Evidence map›Paper›PMID 28876418›Full record

ArticleRevista do Instituto de Medicina Tropical de Sao Paulo2017

A conventional PCR for differentiating common taeniid species of dogs based on in silico microsatellite analysis.

Saeedeh Shamsaddini, Mohammad Ali Mohammadi, Seyed Reza Mirbadie, Sima Rostami, Mansoureh Dehghani, Balal Sadeghi, Majid Fasihi Harandi

Abstract read
In one paragraph

Article in Revista do Instituto de Medicina Tropical de Sao Paulo, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Quantifying the load ofJournal of parasitic diseases : official organ of the Indian Society for Parasitology · 2020
    Article
  3. Article
4 · The record

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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

7 authors.

Saeedeh ShamsaddiniKerman University of Medical Sciences, Research Center for Hydatid Disease in Iran, Kerman, Iran.
Mohammad Ali MohammadiKerman University of Medical Sciences, Sirjan School of Medical Sciences, Sirjan, Iran.
Seyed Reza MirbadieShahroud University of Medical Sciences, School of Medicine, Shahroud, Iran.
Sima RostamiAlborz University of Medical Sciences, Dietary Supplements and Probiotics Research Center, Karaj, Iran.
Mansoureh DehghaniKerman University of Medical Sciences, Research Center for Hydatid Disease in Iran, Kerman, Iran.
Balal SadeghiShahid Bahonar University of Kerman, Faculty of Veterinary Medicine, Department of Food Hygiene and Public Health, Kerman, Iran.
Majid Fasihi HarandiKerman University of Medical Sciences, Research Center for Hydatid Disease in Iran, Kerman, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Canine taeniids are among the major tapeworms with remarkable medical and economic significance. Reliable diagnosis and differentiation of dog taeniids using simple and sensitive tools are of paramount importance for establishing an efficient surveillance system. Microsatellites as abundant unique tandem repeats of short DNA motifs are useful genetic markers for molecular epidemiological studies. The purpose of the present study was to find a primer pair for rapid differentiation of major tapeworms of dogs, Taenia hydatigena, T. multiceps, T. ovis and Echinococcus granulosus, by screening existing nucleotide data. All the mitochondrial genome records as well as non-coding ITS1 sequences of Taeniidae species were downloaded from Nucleotide database from NCBI. For prediction and analysis of potential loci of STR/SSR in ITS1 as well as mitochondrial regions, we used ChloroMitoSSRDB 2.0 and GMATo v1.2. software. Different tapeworm species were categorized according to different motif sequences and type and size of each microsatellite locus. Three primer sets were designed and tested for differentiating taeniid species and evaluated in a conventional PCR system. Four taeniid species were successfully differentiated using a primer pair in a simple conventional PCR system. We predicted 2-19 and 1-4 microsatellite loci in ITS1 and mitochondrial genome, respectively. In ITS1, 41 Di and 21 Tri motifs were found in the taeniids while the majority of the motifs in the mitochondrial genome were Tetra (89) and Tri (70). It is documented that the number and diversity of microsatellite loci is higher in nuclear ITS1 region than mostly coding mitochondrial genome.

Indexed as

Microsatellite RepeatsAnimalsDNA PrimersDogsMitochondriaPolymerase Chain ReactionSheepTaeniaDNA Primers

Identifiers

PMID28876418
PMCPMC5587035

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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.