2017
DOI: 10.1007/s13765-017-0265-0
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Targeted metabolite profiling to evaluate unintended metabolic changes of genetic modification in resveratrol-enriched rice (Oryza sativa L.)

Abstract: Resveratrol-enriched rice (RR) includes the stilbene synthase gene for resveratrol synthesis and the phosphinothricin-N-acetyltransferase gene for glufosinate tolerance. To investigate unintended effects resulting from RR's genetically modified chemical composition, 56 polar and nonpolar secondary metabolites were analyzed with gas chromatography-mass spectrometry in RR and conventional non-transgenic rice. Rice was cultivated during two seasons along three representative climatic regions in the Republic of Ko… Show more

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Cited by 17 publications
(11 citation statements)
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“…With regard to metabolic variations, environmental factors, e.g., growing season, location, sowing date, and type of abiotic stress, play a larger role than genetic modifications [26][27][28]. Because those factors may be the dominant parameter driving the variability of metabolite profiles in the PCA, we also conducted a comparative analysis to examine individual differences in the datasets of transgenic soybean versus its non-transgenic counterpart.…”
Section: Discussionmentioning
confidence: 99%
“…With regard to metabolic variations, environmental factors, e.g., growing season, location, sowing date, and type of abiotic stress, play a larger role than genetic modifications [26][27][28]. Because those factors may be the dominant parameter driving the variability of metabolite profiles in the PCA, we also conducted a comparative analysis to examine individual differences in the datasets of transgenic soybean versus its non-transgenic counterpart.…”
Section: Discussionmentioning
confidence: 99%
“…Inferential tests of differences (independent t-tests) and relationships (Pearson's coefficient) were performed using SAS software (version 9.2: SAS Institute, Cary, NC, USA). The relative quantification data acquired from GC-TOFMS were subjected to principal component analysis (PCA) using SIMCA-P software (version 13.0; Umetrics, Umea, Sweden) to evaluate similarity or dissimilarity between groups of multivariate data [12]. The PCA output consisted of score plots for visualizing the contrast between different samples and loading plots to explain cluster separation.…”
Section: Discussionmentioning
confidence: 99%
“…All analyses were performed at least three times. Principal component analysis (PCA; SIMCA-P version 13.0; Umetrics, Umeå, Sweden) was conducted using the mineral element data and the metabolite data as in Kim et al [9]. The analysis was set to produce score plots to illustrate the dissimilarity between samples treated with different nutrient deficiencies and loading plots to show mineral elements and metabolites explaining the cluster separation.…”
Section: Discussionmentioning
confidence: 99%
“…Primary metabolites were extracted as described by Kim et al [9]. Powdered sample that was freeze-dried and ground (100 mg) was mixed with 1 mL of a mixture containing methanol, water, and chloroform (2.5:1:1 volume ratio) and 60 lL of ribitol as an internal standard (0.2 mg/mL) at 37°C for 30 min with a mixing frequency of 1200 rpm using a Thermomixer Compact (Eppendorf AG, Hamburg, Germany).…”
Section: Metabolic Profilingmentioning
confidence: 99%