MORPHOLOGY, SYSTEMATICS, EVOLUTION
DNA Barcodes Can Distinguish Species of Indian Mosquitoes
(Diptera: Culicidae)
N. PRADEEP KUMAR,1 A. R. RAJAVEL, R. NATARAJAN,
AND
P. JAMBULINGAM
Vector Control Research Centre (Indian Council of Medical Research), Medical Complex, Indira Nagar,
Pondicherry, 605006 India
J. Med. Entomol. 44(1): 1Ð7 (2007)
KEY WORDS DNA barcodes, Culicidae, taxonomy, India
Description and study of biodiversity is an important
aspect to understand the intricate evolutionary trends
of life. Linnaean classiÞcation of animals and plants
remains as an important step made toward this goal,
and with that commenced the systematics based on
morphological characteristics, which is being followed
for more than two centuries. However, only ⬇10% of
extant species on earth (10 Ð15 million) are known to
science so far (Besansky et al. 2003, Pennisi 2003).
Recent studies on DNA-based approaches show a
promising trend in the rapid description of biodiversity (Hebert et al. 2003a; Hebert and Gregory 2005).
HebertÕs approach to DNA barcode the entire animal
kingdom based on single gene could be advantageous,
being economic and practicable, provided the analysis
of the DNA sequences of this gene may yield a useful
tool for species identiÞcation in different species of
the Animal Kingdom. The mitochondrial genome was
selected for this approach, owing to its advantages
such as maternal lineage, lack of recombination, lack
of “indels,” and higher mutation rates (Saccone et al.
1999). Among the mitochondrial genes, cytochrome c
oxidase subunit 1 (COI) is reported to be the most
conserved gene in the amino acid sequences and
hence has distinct advantage for taxonomic studies
(Knowlton and Weigt 1998). However, differences of
opinion exist in adopting this technology toward spe1
Corresponding author, e-mail: kumarnp@yahoo.com.
cies identiÞcation, and the ongoing studies on the
construction of barcodes of life (Ballard and Whitlock
2004, CBOL 2005). So far, this methodology had been
used to testify the identiÞcation of widely varied animals as Lepidoptera (phylum Invertebrata, class Insecta) (Hebert et al. 2003a,b, 2004a; Hajibabaei et al.
2006), birds (phylum Vertebrata, class Aves) (Hebert
et al. 2004b), and tachinid parasitoids successfully.
Also, this methodology is being currently followed for
barcoding animals of different groups such as Þshes
and primates (CBOL 2005, Lorenz et al. 2005).
However, no studies exist on the utility of DNA
barcodes for identiÞcation of mosquitoes, which comprise ⬇3,500 species globally. The morphological identiÞcation keys used currently for identiÞcation of mosquitoes are mainly speciÞc to few developmental
stages (imaginal and fourth instars) only, which makes
it difÞcult to identify other stages of development
collected in the Þeld, without rearing them in the
laboratory. Also, many adult specimens collected in
routine disease surveillance programs get damaged
(they loose important identiÞcation characteristics
such as bristles and scales) and hence are impossible
to identify. In addition, existence of sibling species has
further complicated the species identiÞcation of mosquitoes. These sibling species are morphologically indistinguishable and could be identiÞed only by cytotaxonomically using polytene chromosomes, speciÞc
to certain tissues in particular developmental stages.
0022-2585/07/0001Ð0007$04.00/0 䉷 2007 Entomological Society of America
Downloaded from http://jme.oxfordjournals.org/ by guest on January 17, 2017
ABSTRACT Species identiÞcation of mosquitoes (Diptera: Culicidae) based on morphological
characteristics remains often difÞcult in Þeld-collected mosquito specimens in vector-borne disease
surveillance programs. The use of DNA barcodes has been proposed recently as a tool for identiÞcation
of the species in many diverse groups of animals. However, the efÞcacy of this tool for mosquitoes
remains unexplored. Hence, a study was undertaken to construct DNA barcodes for several species
of mosquitoes prevalent in India, which included major vector species. In total, 111 specimens of
mosquitoes belonging to 15 genera, morphologically identiÞed to be 63 species, were used. This
number also included multiple specimens for 22 species. DNA barcode approach based on DNA
sequences of mitochondrial cytochrome oxidase gene sequences could identify 62 species among
these, in conÞrmation with the conventional taxonomy. However, two closely related species, Ochlerotatus portonovoensis (Tiwari & Hiriyan) and Ochlerotatus wardi (Reinert) could not be identiÞed
as separate species based on DNA barcode approach, their lineages indicating negligible genetic
divergence (Kimura two-parameter genetic distance ⫽ 0.0043).
