Differential Metabolite Profiling of Plant Tissues

The LC-MS raw data was analyzed by the Progqenesis QI v2.3 software (Nonlinear Dynamics, Newcastle, UK) for extracting characteristic ions of metabolites. Data processing parameters were set as following: precursor tolerance: five ppm, fragment tolerance: 10 ppm, product ion threshold: 5%. The LC-MS data was uploaded to SIMCA software package (version 14.0, Umetrics, Umeå, Sweden) for statistical analysis. The LC-MS data were obtained according to three-dimensional datasets including m/z, peak retention time (PRT) and peak intensities, and PRT-m/z pairs were used as the identifier for each ion. Metabolite identification was based on Plant Metabolome Database.^{23 (link)} Hierarchical cluster heatmap analysis (HCA), principal component analysis (PCA) and (orthogonal) partial least squares-discriminant analysis ((O)PLS-DA) were used to visualize the differential metabolites among the samples. In (O)PLS-DA analysis, variable importance in projection (VIP) and p-value can be used to select differentially expressed metabolites (DEMs) in seeds and bark, while the metabolites had the values of VIP > 1, p-value < 0.05 and fold change ≥ 2 or fold change ≤ 0.5. HCA and volcano plots were performed in the R software version 4.1.2 (www.r-project.org). Enrichment analysis was performed using MetaboAnalyst (www.Metaboanalyst.ca).