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7 Limitations of DNA Barcoding Employing mtCOI
K.B. Rebijith et al.
Planococcus kraunhiae (12)
Planococcus lilacinus (6)
Planococcus ficus (4)
Planococcus citri (9)
Crisicoccus pini (2)
Atrococcus paludinus (3)
Pseudococcus calceolariae (7)
Dysmicoccus lepelleyi (7)
Pseudococcus cryptus (5)
Pseudococcus com stocki (9)
Paracoccus marginatus (7)
Balanococcus takahashii (2)
Pseudococcus jackbeardsleyi (8)
Pseudococcus viburni (3)
Crisicoccus matsumotoi (19)
Dysmicoccus brevipes (3)
Dysmicoccus neobrevipes (15)
Maconellicoccus hirsutus (4)
Palmicultor lumpurensis (3)
Ferrisia virgata (2)
Ferrisia malvastra (4)
Dysmicoccus wistariae (2)
Pseudococcus longispinus (12)
Phenacoccus aceris (11)
Heliococcus kurilensis (7)
Phenacoccus solani (9)
Fig. 5.3 NJ tree with bootstrap support (1000 replicates)
showing clusters of species for mtCOI sequences. Distinct
clades for 29 species of aphids can be seen in the ﬁgure, in
which four species, namely Planococcus ﬁcus, Crisicoccus
matsumotoi, Phenacoccus solani and P. aceris showing
two distinct groups with >90 % bootstrap support. The
numbers indicated in brackets represent the individuals
analysed in the corresponding species
sible to estimate species boundaries which
would have been estimated from a broader
• Mutation rate: For the DNA barcode to be
used as standalone, there should be a consis-
tent mutation rate, such as the proposed 2–3 %
divergence to correlate with species limit on a
consistent basis. Speciation, uniquely driven
by changes in mtDNA or speciation event,
necessarily alters the mtDNA haplotypes.
Molecular Identiﬁcation of Mealybugs
Fig. 5.4 Neighbour joining (NJ) showing intra-speciﬁc variation in the barcode region for four species of mealybugs,
namely Planococcus ﬁcus (a), Phenacoccus solani (b), Crisicoccus matsumotoi (c) and P. aceris (d)
• Heteroplasmy: This refers to the classical
view of mitochondria functionally haploid
with multiple identical copies. However, single nucleotide differences are common in
some species and are also abundant in some,
especially at the restriction sites.
• Compounding genetic factors: Coinheritance
factors that bias single mitochondrial inheritance and most obvious are (a) mitochondrial
selection either on the barcoding gene itself or
on the other linked genes; (b) cytoplasmically
inherited bacteria like Wolbachia and some
Rickettsia which alter the inheritance factors
(Rubinoff et al. 2006).
• Identiﬁcation depends on the intra- and interspeciﬁc genetic variations.
• Difﬁcult to resolve, recently diverged species
that arose through hybridization.
• No single gene is conserved in all domains of
life and exhibit enough sequence divergence
for species discrimination.
There are about 52 million sequence records
available currently, and it is expected that the
barcoding initiative of the animal kingdom will
produce about 100 million sequences and will be
available through GenBank.
An international database called BOLD
(Barcode of Life Data system) organizes the
sequence data on species identiﬁcation, which
was initially developed as an informatics work
bench for a single, high-volume DNA barcode
facility. Later, the same has been selected by
the Canadian Barcode of Life Network (www.
bolnet.ca) to barcode all the eukaryotic life of
Canada, and subsequently, it has been adopted
by major barcode communities like birds,
ﬁshes, lepidoptera, etc. BOLD provides an integrated bioinformatics platform that supports all
phases of analytical pathway from specimen
collection to a tightly validated barcode library.
It also provides a vehicle for collaboration
across research communities by coupling ﬂexible security and data entry features with web
based delivery. A copy of all sequences in
BOLD is also sent to NCBI, DDBJ, and EMBL
as soon as the results are ready for public
K.B. Rebijith et al.
Other Targets for Molecular
Identiﬁcation of Insects
Ribosomes are the major components of cells
that are involved in translating the mRNA into
proteins. Ribosomes consist of both proteins
and RNAs. The ribosomal RNA (rRNA) regions
that are conserved and more variable regions
can serve as both slow and fast clocks in identifying and unravelling the molecular phylogeny.
In eukaryotes (including insects), the genes
encoding both 18S and 28S rRNA are clustered
as tandem repeats in the nucleolus; in most animals, there are 100–500 copies of rDNA in the
nuclear genome in tandemly repeated transcription units. The repeated transcription unit is
composed of a leader promoter region known as
external transcribed spacer region (ETS), 18S
rDNA coding region, internal transcribed spacer
region (ITS), 28S rDNA coding region and an
internal non-coding transcribed spacer region
(IGS). In addition to the above, R1 and R2 retro
transposable elements are found in speciﬁc
locations (Fig. 5.5).