2
JOURNAL OF MEDICAL ENTOMOLOGY
Hence, standardization of tools that could identify
mosquito species even from a small piece of tissue
from any developmental stage would be of importance
for the taxonomy of mosquitoes. Construction of DNA
barcodes for each species of mosquito would provide
an important tool for identiÞcation of mosquito species and may enable description of the species biodiversity of this important group of insects. Here, we
present the Þrst report on construction of DNA barcodes for 63 species of mosquito species prevalent in
India. Multiple specimens, collected from different
regions of the country also were included in the study.
Together, data on 111 DNA sequences of mosquito
specimens collected from different regions of India
was used in the study.
Materials and Methods
Þnal extension at 72⬚C for 10 min. The 50-␮l reaction
included 1.5 U of Thermus aquaticus polymerase, 5 ␮l
of 10⫻ PCR buffer, 2.5 mM magnesium chloride, 2.5 ␮l
of Q solution (QIAGEN GmbH, Hilden, Germany),
and 0.5 ␮l of 10 pmol each of forward and reverse
primers, along with the DNA of the mosquito species.
A Blast search with the conserved DNA primers proposed by Hebert et al. (2003a) did not yield desirable
similarity for different sequences of COI region of
mosquitoes available with the GenBank. Hence, initially the primer set C1J-1718 (forward) and C1N-2191
(reverse) described by Simon et al. 1994 was used in
the study. However, this DNA primer set could amplify only ⬇500 bp of COI DNA, and there was difÞculty in amplifying COI region of different genera
used in the study. Hence, as proposed in the DNA
Primer Design section of Laboratory Protocol for COI
AmpliÞcation (CBOL 2005), a consensus DNA primer
which could amplify ⬇700 bp of the COI was designed
using Primer3 software (Whitehead/MIT Center for
Genome Research, Cambridge, MA). Because the ampliÞed product of these DNA primers spans the region
ampliÞed by the earlier primers (Simon et al. 1994)
and that of HebertÕs 648-bp region, this DNA primer
set was used subsequently in the study. Details of both
the primer sets used in the study are as follows: 1)
DNA primers (Simon et al. 1994): forward primer,
5⬘-GGAGGATTTGGAAATTGATTAGTT-3⬘ and reverse primer, 5⬘-CCCGGTAAAATTAAAATATAAACTTC-3⬘; and 2) DNA primers designed in the
current study: forward primer, 5⬘-GGATTTGGAAATTGATTAGTTCCTT-3⬘ and reverse primer, 5⬘
AAAAATTTTAATTCCAGTTGGAACAGC 3⬘. These
DNA primers were custom synthesized by Metabion
(Martinsried, Germany) and were high-performance
liquid chromatography puriÞed.
DNA Sequencing and Analysis. The ampliÞed fragments were run on a 1% agarose gel to check the
integrity of the fragments and the PCR product was
puriÞed by QIAGEN GmbH PCR puriÞcation kit. The
puriÞed products were eluted to 20 ␮l of deionized
water, and a portion of it was lyophilized in a Speed
Vac concentrator (Thermo Electron Corporation,
Waltham, MA) and was shipped to MWG (Edersberg,
Germany/Microsynth, Balgach, Switzerland) for custom sequencing. Both reads (from forward primer as
well as reverse primer) were done, and the sequences
were analyzed as follows. The DNA sequences were
subjected to alignment using ClustalW. Sequence divergences among individuals were quantiÞed by using
the Kimura two-parameter distance model (Kimura
1980). A neighborhood joining (NJ) tree of K2P distances was created to provide a graphic representation
of the clustering pattern among different species (Saitou and Nei 1987, Hajibabaei et al. 2006). These analyses of the sequences were conducted using MEGA
version 3.1 software (Kumar et al. 2004).
Results and Discussion
All DNA extractions were done using adults, of
which 70 were female and 41 were male. Of these
Downloaded from http://jme.oxfordjournals.org/ by guest on January 17, 2017
Mosquito Specimens. Mosquito specimens used for
constructing DNA barcodes were from collections
made from different states for mosquito biodiversity
study in India. Larval and adult collections of mosquitoes were done in the Þeld. When larvae were
collected, they were reared individually to adults, and
associated larval and pupal skins were mounted. The
emerged adults were identiÞed morphologically and
assigned a museum identiÞcation number and were
used for DNA extraction with the corresponding larval
and pupal skins deposited as voucher specimens in the
Vector Control Research Centre Mosquito Museum
(Rajavel et al. 2005). When collected as adults, females were isolated for oviposition, and the F1 generation adults were used for DNA extraction, with the
corresponding larval and pupal skins deposited in the
museum. In a few adults, DNA was extracted using legs
of one side, with the adult retained in the museum as
voucher specimen. When male specimens were used
for DNA extraction, the genitalia was mounted and
deposited in the museum. Species identiÞcation was
done based on taxonomic keys (Christophers 1933,
Barraud 1934, Huang 1972, Sirivanakarn 1976, Harrison 1980, Reuben et al. 1994). In sibling species complexes, specimens used were sensu lato, except for
Anopheles subpictus complex, which included both
sensu lato and morphologically identiÞed specimens
(Suguna et al. 1994).
