한빛사 논문
국립농업과학원
Ye Jin Kima,1, Young Jin Parka,1, Sung-Dug Ohb,1, Jeong Su Yoona, Jae Geun Kima, Ju-Seok Seoc, Jung-Ho Parkd, Chang-Gi Kimd, Soo-Yun Parkb, Soon Ki Parke, Man-Soo Choif, Jae Kwang Kima,*
aDivision of Life Sciences, Incheon National University, Yeonsu-gu, Incheon 22012, Republic of Korea
bDepartment of Agricultural Biotechnology, National Institute of Agricultural Sciences, Rural Development Administration, Jeonju 54874, Republic of Korea
cCelltrion Inc., Incheon 22014, Republic of Korea
dBio-Evaluation Center, Korea Research Institute of Bioscience and Biotechnology, Cheongju 28116, Republic of Korea
eSchool of Applied Biosciences, Kyungpook National University, Daegu 41566, Republic of Korea
fDivision of Crop Foundation, National Institute of Crop Science, Rural Development Administration, Wanju 55365, Republic of Korea
1Ye Jin Kim, Young Jin Park, and Sung-Dug Oh contributed equally to this work.
*Corresponding author.
Abstract
Genetically modified (GM) soybean events CT-4025 and CT-1001, which contain genes encoding thioredoxin and epidermal growth factor, respectively, have previously been developed for use in cosmetic materials. In this study, compositional analyses and metabolic profiling were carried out to assess the unintended effects on the composition of metabolites between GM soybeans and non-GM soybeans. The soybeans were cultivated in 2016 and 2017 in two regions (Ochang and Jeonju) in the Republic of Korea. Statistical analyses were performed using univariate and multivariate methods. Results from the compositional analysis showed that the compositional variation in the tested GM varieties was within the range of conventional varieties. Furthermore, the results of multivariate analysis revealed that the growing year had a much stronger effect on soybean composition than did the growing site or genotypes. In the case of soybeans harvested in 2016, the levels of most amino acids decreased while those of secondary metabolites and sucrose increased, indicating that water stress due to low rainfall in 2016 induced metabolic changes. These results suggest that environmental factors have a major impact on the composition of GM and non-GM soybeans. We further demonstrated that metabolic approaches are useful for investigating the environmental change-induced metabolic network in GM crops intended for use in cosmetic materials.
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