Location: Vegetable Research
Project Number: 6080-22000-032-014-S
Project Type: Non-Assistance Cooperative Agreement
Start Date: Aug 1, 2023
End Date: Oct 1, 2025
Objective:
1. To evaluate tomato for tomato brown rugose fruit virus (ToBRFV) resistance and salt tolerance in tomato.
2. To evaluate Pythium tolerance in leafy vegetables such as spinach and arugula.
3. To conduct QTL and association analysis of ToBRFV resistance in tomato.
4. To conduct genome-wide association study and genomic prediction of Pythium tolerance in vegetables.
Approach:
Tomato brown rugose fruit virus (ToBRFV) resistance evaluation in tomato: The greenhouse phenotyping of ToBRFV resistance will be conducted at ARS, USDA at Charleston, SC. The ToBRFV-US isolate CA18-01 (GenBank accession no. MT002973) will be used for ToBRFV evaluation. The virus inoculum preparation and mechanical inoculation on test plants will follow the procedure established in the lab.
Phenotyping of salt tolerance in tomato: Salt tolerance evaluation will be conducted in the University of Arkansas, Fayetteville greenhouse. The tomato genotypes will be planted in 3 replicated trays (6 plants/ tray rows) for salt treatments (100 ml of 100 mM NaCl) and the well-watered set will be used as control.
Phenotyping for Pythium tolerance in spinach and arugula: A pathogenicity test will be conducted to determine pre- and post-emergence damping-off caused by Pythium on spinach (Viroflay) to screen Pythium tolerance germplasm in spinach, arugula and tomato. In addition, we will evaluate the nutritional and healthy-promotion components in spinach and arugula.
Phenotypic data analysis: Phenotypic data will be analyzed using JMP Genomics.
DNA extraction, genotyping by sequencing (GBS), single nucleotide polymorphism (SNP) discovery and genotyping: Genomic DNA is extracted from fresh leaves of tomato using the CTAB method. DNA sequencing is conducted using genotyping by sequencing (GBS). The short-read sequences data (350bp) are analyzed using Tassel 5 and Stacks software for SNP discovery.
Genetic diversity analysis: The genetic diversity will be analyzed using STRCTURE 2 and MAGA 7.
Quantitative trait loci (QTL) mapping: QTL analysis will be performed using single marker regression (SMR), composite interval mapping (CIM), and multiple-interval mapping (MIM) analyses in QGene.
Genome-wide association study (GWAS): GWAS will be performed using GAPIT3, where GLM, MLM, FarmCPU and BLINK will be used to identify associated SNP markers and candidate genes.
Genomic selection: Genomic estimated breeding value (GEBV) will be estimated using rrBLUP, gBLUP, cBLUP, BayesA, BayesB, and Bayesian LASSO to do genomic prediction in the statistical analysis.
