Drought stress is major abiotic stress that affects soybean production. Therefore, it is widely desirable that soybean becomes more tolerant to stress. To provide insights into regulatory mechanisms of the stress response, we compared the global gene expression profiles from leaves of two soybean genotypes that display different responses to water-deficit (BR 16 and Embrapa 48, drought-sensitive and droughttolerant, respectively). After the RNA-seq analysis, a total of 5335 down-regulated and 3170 up-regulated genes were identified in the BR16. On the other hand, the number of genes differentially expressed was markedly lower in the Embrapa 48, 355 up-regulated and 471 down-regulated genes. However, induction and expression of protein kinases and transcription factors indicated signaling cascades involved in the drought tolerance. Overall, the results suggest that the metabolism of pectin is differently modulated in response to drought stress and may play a role in the soybean defense mechanism against drought. This occurs via an increase of the cell wall plasticity and crosslink, which contributed to a higher hydraulic conductance (K f ) and relative water content (RWC%). The drought-tolerance mechanism of the Embrapa 48 genotype involves remodeling of the cell wall and increase of the hydraulic conductance to the maintenance of cell turgor and metabolic processes, resulting in the highest leaf RWC, photosynthetic rate (A), transpiration (E) and carboxylation (A/C i ). Thus, we concluded that the cell wall adjustment under drought is important for a more efficient water use which promoted a more active photosynthetic metabolism, maintaining higher plant growth under drought stress.
Plants produce a variety of compounds with diverse structure and abundance that play an important role in the development, growth and response to the environment. Metabolomics involves studies of a great number of metabolites, which are small molecules present in biological systems.Metabolite profiles can be obtained from several samples by LC/MS (liquid chromatography coupled to mass spectrometry). However, the large number of ions detected for each run from different treatments and replicates require automatic processing for both spectra (metabolite identification and quantification) and global analysis of the metabolome. Thus, this protocol describes in detail, step-by-step, the comparison of the metabolite profiles from LC/MS data for determination of dysregulated pathways, as well as for Exploratory Statistical and Functional Enrichment Analyzes. .
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