Different portions of the repeated transcription units evolve at different rates in the nuclear
genome; a higher degree of polymorphism is
found in the non-coding segments (IGS, ITS,
ETS), and the most variable part of the repeated
unit is IGS, which contains reiterated sub-repeats
ranging from 50 to several hundred base pairs in
length. The coding regions of the repeated unit
change relatively less and can be used for systematic studies of higher taxa or for ancient lineages. Ribosomal RNA genes undergo concerted
evolution so that the sequence similarity of the
members of an RNA family is expected to be
greater within species than between species.
Fig. 5.5 Gene organization of ribosomal genes
In addition to the above reterotransposons, R1
and R2 have been in the 28S rRNA genes of most
insects, are associated with arthropods, and are
usually precisely located at the same nucleotide
position within the 28S rRNA gene. Most of the
R2 elements are located about 74 bp upstream
from the site of R1 insertions. R1 and R2 do not
have long terminal repeats and block the production of functional rRNA, since there are many
rRNA genes, and R2 are kept from invading by
miRNA/siRNA. Usually, R1 and R2 do not have
accumulated mutations that would make them
Satellite DNA may consist of a large fraction of
the total DNA in an insect. Microsatellites are
usually species speciﬁc, and evolve at very high
rates. Satellite DNA can also be used for species
identiﬁcation and analysis of populations.
Nuclear Protein Coding Genes
A variety of protein coding loci have been used
in molecular systematics, and some of them are
1. alpha amylase 2. acetyl choline esterase 3.
actin 4. alcohol dehydrogenase 5. arylphorin
6. cecropin 7. chorin 8. dopa carbaxylase 9.
elongation factor 1 alpha 10. esterase 11. glycerol 3 phosphate 12. glycerol 6 phosphate
dehydrogenase 13. guanylate cyclase 14. globin family genes 15. histones 1 and 4 16.
hunch back 17. kruppel 18. luciferase 19.
lysozyme intron 20. myosin alkali light
chain intron 21. nullo 22. opsin 23. period 24.
Molecular Identiﬁcation of Mealybugs
phosphogluco isomerase 25. phosphoenol
pyruate carboxy kinase 26. prune 27. copper,
zinc superoxide dismutase 28. sodium channel
para locus I 29. snail 30. timeless 31. triosephosphate isomerase 32. vestigial 33. white
34. wingless 35. xanthine dehydrogenase 36.
yolk protein 1 and 2 37. zeste.
• May be heterozygous and present in low copy
• Many genes contain large introns that makes it
difﬁcult to amplify more than one exon.
• Many single-copy loci are actually are present
in more than one copy.
• Pseudogenes may create problem if comparisons are made inadvertently.
Even with all the limitations, the molecular
identiﬁcation of insects employing mtCOI is
gaining momentum, and as of now it can be an
effective adjunct tool for the integrated taxonomy. Many barcoding initiatives are beginning to
take shape, such as the recent initiative on
Barcoding of butterﬂies of India funded by the
Department of Biotechnology. With the increase
in international trade on agricultural produces
where the danger of introduction of invasive species looms large, DNA barcoding is going to play
a vital role in the quick identiﬁcation of insectpests at the port of entry. As ambitiously envisaged, the development and deployment of the
hand-held sequencer, which is supported by the
global networked database, is going to revolutionize the way we identify insects that are
already described, along with the new ones.
1. The relationship of six mealybug species (Pl.
citri, Pl.ﬁcus, P.ovae, Ps.longispinus, Ps.vibruni,
Ph.aceris) was studied using randomly ampliﬁed
polymorphic DNA-polymerase chain reaction
(RAPD-PCR) in Turkey. Cluster analyses of
RAPD data clearly separated the species into
two groups (Serce et al. 2007).
2. Seven species of mealybugs (Ps maritimus,
Ps.vibruni. Ps.longispinus, Ps.calceolariae,
Pl.ﬁcus, Pl.citri, Ferrisia gilli Gullan) were
identiﬁed using a Multiplex PCR based on the
mitochondrial cytochrome oxidase subunit
gene (Daane et al. 2011).
3. There was a slight difference in morphological characters in the populations of
Planococcus ﬁcus, indicating that there are
two different populations of the same species
in Tunisian vineyards. Likewise, in the molecular analyses, two separate clades were
revealed in the neighbour-joining phylogenetic tree, supporting the morphological studies and suggesting there are two distinct
populations of grape vine in Tunisia, which
might be two different biotypes (Mansour
et al. 2012).
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