Indian Journal of Geo-Marine Sciences
Vol. 45(4), April 2016, pp. 603-612
Genetic diversity in natural populations of neogastropod, Babylonia
Zeylanica (Bruguiere, 1739) along Tamilnadu, southeast coast of India: A
molecular approach through microsatellite markers
Mootapally Chandra Shekar1, 2*, Sabapathi Arularasan1, Galib Uz Zaman2, Pandian Krishnan3 & Eswaran
Suresh4
1
Centre of Advanced Study in Marine Biology, Annamalai University, Parangipettai-608 502, India
Department of Animal Genetics and Breeding, College of Veterinary Science, Assam Agricultural University, Guwahati781022, India
3
Conservation of Costal and Marine Resources Division, National Center for Sustainable Coastal Management, Anna
University, Guindy-600025, India
4
National Bureau of Fish Genetic Resources (ICAR), Lucknow - 226002, India
*[E-mail: [email protected]]
2
Received 30 May 2014; revised 27 November 2014
Genetic diversity and population structure of six populations of commercially important whelk, B.
zeylanica from Southeast coast of India were studied. A total of 187 individuals were genotyped at 12 loci and
differences in the genetic diversity between populations were correlated with known population histories.
Study identified 475 alleles and all the studied loci were highly polymorphic. The number of alleles ranged
between 4 and 12 with a global mean of 6.597. Global mean of observed and expected heterozygosities were
0.547 and 0.794 respectively. Within population inbreeding estimate (FIS) value (0.311) indicated shortfall of
heterozygosity in the populations. Microsatellite analysis revealed less genetic diversity in all studied genetic
groups. Analysis of Molecular Variance (AMOVA) showed that 4% of the total variation was due to
differences between genetic groups.
[Keywords: Babylonia Zeylanica; Microsatellites; Heterozygosity; Polymorphic Information Content]
Introduction
Whelks (B. zeylanica) are important food
species in Indo-pacific region1. Production of
B. zeylanica in India increased considerably
from 30,499 t in 1950 to l,21,657 t in 20112.
High demand for export of B. zeylanica meat
has lead to overexploitation of undersized whelk
which results in the reduction of the natural
stock. Recently, due to over exploitation, some
species have been listed as endangered3. In
2001, the gastropods like trochus, turbo and
large number of other ornamental species have
been listed under schedule I of the Wild Life
Protection Act, 19724. Literatures on population
genetics of marine molluscs are very scanty5.
Moreover, recent developments in gastropod
fishery and its utilization indicate the need to
have scientific data on the genetic diversity of
selected gastropods for planning their
conservation and management6.
B. zeylanica has a very smooth shell with high
spire, rounded whorls, slightly impressed sutures
and a large ovate body whorl. Though, the shell
bears distinctive brownish patches on white
background, the major characteristic is the violet
staining at the fasciole (Fig. 1). This species is
distributed in southeast and southwest coasts of
India and also in Andaman and Nicobar and
Lakshadweep Island waters.
Fig. 1— a typical B. zeylanica from Tamilnadu coastal
waters
604
INDIAN J. MAR. SCI., VOL. 45, NO. 4 APRIL 2016
Information on genetic diversity of a
particular species under natural conditions will
provide inputs for their domestication7.
Knowledge about genetic diversity levels and
population differentiation through microsatellite
analysis on natural populations will be useful for
formulating
management
measures
for
sustainable exploitation and conservation of this
commercially
important
species.
Table 1—Summary of sampling locations and number of whelks sampled
Species
B. zeylanica
Sampling sites
Mudasal Odai
Nagapattinam
Rameshwaram
Punnaikayal
Arogyapuram
Colachel
Acronyms
MUD
NAG
RAM
PUN
ARO
COL
Population genetic studies of commercially
important
marine
molluscs
based
on
microsatellite markers are useful for the analysis
of population structure and relationships as
demonstrated by various studies viz., genetic
diversity in Mytilus galloprovincialis of Iberian
Peninsula8, marine black nerite, Nerita
atramentosa9, swan mussel, Anodonta cygnea10,
spotted Babylonia areolata11 and parentage
assignment in the eastern oyster12 as well as
other marine molluscs species from other
countries. However, the population structure of
B. zeylanica from Indian seas has not been
assessed yet using molecular markers.
Twelve
well-characterized
polymorphic
microsatellite loci of widely separated natural
populations of B. zeylanica from southeast coast
of India is examined in the present study to
understand their genetic diversity and population
structure in the natural populations along
Tamilnadu coast using microsatellite markers
hence to establish a microsatellite profile.
Latitude and longitude
11°29’07.74” N 79°46’28.10” E
10°45’37.94” N 79°50’57.82” E
9°16’49.46” N 79°19’02.44” E
8°38’15.20” N 78°07’13.63” E
8°07’10.76” N 77°33’32.25” E
8°10’20.67” N 77°14’56.42” E
Total
Number of samples
30
30
32
32
31
32
187
Materials and Methods
Fresh specimens of B. zeylanica were
collected from commercial catch of fish landing
centers at different localities in Tamilnadu (Fig.
