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

Overview of attention for article published in BMC Biotechnology, August 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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2 patents

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Title
A bioinformatics approach for identifying transgene insertion sites using whole genome sequencing data
Published in
BMC Biotechnology, August 2017
DOI 10.1186/s12896-017-0386-x
Pubmed ID
Authors

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

Abstract

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. 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. 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. 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 90 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 18 20%
Researcher 17 19%
Student > Ph. D. Student 14 16%
Student > Master 5 6%
Student > Postgraduate 4 4%
Other 9 10%
Unknown 23 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 38%
Biochemistry, Genetics and Molecular Biology 20 22%
Computer Science 3 3%
Immunology and Microbiology 2 2%
Engineering 2 2%
Other 5 6%
Unknown 24 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 June 2022.
All research outputs
#4,145,517
of 22,668,244 outputs
Outputs from BMC Biotechnology
#211
of 934 outputs
Outputs of similar age
#74,345
of 315,687 outputs
Outputs of similar age from BMC Biotechnology
#2
of 10 outputs
Altmetric has tracked 22,668,244 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 934 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.7. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,687 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.