Evidence map›Paper›PMID 28810845›Full record

ArticleBMC biotechnology2017

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

Doori Park, Su-Hyun Park, Yong Wook Ban, Youn Shic Kim, Kyoung-Cheul Park, Nam-Soo Kim, Ju-Kon Kim, Ik-Young Choi

Abstract read
In one paragraph

Article in BMC biotechnology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed.

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  18. Influence of transgenesis on genome variability in cucumber lines with aPhysiology and molecular biology of plants : an international journal of functional plant biology · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Doori ParkDepartment of Agriculture and Life Industry, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon, Gangwon, 24341, Republic of Korea.
Su-Hyun ParkGraduate School of International Agricultural Technology and Crop Biotech Institute/GreenBio Science and Technology, Seoul National University, 1447, Pyeongchang, Gangwon, 25354, Republic of Korea.
Yong Wook BanDepartment of Agriculture and Life Industry, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon, Gangwon, 24341, Republic of Korea.
Youn Shic KimGraduate School of International Agricultural Technology and Crop Biotech Institute/GreenBio Science and Technology, Seoul National University, 1447, Pyeongchang, Gangwon, 25354, Republic of Korea.
Kyoung-Cheul ParkDepartment of Agriculture and Life Industry, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon, Gangwon, 24341, Republic of Korea.
Nam-Soo KimDepartment of Molecular Bioscience, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon, Gangwon, 24341, Republic of Korea.
Ju-Kon KimGraduate School of International Agricultural Technology and Crop Biotech Institute/GreenBio Science and Technology, Seoul National University, 1447, Pyeongchang, Gangwon, 25354, Republic of Korea. jukon@snu.ac.kr.
Ik-Young ChoiDepartment of Agriculture and Life Industry, Kangwon National University, 1 Kangwondaehak-gil, Chuncheon, Gangwon, 24341, Republic of Korea. choii@kangwon.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetically 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.

methodsTo 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.

resultsHerein, 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.

conclusionNGS 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.

Indexed as

TransgenesBacillus thuringiensis ToxinsBacterial ProteinsChromosome MappingComputational BiologyCrops, AgriculturalDNA, BacterialEndotoxinsGene DosageGenome, PlantHemolysin ProteinsHigh-Throughput Nucleotide SequencingOryzaPlants, Genetically ModifiedWorkflowBacillus thuringiensis ToxinsBacterial ProteinsDNA, BacterialEndotoxinsHemolysin Proteinsinsecticidal crystal protein, Bacillus ThuringiensisT-DNABioinformaticsGenetically modified organism (GMO)GM riceGM safetyMolecular characterizationNext-generation sequencing (NGS)

Identifiers

PMID28810845
PMCPMC5558722

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.