2). 30 to 32 specimens were collected from each
location, with the total collection of 187 (Table
1). Foot tissue of each specimen was fixed in
TNES-buffer13 and stored at 4°C until use.
Genomic DNA was isolated from foot tissue of
B. zeylanica following the phenol-chloroform
method14 with minor modifications. DNAzol
(Invitrogen) reagent was used instead of SDS
and proteinase K. The DNA was observed on 0.8
% agarose gel containing ethidium bromide. The
quantification of DNA was done using ND-1000
spectrophotometer (Thermo scientific). A total
of 12 well-characterized microsatellite markers
(Table 2) developed by Longo et al.15 for black
murex, Hexaplex nigritus were used based on
their level of polymorphism, allele size range
and reliability of allele to evaluate genetic
structure in B. zeylanica.
Table 2— Details of microsatellite markers used in present study
Sl. No. Locus name
Primer sequences (5’ 3’)
Repeat motif Labeled dye Ta (°C) Allele size range (bp)
1
HNI_A3
F:CCATTGCTGAGAGACTGAAGAA
(CA)22
6 FAM
58
238–268
R: ACATTTGCGCTTAGTTTGACTG
136–216
2
HNI_A12 F:AGTAGGCGGCATTTCACTTC
(CA)37
ROX
58
R:CACGAAACTCTGCAAAGACG
3
HNI_A5
F: CTGTGCAACATCTCTCATTGTT
(TAA)7
Tamra
57
164–182
R:ATTTTGCGCTATACCAAGAATG
202–282
4
HNI_A120 F:CTAGCCCCAGTGTATGGTC
(CA)21
HEX
57
R:GGTGTCAGTCCTCATTTGG
5
HNI_A10 F:GAATCCATCCTATGTTTTCAAG
(CA)31
6 FAM
56
133–237
R:AAAGAGAGAGGGGAAGAATAAG
6
HNI_B9
F:GGGGTCTACAACACGGTG
(CATC)19
Tamra
56
121–161
R:GATGGGAATGGATGGTTG
7
HNI_B120 F:GCAAACACACTCACACACTTT
(CTAC)26
ROX
57
240–286
R:CATCCAAGTAAGCAGGAAGAC
CHANDRA SHEKAR et al.: MICROSATELLITE ANALYSIS IN BABYLONIA ZEYLANICA
8
9
10
11
12
HNI_A117 F:GGCAGAACGGCATTAACTATG
R:CAGGGATCGACAGAGAATCAG
HNI_C12 F:TGTCGAATACGATGGAGAGTG
R:GGTCTGCTTTACCATTGGAAG
HNI_B12 F:CACGCACACGTTATACATACAC
R:CTTATTCTTCCCCTCTCTCTTT
HNI_B104 F:ATCGAAGAAGTGGGCATATTG
R:ACTGGTAAGATGGGGTTGTTG
HNI_C102 F:TGAGGCTTCGTGTTGAAG
R:CGTCATAAATGCAAACATAGTG
605
(TCTG)8
6 FAM
57
120–138
(TACA)23
HEX
58
229–301
(CA)51
Tamra
58
267–329
(CATC)14
HEX
57
153–215
(TACA)21
6 FAM
57
109–189
Fig. 2—Distribution of sampling localities for natural population of B. zeylanica for present study (Politeness to Google
earth map)
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INDIAN J. MAR. SCI., VOL. 45, NO. 4 APRIL 2016
The forward primer of each marker was
fluorescently labeled with FAM, ROX, TAMRA
or HEX dye. All microsatellite markers were
first checked under single locus amplification
conditions to evaluate their performance in the
multiplex. Multiplex PCR was used for
multicolor fluorescence genotyping following
Henegariu et al.16 and Loffert et al.17 for setting
up the initial parameters. The basic PCR reaction
mixture (15 µl) containing 20-50 ng of template
DNA; 1.5 mM MgCl2; 5 picomoles each of
forward and reverse primers; 1 unit of taq DNA
polymerase and 200 mM dNTPs was prepared.
Amplification was carried out with initial
denaturation at 95°C for 2 min followed by 30
cycles of denaturation (95°C for 30 sec),
annealing (52°C to 58°C for 30 sec) and
extension (72°C for 45 sec) using Applied
Biosystems VeritiTM 96- well thermal cycler.
