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GmoDetector: An accurate and efficient GMO identification approach and its applications.
Chen, Lihong; Zhou, Junfei; Li, Tiantian; Fang, Zhiwei; Li, Lun; Huang, Gang; Gao, Lifen; Zhu, Xiaobo; Zhou, Xusheng; Xiao, Huafeng; Zhang, Jing; Xiong, QiJie; Zhang, Jianan; Ma, Aijin; Zhai, Wenxue; Zhang, Weixiong; Peng, Hai.
Afiliação
  • Chen L; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Zhou J; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Li T; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Fang Z; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Li L; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Huang G; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Gao L; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Zhu X; Wuhan Qingfahesheng Seed Co., Ltd., Wuhan, Hubei 430056, PR China.
  • Zhou X; Wuhan Qingfahesheng Seed Co., Ltd., Wuhan, Hubei 430056, PR China.
  • Xiao H; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Zhang J; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Xiong Q; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China.
  • Zhang J; MolBreeding Biotechnology Co., Ltd., Shijiazhuang 050035, PR China.
  • Ma A; School of Food and Health, Beijing Technology and Business University, Beijing 100048, PR China. Electronic address: maaj@btbu.edu.cn.
  • Zhai W; Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, PR China. Electronic address: wxzhai@genetics.ac.cn.
  • Zhang W; Department of Computer Science and Engineering, Department of Genetics, Washington University in St. Louis, MO 63130, USA. Electronic address: weixiong.zhang@wustl.edu.
  • Peng H; Institute for Systems Biology, Jianghan University, Wuhan, Hubei 430056, PR China; State Key Laboratory of Hybrid Rice, Hunan Hybrid Rice Research Center, Changsha 410125, PR China; Mingliao Biotechnology Co., Ltd., Wuhan 430056, PR China; School of Food and Health, Beijing Technology and Business U
Food Res Int ; 149: 110662, 2021 11.
Article em En | MEDLINE | ID: mdl-34600664
ABSTRACT
The rapid increase of genetically modified organisms (GMOs) entering the food and feed markets, and the contamination of donor (micro)organisms of transgenic elements make it more challenging for the existing GMO detection. In this study, we developed a high-throughput and contamination-removal GMO detection approach named as GmoDetector. GmoDetector targeted 64 common transgenic elements and 76 GMO-specific events collected from 251 singular GM events, and combined with next generation sequencing (NGS) and target enrichment technology to detect various GMOs. As a result, GmoDetector was able to exclude the donor (micro)organism contamination, and detect the authorized and unauthorized GMOs (UGMOs) in any forms of food or feed, such as processed or unprocessed. The sensitivity of GmoDetector is as low as 0.1% (GMO content), which has met the GMO labeling threshold for all countries. Therefore, GmoDetector is a robust tool for accurate and efficient detection of the authorized and UGMOs.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequenciamento de Nucleotídeos em Larga Escala Idioma: En Ano de publicação: 2021 Tipo de documento: Article