Plants continuously produce essential metabolites that regulate their growth and development. The enrichment of specific metabolites determines plant interactions with the immediate environment, and some metabolites become critical in defence responses against biotic and abiotic stresses. Here, an untargeted UHPLC-qTOF-MS approach was employed to profile metabolites of wheat cultivars resistant or susceptible to the pathogen Puccinia striiformis f. sp. tritici (Pst) and Aluminium (Al3+) toxicity. Multivariate statistical analysis (MVDA) tools, viz. principal component analysis (PCA) and hierarchical cluster analysis (HiCA) were used to qualify the correlation between the identified metabolites and the designated traits. A total of 100 metabolites were identified from primary and secondary metabolisms, including phenolic compounds, such as flavonoid glycosides and hydroxycinnamic acid (HCA) derivatives, fatty acids, amino acids, and organic acids. All metabolites were significantly variable among the five wheat cultivars. The Pst susceptible cultivars demonstrated elevated concentrations of HCAs compared to their resistant counterparts. In contrast, 'Koonap' displayed higher levels of flavonoid glycosides, which could point to its resistant phenotype to Pst and Al3+ toxicity. The data provides an insight into the metabolomic profiles and thus the genetic background of Pst- and Al3+-resistant and susceptible wheat varieties. This study demonstrates the prospects of applied metabolomics for chemotaxonomic classification, phenotyping, and potential use in plant breeding and crop improvement.
Keywords: Puccinia striiformis f. sp. tritici; metabolomics; multivariate statistical analysis; primary and secondary metabolism; wheat.