Genotyping was carried out on an automated
DNA Sequencer (ABI HITACHI 3500) and data
were analyzed using Gene Mapper v. 4.0
(Applied Biosystems) to generate genotype calls
for each locus by using GS 500 (- 250) LIZ as
size standard. GenAlex v. 6.518 was used to
estimate genetic diversity and differentiation
parameters. Parameters estimated include
number of alleles (Na), allele frequencies,
effective number of alleles (Ne), Private alleles,
observed (Ho) and expected (He) heterozygosity,
F-statistics, Shanon’s information index (I),
Hardy-Weinberg equilibrium (HWE), Principal
component analysis (PCA) and Analysis of
molecular variance (AMOVA). Polymorphic
information content (PIC) was calculated using
Excel Microsatellite Toolkit 3.119. Expected
frequencies of null alleles at the 12 loci were
calculated using Micro-Checker v. 2.2.120.
Phylogenetic and molecular evolutionary
analyses were conducted using MEGA v. 5.0521.
F-statistics were estimated following Weir
and Cockerham22. Wright’s FIS summarizes the
effects of non random mating within
subpopulations
on
average
individual
heterozygosity. FST characterizes the reduction in
individual heterozygosity expected within
subpopulations relative to a total population as a
result of genetic drift, effectively measuring the
extent of population subdivision and the
counteracting evolutionary processes of drift on
the one hand and gene flow on the other. Finally,
FIT summarizes the extent to which average
individual heterozygosity deviates from HardyWeinberg expectations due to both nonrandom
mating within subpopulations and population
subdivision23.
CHANDRA SHEKAR et al.: MICROSATELLITE ANALYSIS IN BABYLONIA ZEYLANICA
POP
MUD
NAG
RAM
PUN
ARO
COL
All
POP
PAR
Na
Ne
I
Ho
He
PIC
FIS
PHW
Na
Ne
I
Ho
He
PIC
FIS
PHW
Na
Ne
I
Ho
He
PIC
FIS
PHW
Na
Ne
I
Ho
He
PIC
FIS
PHW
Na
Ne
I
Ho
He
PIC
FIS
PHW
Na
Ne
I
Ho
He
PIC
FIS
PHW
Na
Ne
I
Ho
He
PIC
FIS
Panel 1
M1 M2
7
5
4.283
3.919
1.615
1.429
0.500
0.435
0.766
0.745
0.730
0.700
0.348
0.416
0.000** 0.015*
6
4
3.630
3.136
1.478
1.201
0.214
0.286
0.724
0.681
0.686
0.616
0.704
0.581
0.004** 0.039*
9
9
7.225
7.410
2.054
2.082
0.529
0.412
0.862
0.865
0.846
0.850
0.386
0.524
0.005** 0.000**
8
9
5.311
6.480
1.835
1.998
0.556
0.389
0.812
0.846
0.788
0.827
0.316
0.540
0.000** 0.001**
6
8
5.000
5.357
1.691
1.832
0.533
0.467
0.800
0.813
0.771
0.788
0.333
0.426
0.000** 0.007**
7
7
4.785
6.481
1.737
1.905
0.625
0.250
0.791
0.846
0.764
0.826
0.210
0.704
0.002** 0.000**
7.000
7.167
5.039
5.464
1.735
1.741
0.373
0.493
0.793
0.799
0.764
0.768
0.383
0.532
Table 3—Microsatellite analysis in natural populations of B. Zeylanica
Locus name duplex panel wise
Panel 2
Panel 3
Panel 4
Panel 5
M3
M4
M5
M6
M7
M8
M9
M10
4
5
8
8
5
5
7
7
3.806
4.188
7.293
6.107
4.190
4.100
4.959
5.405
1.360
1.493
2.035
1.925
1.515
1.493
1.752
1.795
0.500
0.750
0.895
0.850
0.636
0.583
0.519
0.850
0.737
0.761
0.863
0.836
0.761
0.756
0.798
0.815
0.689
0.721
0.847
0.817
0.723
0.716
0.772
0.790
0.322
0.015
-0.037 -0.016 0.164
0.228
0.351
-0.043
0.033* 0.027* 0.000** 0.000** 0.001** 0.001** 0.000** 0.001**
4
4
5
4
7
5
5
4
3.130
3.141
4.261
3.294
4.962
3.846
4.506
3.723
1.237
1.261
1.532
1.279
1.779
1.471
1.552
1.345
0.167
0.375
0.714
0.571
0.786
0.600
0.786
0.545
0.681
0.682
0.765
0.696
0.798
0.740
0.778
0.731
0.622
0.632
0.730
0.644
0.775
0.701
0.742
0.681
0.755
0.450
0.067
0.179
0.016
0.189
-0.010 0.254
NS
0.000** 0.001** 0.002** 0.004**
0.000** 0.000** 0.000** 0.129
5
7
6
7
9
7
9
7
4.246
6.125
4.898
6.259
7.506
5.729
6.494
6.429
1.518
1.871
1.677
1.883
