Genetic Characterization Of Perna Viridis L. In Peninsular ...

c Indian Academy of Sciences
RESEARCH ARTICLE
Genetic characterization of Perna viridis L. in peninsular Malaysia
using microsatellite markers
C. C. ONG1, K. YUSOFF2, C. K. YAP1 and S. G. TAN3∗
1Genetics Laboratory, Department of Biology, Faculty of Science, Universiti Putra Malaysia,
43400 UPM Serdang, Malaysia
2Department of Microbiology, 3Department of Cell and Molecular Biology, Faculty of Biotechnology and
Biomolecular Sciences, Universiti Putra Malaysia, 43400 UPM Serdang, Malaysia
Abstract
A total of 19 polymorphic microsatellite loci were used to analyse levels of genetic variation for 10 populations of Perna
viridis L. collected from all over peninsular Malaysia. The populations involved in this study included Pulau Aman in Penang,
Tanjung Rhu in Kedah, Bagan Tiang in Perak, Pulau Ketam in Selangor, Muar, Parit Jawa, Pantai Lido and Kampung Pasir
Puteh in Johore, and Kuala Pontian and Nenasi in Pahang state. The number of alleles per locus ranged from two to seven,
with an average of 3.1. Heterozygote deﬁciencies were observed across all the 10 populations. Characterization of the
populations revealed that local populations of P. viridis in peninsular Malaysia were genetically similar enough to be used
as a biomonitoring agent for heavy metal contamination in the Straits of Malacca. Cluster analysis grouped the P. viridis
populations according to their geographical distributions with the exception of Parit Jawa. The analysis also revealed that P.
viridis from the northern parts of peninsular Malaysia were found to be the most distant populations among the populations
of mussels investigated and P. viridis from the eastern part of peninsular Malaysia were closer to the central and southern
populations than to the northern populations.
[Ong C. C., Yusoﬀ K., Yap C. K. and Tan S. G. 2009 Genetic characterization of Perna viridis L. in peninsular Malaysia using microsatellite
markers. J. Genet. 88, 153–163]
Introduction
contamination in the Straits of Malacca; which is one of the
busiest shipping lanes in the world. However, before this
The green-lipped mussel, Perna viridis L., is native to the
species can be used as a biomonitoring agent for heavy metal
Indo–Paciﬁc region and currently they are being extensively
contamination in the Straits of Malacca, it needs to fulﬁll
cultured in many Asian countries; largely because of their
several recommended criteria. Among the criteria are that
value as a cheap source of animal protein for human con-
P. viridis collected from diﬀerent geographical populations
sumption (Nicholson and Lam 2005). Besides being con-
along the straits should have similar morphological charac-
sumed as a protein rich food, they are also used as a biomon-
teristics for easy and correct species identiﬁcation, and low-
itoring agent for heavy metal contamination in various Asian
to-moderate degrees of genetic diﬀerentiation as they may
countries (Monirith et al. 2003).
genetically adapt to heavy metal stresses (Gyllensten and Ry-
In Malaysia, this mussel is widely distributed along the
man 1985; Rainbow 1995). Therefore, studies on the pop-
Straits of Malacca and, to a lesser extent, in certain parts of
ulation genetic structure of P. viridis in Malaysia should be
Sabah state on Borneo Island and the east coast of peninsu-
done to validate whether P. viridis populations collected from
lar Malaysia. This mussel has been proposed by Ismail et
the coastal waters of peninsular Malaysia have low degree of
al. (2000) as a potential biomonitoring agent for heavy metal
genetic diﬀerentiation so that any diﬀerences in the biomon-
itoring parameters obtained from the tissues of mussels from
diﬀerent areas were not confounded by genetic factors rather
*For correspondence. E-mail: sgtan 98@yahoo.com.
Keywords. biomonitoring agent; green-lipped mussel; microsatellite markers; population structure; genetic variation; Perna viridis.
Journal of Genetics, Vol. 88, No. 2, August 2009
153

C. C. Ong et al.
than being due to real diﬀerences in the environmental pol-
Materials and methods
lutants levels.
Materials
Until today molecular genetic markers such as allozymes,
RAPD and RAM have been used to elucidate genetic infor-
P. viridis were collected from 10 diﬀerent locations (ﬁgure 1)
mation relating to local populations of P. viridis. Results
in peninsular Malaysia. The sample size for each locations
based on allozymes support the use of P. viridis as a biomoni-
was 20, except for Pulau Aman (Penang) only 10 individuals
toring agent for heavy metal contamination in the straits (Yap
were obtained. Table 1 shows the sampling date, sample size
et al. 2002). However, Yap et al. (2004) reported that there is
a distinct genetic variation between P. viridis populations col-
lected from contaminated and uncontaminated sites, in which
a population from a contaminated site showed an excess of
heterozygosity when compared to those of the populations
from three uncontaminated sites. This in turn would put into
question the genetic relationships among the eight P. viridis
populations that were obtained by Yap et al. (2002), because
the selective neutrality of all the allozymes that were used
to estimate the genetic distance values had been assumed.
Moreover, a study by Chua et al. (2003) based on RAPD and
RAM markers showed clustering of populations that diﬀered
from those derived from the use of allozyme marker data.
In order to clarify the above, it is apparent that a more
powerful marker system is required and a single locus DNA
microsatellite markers appears to be the best choice be-
cause of reproducibility, codominant inheritance, high lev-
els of polymorphism, assay ability by PCR, conformity to
Mendelian inheritance and selective neutrality. Therefore,
the objective of this paper is to validate whether local popula-
tions of P. viridis collected from the coastal waters of penin-
sular Malaysia are genetically similar enough to be used as
a biomonitoring agent for heavy metal contamination in the
Straits of Malacca by using the more informative single lo-
cus DNA microsatellite markers compared to the ﬁndings by
using allozymes (Yap et al. 2002).
