In plants, salicylic acid (SA) is a hormone that mediates a plant’s defense against pathogens. SA also takes an active role in a plant’s response to various abiotic stresses, including chilling, drought, salinity, and heavy metals. In addition, in recent years, numerous studies have confirmed the important role of SA in plant morphogenesis. In this review, we summarize data on changes in root morphology following SA treatments under both normal and stress conditions. Finally, we provide evidence for the role of SA in maintaining the balance between stress responses and morphogenesis in plant development, and also for the presence of SA crosstalk with other plant hormones during this process.

RNA isolation from fungi and fungus-like organisms is not an easy task. Active endogenous RNases quickly hydrolyze RNA after the sample collection, and the thick cell wall prevents inhibitors from penetrating the cells. Therefore, the initial collection and grinding steps may be crucial for the total RNA isolation from the mycelium. When isolating RNA from Phytophthora infestans, we varied the grinding time of the Tissue Lyser and used TRIzol and beta-mercaptoethanol to inhibit the RNase. In addition, we tested the mortar and pestle grinding of mycelium in liquid nitrogen, with this method showing the most consistent results. During the sample grinding with the Tissue Lyser device, adding an RNase inhibitor proved to be a prerequisite, and the best results were achieved using TRIzol. We considered ten different combinations of grinding conditions and isolation methods. The classical combination of a mortar and pestle, followed by TRIzol, has proved to be the most efficient.

Meta-analysis of transcriptomic data from different experiments has become increasingly prevalent due to a significantly increasing number of genome-wide experiments investigating gene expression changes under various conditions. Such data integration provides greater accuracy in identifying candidate genes and allows testing new hypotheses, which could not be validated in individual studies. To increase the relevance of experiment integration, it is necessary to optimize the selection of experiments. In this paper, we propose a set of quantitative indicators for a comprehensive comparative description of transcriptomic data. These indicators can be easily visualized and interpreted. They include the number of differentially expressed genes (DEGs), the proportion of experiment-specific (unique) DEGs in each data set, the pairwise similarity of experiments in DEG composition and the homogeneity of DEG profiles. For automatic calculation and visualization of these indicators, we have developed the program InterTransViewer. We have used InterTransViewer to comparatively describe 23 auxin- and 16 ethylene- or 1-aminocyclopropane-1-carboxylic acid (ACC)-induced transcriptomes in Arabidopsis thaliana L. We have demonstrated that analysis of the characteristics of individual DEG profiles and their pairwise comparisons based on DEG composition allow the user to rank experiments in the context of each other, assess the tendency towards their integration or segregation, and generate hypotheses about the influence of non-target factors on the transcriptional response. As a result, InterTransViewer identifies potentially homogeneous groups of experiments. Subsequent estimation of the profile homogeneity within these groups using resampling and setting a significance threshold helps to decide whether these data are appropriate for meta-analysis. Overall, InterTransViewer makes it possible to efficiently select experiments for meta-analysis depending on its task and methods.