2.086
1.824
2.002
1.897
0.273
0.286
0.235
0.615
0.412
0.846
0.529
0.533
0.764
0.837
0.796
0.840
0.867
0.825
0.846
0.844
0.726
0.816
0.766
0.820
0.852
0.802
0.828
0.825
0.643
0.659
0.704
0.268
0.525
-0.025 0.374
0.368
0.000** 0.000** 0.000** 0.001** 0.000** 0.000** 0.000** 0.000**
4
8
7
7
12
8
9
9
3.532
5.684
5.400
5.378
9.257
6.481
6.291
7.200
1.318
1.875
1.798
1.796
2.325
1.966
1.983
2.062
0.071
0.278
0.333
0.273
0.500
0.688
0.611
0.500
0.717
0.824
0.815
0.814
0.892
0.846
0.841
0.861
0.665
0.802
0.790
0.789
0.882
0.828
0.822
0.845
0.900
0.663
0.591
0.665
0.439
0.187
0.273
0.419
0.000** 0.000** 0.000** 0.001** 0.000** 0.000** 0.000** 0.000**
5
7
6
7
11
7
6
8
3.674
4.506
4.173
5.844
8.982
4.592
5.294
6.081
1.412
1.690
1.562
1.849
2.290
1.708
1.721
1.928
0.462
0.357
0.077
1.000
0.813
0.800
0.533
0.667
0.728
0.778
0.760
0.829
0.889
0.782
0.811
0.836
0.682
0.748
0.722
0.807
0.878
0.755
0.784
0.816
0.366
0.541
0.899
-0.206 0.086
-0.023 0.342
0.202
0.160 NS 0.002** 0.000** 0.000** 0.000** 0.000** 0.004** 0.004**
7
6
7
6
6
8
6
6
4.655
5.333
5.538
4.096
4.042
6.716
5.020
4.235
1.677
1.721
1.809
1.573
1.549
1.974
1.701
1.564
0.250
0.125
0.222
0.688
0.412
0.867
0.500
0.833
0.785
0.813
0.819
0.756
0.753
0.851
0.801
0.764
0.753
0.785
0.795
0.721
0.715
0.833
0.773
0.727
0.682
0.846
0.729
0.090
0.453
-0.018 0.376
-0.091
0.000** 0.000** 0.000** 0.000** 0.000** 0.000** 0.000** 0.000**
4.833
6.167
6.500
6.500
8.333
6.667
7.000
6.833
3.840
4.830
5.261
5.163
6.490
5.244
5.427
5.512
1.421
1.652
1.735
1.717
1.924
1.739
1.785
1.765
0.287
0.362
0.413
0.666
0.593
0.731
0.580
0.655
0.735
0.782
0.803
0.795
0.827
0.800
0.813
0.809
0.690
0.751
0.775
0.766
0.804
0.772
0.787
0.781
0.611
0.529
0.492
0.163
0.281
0.090
0.284
0.185
Panel 6
M11
M12
4
5
3.209
4.545
1.248
1.561
0.789
0.800
0.688
0.780
0.629
0.745
-0.147 -0.026
0.010** 0.000**
6
6
5.158
5.445
1.707
1.742
0.857
1.000
0.806
0.816
0.778
0.790
-0.063 -0.225
0.005** 0.000**
9
6
6.964
4.219
2.035
1.566
0.471
0.588
0.856
0.763
0.840
0.727
0.451
0.229
0.000** 0.001**
8
6
6.968
4.765
2.007
1.658
0.500
0.556
0.856
0.790
0.840
0.759
0.416
0.297
0.000** 0.001**
5
7
4.447
3.913
1.538
1.575
0.769
0.667
0.775
0.744
0.738
0.709
0.008
0.104
0.001** 0.010**
6
5
5.626
3.850
1.759
1.466
0.813
0.688
0.822
0.740
0.797
0.699
0.012
0.071
0.000** 0.000**
6.333
5.833
5.395
4.456
1.716
1.595
0.700
0.716
0.801
0.772
0.770
0.738
0.113
0.075
607
Average
across loci
5.833±0.423
4.667±0.325
1.602±0.067
0.676±0.047
0.776±0.014
0.740±0.059
0.131
5.000±0.302
4.019±0.241
1.465±0.059
0.575±0.077
0.742±0.015
0.700±0.063
0.241
7.500±0.417
6.125±0.332
1.875±0.057
0.477±0.049
0.830±0.011
0.808±0.045
0.425
7.917±0.557
6.062±0.412
1.885±0.071
0.438±0.050
0.826±0.013
0.803±0.054
0.476
6.917±0.468
5.155±0.408
1.733±0.066
0.595±0.071
0.795±0.013
0.767±0.053
0.257
6.417±0.229
5.031±0.272
1.703±0.043
0.523±0.077
0.795±0.011
0.766±0.044
0.339
6.597±0.200
5.177±0.159
1.710±0.030
0.547±0.027
0.794±0.006
0.764±0.040
0.311±0.033
* Significant (P≤0.05); **Highly significant (P≤0.01); NS Not significant (P≥0.05); POP: Population; PAR: Parameter; M1:
HNI_A3; M2: HNI_A12; M3: HNI_A5; M4: HNI_A120; M5: HNI_A10; M6: HNI_B9; M7: HNI_B120; M8: HNI_A117;
M9: HNI_C12; M10: HNI_B12; M11: HNI_B104; M12: HNI_C102; Na: Number of alleles; Ne: Effective number of alleles;
PIC: Polymorphic information content; Ho: Observed Heterozygosity; He: Expected Heterozygosity; FIS: Deficit or excess of
Heterozygotes; PHW, Probability value of significant deviation from Hardy–Weinberg equilibrium; I: Shannon’s Information
Index.
