resistance, and the single QTN from BLINK explained 27%. Relevant candidate genes were found within the linkage disequilibrium (LD) blocks of these significant SNPs, including genes encoding aquaporins, expansins, 2S albumins, and glutathione S-transferases which have been shown to be involved in imparting resistance to spp. Genomic predictions (GP) for race 2 resistance using all 2,126,759 SNPs resulted in a mean prediction accuracy of 0.08 with five-fold cross-validation employing genomic best linear unbiased prediction (gBLUP) or ridge-regression best linear unbiased prediction (rrBLUP). Mean prediction accuracy with gBLUP leave-one-out cross-validation was 0.48. Thus, along with identifying genomic regions associated with race 2 resistance among the accessions, this study observed prediction accuracies that were strongly influenced by population size.
枯萎病菌（Fusarium wilt）引起的 （sp.）race 2 是西瓜的一种严重疾病，可导致产量减少 80%。全基因组关联研究（GWAS）是解析性状遗传基础的一种有价值的工具。美国农业部种质资源收集的 120 个 （accessions）进行了全基因组重测序，产生了 2126759 个单核苷酸多态性（SNP）标记，用于 GWAS。使用 R 包 GAPIT 进行了三种模型的 GWAS。混合线性模型（MLM）分析未鉴定出任何显著的标记关联。FarmCPU 在三个不同的染色体（即染色体 1、5 和 9）上鉴定出四个数量性状核苷酸（QTN），贝叶斯信息和连锁不平衡迭代嵌套关键方法（BLINK）鉴定出一个位于染色体 10 上的 QTN 与 race 2 抗性显著相关。FarmCPU 鉴定出四个解释了 60%的 race 2 抗性的 QTN，而 BLINK 的单个 QTN 解释了 27%。在这些显著 SNP 的连锁不平衡（LD）块中发现了相关的候选基因，包括编码水通道蛋白、扩张蛋白、2S 白蛋白和谷胱甘肽 S-转移酶的基因，这些基因已被证明参与赋予对 spp.的抗性。使用所有 2126759 个 SNP 对 race 2 抗性进行基因组预测（GP），通过使用基因组最佳线性无偏预测（gBLUP）或岭回归最佳线性无偏预测（rrBLUP）进行五次交叉验证，平均预测准确性为 0.08。使用 gBLUP 进行一次留一交叉验证的平均预测准确性为 0.48。因此，除了确定 （accessions）中与 race 2 抗性相关的基因组区域外，本研究还观察到预测准确性受到群体大小的强烈影响。
