Omics based approaches to decipher the leaf ionome and transcriptome changes in Solanum lycopersicum L. upon Tomato Brown Rugose Fruit Virus (ToBRFV) infection

Abstract

The Tomato Brown Rugose Fruit Virus (ToBRFV) is a pathogen that mostly affects plants from the Solanaceae family. This virus severely affects the yield of tomato (Solanum lycopersicum L.) plants, thus creating an urgent need to research the basis of resistance to manage the disease. To understand the molecular basis of resistance, we employed omics-based approaches involving leaf ionomics and transcriptomics to help us decipher the interaction between elemental and nutritional composition and investigate its effect on the gene expression profile upon the ToBRFV infection in tomatoes. Ionomics was used to investigate the accumulation of trace elements in leaves, showcasing that the plants resistant to the virus had significantly higher concentrations of iron (p-value = 0.039) and nickel (p-value = 0.042) than the susceptible ones. By correlating these findings with transcriptomics, we identified some key genes involved in iron homeostasis and abscisic acid pathways, potentially responsible for conferring resistance against the pathogen. From the obtained list of differentially expressed genes, a panel of mutation profile was discovered with three important genes-Solyc02g068590.3.1 (K+ transporter), Solyc01g111890.3.1 (LRR), and Solyc02g061770.4.1 (Chitinase) showing persistent missense mutations. We ascertain the role of these genes and establish their association with plant resistance using genotyping assays in various tomato lines. The targeted selection of these genetic determinants can further enhance plant breeding and crop yield management strategies.

Fig 1. Details of leaf samples used for transcriptomics, variant analysis and ionomics purposes.

Fig 2

(a) PCA plot of ionomic samples from the leaf samples, highlighting iron and nickel, (b) Clustering of samples on grouping them by means, (c and d) Box plots the Fe and Ni concentrations respectively in susceptible and resistant samples.

Fig 3. PCA clustering showing that the artificially infected samples separate well from the controlled samples.

Fig 4. Heatmap of differentially expressed genes between the control and infected samples based on TPM values.

Fig 5. The waterfall plot represents the mutation type in a list of genes for every individual sample.

The bars with no colour indicate that the sample has the same allele as the reference genome.

Fig 6. Genotype frequencies of validated SNP targets using rhAmp assay in plants with resistant and susceptible lines.