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INDIAN J. MAR. SCI., VOL. 45, NO. 4 APRIL 2016
Linkage disequilibrium was tested using a
contingency table test for genotype linkage
disequilibrium between pairs of loci in a
population, based upon the null hypothesis that
genotypes at one locus are independent of
genotypes at other locus. Relationships based on
genetic distance estimates generated from
microsatellite data among the six B. zeylanica
populations were made and a dendrogram was
plotted, employing the UPGMA method with
arithmetic averages24 based on Nei's25 genetic
distance estimates, in MEGA. To test the
confidence level of each branch in the
dendrogram, data were bootstrapped 1000 times.
PCA leads to a representation of populations as a
cloud of points in a metric space. Comparison
between the inertia of single-marker enables to
compare the typological value of markers.
Inertia can be split up according to axes and/or
loci. AMOVA was computed to determine the
genetic differentiation between groups through
FST estimations22.
Results
Genetic variability within populations
A total of 475 alleles were detected over all
twelve microsatellite loci, with the number of
alleles per locus ranging from four at HN1_A12,
HN1_A5, HN1_A120, HN1_B9, HN1_B12 and
HN1_B104 to 12 at HN1_B120 (Table 3). All
natural populations exhibited relatively low
genetic variation and were dissimilar with
average number of alleles per locus varying from
5.000 (NAG) to 7.917 (PUN) and average
number of effective alleles varying from 4.019
(NAG) to 6.125 (RAM) with the global mean of
6.597 and 5.177 respectively. Observed
heterozygosities across loci ranged from 0.438
(PUN) to 0.676 (MUD) and expected
heterozygosities ranged from 0.742 (NAG) to
0.830 (RAM) with the global mean of 0.547 and
0.794 respectively. Observed heterozygosities
were lower than expected in the all studied
populations. Both effective alleles and expected
heterozygosities differed significantly across all
populations. PIC value revealed that all of the
loci studied were highly polymorphic in nature
with a global mean of 0.764±0.040 (Table 3).
Wright's26 fixation index (FIS) a measure of
heterozygote deficiency or excess (inbreeding co
efficient), and significance values for each locus
in six populations are given in Table 3.
Significant departures from Hardy–Weinberg
expectations were observed in 2 of 72 (12 loci×6
populations) single locus exact tests after
applying a sequential Bonferroni correction.
Even though, Shannon’s information index (I)
which measures the level of diversity, was
sufficiently high with a global mean of
1.710±0.030 (Table 3), FIS values greater than
zero indicating a deficiency of heterozygotes
was evident in these cases. Microsatellite loci
exhibiting +FIS values were tested for presence
of null alleles. Estimated null allele frequencies
assessed with MICROCHECKER were not
significant (P>0.05) indicating the absence of
null alleles and false homozygotes at any locus.
Therefore, for population genetic analysis,
information from all twelve microsatellite loci
was considered. A total of eleven private alleles
were observed in MUD (at loci HN1_A3,
HN1_A10, HN1_C12 and HN1_B12), NAG (at
loci HN1_B104 and HNI_C102), RAM (at loci
HN1_A12 and HN1_A117) and COL (at loci
HN1_A10 and HN1_A117) populations (Table
4).
Table 4—Private alleles in microsatellite and their
frequencies in present study
Locus
Allele frequency
Allele
Size (bp) MUD NAG RAM
COL
HNI_A3
254
0.021
HNI_A10
201
0.105
HNI_C12
289
0.037
HNI_B12
301
0.125
HNI_B12
305
0.050
HNI_B104
211
0.071
HNI_C102
187
0.139
HNI_A12
134
0.147
HNI_A117
118
0.231
HNI_A10
143
0.222
HNI_A117
126
0.200
Genetic differentiation between populations
Wright’s FST characterizes the reduction in
individual heterozygosity expected within
subpopulations relative to a total population as a
result of genetic drift, effectively measuring the
extent of population subdivision and the
counteracting evolutionary processes of drift on
the one hand and gene flow on the other23. Pairwise FST estimates between population pairs
varied significantly (P˂0.01) from zero for all
the pairs along the Tamilnadu coast of India
(Table 5).
