Research on Differential Metabolites in Distinction of Rice (Oryza sativa L.) Origin Based on GC-MS

Abstract

The analytical method for the metabolomics of the 60 rice seeds from two main rice origins in Heilongjiang Province was developed based on gas chromatography coupled with mass spectrum. The specific differential metabolites between two rice origins were identified, and the distinguish of the two main origins was illustrated by using the R software platform with XCMS software package for gas chromatography coupled with mass spectrum data processing, combined with multivariate statistical analysis software. The result indicated that the 173 peaks were detected, and 54 of which were structurally identified, covering amino acids, aliphatic acid, sugar, polyols, and so on. By comparing the data of Wuchang and Jiansanjiang origins, it was found that there were 9 special metabolites in Wuchang origin and 8 special metabolites in Jiansanjiang origin. The 10 differential metabolites with significant changes (P<0.05, VIP ≥ 1) were filtrated. It is indicated that the differential metabolites of rice carry information of their origin and there are the differences in the metabolites of rice in two main origins. The proposed method is expected to be useful for the metabolomic researches of rice.

Correlation between Irradiation Treatment and Metabolite Changes in Bactrocera dorsalis (Diptera: Tephritidae) Larvae Using Solid-Phase Microextraction (SPME) Coupled with Gas Chromatography-Mass Spectrometry (GC-MS)

“…Partial least-squares discriminant analysis (PLS-DA) is a multidimensional statistical analysis method for supervised pattern recognition [ 34 , 35 ]. Compared with PCA, PLS-DA not only reduces the dimension, but also combines the regression model to make a discriminant analysis of the regression results with a certain discriminant threshold, which is helpful to identify differences in compounds between groups.…”

“…The edited data matrix was imported into RStudio, and the unsupervised PCA and supervised PLS-DA were analyzed in R (Version: 4.1.3) prcomp package and mixOmics package. The differential metabolites were screened according to VIP-value and Student t -test, and the significant differences among the experimental groups were analyzed [ 35 , 56 ]. The selected differential metabolites were annotated in KEGG, and all the pathways of differential metabolites mapping were retrieved [ 57 ].…”

The use of ecological analytical tools as an unconventional approach for untargeted metabolomics data analysis: the case of Cecropia obtusifolia and its adaptive responses to nitrate starvation

“…Pairwise comparisons of C27 at early times vs. C16 and C4 at late times were performed for both ionization modes, generating paired comparisons between the control concentration and the stress concentrations at early times vs. late times. MetaboAnalyst 4.0 software was used as the analysis tool (Chong et al 2019;Feng et al 2019;Wang et al 2020). Furthermore, hierarchical clustering heatmaps were generated as a visualization tool to represent the relative abundance of m/z_rt pairs detected in each sample based on color intensity (Wilkinson and Friendly 2009).…”

Analysis of metabolites and metabolic pathways in three maize (Zea mays L.) varieties from the same origin using GC–MS

“…For example, Zhang et al 6 employed gas chromatography-mass spectrometry (GC-MS) to isolate and identify metabolites of potato tubers in northeastern China. Feng et al 7 studied rice metabolites from different regions of the same province by using GC/MS technology. Florent et al 8 successfully performed a quantitative analysis of cuticular wax in wheat tissues.…”

“…The GC-MS analysis conditions were established according to the method described by Feng et al 7 . To start the analysis, one microlitre of sample solution was injected into the chromatograph with an autosampler.…”