DNA Extraction and Polymerase Chain Reaction
(PCR). Total DNA from individual mosquitoes was
extracted following a modiÞed method proposed by
Collins et al. (1987). The DNA were pelleted, dissolved in water, and subjected to a phenol chloroform
isoamyl extraction followed by chloroform. DNA were
precipitated using NaAc/ethanol and dissolved in 30
␮l of deionized water (Sigma-Aldrich, St. Louis, MO).
PCR was performed to amplify the 5⬘ COI region of
mitochondrial DNA by using the following cycle in a
Bio-Rad iCycler. PCR conditions were as follows: an
initial denaturation of 5 min (95⬚C) was followed by
Þve cycles of 94⬚C for 40 s (denaturation), 45⬚C for 1
min (annealing), and 72⬚C for 1 min (extension) and
35 cycles of 94⬚C for 40 s (denaturation), 51⬚C for 1
min (annealing), 72⬚C for 1 min (extension), and a
Vol. 44, no. 1
Species
Aedeomyia (Aedeomyia) catasticta
Aedes (Aedimorphus) vexans
Aedes (Diceromyia) iyengari
Aedes (Fredwardsius) vittatus
Aedes (Lorrainea) fumidus
Aedes (Stegomyia) aegypti
Aedes (Stegomyia) aegypti
Aedes (Stegomyia) albopictus
Aedes (Stegomyia) albopictus
Aedes (Stegomyia) albopictus
Aedes (Stegomyia) albopictus
Anopheles (Anopheles) barbirostris
Anopheles (Anopheles) peditaeniatus
Anopheles (Cellia) aitkeni
Anopheles (Cellia) annularis
Anopheles (Cellia) culicifacies s.l.
Anopheles (Cellia) culicifacies s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) fluviatilis s.l.
Anopheles (Cellia) jamesi
Anopheles (Cellia) jeyporiensis
Anopheles (Cellia) jeyporiensis
Anopheles (Cellia) jeyporiensis
Anopheles (Cellia) jeyporiensis
Anopheles (Cellia) jeyporiensis
Anopheles (Cellia) maculatus
Anopheles (Cellia) minimus s.l.
Anopheles (Cellia) pallidus
Anopheles (Cellia) pallidus
Anopheles (Cellia) splendidus
Anopheles (Cellia) stephensi
Anopheles (Cellia) stephensi
Anopheles (Cellia) stephensi
Anopheles (Cellia) stephensi
Anopheles (Cellia) stephensi
Anopheles (Cellia) subpictus s.l.
Anopheles (Cellia) subpictus s.l.
Anopheles (Cellia) subpictus s.l.
Anopheles (Cellia) subpictus s.l.