Figure 1. Map of peninsular Malaysia indicating the sampling sites
of P. viridis.
Table 1. Sampling date, sample size (N), longitude and latitude of the sampling sites, method of sample collection and description of
sampling sites for P. viridis from 10 locations in peninsular Malaysia.
Latitude
Longitude
Method of
No.
Location
State
Sampling date
N
(north)
(east)
collection
Description of sampling site
1
Tanjung Rhu
Kedah
April 2002
20
6◦25
99◦44
Wild
Recreational and aquacultural areas
2
Pulau Aman
Penang
April 2002
10
5◦17
100◦23
Wild
Fish aquacultural area
3
Bagan Tiang
Perak
April 2002
20
5◦07
100◦25
Wild
Aquacultural area
4
Pulau Ketam
Selangor
June 2002
20
3◦01
101◦16
Wild
Fishing village
5
Muar
Johore
February 2002
20
2◦02
102◦34
Wild
Agricultural area
6
Parit Jawa
Johore
April 2004
20
1◦57
102◦39
Bought from
Mussel aquacultural area
roadside
7
Pantai Lido
Johore
April 2002
20
1◦27
103◦41
Wild
Urban and agricultural areas
8
Kampung
Johore
April 2002
20
1◦26
103◦55
Wild
Industrial, shipping and urban runoﬀ
Pasir Puteh
9
Kuala Pontian
Pahang
April 2004
20
2◦46
103◦32
Cultured
Mussel aquacultural site; clean site
10
Nenasi
Pahang
April 2004
20
3◦08
103◦27
Near by
A lighthouse; pristine waters
lighthouse
154
Journal of Genetics, Vol. 88, No. 2, August 2009

Genetic variation of Perna viridis L. in peninsular malaysia
(N), longitude and latitude of the sampling sites, method of
dle. According to the manufacturer, the gel is capable of
sample collection and description of sampling sites for the 10
resolving PCR fragments diﬀering in size by 4 bp. A 2–4%
locations. In the laboratory, the adductor muscle was excised
®
MetaPhor
agarose gel has approximately the resolution
from the mussel and kept at −80◦C prior to DNA extraction
power of 4%–8% polyacrylamide gel.
Comparative runs
and analysis.
were initially done on 8% (w/v) polyacrylamide gel to con-
ﬁrm this. The PAGE gels were also stained in ethidium bro-
Isolation of genomic DNA and microsatellite ampliﬁcation
mide (0.1 mg/mL) and photographed using the Alpha Imager
Genomic DNA from P. viridis adductor muscle was iso-
gel documentation system (Siber Hegner, Zurich, Switzer-
lated by using a CTAB-based protocol described by
land).
Winnepennincks et al. (1993) with minor modiﬁca-
tions.
The modiﬁcations were omission of 0.2% v/v β-
Data analysis
mercaptoethanol, which hinders DNA oxidation during the
extraction, from the extraction buﬀer, and inclusion of phe-
Genetic variability measures including mean number of al-
nol : chloroform : isoamylalcohol extraction step to remove
leles per locus and mean heterozygosity were calculated
proteins from the cell lysate before proceeding to the ethanol
for all the populations.
The F-statistics were calculated
precipitation step.
according to Wright (1978), providing a measure of the
PCR ampliﬁcations were performed in a 10 μL ﬁnal re-
deﬁciency or excess of heterozygotes. Chi-square goodness-
action volume containing 25 ng of genomic DNA, 1× PCR
of-ﬁt tests were used to determine whether the observed
®
genotypic numbers were consistent with Hardy–Weinberg
buﬀer (10 mM Tris-HCl, 50 mM KCl and 0.1% Triton
X-
expectations for each population. Nei (1978) unbiased ge-
100), 0.25 mM each of dNTPs, 0.15 μM of each reverse and
netic distance (D
forward primers, 1–3.75 mM of MgCl
N), which takes small sample size into con-
2 and 0.5–1.5 U of
sideration, was calculated to assess the genetic distances
Taq DNA polymerase (Promega, Madison, USA). Ampliﬁ-
among the populations. All the genetic data were analysed
cations were performed in a Peltier Thermal Cycler PTC-
by using the POPGENE version 1.32 (Yeh and Boyle 1997),
220 (MJ Research, Waltham, USA) with an initial 3 min of
except for the hierarchical F-statistics analysis, which was
pre-denaturation at 95◦C, followed by 35–40 cycles of denat-
done using the BIOSYS-1 computer package of Swoﬀord
uration at 94◦C for 30 s, an optimum annealing temperature
and Selander (1989). By using the multivariate analysis soft-
(as shown in table 1 of appendix) for 30 s and extension at
ware NT-SYS (Rohlf 1989), an UPGMA dendrogram was
68◦C for 30 s. The ampliﬁcations were concluded with a 5
constructed based on Nei (1978) unbiased genetic distance
min ﬁnal extension at 68◦C.
estimates to depict the genetic relationships among the pop-
The P. viridis speciﬁc primer pairs that were used in this
ulations of P. viridis.
study are presented in table 1 of appendix. Loci BP2-49-
1, BP2-49-2, VJ1-12-2 and VJ1-18-1 were from Ong et al.
(2005), loci BP2-35-2, BP9-7-1, BP9-13-2, BP9-16-2, BP9-
Results
19-2, BP9-27-1, BP14-7-1, VJ1-9-1, VJ1-15-1, VJ1-21-2
®
and VJ1-22-2 were from Ong et al. (2008), while loci BP10-
Metaphor
agarose gel versus polyacrylamide gel
5-1, BP10-16-1, BP10-17-2 and LR1-58-1 are reported here
Comparisons of the electrophoresis gel resolutions between
for the ﬁrst time.
