Evidence map›Paper›PMID 24088728›Full record

ArticleScientific reports2013

Characterization of GM events by insert knowledge adapted re-sequencing approaches.

Litao Yang, Congmao Wang, Arne Holst-Jensen, Dany Morisset, Yongjun Lin, Dabing Zhang

Abstract read
In one paragraph

Article in Scientific reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

45 citing papers in PubMed.

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  17. 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

6 authors.

Litao Yang1] Collaborative Innovation center for biosafety of GMOs, National Center for Molecular Characterization of GMOs, School of Life Science and Biotechnology, Shanghai Jiao Tong University. 800 Dongchuan Road, Shanghai 200240. P. R. China [2].
Congmao Wang
Arne Holst-Jensen
Dany Morisset
Yongjun Lin
Dabing Zhang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Detection methods and data from molecular characterization of genetically modified (GM) events are needed by stakeholders of public risk assessors and regulators. Generally, the molecular characteristics of GM events are incomprehensively revealed by current approaches and biased towards detecting transformation vector derived sequences. GM events are classified based on available knowledge of the sequences of vectors and inserts (insert knowledge). Herein we present three insert knowledge-adapted approaches for characterization GM events (TT51-1 and T1c-19 rice as examples) based on paired-end re-sequencing with the advantages of comprehensiveness, accuracy, and automation. The comprehensive molecular characteristics of two rice events were revealed with additional unintended insertions comparing with the results from PCR and Southern blotting. Comprehensive transgene characterization of TT51-1 and T1c-19 is shown to be independent of a priori knowledge of the insert and vector sequences employing the developed approaches. This provides an opportunity to identify and characterize also unknown GM events.

Indexed as

Computational BiologyComputer SimulationDNA, PlantGenetic VectorsMutagenesis, InsertionalOryzaPlants, Genetically ModifiedPolymerase Chain ReactionSequence Analysis, DNATransgenesDNA, Plant

Identifiers

PMID24088728
PMCPMC3789143

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.