Evidence map›Paper›PMID 25343255›Full record

ArticlePloS one2014

Molecular inversion probe: a new tool for highly specific detection of plant pathogens.

Han Yih Lau, Ramkumar Palanisamy, Matt Trau, Jose R Botella

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

4 authors.

Han Yih LauPlant Genetic Engineering Laboratory, School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia; Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, Queensland, Australia.
Ramkumar PalanisamyAustralian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, Queensland, Australia.
Matt TrauAustralian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, Queensland, Australia.
Jose R BotellaPlant Genetic Engineering Laboratory, School of Agriculture and Food Sciences, University of Queensland, Brisbane, Queensland, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly specific detection methods, capable of reliably identifying plant pathogens are crucial in plant disease management strategies to reduce losses in agriculture by preventing the spread of diseases. We describe a novel molecular inversion probe (MIP) assay that can be potentially developed into a robust multiplex platform to detect and identify plant pathogens. A MIP has been designed for the plant pathogenic fungus Fusarium oxysporum f.sp. conglutinans and the proof of concept for the efficiency of this technology is provided. We demonstrate that this methodology can detect as little as 2.5 ng of pathogen DNA and is highly specific, being able to accurately differentiate Fusarium oxysporum f.sp. conglutinans from other fungal pathogens such as Botrytis cinerea and even pathogens of the same species such as Fusarium oxysporum f.sp. lycopersici. The MIP assay was able to detect the presence of the pathogen in infected Arabidopsis thaliana plants as soon as the tissues contained minimal amounts of pathogen. MIP methods are intrinsically highly multiplexable and future development of specific MIPs could lead to the establishment of a diagnostic method that could potentially screen infected plants for hundreds of pathogens in a single assay.

Indexed as

Molecular Probe TechniquesArabidopsisBiological AssayDNA, FungalDNA, PlantFusariumLimit of DetectionMolecular ProbesPlant DiseasesReal-Time Polymerase Chain ReactionDNA, FungalDNA, PlantMolecular Probes

Identifiers

PMID25343255
PMCPMC4208852

What OpenQuestion holds

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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.