®
4% Metaphor
agarose and 8% polyacrylamide gels re-
vealed that there was no signiﬁcant diﬀerence between the
Electrophoresis of PCR products
results produced by either gel type (ﬁgure 2). This result
A total of 10 μL of PCR product was mixed with 3 μL of
®
showed that the resolution for 4% Metaphor
agarose gel
gel-loadding buﬀer (0.25% bromophenol blue, 0.25% xylene
was as good as 8% polyacrylamide gel, as claimed by its
cyanol FF and 40% w/v sucrose in water). A 20 bp DNA
manufacturer. However, polyacrylamide gel was still used
ladder (200 ng/μ L; BioWhittaker Molecular Applications,
®
whenever the separation of bands was unclear in Metaphor
Rockland, USA) was used as the molecular weight standard.
agarose gel, for conﬁrmation purposes.
The PCR products were then electrophoresed on 4% (w/v)
®
horizontal MetaPhor
agarose gel (BioWhittaker Molecular
Analysis of genetic variability
Applications, Rockland, USA) at 74 V for 3–4 h with 1×
TBE (89 mM Tris-base, 89 mM boric acid and 2 mM EDTA)
The genetic variability indices estimated for the 10 P. viridis
as running buﬀer. The gel was then stained in ethidium bro-
populations are summarized in table 2 and table 2 of ap-
mide (0.1 mg/mL) and photographed using the Alpha Imager
pendix. The range of number of alleles observed at each of
Gel Documentation System (Siber Hegner, Zurich, Switzer-
the 19 loci across all the populations was two to seven. All
land).
the 10 populations showed lower mean observed heterozy-
®
MetaPhor
agarose gel was used due to its high-
gosity values than expected. The highest mean observed het-
resolution capabilities and its being easy to cast and han-
erozygosity was found in the Pulau Ketam population with
Journal of Genetics, Vol. 88, No. 2, August 2009
155

C. C. Ong et al.
ulation had the highest diﬀerence between the means of ob-
served and expected heterozygosity values (0.08) while the
Parit Jawa and Kuala Pontian population had the least diﬀer-
ence (0.02). Values of F-statistics for P. viridis are presented
in table 2. The mean FIS, FIT and FST values were 0.174,
0.255 and 0.098, respectively. The positive values of both
the mean FIS and the mean FIT indicated deﬁcit of heterozy-
gosity across all the populations and the mean FST value of
0.098 showed very moderate genetic diﬀerentiation among
the populations of P. viridis. Two loci; namely BP2-35-2 and
BP14-7-1 showed signiﬁcant deviations from HWE in all the
10 populations.
®
Genetic diﬀerentiation
Figure 2. Comparison between 4% Metaphor
agarose gel and 8%
polyacrylamide gel electrophoresis of the ampliﬁcation products of
Wright’s (1978) hierarchical F-statistics (table 3) shows that
primer pair BP2-35-2 from the Pantai Lido population: (A) the
®
populations within the two, three and four regions accounted
banding proﬁles when electrophoresed on 4% Metaphor
agarose
for 13.9%, 36.1% and 47.2%, respectively, of the total vari-
gel, and (B) the same PCR products run on 8% polyacrylamide.
ance, while the between and among region variance com-
a value of 0.21, while the lowest was found in the Pulau
ponents were 86.1%, 63.8% and 52.8% of the total, re-
Aman population with a value of 0.14. The Pantai Lido pop-
spectively, depending on which hierarchy was considered.
Table 2. Population genetics parameters for 19 polymorphic microsatellite loci
in the 10 P. viridis populations.
Locus
NO (NE)
Ho
He
FIS
FIT
FST
BP2-35-2
4 (1.60)
0.050
0.380
0.855
0.869
0.096
BP2-49-1
5 (1.30)
0.194
0.234
0.134
0.169
0.040
BP2-49-2
4 (1.37)
0.281
0.268
−0.090
−0.050
0.037
BP9-7-1
2 (1.11)
0.103
0.098
−0.071
−0.057
0.013
BP9-13-2
2 (1.06)
0.058
0.056
−0.148
−0.031
0.102
BP9-16-2
2 (1.46)
0.390
0.315
−0.255
−0.240
0.012
BP9-19-2
2 (1.05)
0.045
0.044
−0.053
−0.024
0.027
BP9-27-1
3 (1.24)
0.220
0.197
−0.167
−0.114
0.045
BP10-5-1
2 (1.17)
0.154
0.142
−0.099
−0.085
0.013
BP10-16-1
2 (1.04)
0.042
0.042
−0.046
−0.020
0.024
BP10-17-2
4 (2.33)
0.475
0.573
0.106
0.155
0.055
BP14-7-1
7 (2.88)
0.087
0.654
0.822
0.863
0.229
LR1-58-1
4 (2.05)
0.183
0.514
0.591
0.638
0.115
VJ1-9-1
2 (1.57)
0.480
0.366
−0.395
−0.317
0.056
VJ1-12-2
3 (1.20)
0.148
0.165
0.129
0.143
0.017
VJ1-15-1
2 (1.06)
0.050
0.059
0.015
0.137
0.124
VJ1-18-1
4 (2.45)
0.484
0.593
−0.008
0.197
0.204
VJ1-21-2
2 (1.10)
0.097
0.093
−0.089
−0.049
0.037
VJ1-22-2
2 (1.08)
0.075
0.072
−0.059
−0.036
0.022
Mean
3.1 (1.48)
0.191
0.256
0.174†
0.255
0.098
NO, observed number of alleles; NE, eﬀective number of alleles (Kimura and
Crow 1964); Ho, observed heterozygosity; He, expected heterozygosity.