CHANDRA SHEKAR et al.: MICROSATELLITE ANALYSIS IN BABYLONIA ZEYLANICA
609
Table 5—Pairwise FST (above diagonal) and DA (below
Table 6—AMOVA analysis in six populations
diagonal) among six populations
Variance Percentage
Source of
Degree of Sum of
MUD NAG
RAM
PUN
ARO
COL variation
freedom
squares component of variation
MUD 0.041** 0.061** 0.068** 0.083** 0.093** Among Pops
5
164.879
0.614
4%
NAG 0.315 0.071** 0.076** 0.098** 0.110** Within Pops
181
2503.923
13.834
96%
RAM 0.742 0.801
0.021** 0.059** 0.054** Total
186
2668.802
14.448
100%
PUN 0.873 0.888
0.243
0.045** 0.053**
evolutionary
history
was
inferred
using
The
ARO 1.073 1.266
0.775
0.505
0.064**
the UPGMA method based on Nei’s genetic
COL 1.399 1.687
0.680
0.663
0.770
-
The overall FST value of 0.106 indicated that
10.6% of the detected variation arises from
between population differences and 89.4% from
within population differentiation.
Genetic
distance (DA) tended to be the least (0.243)
between PUN and RAM and the widest (1.687)
between COL and NAG (Table 5). The genetic
differentiation between different pairs of
populations was significantly different from
zero. Further, an AMOVA analysis was carried
out to analyze the variation within and between
populations which revealed that percentage of
variation among and within populations were 4
and 96 respectively (Table 6).
distances (DA) (Fig. 3). Optimal tree with the
sum of branch length = 2.03727854 is shown.
The tree is drawn to scale, with branch lengths
in the same units as those of the evolutionary
distances used to infer the phylogenetic tree.
Clustering pattern of the whelk populations
showed their geographical origin. To
supplement, principal component analysis
(PCA) was performed using the DA values (in
Fig. 4). The first two principal components
explained 52.37% of the total variation. The
first axis contributed about 36.46% of the inertia
and distinguished the all studied populations
from each other. Second axis contributed
15.19% of the inertia, as a result, these two axes
revealed a pattern of association.
0.1200
RAM
0.2000
0.1200
PUN
0.3200
0.1936
ARO
0.3517
COL
0.1550
0.5
0.4
MUD
0.1550
0.3903
0.3
0.2
0.1
NAG
0.0
Fig. 3— UPGMA clustering using Nei's unbiased genetic distance (1978) of the B. zeylanica sampling locations based on
twelve microsatellite loci
Fig. 4—Coordinates of the six populations plotted in dimensions 1 and 2 of the PC
610
INDIAN J. MAR. SCI., VOL. 45, NO. 4 APRIL 2016
Discussion
Twelve polymorphic microsatellite loci
developed for Hexaplex nigritus by Longo et
al.15 were used to evaluate genetic diversity
and genetic variation in natural population of
B. zeylanica collected from four different
geographical locations of Tamil Nadu coastal
waters of India (Fig. 2). Microsatellite markers
used for genetic diversity studies should have
more than four alleles in order to have a precise
estimate of genetics distance27. In the present
investigation all markers had more than four
numbers of alleles indicating that the markers
used are appropriate to analyse diversity in the
whelk genetic groups of Tamilnadu coastal
waters.
Allelic and gene diversities are considered
as responsible indicators of genetic variation
within the populations28. All the investigated
populations in the present study have shown
low genetic variability based on their estimates
of effective number of alleles and observed
heterozygosity. The global mean number of
alleles observed (6.597) in the present study is
lower than the mean number (13.125) reported
for B. areolata 11 and H. nigritus (19.385),
marine gastropods15. Global mean of effective
alleles (5.177) is lower than the observed
number of alleles which might be due to very
low frequency of most of the alleles at each
locus and few alleles might have contributed to
the major part of the allelic frequency.
However, contrary to the present finding, lower
mean number of effective alleles (4.664) was
reported in B. spirata29.
The global mean of observed and expected
heterozygosity (0.547 and 0.794) in the present
study is lower than the observed (0.700) and
expected (0.854) heterozygosity in B. areolata
11
. However, the present findings of observed
and expected heterozygosities observed in the
present investigation are in accordance with the
findings of Longo et al.15 in H. nigritus
populations viz., Punta Chueca (PCH) (0.608
and 0.742); El Borrascoso (EBO) (0.632 and
0.747); Isla San Jorge (ISJ) (0.679 and 0.775);
San Luis Gonzaga (SLG) (0.7 and 0.762).
Genetic markers showing PIC values higher
than 0.5 are normally considered as
informative in population genetic analyses30.
Consequently, all the loci in the present
investigation possessed high PIC values (above
0.50) signifying once again that these markers
are highly informative for characterization of
B. zeylanica genetic groups of South East coast
of India. Global mean PIC value (Table 3) in
the B. zeylanica populations under study
(0.764) corroborated with the mean PIC
(0.727) in B. spirata29.
