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Updated: Jan 15, 2026

Tomato Root Transformation Followed by Inoculation with Ralstonia Solanacearum for Straightforward Genetic Analysis of Bacterial Wilt Disease
Published on: March 11, 2020
Genome-wide association study identifies quantitative trait loci associated with resistance to Verticillium dahliae
Tika B Adhikari1, Bode A Olukolu2, Anju Pandey3
1Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, North Carolina, USA.
Abstract:
Verticillium wilt (VW) disease, caused by Verticillium dahliae Kleb., is a major threat to tomato (Solanum lycopersicum L.) production. Identifying loci associated with VW resistance can accelerate breeding efforts and support sustainable disease management. Although the Ve1 and Ve2 genes confer resistance to V. dahliae races 1 and 2, the emergence of race 3 in the United States poses a new challenge. To investigate the genetic basis of quantitative resistance to the race 3 strain KJ14a, we evaluated 250 diverse tomato accessions. Disease severity and incidence were assessed weekly over 5 weeks, using chlorosis/necrosis percentage (CN_perc) and the number of symptomatic leaves (LC) as phenotypes. OmeSeq quantitative reduced-representation sequencing yielded 42,941 high-quality single nucleotide polymorphism and insertion-deletion markers. Genome-wide association study (GWAS) and local linkage disequilibrium analyses identified four candidate genes associated with VW resistance on chromosomes 3, 5, and 7, including two loci mapping to previously reported quantitative trait loci and two novel resistance loci on chromosome 5. The candidate genes are involved in plant defense and the modification of cell walls. To validate and assess the breeding potential of marker-trait associations, we applied GWAS-assisted best linear unbiased prediction (GWABLUP). Using an additive + dominance model and GWABLUP with top 100 associated markers, predictive ability for LC improved by 16.4% and 4.8%, and for CN_perc by 11.7% and 7.9%, compared to standard genomic best linear unbiased prediction using 100 and 18,000 genome-wide markers, respectively. These results offer valuable insights into the genetic architecture of VW resistance to race 3 and demonstrate the potential of combining GWAS and genomic prediction to accelerate tomato breeding for durable disease resistance.