Anopheles (Cellia) subpictus A
Anopheles (Cellia) subpictus B
Anopheles (Cellia) subpictus B
Serial
no.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
Pathirapuliyur
Periakattupalayam
Thannerbagi
Moratandi
Coringa
Paari nagar
Ennorekuppam
Gorimedu
Uppandara
Saharpur
Vikhroli
Kizhoor
Kedar road
Saharpur
Purthidigia
Purthidigia
Rameswaram
Mamalapusi
Attavalasa
Govindapally
Attavalasa
Attavalasa
Attavalasa
Attavalasa
Mailam
Attavalasa
Attavalasa
Govindapally
Attavalasa
Attavalasa
Mamalapusi
Mamalapusi
Gopalankadai
Purthidigia
Badakamurda
Bommiapalayam
Nagapattinam
Pattukottai
Bommiapalayam
Pattukottai
Mailam
Mamalapusi
Konthamur
Moorthikuppam
Moorthikuppam
Bahoor
Bahoor
Locality
State
12⬚ 07.197⬘ 79⬚ 36.282⬘
11⬚ 50.927⬘ 79⬚ 48.295⬘
12⬚ 53.580⬘ 74⬚ 48.920⬘
11⬚ 58.502⬘ 79⬚ 47.460⬘
16⬚ 52.972⬘ 82⬚ 15.070⬘
11⬚ 57.056⬘ 79⬚ 48.632⬘
13⬚ 13.784⬘ 80⬚ 19.578⬘
11⬚ 57.096⬘ 79⬚ 47.613⬘
12⬚ 52.189⬘ 74⬚ 52.103⬘
21⬚ 35.695⬘ 85⬚ 24.936⬘
19⬚ 05.774⬘ 72⬚ 56.430⬘
11⬚ 53.344⬘ 79⬚ 41.010⬘
11⬚ 59.413⬘ 79⬚ 28.283⬘
21⬚ 35.877⬘ 85⬚ 24.959⬘
22⬚ 09.337⬘ 85⬚ 33.759⬘
22⬚ 09.337⬘ 85⬚ 33.759⬘
09⬚ 15.24⬘ 79⬚ 16.44⬘
21⬚ 33.358⬘ 85⬚ 28.697⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.363⬘ 82⬚ 15.397⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
12⬚ 07.555⬘ 79⬚ 36.694⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.363⬘ 82⬚ 15.397⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
18⬚ 30.326⬘ 82⬚ 01.179⬘
21⬚ 33.463⬘ 85⬚ 28.650⬘
21⬚ 33.358⬘ 85⬚ 28.697⬘
11⬚ 55.704⬘ 79⬚ 45.767⬘
22⬚ 09.337⬘ 85⬚ 33.759⬘
22⬚ 11.626⬘ 85⬚ 31.510⬘
11⬚ 59.638⬘ 79⬚ 51.055⬘
10⬚ 52.467⬘ 79⬚ 50.119⬘
11⬚ 14.46⬘ 79⬚ 43.36⬘
11⬚ 59.638⬘ 79⬚ 51.055⬘
11⬚ 14.46⬘ 79⬚ 43.36⬘
12⬚ 07.555⬘ 79⬚ 36.694⬘
21⬚ 33.370⬘ 85⬚ 28.670⬘
12⬚ 08.068⬘ 79⬚ 43.507⬘
11⬚ 47.364⬘ 79⬚ 47.690⬘
11⬚ 47.364⬘ 79⬚ 47.690⬘
11⬚ 47.667⬘ 79⬚ 45.687⬘
11⬚ 47.667⬘ 79⬚ 45.687⬘
GPS coordinates
Collection details of specimens
Pondicherry
Pondicherry
Karnataka
Pondicherry
Andhra Pradesh
Pondicherry
Tamil Nadu
Pondicherry
Karnataka
Orissa
Maharashtra
Pondicherry
Pondicherry
Orissa
Orissa
Orissa
Tamil Nadu
Orissa
Orissa
Orissa
Orissa
Orissa
Orissa
Orissa
Pondicherry
Orissa
Orissa
Orissa
Orissa
Orissa
Orissa
Orissa
Pondicherry
Orissa
Orissa
Pondicherry
Tamil Nadu
Tamil Nadu
Pondicherry
Tamil Nadu
Pondicherry
Orissa
Pondicherry
Pondicherry
Pondicherry
Pondicherry
Pondicherry
Details of mosquito specimens used for DNA barcoding and analysis
VCRC
Museum no.
A11437
A11529
A10198
A11499
A11451
A11491
A13663
A11475
A10211
A10456
A11176
A11462
A11517
A10486
A11511
A11512
DB173
A11505
A12467
A12478
A12482
A12471
A12452
A12501
A11440
A12479
A12500
A12502
A12506
A12507
A10474
A11510
A11442
A11509
A11508
A11459
A13574
A13667
A11467
A13668
A11438
A11506
A11457
A11538
A11537
A11536
A11535
Habit/habitat
Quarry pit
Casuarina pit
Tyre
Cement tank
Tree hole
Pot
Well
Tar tin
Tree hole
Bamboo
Resting on root
Canal
Road side pool
Stream
Resting in cattle shed
Resting in cattle shed
Resting in human dwelling
Resting in human dwelling
Resting in cattle shed
Resting in human dwelling
Resting in cattle shed
Resting in cattle shed
Resting in cattle shed
Resting in cattle shed
Pond
Resting in cattle shed
Resting in cattle shed
Resting in cattle shed
Resting in cattle shed
Resting in cattle shed
Paddy Þeld
Resting in human dwelling
Paddy Þeld
Resting in cattle shed
Light trap
Well
Well
Well
Well
Well
Pond
Light trap
Cement tank
Resting in cattle shed
Resting in human dwelling
Resting in cattle shed
Resting in cattle shed
AY729969
AY917213
DQ431717
AY834246
AY729978
AY729987
DQ424949
AY729984
AY834241
DQ310142
DQ424959
AY729982
DQ149237
AY917209
AY917197
AY917198
DQ424962
AY917202
DQ154155
DQ154156
DQ154158
DQ310150
DQ317595
DQ317596
AY729972
DQ154157
DQ154159
DQ317591
DQ317592
DQ317593
DQ267690
AY917196
AY729974
AY917212
AY917207
AY729980
DQ154166
DQ310143
DQ310148
DQ317594
AY729970
AY917203
DQ267688
DQ310145
DQ310146
DQ310147
DQ310149
GenBank
accession no.
