Literature DB >> 28131814

Molecular characterization of genetically-modified crops: Challenges and strategies.

Rong Li1, Sheng Quan2, Xiaofang Yan3, Sukumar Biswas2, Dabing Zhang1, Jianxin Shi4.   

Abstract

Molecular characterization lays a foundation for safety assessment and subsequent monitoring of genetically modified (GM) crops. Due to the target-specific nature, conventional polymerase chain reaction (PCR)-based methods cannot comprehensively detect unintended gene insertions, let alone unknown GM events. As more and more new developed GM crops including new plant breeding technology (NPBT) generated crops are in the pipeline for commercialization, alternative -omics approaches, particularly next generation sequencing, have been developed for molecular characterization of authorized or unauthorized GM (UGM) crops. This review summarizes first those methods, addresses their challenges, and discusses possible strategies for molecular characterization of engineered crops generated by NPBT, highlighting needs for a global information-sharing database and cost-effective, accurate and comprehensive molecular characterization approaches.
Copyright © 2017 Elsevier Inc. All rights reserved.

Keywords:  Cisgenesis; Genome editing; Next generation sequencing; T-DNA; Transgenesis

Mesh:

Year:  2017        PMID: 28131814     DOI: 10.1016/j.biotechadv.2017.01.005

Source DB:  PubMed          Journal:  Biotechnol Adv        ISSN: 0734-9750            Impact factor:   14.227


  10 in total

1.  Using problem formulation to clarify the meaning of weight of evidence and biological relevance in environmental risk assessments for genetically modified crops.

Authors:  Alan Raybould; Karen Holt; Ian Kimber
Journal:  GM Crops Food       Date:  2019-06-11       Impact factor: 3.074

2.  Problem formulation and phenotypic characterisation for the development of novel crops.

Authors:  Alan Raybould
Journal:  Transgenic Res       Date:  2019-08       Impact factor: 2.788

3.  NGS sequencing reveals that many of the genetic variations in transgenic rice plants match the variations found in natural rice population.

Authors:  Doori Park; Su-Hyun Park; Youn Shic Kim; Beom-Soon Choi; Ju-Kon Kim; Nam-Soo Kim; Ik-Young Choi
Journal:  Genes Genomics       Date:  2018-11-07       Impact factor: 1.839

Review 4.  Genome editing in livestock: Are we ready for a revolution in animal breeding industry?

Authors:  Jinxue Ruan; Jie Xu; Ruby Yanru Chen-Tsai; Kui Li
Journal:  Transgenic Res       Date:  2017-11-01       Impact factor: 2.788

5.  A paired-end whole-genome sequencing approach enables comprehensive characterization of transgene integration in rice.

Authors:  Wenting Xu; Hanwen Zhang; Yuchen Zhang; Ping Shen; Xiang Li; Rong Li; Litao Yang
Journal:  Commun Biol       Date:  2022-07-05

6.  LIFE-Seq: a universal Large Integrated DNA Fragment Enrichment Sequencing strategy for deciphering the transgene integration of genetically modified organisms.

Authors:  Hanwen Zhang; Rong Li; Yongkun Guo; Yuchen Zhang; Dabing Zhang; Litao Yang
Journal:  Plant Biotechnol J       Date:  2022-02-01       Impact factor: 13.263

7.  Sequencing of two transgenic early-flowering poplar lines confirmed vector-free single-locus T-DNA integration.

Authors:  Birgit Kersten; Ana Paula Leite Montalvão; Hans Hoenicka; Cristina Vettori; Donatella Paffetti; Matthias Fladung
Journal:  Transgenic Res       Date:  2020-04-30       Impact factor: 2.788

Review 8.  Safety Assessment of Genetically Modified Feed: Is There Any Difference From Food?

Authors:  Paula A Giraldo; Hiroshi Shinozuka; German C Spangenberg; Noel O I Cogan; Kevin F Smith
Journal:  Front Plant Sci       Date:  2019-12-11       Impact factor: 5.753

9.  Development and performance evaluation of whole-genome sequencing with paired-end and mate-pair strategies in molecular characterization of GM crops: One GM rice 114-7-2 line as an example.

Authors:  Hanwen Zhang; Yuchen Zhang; Wenting Xu; Rong Li; Dabing Zhang; Litao Yang
Journal:  Food Chem (Oxf)       Date:  2021-12-07

10.  Large-scale phenomics analysis of a T-DNA tagged mutant population.

Authors:  Hshin-Ping Wu; Fu-Jin Wei; Cheng-Chieh Wu; Shuen-Fang Lo; Liang-Jwu Chen; Ming-Jen Fan; Shu Chen; Ien-Chie Wen; Su-May Yu; Tuan-Hua David Ho; Ming-Hsin Lai; Yue-Ie C Hsing
Journal:  Gigascience       Date:  2017-08-01       Impact factor: 6.524

  10 in total

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