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. 2020 Apr 17;9(4):520.
doi: 10.3390/plants9040520.

Metabolomics Response for Drought Stress Tolerance in Chinese Wheat Genotypes (Triticum aestivum)

Affiliations

Metabolomics Response for Drought Stress Tolerance in Chinese Wheat Genotypes (Triticum aestivum)

Xiaoyang Guo et al. Plants (Basel). .

Abstract

Metabolomics is an effective biotechnological tool that can be used to attain comprehensive information on metabolites. In this study, the profiles of metabolites produced by wheat seedlings in response to drought stress were investigated using an untargeted approach with ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to determine various physiological processes related to drought tolerance from the cross between drought-tolerant genotype (HX10) and drought-sensitive genotype (YN211). The current study results showed that under drought stress, HX10 exhibited higher growth indices than YN211. After drought stress treatment, a series of phenolics accumulated higher in HX10 than in YN211, whereas the amount of thymine, a pyrimidine, is almost 13 folds of that in YN211. These metabolites, as well as high levels of different amino acids, alkaloids, organic acids, and flavonoids in the drought treated HX10 could help to explain its strong drought-tolerant capacity. The current study explored the understanding of the mechanisms involved in the drought response of wheat seedling; these metabolome data could also be used for potential QTL or GWAS studies to identify locus (loci) or gene(s) associated with these metabolic traits for the crop improvement.

Keywords: drought stress; metabolites; photosynthesis indices; untargeted approach; wheat.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Growth performances of two wheat genotypes under control and drought stress conditions at the seedling stage. (A), the two wheat genotypes exhibited morphological differences after seven days treatment with 20% PEG. (B), growth parameters of two wheat genotypes. CK1:YN211 under normal conditions, T1: YN211 under drought treatment, CK2:HX10 under normal conditions, T2: HX10 under drought treatment. Asterisk (*) and double asterisk (**) indicate significant (p < 0.05) and highly significant (p < 0.01) differences between controls and treatments, respectively.
Figure 2
Figure 2
Principal component analysis (PCA) of metabolic profiles in leaves of HX10 and YN211 under control or drought stress (eight biological replicates). CK1:YN211 under normal conditions, T1: YN211 under drought treatment, CK2:HX10 under normal conditions, T2: HX10 under drought treatment.
Figure 3
Figure 3
Partial least squares discriminant analysis (PLS-DA) of metabolic profiles in the leaves of HX10 and YN211 under control or drought stress (eight biological replicates). CK1:YN211 under normal conditions, T1: YN211 under drought treatment, CK2:HX10 under normal conditions, T2: HX10 under drought treatment.
Figure 4
Figure 4
Volcanic plots of metabolites in wheat leaves of two genotypes under control or drought. The x-axis represents log2 value of fold change of each metabolite, y-axis represents the p-value of metabolites (log10 value), gray represents metabolites with no significant difference, red represents up-regulated metabolites, green represents down-regulated metabolites. CK1:YN211 under normal conditions, T1: YN211 under drought stress, CK2:HX10 under normal conditions, T2: HX10 under drought stress.
Figure 5
Figure 5
Classification of 56 differently accumulated metabolites between two wheat genotypes under drought stress.
Figure 6
Figure 6
Relative contents of the 24 metabolites accumulated at a higher level in HX10 after drought treatment in all samples. CK1:YN211 under normal conditions, T1: YN211 under drought treatment, CK2:HX10 under normal conditions, T2: HX10 under drought treatment.

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