Transcriptome datasets of salicylic acid-treated tomato plant cultures under normal and stress conditions

Extreme weather events pose a significant challenge to agricultural systems, as they induce various abiotic stress responses in plants. Preventive crop protection strategies that aim to enhance plant resistance in advance are gaining increasing importance to mitigate these stress effects. Priming treatments based on the activation of the immune response allow plants to be prepared for stress by triggering some of the defense mechanisms before the actual stress occurs. In the study, healthy, young tomato plants were pre-treated with a foliar spray containing salicylic acid and then subjected to drought stress during the vegetation period. NGS-based shallow RNA sequencing was used to examine the samples at the molecular level. Following bioinformatic processing and evaluation of the obtained sequence data, it was possible to analyse the putative stimulatory effects of salicylic acid treatment and to monitor the development of long-term adaptation processes induced by priming, such as the development of plant stress memory under stress conditions. The sequencing data were submitted in the NCBI database in the form of four forward SRA data sets, in three biological replicates, providing a total of 12 SRA data sets. Furthermore, a de novo transcriptome assembly (TSA) file generated from the quality-controlled reads, along with a read count table obtained from from RNA-seq analysis, was deposited in the Mendeley Data repository. Since Kecskeméti 549 is a special local tomato variety, no reference genome is available in public databases; therefore, the de novo assembly method was chosen for the reconstruction of the transcriptome. The created datasets provide an opportunity for future studies to explore the short-term (priming effect) and prolonged (during stress exposure) molecular consequences of the treatments. The data can also be used to identify and monitor plant biochemical processes induced by salicylic acid, with particular attention to changes in gene expression patterns.