†The mean FIS value based on 16 polymorphic microsatellite loci was −0.068
when three loci; namely, BP2-35-3, LR1-58-1 and BP14-7-1 were excluded
from this analysis in order to determine whether the FIS value would still show
deﬁcit of heterozygosity across the 10 P. viridis populations.
156
Journal of Genetics, Vol. 88, No. 2, August 2009

Genetic variation of Perna viridis L. in peninsular malaysia
Therefore, the hierarchical F-statistics suggest that a greater
was found between the Pulau Aman and Kuala Pontian pop-
amount of the genetic variation is due to diﬀerentiation be-
ulations and while the Nenasi and Kuala Pontian populations
tween (northern and southern) or among (northern, central,
had the lowest DN value (0.0070) (table 4).
southern and eastern) regions.
The UPGMA dendrogram constructed based on DN esti-
mates revealed two major clusters (ﬁgure 3). The ﬁrst clus-
Genetic distance and cluster analysis
ter consisted of P. viridis collected from the northern part
The analysis of Nei (1978) unbiased genetic distance (DN)
of peninsular Malaysia (the Pulau Aman and Tanjung Rhu
among the 10 populations showed high genetic similarity
populations) while the second cluster consisted of popula-
among the 10 populations of P. viridis with a range of DN
tions collected from the central, southern and eastern parts
values from 0.0070 to 0.0785. The highest DN value (0.0785)
of peninsular Malaysia.
The second cluster was further
Table 3. Wright’s (1978) hierarchical F-statistics of genetic diﬀerentiation for
the 10 P. viridis populations grouped into two (northern and southern), three
(northern, central and southern) and four (northern, central, southern and east-
ern) regions.
Contrast
Variance component
(%)
Fxy
Populations in two regions
0.05
13.9
0.011
Populations in three regions
0.13
36.1
0.027
Populations in four regions
0.17
47.2
0.035
Between two regions
0.31
86.1
0.064
Among three regions
0.23
63.8
0.049
Among four regions
0.19
52.8
0.041
Among all populations
0.36
100.0
0.075
Note: The two regions were northern (Tanjung Rhu and Pulau Aman) and south-
ern (Bagan Tiang, Pulau Ketam, Muar, Parit Jawa, Pantai Lido, Kampung Pasir
Puteh, Kuala Pontian and Nenasi); the three regions were northern (Tanjung
Rhu and Pulau Aman), central (Bagan Tiang, Pulau Ketam, Muar, Parit Jawa)
and southern (Pantai Lido, Kampung Pasir Puteh, Kuala Pontian and Nenasi);
the four regions were northern (Tanjung Rhu and Pulau Aman), central (Bagan
Tiang, Pulau Ketam, Muar, Parit Jawa), southern (Pantai Lido and Kampung
Pasir Puteh) and eastern (Kuala Pontian and Nenasi).
Figure 3. UPGMA dendrogram of genetic relationships among 10 populations of P. viridis based on
Nei’s (1978) unbiased genetic distance derived from 19 microsatellite loci.
Journal of Genetics, Vol. 88, No. 2, August 2009
157

C. C. Ong et al.
Table 4. Nei’s (1978) unbiased measures of genetic distance based on 19 microsatellite loci in the 10 populations of P. viridis
from peninsular Malaysia.
Populations
Pulau
Tanjung
Bagan
Pulau
Muar
Parit
Pantai
Kampung
Kuala
Nenasi
Aman
Rhu
Tiang
Ketam
Jawa
Lido
Pasir Puteh
Pontian
Pulau
******
Aman
Tanjung
0.0172
******
Rhu
Bagan
0.0482
0.0306
******
Tiang
Pulau
0.0393
0.0296
0.0072
******
Ketam
Muar
0.0502
0.0394
0.0117
0.0134
******
Parit
0.0584
0.0319
0.0176
0.0318
0.0356
******
Jawa
Pantai
0.0210
0.0180
0.0143
0.0168
0.0212
0.0235
******
Lido
Kampung
0.0486
0.0319
0.0274
0.0291
0.0360
0.0237
0.0168
******
Pasir Puteh
Kuala
0.0785
0.0432
0.0296
0.0368
0.0548
0.0213
0.0345
0.0173
******
Pontian
Nenasi
0.0772
0.0467
0.0348
0.0417
0.0571
0.0223
0.0329
0.0112
0.0070
******
diﬀerentiated into two subclusters, with the Bagan Tiang, Pu-
®
of P. viridis. The MetaPhor
agarose gels that we used to
lau Ketam, Muar and Pantai Lido populations in the ﬁrst sub-
type the microsatellite loci in this study had been shown by
cluster and the Kampung Pasir Puteh, Kuala Pontian, Nenasi
Ochsenreither et al. (2006) to be as eﬃcient as polyacry-
and Parit Jawa populations in the second subcluster.
lamide gels and an automated capillary sequencer system
(CEQ 8000; Beckman Coulter, Fullerton, USA) and by Ka-
mara et al. (2007) to be comparable with the ABI PRISM
Discussion
3100 Genetic Analyzer (Applied Biosystems, Foster City,
USA) for microsatellite allele discrimination.