KUMAR ET AL.: DNA BARCODES OF INDIAN CULICIDAE
Downloaded from http://jme.oxfordjournals.org/ by guest on January 17, 2017
Table 1.
January 2007
3
Species
Anopheles (Cellia) vagus
Anopheles (Cellia) varuna
Armigeres (Armigeres) subalbatus
Armigeres (Armigeres) subalbatus
Armigeres (Armigeres) subalbatus
Culex (Culex) bitaeniorhynchus
Culex (Culex) bitaeniorhynchus
Culex (Culex) fuscocephala
Culex (Culex) gelidus
Culex (Culex) hutchinsoni
Culex (Culex) pseudovishnui
Culex (Culex) pseudovishnui
Culex (Culex) quinquefasciatus
Culex (Culex) quinquefasciatus
Culex (Culex) sitiens
Culex (Culex) sitiens
Culex (Culex) sitiens
Culex (Culex) sitiens
Culex (Culex) sitiens
Culex (Culex) tritaeniorhynchus
Culex (Culex) tritaeniorhynchus
Culex (Culex) tritaeniorhynchus
Culex (Culex) tritaeniorhynchus
Culex (Culex) vishnui
Culex (Culex) vishnui
Culex (Culex) whitmorei
Culex (Culiciomyia) nigropunctatus
Culex (Culiciomyia) pallidothorax
Culex (Eumelanomyia) brevipalpis
Culex (Eumelanomyia) brevipalpis
Culex (Eumelanomyia) brevipalpis
Culex (Eumelanomyia) malayi
Culex (Eumelanomyia) pluvialis
Culex (Lophoceraomyia) infantulus
Culex (Lophoceraomyia) infantulus
Culex (Lophoceraomyia) minor
Culex (Lophoceraomyia) minutissimus
Culex (Lophoceraomyia) rubithoracis
Culex (Lutzia) fuscanus
Ficalbia minima
Heizmannia (Heizmannia) chandi
Heizmannia (Mattinglyia) discrepans
Malaya genurostris
Mansonia (Mansonioides) annulifera
Mansonia (Mansonioides) uniformis
Mimomyia (Mimomyia) chamberlaini
Ochlerotatus (Finlaya) cogilli
Serial
no.
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
Continued
Aranganur
Kurumpuram
Auroville
Thallapadi
Chorao
Nanjappa nagar
Mettupalayam
Edainchavadi
Mettupalayam
Kedar road
Kizhoor
Pallinelianur
Kattukuppam
Panchavadi
Koraikuppam
Srinivasapuram
Wandoor
Kanyapuram
Moorthikuppam
Pinnachikuppam
Kizhoor
Moorthikuppam
Maravakadu
Gopalankadai
Katterikuppam
Baluguda
Mettupalayam
Arakku
Gorimedu
Mamalapusi
Londamundasi
Alagramam
Navohar
Mettupalayam
Purthidigia
Badagosda
Kurumpuram
Kizhoor
Gorimedu
Bahoor
Saharpur
Dharmasthala
Badagosda
Pinnachikuppam
Veerampattinam
Manghakuppam
Uppandara
Locality
11⬚ 49.982⬘ 79⬚ 44.958⬘
12⬚ 13.253⬘ 79⬚ 53.447⬘
11⬚ 59.119⬘ 79⬚ 47.489⬘
12⬚ 45.695⬘ 74⬚ 51.857⬘
15⬚ 30.741⬘ 73⬚ 52.098⬘
10⬚ 36.46⬘ 92⬚ 36.30⬘
11⬚ 56.696⬘ 79⬚ 45.412⬘
11⬚ 59.844⬘ 79⬚ 50.260⬘
11⬚ 56.696⬘ 79⬚ 45.412⬘
11⬚ 59.413⬘ 79⬚ 28.283⬘
11⬚ 53.280⬘ 79⬚ 40.920⬘
11⬚ 54.464⬘ 79⬚ 39.087⬘
11⬚ 47.532⬘ 79⬚ 46.432⬘
12⬚ 00.578⬘ 79⬚ 46.322⬘
13⬚ 22.881⬘ 80⬚ 19.934⬘
13⬚ 00.993⬘ 80⬚ 16.623⬘
11⬚ 35.407⬘ 92⬚ 37.100⬘
11⬚ 41.34⬘ 92⬚ 42.47⬘
11⬚ 47.364⬘ 79⬚ 47.690⬘
