Genome-Wide Association Mapping and Genomic Prediction of Fusarium Wilt Race 2 Resistance in the USDA Citrullus amarus Collection

Abstract

Fusarium wilt caused by Fusarium oxysporum f. sp. niveum (Fon) 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. Citrullus amarus accessions (n = 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 Fon race 2 resistance. FarmCPU identified four QTN that explained 60% of Fon 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 Fusarium spp. Genomic predictions (GP) for Fon 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 Fon race 2 resistance among the accessions, this study observed prediction accuracies that were strongly influenced by population size.