In this study, 19 polymorphic microsatellite loci were used
Heterozygote deﬁciency was observed across all the 10
to analyse the levels of genetic variation for 10 populations
populations. This ﬁnding was not uncommon as studies of
of P. viridis collected from all over peninsular Malaysia. The
marine bivalves often report lower values of observed het-
analysis revealed low genetic variation within and among the
erozygosities than those expected under Hardy–Weinberg
10 populations of P. viridis and this supports the use of local
equilibrium (Zouros and Foltz 1984; Arnaud-Haond et al.
populations of P. viridis as a suitable biomonitoring agent for
2003). Inbreeding, Wahlund eﬀect, null alleles, natural se-
heavy metal contamination in the Straits of Malacca. From
lection, mutation, gene ﬂow, genetic drift and aneuploidy
a biomonitoring point of view, it is very important to use
are some of the reasons that have been oﬀered to explain
a single species to act as a biomonitor. This single species
these phenomena (Lowe et al. 2004). O’Connell and Wright
should have similar morphological characteristic and low-
(1997) suggested that a minimum sample size of 50 individ-
to-moderate degrees of genetic diﬀerentiation because dif-
uals per population should be considered for loci showing
ferent species or subspecies have diﬀerent rates of regula-
between ﬁve and ten alleles. In this study, except for one
tion, excretion and sequestration of contaminants (metals) in
site, 20 samples were typed due to both the limited num-
the mussel body which may render invalid the results of a
ber of samples available and the expense of the assay. The
biomonitoring programme.
presence of null alleles could also aﬀect our results as this
The number of alleles at each of the 19 loci that ranged
is a common problem with microsatellite loci (Callen et al.
from two to seven per locus (average 3.1 per locus) was
1993; Hare et al. 1996; O’Connell and Wright 1997). An
higher than those from a previous study using allozyme
individual heterozygous for a null allele would be scored as
markers (Yap et al. 2002).
However, this was relatively
being homozygous for the alternative allele (Kalinowski and
low when compared to the generally reported number of
Taper 2006).
alleles per locus for microsatellite loci in the literature,
Analysis of F-statistics revealed that the overall FIS value
which usually ranged from two to more than 10, suggest-
was largely inﬂuenced by three loci; namely BP2-35-2, LR1-
ing low levels of allelic diversity for the local populations
158
Journal of Genetics, Vol. 88, No. 2, August 2009

Genetic variation of Perna viridis L. in peninsular malaysia
58-1 and BP14-7-1 which showed considerably higher pos-
gions. The Kampung Pasir Puteh (east side of the Johore
itive FIS values compared to the other loci and two loci,
Straits) and Pantai Lido (west side of the Johore Straits)
namely BP14-7-1 and BP2-35-2, showed signiﬁcant devia-
were grouped separately into diﬀerent subclusters although
tions from HWE in all the 10 populations. Further statistical
both are located near to each other in the Straits of Johore,
analysis excluding these three loci was carried out in order to
which separates the Malaysian state of Johore to the north
determine whether the FIS value would still show a deﬁcit of
from Singapore to the south. The most likely explanation for
heterozygosity across the 10 P. viridis populations. A nega-
this observation is that the Johore causeway linking Johore
tive mean FIS value of −0.068, indicating excess of heterozy-
to Singapore island blocked the gene ﬂow by pelagic disper-
gosity, was obtained when the three loci were excluded from
sal between these two sites which are on diﬀerent sides of
the analysis (table 2). FST values can be used to determine
the causeway. Hence this physical barrier to the free ﬂow
the degree of genetic diﬀerentiation among populations of P.
of sea water has had a biological eﬀect on the green-lipped
viridis. According to Wright (1978), there are four qualita-
mussel. Yap et al. (2004) reported higher concentrations of
tive guidelines for the interpretation of FST: 0–0.05 for little
copper and cadmium in the total soft tissues of mussels col-
genetic diﬀerentiation, 0.05–0.15 for moderate genetic dif-
lected from Kampung Pasir Puteh when compared to those
ferentiation, 0.15–0.25 for large genetic diﬀerentiation and
from other geographical populations. Although the 19 poly-
above 0.25 for very large genetic diﬀerentiation. Based on
morphic microsatellite loci used in this study did not specif-
these guidelines, the FST values showed that our samples be-
ically distinguish the mussels from this area from those of
longed to the same species but with moderate genetic diﬀer-
the other geographical populations we studied, they are use-
entiation among the regional populations. Hence, this mussel
ful to identify the geographical origins of the mussel popula-
is suitable to be used as a biomonitoring agent for the waters
tions since the dendrogram clearly grouped the populations
of peninsular Malaysia since the same species is found in the
into distinct geographical regions. The Parit Jawa popula-
Straits of Malacca, the Straits of Johore and the South China
tion, the only samples used in this study that were bought
Sea which surround the peninsula. Our FST values are also
from a road side stall rather than being collected by us, clus-
close to those reported by Gosling et al. (2008) for zebra
tered together with the south eastern and eastern Kampung
mussel, Dreissena polymorpha (0.118), Holland (2001) for
Pasir Puteh, Kuala Pontian and Nenasi populations. This
brown mussel Perna perna (0.007–0.042) and by Johnson
was not in accordance with Parit Jawa’s geographical loca-
et al. (1998) for four species of mussels namely Amblema
tion on the south west coast of the peninsula and showed
plicata (0.082), Plectomerus dombeyanus (0.121), Quadrula
the power of our molecular markers in revealing samples of
pustulosa (0.108) and Q. quadrula (0.160).
doubtful origins. Hence, these commercially sold samples
The genetic distance values presented in table 4 showed
were probably not local samples as claimed by the vendor.
high genetic similarity among the 10 populations of P. viridis
Based on the dendrogram presented in ﬁgure 3, these sam-
with DN values ranging from 0.0070 to 0.0785. Cluster
ples most likely originated from an area east of the Johore
analysis grouped the 10 populations according to their ge-
causeway since it clustered with populations from that region
ographical distributions except for the Parit Jawa population.
