Genome-Wide Association and Genomic Prediction of Powdery Mildew and CYSDV Resistance in Melon

Abstract

Cucurbit powdery mildew (CPM) and Cucurbit yellow stunting disorder virus (CYSDV) are major constraints to sustainable melon (Cucumis melo L.) production worldwide. To elucidate the genetic basis of resistance and accelerate breeding, we integrated genome-wide association studies (GWASs), transcriptome validation, and genomic selection (GS) using a global panel of 341 melon accessions. Re-analysis of GWAS using BLINK and FarmCPU identified 18 and 19 marker–trait associations exceeding the exploratory threshold for CPM and CYSDV, respectively. Candidate gene analysis highlighted genes involved in lipid metabolism, membrane integrity, hormone signaling, transcriptional regulation, reactive oxygen species detoxification, and antiviral defense, including MLO-like protein, lipid transfer protein, hydroxyproline-rich glycoprotein, glutathione synthetase, RNA helicase, and elongation factor-like protein. Transcriptome analysis further validated several CPM-associated loci through infection-responsive expression patterns, strengthening their candidacy for disease resistance. Genomic prediction using Bayesian Ridge (BRR), gBLUP, Bayesian LASSO, Bayes A, and Bayes B, evaluated under 10-fold cross-validation, achieved consistently high prediction accuracies for CPM and moderate accuracies for CYSDV, reflecting differences in their underlying genetic architecture. Collectively, these findings identify putative associated resistance loci and demonstrate the utility of integrating GWAS, transcriptomics, and genomic selection to enhance marker-assisted and genomic-assisted breeding for durable resistance to fungal and viral diseases in melon.