11⬚ 48.753⬘ 79⬚ 45.763⬘
11⬚ 53.280⬘ 79⬚ 40.920⬘
11⬚ 47.364⬘ 79⬚ 47.690⬘
10⬚ 18.844⬘ 79⬚ 27.055⬘
11⬚ 55.704⬘ 79⬚ 45.767⬘
12⬚ 00.364⬘ 79⬚ 47.690⬘
18⬚ 17.033⬘ 82⬚ 56.323⬘
11⬚ 56.696⬘ 79⬚ 45.412⬘
18⬚ 15.388⬘ 83⬚ 01.870⬘
11⬚ 57.096⬘ 79⬚ 47.613⬘
21⬚ 33.496⬘ 85⬚ 28.740⬘
22⬚ 06.397⬘ 85⬚ 28.598⬘
12⬚ 09.780⬘ 79⬚ 35.701⬘
12⬚ 54.453⬘ 75⬚ 04.464⬘
11⬚ 56.696⬘ 79⬚ 45.412⬘
22⬚ 09.512⬘ 85⬚ 33.835⬘
21⬚ 35.180⬘ 85⬚ 25.261⬘
12⬚ 13.253⬘ 79⬚ 53.447⬘
11⬚ 53.344⬘ 79⬚ 41.010⬘
11⬚ 57.096⬘ 79⬚ 47.613⬘
11⬚ 47.667⬘ 79⬚ 45.687⬘
21⬚ 35.695⬘ 85⬚ 24.936⬘
12⬚ 56.253⬘ 75⬚ 08.774⬘
21⬚ 35.087⬘ 85⬚ 25.327⬘
11⬚ 48.753⬘ 79⬚ 45.763⬘
11⬚ 53.079⬘ 79⬚ 49.049⬘
12⬚ 04.415⬘ 79⬚ 52.896⬘
12⬚ 52.189⬘ 74⬚ 52.103⬘
GPS coordinates
Collection details of specimens
Pondicherry
Tamil Nadu
Pondicherry
Karnataka
Goa
Andamans
Pondicherry
Pondicherry
Pondicherry
Pondicherry
Pondicherry
Tamil Nadu
Pondicherry
Pondicherry
Tamil Nadu
Tamil Nadu
Andamans
Andamans
Pondicherry
Pondicherry
Pondicherry
Pondicherry
Tamil Nadu
Pondicherry
Pondicherry
Andhra Pradesh
Pondicherry
Andhra Pradesh
Pondicherry
Orissa
Orissa
Pondicherry
Karnataka
Pondicherry
Orissa
Orissa
Tamil Nadu
Pondicherry
Pondicherry
Pondicherry
Orissa
Karnataka
Orissa
Pondicherry
Pondicherry
Pondicherry
Karnataka
State
VCRC
Museum no.
A11500
A11527
A11490
A9802
A10597
A12558
A11427
A11515
A11428
A11522
A11501
A11532
A11448
A11460
A13575
A13577
A12560
A12561
A11528
A11443
A11502
A11444
A8364
A11441
A11530
A12348
A11445
A12334
A11481
A10397
A5601
A11519
A9239
A11430
A11507
A10490
A11523
A11461
A11478
A11434
A10454
A10197
A10450
A11439
A11494
A11458
A10120
Habit/habitat
Paddy Þeld
Stream pool
Cement tank
Coconut shell
Biting outdoor
Ground pool
Resting in well
Ground pool
Resting in well
Ground pool
Paddy Þeld
Canal
Cement tank
Cess pit
Backwater pool
Well
Backwater pool
Paddy Þeld
Resting in cattle shed
Canal
Paddy Þeld
Pond
Resting in crab hole
Paddy Þeld
Canal
Light trap
Unused well
Paddy Þeld
Cement tank
Tree hole
Outdoor resting
Ground pool
Resting in cement tank
Resting in well
Outdoor resting
Stream pool
Pit shelter
Canal
Cement tank
Resting in Pistia plant
Bamboo
Bamboo
Leaf axil
Canal
Pond
Ground pool
Tree hole
AY834247
DQ149241
AY729986
AY834244
DQ424958
DQ154162
DQ267687
DQ149236
AY729965
DQ149239
AY834248
AY917215
AY729977
DQ267689
DQ154160
DQ154161
DQ154163
DQ310144
DQ317598
AY729975
AY834249
AY917206
DQ424952
AY729973
AY917214
DQ154167
AY729976
DQ154154
AY834238
DQ424960
DQ424961
DQ149238
DQ317597
AY729966
DQ267691
AY917211
DQ149240
AY729981
AY729985
AY729967
AY917208
AY834242
AY917204
AY729971
AY729988
AY729979
AY834240
GenBank
accession no.
