Evidence map›Paper›PMID 26274489›Full record

ArticlePloS one2015

Molecular Detection of 10 of the Most Unwanted Alien Forest Pathogens in Canada Using Real-Time PCR.

Josyanne Lamarche, Amélie Potvin, Gervais Pelletier, Don Stewart, Nicolas Feau, Dario I O Alayon, Angela L Dale, Aaron Coelho, Adnan Uzunovic, Guillaume J Bilodeau and 3 more

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Rapid Detection ofPlants (Basel, Switzerland) · 2021
    Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Pest categorisation ofEFSA journal. European Food Safety Authority · 2018
    Article
  16. Article
  17. Article
  18. Genome sequences of sixGenomics data · 2016
    Article
  19. Scaling up discovery of hidden diversity in fungi: impacts of barcoding approaches.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2016
    Review
  20. Article
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

13 authors.

Josyanne LamarcheNatural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada.
Amélie PotvinNatural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada.
Gervais PelletierNatural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada.
Don StewartNatural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada.
Nicolas FeauDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada.
Dario I O AlayonDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada.
Angela L DaleDepartment of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada; FPInnovations, Vancouver, BC, Canada.
Aaron CoelhoFPInnovations, Vancouver, BC, Canada.
Adnan UzunovicFPInnovations, Vancouver, BC, Canada.
Guillaume J BilodeauCanadian Food Inspection Agency, Pathogen Identification Research Laboratory (PIRL), Ottawa, ON, Canada.
Stephan C BrièreCanadian Food Inspection Agency, Pathogen Pathology Laboratory (PPL), Ottawa, ON, Canada.
Richard C HamelinNatural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada; Department of Forest and Conservation Sciences, Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada.
Philippe TanguayNatural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Invasive alien tree pathogens can cause significant economic losses as well as large-scale damage to natural ecosystems. Early detection to prevent their establishment and spread is an important approach used by several national plant protection organizations (NPPOs). Molecular detection tools targeting 10 of the most unwanted alien forest pathogens in Canada were developed as part of the TAIGA project (http://taigaforesthealth.com/). Forest pathogens were selected following an independent prioritization. Specific TaqMan real-time PCR detection assays were designed to function under homogeneous conditions so that they may be used in 96- or 384-well plate format arrays for high-throughput testing of large numbers of samples against multiple targets. Assays were validated for 1) specificity, 2) sensitivity, 3) precision, and 4) robustness on environmental samples. All assays were highly specific when evaluated against a panel of pure cultures of target and phylogenetically closely-related species. Sensitivity, evaluated by assessing the limit of detection (with a threshold of 95% of positive samples), was found to be between one and ten target gene region copies. Precision or repeatability of each assay revealed a mean coefficient of variation of 3.4%. All assays successfully allowed detection of target pathogen on positive environmental samples, without any non-specific amplification. These molecular detection tools will allow for rapid and reliable detection of 10 of the most unwanted alien forest pathogens in Canada.

Indexed as

CanadaDNA, FungalForestsFungiMycological Typing TechniquesPhylogenyReal-Time Polymerase Chain ReactionSensitivity and SpecificityTreesDNA, Fungal

Identifiers

PMID26274489
PMCPMC4537292

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.