rather than with those from west of the causeway where Parit
The dendrogram showed that P. viridis populations from the
Jawa is geographically located. The dendrogram (ﬁgure 3)
northern part of peninsular Malaysia (Tanjung Rhu and Pulau
also indicated that P. viridis from the eastern part of peninsu-
Aman) were the most distant populations while the central
lar Malaysia (Kuala Pontian and Nenasi) were closer to the
and southern populations, particularly those from the Straits
central and southern populations than to the northern popula-
of Malacca and the west side of the Johore Straits seemed
tions. During our sampling, hardly any P. viridis were found
to be closely related populations. This pattern of clustering
along the east coast of peninsular Malaysia except in Kuala
showed agreement with the results obtained using allozyme
Pontian and Nenasi. The Kuala Pontian mussels were ob-
data (Yap et al. 2002). It could be that the two major clus-
tained from a mussel aquaculture site while the Nenasi pop-
ters observed were due to limited genetic exchange result-
ulation was collected from a nearby lighthouse.
ing from the movements of currents in the straits or to local
In conclusion, the ﬁndings from this study conﬁrmed that
selection pressure. Close proximity between localities will
the local populations of P. viridis in peninsular Malaysia are
increase gene ﬂow, which tends to result in genetic unifor-
genetically similar enough to be used as a biomonitoring
mity among the populations. Geographically, the Straits of
agent for heavy metal contamination in the seas which sur-
Malacca are narrower in the southern part when compared
round peninsular Malaysia since they are of the same species
to the northern part and this will encourage greater genetic
and with only moderate diﬀerentiation among regional pop-
exchange between P. viridis populations in the southern re-
ulations.
Journal of Genetics, Vol. 88, No. 2, August 2009
159

C. C. Ong et al.
Appendix
Table 1. Primer sequences of 19 polymorphic microsatellite loci that were used to char-
acterize the 10 P. viridis populations in peninsular Malaysia and their speciﬁc annealing
temperature (Ta) of PCR ampliﬁcation.
Locus
Primer sequence 5 to 3
Ta
Expected
GenBank
size (bp)
accession no.
BP2-35-2
F: CTC TTT CAT CTT TCA CCT C
40
222
DQ010059
R: CGT CAG GTA CTC CAT ATC C
BP2-49-1
F: GGT ACT TTT CTC ACT TCA CA
44
229
AY850129
R: GGA GTG AAC CTC TTC GAC
BP2-49-2
F: GTT AAA CAA CCA ACC AAC G
44
215
AY850129
R: GTC TTT TTG TCA TTG CAC AC
BP9-7-1
F: GTA TAT CAG AGA GAG AGA G
40
299
DQ112051
R: AGG AAC TGA ACA CTG TTT G
BP9-13-2
F: CTC CCT ACT AAT GAG GAC AT
40
263
DQ112055
R: TTC TAT GTG AGA GAG AGA G
BP9-16-2
F: GGC AAC ATT AGA AGT TCT GT
40
213
DQ112058
R: TTG TAT ACC AGA GAG AGA G
BP9-19-2
F: CTC CCT ACT AAT GAG GAC AT
40
263
DQ112060
R: TTC TAT GTG AGA GAG AGA G
BP9-27-1
F: GTA TGT CAG AGA GAG AGA G
40
268
DQ112066
R: CAC CCA TAG AGT ATG TCA TT
BP10-5-1
F: GGT AGG TTC TCT CTC TCT CTC
48
233
DQ112034
R: TTT CAG TAT TCA GGG CAC TT
BP10-16-1
F: TGT GTG TTC TCT CTC TCT C
40
207
DQ112044
R: CTG TCT TTG CTA GTT CCT C
BP10-17-2
F: ATA CAC TGG GCT ATT CTC TT
40
199
DQ112045
R: TAT TCT CTC TCT CTC TCT C
BP14-7-1
F: TGA GGC GAT AGA TAG ATA G
45
169
AY254777
R: GAT CAA CTG TTA AGC GAT AG
LR1-58-1
F: ACT GAC TGA TGA GGA AAT GG
48
202
DQ010097
R: TGT AGC GGC TCT CTC TCT C
VJ1-9-1
F: TGC GTG TGG AGG CTC TCT
40
205
DQ010072
R: TCA CCT CTT GGT TGA GGA CA
VJ1-12-2
F: ATA GGA TAG AGT CAC GTT AG
41
201
AY850124
R: TAA GAC CTC TCT CTC TCT C
VJ1-15-1
F: GGT TGA GAG CCT CTC TCT CT
42
220
DQ010077
R: AGG AGA ATC CTG CTC TCT TC
VJ1-18-1
F: GTA GCG GCT CTC TCT CTC T
55
258
AY850126
R: GCG TGA CAC TCT TTT TCT TT
VJ1-21-2
F: CTA GTA GAA GCT CTC TCT CTC
40
224
DQ010081
R: GAA GTT TTG CTC ACT CAT CT
VJ1-22-2
F: AGA CGG AAT GCA GTA AGA AG
51
198
DQ010082
R: CAT AAG CAG AAT TCC CAG AG
160
Journal of Genetics, Vol. 88, No. 2, August 2009

Genetic variation of Perna viridis L. in peninsular malaysia
Table 2. Estimates of genetic variability in the 10 P. viridis populations.