The deviation from HWE (Table 3) and
moderately higher global mean FIS (0.311)
observed in the present study could be attributed
to several factors viz., non-random mating, nonamplifying alleles or the genetic drift. A similar
observation of heterozygosity shortfall (32.3 %)
has also been reported in B. spirata
population29. Inbreeding detected in these
populations could possibly be attributed to
increased exploitation rate in recent past and
fishing of undersized whelks, owing to the
market demand. Generally, gastropods are
having slow migration rate and small breeding
territories which lead to their genetic death.
Altogether the effective population size is
curtailed and breeding between relatives
stimulates inbreeding and genetic drift. MicroChecker analysis revealed that absence of null
alleles in B. zeylanica population sampled here
and also supports to nonexistence of stutter
bands31. The fixation coefficient of populations
(FST) had a global mean of 0.106, showing that
10.6% of the genetic variation was explained by
differences between populations. In addition,
AMOVA indicated the genetic variation
between populations to be 4%, confirming
moderately higher within population diversity in
the investigated genetic groups. However, the
measures of population differentiation indicated
trivial differences between groups.
There was no evidence of significant
population sub-structuring among all samples
from natural waters. The PCA (Fig. 4) analysis
using Nei's25 unbiased minimum distance
clearly supported the above population
differentiation analysis based on pair-wise FST
Moreover, an unrooted UPGMA
values.
diagram (Fig. 3) is based on a dissimilarity
matrix of genetic distances that are symmetrical
and unsigned, and as indicated that populations
were grouped according to their geographic
locations.
The present finding of genetic divergence of
microsatellite allele frequencies among sampled
B. zeylanica populations suggests that Indian
CHANDRA SHEKAR et al.: MICROSATELLITE ANALYSIS IN BABYLONIA ZEYLANICA
southeast coast populations are drawn from the
same panmictic, randomly mating gene pool.
Whether each of the six sub-populations studied
should therefore be treated as separate
management units cannot be determined with
the information available now. A natural
extension of the present study will be to
examine life history traits in this species at the
population level to assist in formulating
strategies for managing and supplementing wild
stocks. Whatever management strategies are
eventually
developed,
evaluation
and
monitoring of genetic diversity and population
structure will be critical for their success. The
information would also be required for
successful domestication programme. In the
long term, the extent of genetic gain under
selection is proportional to the available genetic
variance and hence, the study calls for further
investigation to identify the factor(s) that
influence genetic heterogeneity in B. zeylanica
populations.
Conclusion
The PIC values observed in the present study
is indicative of the fact that the markers used are
highly informative for characterization of whelk
germplasms of India. With the actual genetic
diversity and the population structure of these B.
zeylanica species evaluated, it was possible to
clarify the importance as well as to propose
some management strategies for this genetic
resource. This fact, coupled with evident
environmental adaptation, emphasizes the
importance of genetic regulation and
conservation of these indigenously evolved
germplasm and for sustainable utilization. The
results show that levels of genetic diversity in
natural populations of specific genetic group are
moderately low. Estimates of differentiation and
genetic structure confirm the geographical origin
of individual populations.
Acknowedgement
Authors are thankful to the authorities of
Annamalai University for constant support and
encouragement for this study and to authorities
of Network Project on Animal Genetic
Resources- Core Laboratories from Assam,
Gujarat and Chennai for providing necessary
facilities, technical support and valuable
guidance during the period of study. We also
611
take the opportunity to acknowledge the help
rendered by fisherman in the field throughout
sample collections.
References
1. Ayyakkannu K, Fishery status of Babylonia spirata at
Port Novo Southeast coast of India. Phuket. Mar. Boil.
Cent. Spl. Publ., 13 (1994) 53-56.
2. FAO
(2011)
http://www.fao.org/docrep/019/i3507t/i3507t.pdf
3. Dulvy NK, Sadovy Y & Reynolds JN, Extinction
vulnerability in marine populations. Fish and Fisheries,
4 (2003) 25-64.
4. Narasimham KA (2005) Molluscan fisheries of India.
348pp, B.R. Publishing corporation, Delhi, India.
5. Knowlton N, Molecular genetic analyses of species
boundaries in the sea. Hydrobiologia, 420 (2000): 73–
90.
6. Hobday AJ & Tegner MJ (2000) Status review of white
abalone (Halotis sorenseni) throughout its range in
Califomia and Mexico. NOAA Tech. Memor. NMFSSWR-O35, 90 pp.
7. FAO
(2013)
http://www.fao.org/docrep/004/v1430e/V1430E04.htm
8. Diz AP & Presa P, Regional patterns of microsatellite
variation in Mytilus galloprovincialis from the Iberian
Peninsula. Mol. Biol, 154 (2008) 277-286.
9. Castillo JS, Gardner MG & Beheregaray LB, Isolation
and characterization of microsatellite markers for the
marine black nerite, Nerita atramentosa: tools for
assessment and design of marine protected areas.
