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Chapter 5
© 2012 Ramadan and Baeshen, licensee InTech. This is an open access chapter distributed under the terms
of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits
unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Biological Identifications Through DNA Barcodes
Hassan A. I. Ramadan and Nabih A. Baeshen
Additional information is available at the end of the chapter
http://dx.doi.org/10.5772/49967
1. Introduction
Although much biological research depends upon species diagnoses, taxonomic expertise is
collapsing. We are convinced that the sole prospect for a sustainable identification capability
lies in the construction of systems that employ DNA sequences as taxon ‘barcodes’. It was
established previously that the mitochondrial gene cytochrome c oxidase I (COI) can serve
as the core of a global bio- identification system for animals. A new tools were developed
recently to be complementary markers for (COI) DNA barcoding.
Species identification is essential in food quality control procedures or for the detection and
identification of animal material in food samples. Recent food scares e.g. avian flu and swine
flu, malpractices of some food producers and religious reasons have tremendously
reinforced public awareness regarding the composition of food products. However, because
labels do not provide sufficient guarantee about the true contents of a product, it is
necessary to identify and/or authenticate the components of processed food, thus protecting
both consumers and producers from illegal substitutions [1]. In addition, trade of
endangered species has contributed to severe depletion of biodiversity.
Numerous analytical methods that rely on protein analysis have been developed for species
identification, such as electrophoresis techniques [2], immunoassays [3] and liquid
chromatography [4]. However, these methods are of limited use in species identification. The
progress of molecular biology introduced a new approach, which is based on nucleotide
sequence diversities among species in particular regions of DNA [5–7]. The nucleotide regions
chosen for species identification were varied by researchers. Within vertebrates, a cytochrome
b (cyt b) gene in the mitochondrial DNA has been studied from multiple viewpoints including
the nucleotide diversity among species [6] and the availability of nucleotide sequence data for
references [5]. Many of the other regions studied are also located in the mtDNA. The coding
regions for 12S and 16S ribosomal RNA [8–10], and the noncoding D-loop region [7, 11, 12]
have shown their potential to be the targets for the species test.
Biodiversity Conservation and Utilization in a Diverse World
110
Although central to much biological research, the identification of species is often difficult.
DNA sequencing, with key sequences serving as a pattern ‘‘barcode’’, has therefore been
proposed as a technology that might expedite species identification [13].
DNA barcoding promises fast, accurate species identifications by focusing analysis on a
short standardized segment of the genome [14]. Several studies have now established that
sequence diversity in a 650-bp fragment of the mitochondrial gene cytochrome c oxidase I
(cox1; also referred to as COI) provides strong species-level resolution for varied animal
groups including birds [15], fishes [16] and Lepidoptera [17].
Besides the cox1 gene, other mitochondrial markers also have been widely sequenced across
vertebrates for their utility in phylogenetic or to complement cox1 in DNA barcoding.
In amphibians the 16S ribosomal RNA gene (16S) has been suggested as a complementary
DNA barcoding marker [18]. Another protein coding gene, cytochrome b, has also been
suggested as a marker to determine species boundaries [19, 20].
An attempt was made to present a phylogenetic systematic framework for an improved
barcoder as well as a taxonomic framework for interweaving classical taxonomy with the
goals of ‘DNA barcoding’ [21]. Another study showed that DNA arrays and DNA barcodes
are valuable molecular methods for biodiversity monitoring programs [22]. In this chapter
we introduce the use of specific fragments of mitochondrial ribosomal RNA from Egyptian
buffalo to be used as a perfect barcode for identification of closely related species. Also, we
will extend this study to include distantly species identification [23-24]. Our studies were
also extended for chickens and small organisms like mites to be studied by both nuclear and
mitochondrial markers. Identification of these mites is very important for biological control
programs.
All these methods could be used for global bio-identification system or forensic science
development.
2. Materials and methods
2.1. DNA purification
Genomic DNA was extracted from peripheral blood of Egyptian buffalo's and chickens by
using standard commercial Kit (Pure-gene Genomic DNA purification Kit) as recommended
by the manufacturer (www.gentra.com). In case of mites, Genomic DNA was extracted
using Capture Column kit method, total DNA was purified using generation DNA
purification system.
2.2. Primers used for amplifications of PCR specific fragments
2.2.1. D-loop primers
These primers yielded a PCR product of 1142 base pairs. This encompasses the whole of the
D-loop and includes flanking sequence at both ends [12].
Biological Identifications Through DNA Barcodes
111
IL0500: 5’AGGCATTTTCAGTGCCTTGC-3’
IL0501: 5’TAGTGCTAATACCAACGGCC-3’
Two additional new forward primers (SH-1 and SH-2) specific for buffalo were designed
inside the D-loop sequence to facilitate sequencing and correction processes.
