Evidence map›Paper›PMID 17567898›Full record

ArticleBMC biology2007

Design and applicability of DNA arrays and DNA barcodes in biodiversity monitoring.

Mehrdad Hajibabaei, Gregory A C Singer, Elizabeth L Clare, Paul D N Hebert

Abstract readComparative Study
In one paragraph

Article in BMC biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

44 citing papers in PubMed.

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  6. Genetic Diversity among SelectedPlants (Basel, Switzerland) · 2020
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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

4 authors.

Mehrdad HajibabaeiBiodiversity Institute of Ontario, Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada. mhajibab@uoguelph.ca
Gregory A C Singer
Elizabeth L Clare
Paul D N Hebert

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe rapid and accurate identification of species is a critical component of large-scale biodiversity monitoring programs. DNA arrays (micro and macro) and DNA barcodes are two molecular approaches that have recently garnered much attention. Here, we compare these two platforms for identification of an important group, the mammals.

resultsOur analyses, based on the two commonly used mitochondrial genes cytochrome c oxidase I (the standard DNA barcode for animal species) and cytochrome b (a common species-level marker), suggest that both arrays and barcodes are capable of discriminating mammalian species with high accuracy. We used three different datasets of mammalian species, comprising different sampling strategies. For DNA arrays we designed three probes for each species to address intraspecific variation. As for DNA barcoding, our analyses show that both cytochrome c oxidase I and cytochrome b genes, and even smaller fragments of them (mini-barcodes) can successfully discriminate species in a wide variety of specimens.

conclusionThis study showed that DNA arrays and DNA barcodes are valuable molecular methods for biodiversity monitoring programs. Both approaches were capable of discriminating among mammalian species in our test assemblages. However, because designing DNA arrays require advance knowledge of target sequences, the use of this approach could be limited in large scale monitoring programs where unknown haplotypes might be encountered. DNA barcodes, by contrast, are sequencing-based and therefore could provide more flexibility in large-scale studies.

Indexed as

BiodiversityAnimalsComputational BiologyCytochromes bDNA, MitochondrialElectron Transport Complex IVMammalsOligonucleotide Array Sequence AnalysisOligonucleotide ProbesSpecies SpecificityCytochromes bDNA, MitochondrialElectron Transport Complex IVOligonucleotide Probes

Identifiers

PMID17567898
PMCPMC1906742

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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.