Locus
Parameter Pulau
Tanjung
Bagan
Pulau
Muar
Parit
Pantai
Kampung Pasir Kuala Nenasi
Aman
Rhu
Tiang
Ketam
Jawa
Lido
Puteh
Pontian
BP2-35-2
NO (NE)
2 (1.98)
3 (1.65)
3 (1.31)
3 (1.56)
3 (1.23)
2 (1.22)
2 (1.63)
4 (2.19)
3 (1.59)
3 (1.74)
Ho
0.00
0.10
0.05
0.05
0.10
0.00
0.00
0.11
0.05
0.05
He
0.53
0.41
0.24
0.37
0.19
0.18
0.40
0.56
0.38
0.44
χ2
(−)
(−)
(−)
(−)
(−)
(−)
(−)
(−)
(−)
(−)
BP2-49-1
NO (NE)
2 (1.11)
3 (1.33)
2 (1.12)
2 (1.32)
3 (1.29)
2 (1.06)
3 (1.63)
4 (1.43)
3 (1.61)
3 (1.17)
Ho
0.20
0.15
0.15
0.17
0.06
0.15
0.20
0.26
0.05
0.18
He
0.19
0.14
0.14
0.16
0.06
0.14
0.18
0.23
0.05
0.17
χ2
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
BP2-49-2
NO (NE)
2 (1.11)
2 (1.47)
2 (1.17)
3 (1.46)
3 (1.35)
2 (1.60)
2 (1.31)
2 (1.16)
2 (1.34)
2 (1.64)
Ho
0.10
0.40
0.16
0.16
0.30
0.50
0.17
0.15
0.30
0.53
He
0.10
0.33
0.15
0.32
0.27
0.38
0.25
0.14
0.26
0.40
χ2
NS
NS
NS
(−)
NS
NS
NS
NS
NS
NS
BP9-7-1
NO (NE)
2 (1.22)
2 (1.11)
2 (1.11)
2 (1.22)
2 (1.05)
2 (1.05)
2 (1.12)
2 (1.05)
2 (1.11)
2 (1.11)
Ho
0.20
0.11
0.11
0.20
0.05
0.05
0.11
0.05
0.10
0.11
He
0.19
0.10
0.10
0.18
0.05
0.05
0.11
0.05
0.10
0.10
χ2
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
BP9-13-2
NO (NE)
2 (1.11)
1 (1.00)
1 (1.00)
1 (1.00)
1 (1.00)
2 (1.41)
1 (1.00)
1 (1.00)
1 (1.00)
2 (1.16)
Ho
0.10
0.00
0.00
0.00
0.00
0.35
0.00
0.00
0.00
0.15
He
0.10
0.00
0.00
0.00
0.00
0.30
0.00
0.00
0.00
0.14
χ2
NS
Homo
Homo
Homo
Homo
NS
Homo
Homo
Homo
NS
BP9-16-2
NO (NE)
2 (1.38)
2 (1.34)
2 (1.54)
2 (1.41)
2 (1.28)
2 (1.66)
2 (1.43)
2 (1.41)
2 (1.54)
2 (1.57)
Ho
0.33
0.30
0.45
0.35
0.25
0.55
0.37
0.35
0.45
0.47
He
0.29
0.26
0.36
0.30
0.22
0.41
0.31
0.30
0.36
0.37
χ2
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
BP9-19-2
NO (NE)
2 (1.11)
1 (1.00)
1 (1.00)
2 (1.11)
2 (1.11)
1 (1.00)
1 (1.00)
2 (1.05)
2 (1.12)
1 (1.00)
Ho
0.10
0.00
0.00
0.11
0.11
0.00
0.00
0.05
0.11
0.00
He
0.10
0.00
0.00
0.10
0.10
0.00
0.00
0.05
0.11
0.00
χ2
NS
Homo
Homo
NS
NS
Homo
Homo
NS
NS
Homo
BP9-27-1
NO (NE)
1 (1.00)
2 (1.47)
2 (1.47)
2 (1.28)
2 (1.17)
3 (1.23)
2 (1.05)
2 (1.28)
2 (1.33)
2 (1.11)
Ho
0.00
0.40
0.40
0.25
0.16
0.20
0.05
0.25
0.29
0.10
He
0.00
0.33
0.33
0.22
0.15
0.19
0.05
0.22
0.26
0.10
χ2
Homo
NS
NS
NS
NS
NS
NS
NS
NS
NS
BP10-5-1
NO (NE)
2 (1.22)
2 (1.16)
2 (1.16)
2 (1.18)
2 (1.06)
2 (1.16)
2 (1.22)
2 (1.30)
2 (1.05)
2 (1.19)
Ho
0.20
0.15
0.15
0.17
0.06
0.15
0.20
0.26
0.05
0.18
He
0.19
0.14
0.14
0.16
0.06
0.14
0.18
0.23
0.05
0.17
χ2
NS
NS
NS
NS
NS
NS
NS
NS
NS
NS
BP10-16-1 NO (NE)
1 (1.00)
2 (1.05)
2 (1.05)
2 (1.05)
1 (1.00)
2 (1.05)
1 (1.00)
2 (1.16)
1 (1.00)
2 (1.05)
Ho
0.00
0.05
0.05
0.05
0.00
0.05
0.00
0.15
0.00
0.50
He
0.00
0.05
0.05
0.05
0.00
0.05
0.00
0.14
0.00
0.50
χ2
Homo
NS
NS
NS
Homo
NS
Homo
NS
Homo
NS
BP10-17-2 NO (NE)
3 (1.78)
3 (1.60)
4 (2.09)
3 (1.83)
4 (2.67)
4 (2.96)
4 (2.67)
4 (2.61)
4 (2.25)
4 (1.95)
Ho
0.56
0.47
0.37
0.60
0.63
0.53
0.42
0.30
0.65
0.26
He
0.46
0.38
0.54
0.47
0.64
0.68
0.64
0.63
0.57
0.50
χ2
NS
NS
(−)
NS
(−)
(−)
(−)
(−)
(+)
(−)
BP14-7-1
NO (NE)
5 (3.13)
5 (2.97)
5 (3.64)
4 (3.56)
7 (4.88)
3 (1.75)
5 (3.50)
4 (1.61)
1 (1.00)
1 (1.00)
Ho
0.20
0.20
0.00
0.05
0.25
0.05
0.11
0.05
0.00
0.00
He
0.72
0.68
0.75
0.74
0.82
0.44
0.73
0.39
0.00
0.00
χ2
(−)
(−)
(−)
(−)
(−)
(−)
(−)
(−)
Homo
Homo
LR1-58-1
NO (NE)
2 (1.22)
4 (1.46)
3 (1.89)
3 (2.27)
3 (1.87)
3 (1.42)
4 (2.06)
3 (2.15)
3 (2.68)
2 (1.95)
Ho
0.20
0.11
0.16
0.40
0.30
0.05
0.16
0.10
0.35
0.00
Journal of Genetics, Vol. 88, No. 2, August 2009
161

C. C. Ong et al.
Table 2 (contd.)