Conservation Genetic Resource first published online
February 22, 2012 doi:10.1007/s12686-012-9608-7.
10. Geist J, Geismar J & Kuehn R, Isolation and
characterization of the first microsatellite markers for
the endangered swan mussel, Anodonata cygnea L.
(Bivalvia: Unionoidea). Conserv Genet, 11 (2010)
1103-1106.
11. Wang Y, Lu H, Zheng J, Long K, Shi YH, Gu ZF &
Wang AM, Eight polymorphic microsatellite markers
for the spotted babylon, Babylonia areolata
(Buccinidae). Genetics and Molecular Research, 10 (4)
(2011) 3230-3235.
12. Wang Y, Wang X, Wang A & Guo X, A 16microsatellite multiplex assay for parentage assignment
in the eastern oyster (Crassostrea virginica Gmelin).
Aquaculture, 308 (2010):S28-S33.
13. Asahida T, Kobayashi T, Saitoh K & Nakayarma I,
Tissue preservation and total DNA extraction from fish
stored at ambient temperature using buffers containing
of urea. Fisheries Sci., 62 (1996) 727-730.
14. Bayani W, Omar1 W, Shafie M, Shafie B & Kasim Z,
DNA extraction from different preserved tissues of
Cassidula aurisfelis for PCR study. Nature and Science,
7(9) (2009) 8-14.
15. Longo G, Beldade R, Cudney-Bueno R, Raimondi P &
Bernardi G, Isolation and characterization of 13
polymorphic microsatellites for the black murex,
Hexaplex nigritus. Marine Genomics, 4 (2011) 69-70.
16. Henegariu O, Heerema NA, Dlouhy SR, Vance GH &
Vogt PH, Multiplex PCR: Critical parameters and stepby-step protocol. Biotechniques, 23 (1997) 504-511.
PMID: 9298224
612
610612
INDIAN J. MAR. SCI., VOL. 45, NO. 4 APRIL 2016
17. Loffert D, Karger S, Twieling G, Ulber V & Kang J,
Optimization of multiplex PCR. Qiagen News Issue. 2
(1999) 5-8.
18. Peakall ROD & Smouse PE, Genalex 6: Genetic
analysis in Excel. Population genetic software for
teaching and research. Mol. Ecol. Notes, 6(1) (2006):
288-295.
19. Park SDE (2001) Trypanotolerance I West African
cattle and the population genetic effects of selection,
Ph.D. thesis. University of Dublin.
20. Van Oosterhout C, William FH, Derek PMW & Peter S,
Micro-checker: software for identifying and correcting
genotyping errors in microsatellite data. Mol. Ecol.
Notes, 4 (2004): 535-538.
21. Tamura K, Peterson D, Peterson N, Stecher G, Nei M &
Kumar S, MEGA5: Molecular Evolutionary Genetics
Analysis using Maximum Likelihood, Evolutionary
Distance, and Maximum Parsimony Methods. Mol.
Biol. Evol. first published online May 4, 2011
doi:10.1093/molbev/msr121.
22. Weir BS & Cockerham CC, Estimating F-statistics for
the analysis of the population structure. Evolution, 38
(1984) 2601-2608.
23. Hartl DL & Clark AG (1997) Principles of population
genetics, third ed. Sinauer Associates, Inc., Sunderland,
Massachusetts, USA.
.
24. Sneath PHA & Sokal RR (1973) Numerical Taxonomy.
WH Freeman and Co., San Francisco, CA.
25. Nei M, Estimation of average heterozygosity and
genetic distance from a small number of individuals.
Genetics. 89 (1978) 583–590.
26. Wright S (1978) Evolution and the genetics of
populations. Univ. Chicago Press, Chicago.
27. Takezaki N & Nei M, Genetic distances and
reconstruction of phylogenetic tree from microsatellite
DNA. Genetics, 144 (1996) 389-399.
28. Waples RS, A multispecies approach to the analysis of
gene flow in marine shore fishes. Evolution, 41(2)
(1987) 385-400.
29. Arularasan S, Chandra Shekar M, Zaman G,
Karthikeyan SMK, Rank DN, Jisha TK, Muthazlaian R
& Balasubramanian T, Evaluation of within species
Diversity in Natural Stock of Babylonia spirata
(Linnaeus, 1758), Along Tamilnadu Coast of India
Using Microsatellite Markers. World Journal of Fish
and Marine Sci., 6 (1) (2014) 66-71.
30. Botstein D, White RL & Skolmick H, Construction of a
genetic linkage map in man using restriction fragment
length polymorphism. American Journal of Human
Genetics, 32 (1980) 314-331.
31. Van Oosterhout C, Weetman D & Hutchinson WF,
Estimation and adjustment of microsatellite null alleles
in nonequilibrium population. Mol. Ecol. Notes, 6
(2006)
255-256.