SH-1: 5’ CCT CGC ATG TAC GGC ATA CA-3’
SH-2: 5’CAA CCC TTC AGG CAA GGA TC-3’
2.2.2. Primers used for amplification of specific fragments from mites
Two target DNA fragments of the predatory mite, A. swirskii were PCR amplified and
sequenced: a fragment in the central part of the mitochondrial cytochrome oxidase
subunit I gene (COI) and the fragment of the nuclear ribosomal transcribed spacers (ITS)
[25-26]. The COI primers were designed specifically for tetranychid mites. They were:
5’TGATTTTTTGGTCACCCAGAAG3’ and 5’TACAGCTCCTATAGATAAAAC 3'.
The ITS region was amplified using the primers 5’AGAGGAAGTAAAAGTCGTAACAAG
3' for the 3’ end of 18S rDNA and 5' ATATGCTTAAATTCAGGGGG 3’ for the 5' end of
the 28S.
2.2.3. Primers used for amplification of the first 539 base fragment of the D-loop region of
the birds
The conserved primer pair, L16750 (forward; 5’-AGG ACT ACG GCT TGA AAA GC-3’) and
H 547 (reverse; 5’- ATG TGC CTG ACC GAG GAA CAA G-3’) were used to amplify the first
539 base fragment of the D-loop region of the birds. The primer number refers to the
positions of the 3’ end of the primer in the reference sequence [27].
2.2.4. 12S primers
Primers specific for mitochondrial 12S rRNA gene were synthesized [23]:
5’-CAAACTGGGATTAGATACCCCACTAT-3’; 5’-AGGGTGACGGGCGGTGTGT-3’ and
directed towards the two conserved regions of the gene. The primers were synthesized by
Amersham Pharmacia Biotech (U.K.).
2.2.5. 16S primers
PCR amplification and direct sequencing With two universal primers (sense, 5’-
GTGCAAAGGTAGCATAATCA-3’ and antisense, 5’-TGTCCTGATCCAACATCGAG-3’)
directed toward conserved regions [24], the polymerase chain reaction was used to amplify
homologous segments of mitochondrial 16S rRNA from four animal species belonging to
family Bovidae, including river buffalo, cattle, sheep and goat.
Biodiversity Conservation and Utilization in a Diverse World
112
2.3. The amplification reaction
The amplification reaction used for amplification of the D-loop fragment was also used
(with little modifications in temperature cycling) in the other experiments according to the
conditions of each experiment.
The amplification reaction was carried out in a 25 μl reaction mixture consisting of 1.25 unit
Taq polymerase (DyNAzyme), 1X enzyme buffer (1X is 10 mM Tris-HCl, pH 8.8 at 25 0C, 1.5
mM MgCl2, 50 mM KCl and 0.1% Triton X-100) supplied by the manufacture, 1 μM of each
forward and reverse primer, 0.2 mM dNTPs and 100 ng of DNA. The reaction mixture was
overlaid with sterile mineral oil and was run in an MJ research PTC-100 Thermocycler. The
temperature cycling was as follows: 30 cycles of 45 seconds at 94°C; 1 minute at 58°C and 1
minute at 71°C, followed by a final extension at 71°C for 5 minutes. All PCR amplifications
included a negative control reaction which lacked template DNA. No product was seen in
any negative control. Small quantities of the reaction products (5 μl each) were used for
electrophoresis with an appropriate size marker on 1.5% agarose in 1X-Tris acetate buffer
(TAE).
After electrophoresis the gels were stained with ethidium bromide and were examined with
UV lamp at a wave length 312 nm to verify amplification of the chosen specific fragment.
The PCR products were purified using QIAquick PCR purification kit (Qiagen, Inc.) and the
resulting purified products were used in the subsequent sequencing reactions. Sequencing
was performed on an Applied Biosystems 310 genetic analyzer (Applied Biosystem) using
Big Dye terminator cycle sequencing ready reaction mixture according to manufacturer’s
instructions (Applied Biosystems).
2.4. Sequence analysis and multiple sequence alignment
Pairwise sequence alignments were carried out using NCBI-BLASTN 2.2.5 version & PSI
BLAST. Multiple sequence alignments were done using the MUSCLE 3.6 software and
CLUSTALW (1.82). Analysis, manipulation, conservation plots, positional entropy plot and
conserved region analysis was done using the BIOEDIT package. Variable sites were
extracted from the multiple sequence alignment using the MEGA 3.1 package [12].
2.5. Phylogenetic analysis
Phylogenetic model selection was done using the FINDMODEL server available from the
HCV LANL database at (http://hcv.lanl.gov/ /content/hcv-db/findmodel/). A Bayesian
phylogenetic tree was constructed by Markov chain Monte Carlo (MCMC) method as
implemented in the MR BAYES 3.1 package using the Hasegawa-Kishino-Yano plus Gamma
model HKY+G substitution model with an invariant four category gamma distribution
among sites. A 50% consensus tree was generated and the analysis was repeated two times.
Maximum parsimony tree was conducted using MEGA version 4, with 1000 bootstraps for
reliability.