JOURNAL OF MEDICAL ENTOMOLOGY
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Table 1.
4
Vol. 44, no. 1
DQ154153
DQ424953
DQ424957
DQ154164
DQ154165
DQ424948
DQ424951
AY917200
AY917210
AY917201
DQ424954
AY917205
AY917199
AY834245
DQ424950
DQ424955
DQ424956
A12344
A8089
A8356
A12563
A12564
A13607
A8551
A10579
A10487
A11421
A8321
A10451
A10551
A11497
A8541
A4606
A8173
Rock pool
Resting in crab hole
Resting in crab hole
Paddy Þeld
Swamp
Swamp
Resting in crab hole
Bamboo
Bamboo
Tree hole
Resting in crab hole
Tree hole
Crab hole
Ground pool
Biting outdoor
Biting outdoor
Biting outdoor
GPS, global positioning system; VCRC, Vector Control Research Centre.
Ochlerotatus (Finlaya) pseudotaeniatus
Ochlerotatus (Rhinoskusea) portonovoensis
Ochlerotatus (Rhinoskusea) portonovoensis
Ochlerotatus (Rhinoskusea) wardi
Ochlerotatus (Rhinoskusea) wardi
Ochlerotatus (Rhinoskusea) wardi
Ochlerotatus (Rhinoskusea) wardi
Orthopodomyia anopheloides
Tripteroides (Rachionotomyia) aranoides
Uranotaenia (Pseudoficalbia) atra
Uranotaenia (Pseudoficalbia) atra
Uranotaenia (Pseudoficalbia) bicolor
Uranotaenia (Pesudoficalbia) recondita
Verrallina (Neomacleaya) indica
Verrallina (Verrallina) lugubris
Verrallina (Verrallina) lugubris
Verrallina (Verrallina) lugubris
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
Muliaguda bridge
Muthupet
Maravakadu
Wandoor
Santhipur
Rameswaram
Coringa
Badagosda
Saharpur
Zuari
Maravakadu
Mamalapusi
Saharpur
Moratandi
Coringa
Chorao
Muthupet
Andhra Pradesh
Tamil Nadu
Tamil Nadu
Andamans
Andamans
Tamil Nadu
Andhra Pradesh
Orissa
Orissa
Goa
Tamil Nadu
Orissa
Orissa
Pondicherry
Andhra Pradesh
Goa
Tamil Nadu
18⬚ 14.316⬘ 83⬚ 01.768⬘
10⬚ 20.314⬘ 79⬚ 32.313⬘
10⬚ 18.844⬘ 79⬚ 27.055⬘
11⬚ 35.407⬘ 92⬚ 37.100⬘
12⬚ 20.005⬘ 92⬚ 46.256⬘
09⬚ 15.24⬘ 79⬚ 16.44⬘
16⬚ 49.287⬘ 82⬚ 17.989⬘
21⬚ 35.581⬘ 85⬚ 25.169⬘
21⬚ 35.695⬘ 85⬚ 24.936⬘
15⬚ 24.870⬘ 73⬚ 54.628⬘
10⬚ 18.844⬘ 79⬚ 27.055⬘
21⬚ 33.496⬘ 85⬚ 28.740⬘
21⬚ 35.877⬘ 85⬚ 24.959⬘
11⬚ 59.402⬘ 79⬚ 49.051⬘
16⬚ 49.287⬘ 82⬚ 17.989⬘
15⬚ 31.668⬘ 73⬚ 51.886⬘
10⬚ 20.314⬘ 79⬚ 32.313⬘
VCRC
Museum no.
GPS coordinates
Collection details of specimens
State
Locality
Species
Serial
no.
