Transcriptome SNP analysis of tomato seedlings exposed to low‑dose gamma irradiation and cold plasma suggests...

Physical mutagens such as low-dose gamma irradiation and cold plasma have recently emerged as eco-friendly tools for enhancing plant vigor, stress tolerance, and disease resistance. However, their impact on genetic stability remains insufficiently characterized. Here, we performed transcriptome-wide single-nucleotide polymorphism (SNP) discovery in Solanum lycopersicum seedlings infected with Tomato brown rugose fruit virus (ToBRFV; Tobamovirus fructirugosum) and subjected to either 15 Gy gamma irradiation or cold plasma treatment. RNA-Seq analysis revealed distinct mutational footprints: gamma irradiation induced 82 high-confidence SNPs, whereas cold plasma generated 36, with only two SNPs shared between treatments. Chromosomal mapping indicated that gamma-induced SNPs were clustered on chromosomes 7, 12, and 9, while cold plasma-associated mutations were more evenly distributed, predominantly on chromosomes 6 and 11. Most SNPs were localized within protein-coding regions, resulting exclusively in nonsynonymous substitutions; however, the limited SNP dataset and transcriptome-based approach prevent robust inference of selection pressure. Functionally, gamma-induced SNPs were enriched in genes related to terpene biosynthesis, lipid metabolism, and secondary metabolite pathways, while cold plasma targeted genes associated with transcriptional regulation, redox signaling, and chloroplast function, which are closely linked to hormone-mediated signaling networks such as auxin pathways that coordinate plant stress responses and developmental adaptation. Protein modeling further highlighted amino acid substitutions in conserved domains of NB-LRR and regulatory proteins, suggesting possible contributions to plant stress and immune responses. Collectively, our results demonstrate that both treatments induce limited yet functionally relevant transcriptomic mutations within expressed genes, without evidence of widespread mutational disruption at the transcriptome level. However, because the analysis is based on RNA-Seq data, these findings reflect transcriptome-level stability rather than genome-wide genomic safety, and further validation using whole-genome sequencing would be required to assess genome-wide mutational effects.