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A bioinformatics approach for identifying transgene insertion sites using whole genome sequencing data

Cited 20 time in Web of Science Cited 21 time in Scopus
Authors
Park, Doori; Park, Su-Hyun; Ban, Yong Wook; Kim, Youn Shic; Park, Kyoung-Cheul; Kim, Nam-Soo; Kim, Ju-Kon; Choi, Ik-Young
Issue Date
2017-08-15
Publisher
BioMed Central
Citation
BMC Biotechnology, 17(1):67
Keywords
Genetically modified organism (GMO)GM riceNext-generation sequencing (NGS)Molecular characterizationGM safetyBioinformatics
Description
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Abstract
Abstract

Background
Genetically modified crops (GM crops) have been developed to improve the agricultural traits of modern crop cultivars. Safety assessments of GM crops are of paramount importance in research at developmental stages and before releasing transgenic plants into the marketplace. Sequencing technology is developing rapidly, with higher output and labor efficiencies, and will eventually replace existing methods for the molecular characterization of genetically modified organisms.

Methods
To detect the transgenic insertion locations in the three GM rice gnomes, Illumina sequencing reads are mapped and classified to the rice genome and plasmid sequence. The both mapped reads are classified to characterize the junction site between plant and transgene sequence by sequence alignment.

Results
Herein, we present a next generation sequencing (NGS)-based molecular characterization method, using transgenic rice plants SNU-Bt9–5, SNU-Bt9–30, and SNU-Bt9–109. Specifically, using bioinformatics tools, we detected the precise insertion locations and copy numbers of transfer DNA, genetic rearrangements, and the absence of backbone sequences, which were equivalent to results obtained from Southern blot analyses.

Conclusion
NGS methods have been suggested as an effective means of characterizing and detecting transgenic insertion locations in genomes. Our results demonstrate the use of a combination of NGS technology and bioinformatics approaches that offers cost- and time-effective methods for assessing the safety of transgenic plants.
ISSN
1472-6750
Language
English
URI
https://hdl.handle.net/10371/137430
DOI
https://doi.org/10.1186/s12896-017-0386-x
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Graduate School of International Agricultural Technology (국제농업기술대학원)Dept. of International Agricultural Technology (국제농업기술학과)Journal Papers (저널논문_국제농업기술학과)
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