He
0.19
0.32
0.48
0.57
0.48
0.30
0.53
0.55
0.64
0.50
χ2
NS
(−)
(−)
(−)
(−)
(−)
(−)
(−)
(−)
(−)
VJ1-9-1
NO (NE)
2 (1.67)
2 (1.50)
2 (1.25)
2 (1.70)
2 (1.78)
2 (1.25)
2 (1.17)
2 (1.96)
2 (1.22)
2 (1.63)
Ho
0.56
0.42
0.22
0.58
0.65
0.22
0.59
0.85
0.20
0.53
He
0.42
0.34
0.20
0.42
0.45
0.20
0.43
0.50
0.18
0.40
χ2
NS
NS
NS
NS
(+)
NS
NS
(+)
NS
NS
VJ1-12-2
NO (NE)
2 (1.34)
2 (1.17)
2 (1.18)
2 (1.34)
2 (1.05)
2 (1.16)
2 (1.25)
2 (1.11)
2 (1.22)
3 (1.24)
Ho
0.10
0.16
0.17
0.30
0.05
0.05
0.11
0.11
0.20
0.21
He
0.27
0.15
0.16
0.26
0.05
0.14
0.20
0.10
0.18
0.20
χ2
(−)
NS
NS
NS
NS
(−)
(−)
NS
NS
NS
VJ1-15-1
NO (NE)
1 (1.00)
2 (1.49)
2 (1.05)
2 (1.11)
1 (1.00)
2 (1.05)
1 (1.00)
1 (1.00)
1 (1.00)
1 (1.00)
Ho
0.00
0.41
0.05
0.00
0.00
0.05
0.00
0.00
0.00
0.00
He
0.00
0.34
0.05
0.10
0.00
0.05
0.00
0.00
0.00
0.00
χ2
Homo
NS
NS
(−)
Homo
NS
Homo
Homo
Homo
Homo
VJ1-18-1
NO (NE)
1 (1.00)
1 (1.00)
4 (3.38)
4 (3.80)
3 (2.79)
2 (1.96)
3 (1.83)
3 (2.10)
2 (1.96)
3 (2.04)
Ho
0.00
0.00
0.80
0.30
0.45
0.75
0.59
0.44
0.75
0.50
He
0.00
0.00
0.72
0.76
0.66
0.50
0.47
0.54
0.50
0.52
χ2
Homo
Homo
(+)
(−)
(−)
(+)
NS
(−)
(+)
NS
VJ1-21-2
NO (NE)
1 (1.00)
2 (1.05)
2 (1.11)
2 (1.05)
2 (1.11)
1 (1.00)
2 (1.30)
2 (1.05)
2 (1.11)
2 (1.23)
Ho
0.00
0.05
0.11
0.05
0.10
0.00
0.26
0.05
0.10
0.21
He
0.00
0.05
0.10
0.05
0.10
0.00
0.23
0.05
0.10
0.19
χ2
Homo
NS
NS
NS
NS
Homo
NS
NS
NS
NS
VJ1-22-2
NO (NE)
1 (1.00)
2 (1.06)
2 (1.05)
2 (1.05)
2 (1.16)
2 (1.18)
1 (1.00)
2 (1.12)
2 (1.05)
2 (1.06)
Ho
0.00
0.06
0.05
0.05
0.15
0.17
0.00
0.12
0.05
0.06
He
0.00
0.06
0.05
0.05
0.14
0.16
0.00
0.11
0.05
0.06
χ2
Homo
NS
NS
NS
NS
NS
Homo
NS
NS
NS
Mean
NO (NE)
1.9 (1.33) 2.3 (1.36) 2.4 (1.50) 2.4 (1.59) 2.5 (1.57) 2.2 (1.38) 2.2 (1.51) 2.4 (1.46) 2.1 (1.38)
2.2 (1.36)
Ho
0.14
0.19
0.17
0.21
0.20
0.20
0.18
0.20
0.20
0.19
He
0.19
0.22
0.24
0.28
0.24
0.22
0.26
0.26
0.22
0.23
NO, observed number of alleles; NE, eﬀective number of alleles (Kimura and Crow 1964); Ho, observed heterozygosity; He, expected
heterozygosity; χ2, chi-square tests for deviation from Hardy–Weinberg equilibrium (signiﬁcant at P < 0.05); Homo, homozygous; NS,
not signiﬁcant; (+), signiﬁcant excess of observed heterozygosity; (−), signiﬁcant deﬁciency of observed heterozygosity.
Acknowledgements
of genetics (ed. M. K. Thong), pp. 47–48. The Genetic Society
of Malaysia, Bangi.
This work was funded by IRPA grant 09-02-04-EA001 and
Gosling E., Astanei I. and Was A. 2008 Genetic variability in Irish
eScience fund grant 05-01-04-SF0147 from the Ministry of Sci-
populations of the invasive zebra mussel, Dreissena polymor-
ence, Technology and Innovation Malaysia.
pha: discordant estimates of population diﬀerentiation from al-
lozymes and microsatellites. Freshwater Biol. 53, 1303–1315.
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Received 2 September 2008, in ﬁnal revised form 4 December 2008; accepted 28 January 2009
Published on the Web: 18 June 2009
Journal of Genetics, Vol. 88, No. 2, August 2009
163