Continued
5
adults, 65 were reared to adults from larval and three
from pupal collections, 25 were F1 adults obtained
from females collected in the Þeld, and 18 were adults
from the Þeld and from which only the legs were used
for DNA extraction. Larval habitats from which specimens were obtained ranged from groundwater habitats to both natural and artiÞcial container habitats,
whereas adults were collected resting in various sites,
those landing on humans to bite, and those caught in
light traps. The specimens used in this study represent
distribution in eight states and union territories of
India. In total, 111 DNA sequences were deposited
with the GenBank. Collection details including habitat, geocoordinates of localities, voucher specimens,
and GenBank accession numbers of specimens are
given in Table 1.
Gene Sequences, Nucleotide and Amino Acid Diversity, and Genetic Distances. The DNA sequences
ampliÞed using the primers C1J-1718 and C1N-2191
were ⬇500 bp, whereas the sequence with the primer
MTFN and MTRN designed by us was ⬇700 bp. The
latter sequence included the former sequences and
hence 500 bp was taken for the analysis. This region
corresponded to the 5⬘ region of COI gene. The sequences were AT rich for the mitochondrial genome,
the G ⫹ C content being 0.316. The mean genetic
distance (K2P) computed for the different species of
Culicidae belonging to 15 genera studied was found to
be 0.1469. The NJ tree showed 62 species clusters
clearly among the sequences studied, thus identifying
62 species among the specimens analyzed (Fig. 1).
The maximum intra-speciÞc K2P values recorded
among the species clusters was for Anopheles pallidus
Theobald (0.0184). The interspeciÞc K2P values
ranged from 0.0587 (Anopheles fluviatilis James s.l. and
Anopheles minimus Theobald) to 0.2565 [Verrallina
indica (Theobald) and Anopheles jamesi Theobald]
(Table 2, supplemental data available online). Hence,
this study denoted that the K2P genetic distances were
⬎0.02 between different species studied for Culicidae,
as cited elsewhere for other group animals (Hebert et
al. 2003a,b). However, the K2P value between two
very closely related species, Ochlerotatus wardi (Reinert) and Ochlerotatus portonovoensis (Tewari &
Hiriyan), was only 0.0043; thus, they were not identiÞed as separate species. More samples of these species may have to be analyzed before arriving at a
conclusion regarding their species status.
The average K2P value of 0.1469 exhibited by Culicidae is similar to that recorded for Lepidoptera
(Hajibabaei et al. 2006). Also, the COI gene was found
to be very conserved, as described previously (Knowlton and Weigt 1998), the deduced amino acid variability being only 0.0329. This value indicated the
utility of this gene for taxonomy of Culicidae, because
it provides ample nucleotide variability toward species
identiÞcation and its conserved nature for higher orders of taxonomic strata (Hebert et al. 2003a).
The seven specimens of Anopheles subpictus Grassi
used in the study included four sensu lato specimens,
two specimens identiÞed as species B and one specimen identiÞed as species A based on egg ridge num-
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Table 1.
KUMAR ET AL.: DNA BARCODES OF INDIAN CULICIDAE
Habit/habitat
GenBank
accession no.
January 2007
6
JOURNAL OF MEDICAL ENTOMOLOGY
Vol. 44, no. 1
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Fig. 1. NJ phylogenetic tree based on Kimura two-parameter genetic distances of the COI gene sequences of mosquitoes
prevalent in India.
bers. The nucleotide diversity between the specimens
identiÞed as species A and species B was 11.3%, indicating them to be very distinct from each other. The
sensu lato specimens matched with the clade of species A and hence could be the same species. Thus, this
study evinced that the DNA barcode approach could
distinguish members of sibling species complexes in
insects as reported elsewhere (Hebert et al. 2004a).
Unfortunately, the issue of sibling species complexes
could not be addressed further in this study, due to
January 2007
KUMAR ET AL.: DNA BARCODES OF INDIAN CULICIDAE
lack of identiÞed specimens for not only other members of An. subpictus complex but also for sibling species complexes such as An. culicifacies, An. fluviatilis,
and An. minimus. We propose to deal with this aspect
in the future.
The current study indicates the utility of using single-gene sequences (5⬘ region of mitochondrial cytochrome oxidase subunit one gene), toward identiÞcation of the mosquito species. The NJ tree computed
was in general agreement with the taxonomy based on
morphology as reported previously (Hebert et al.
2003a,b. 2004a; Hajibabaei et al. 2006).
Acknowledgments
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Received 24 March 2006; accepted 7 September 2006.
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We are indebted to P. K. Das and K. Balaraman, Vector
Control Research Centre, Pondicherry, India, for encouragement in conducting the study. The technical assistance
provided by Regna Kumari Packirisamy and N. Krishnamoorthy Laboratory technicians is acknowledged.
7