Transcriptional search to identify and assess reference genes for expression analysis in Solanum lycopersicum under stress and hormone treatment conditions

Tomato (Solanum lycopersicum) is a model plant for research on fruit development and stress response, in which gene expression analysis is frequently conducted. Quantitative PCR (qPCR) is a widely used technique for gene expression analysis, and the selection of reference genes may affect the accuracy of results and even conclusions. Although there have been some frequently used reference genes in tomato, it has been shown that the expressions of some of these genes are not constant in different tissues and environmental conditions. Moreover, little information on genomic identification of reference genes is available in tomato. Here, we mined the publicly available transcriptional sequencing data and screened out fifteen candidate reference genes, and the expression stability of these candidate genes and seven traditionally used ones were evaluated under stress and hormone treatment. The results showed that over half of the selected candidate references were housekeeping genes in tomato cells. Among the candidate reference genes and the traditionally used ones, the most stably expressed genes varied under different treatments, and most of these genes were recommended as preferred reference genes at least once except Solyc04g009030 and Solyc07g066610, two traditionally used reference genes. This study provides some novel reference genes in tomato, and the preferred reference genes under different environmental stimuli, which may be useful for future research. Our study suggests that excavating stably expressed genes from transcriptome sequencing data is a reliable approach to screening reference genes for qPCR analysis.

Automated summary

Tomato is a model plant for fruit development and stress response research, with gene expression analysis frequently conducted through techniques like qPCR. This study identified new reference genes in tomato by mining transcriptome sequencing data, evaluating their stability under different treatments. The results showed that the stability of reference genes varied under different conditions, with most genes recommended as preferred reference genes.