The mud crab (Scylla paramamosain) is a carnivorous portunid crab, mainly distributed along the southeastern coast of China. Mitochondrial DNA analysis in a previous study indicated a high level of genetic diversity and a low level of genetic differentiation. In this study, population genetic diversity and differentiation of S. paramamosain were investigated using nine microsatellite markers. In total, 397 wild specimens from 11 locations on the southeastern coast of China were sampled and genotyped. A high level of genetic diversity was observed, with the number of alleles, and the observed and expected heterozygosity per location in the range 7.8–9.6, 0.62–0.77 and 0.66–0.76, respectively. AMOVA analysis indicated a low level of genetic differentiation among the 11 locations, despite the fact that a statistically significant fixation index (FST) value was found (FST=0.0183, P<0.05). Out of 55 pairwise location comparisons, 39 showed significant FST values (P<0.05), but all of them were lower than 0.05, except for one between Sanmen and Shantou locations. No significant deficiency of heterozygotes (inbreeding coefficient FIS=0.0007, P>0.05) was detected for all locations except Sanmen and Zhanjiang. Cluster analysis using UPGMA showed that all locations fell into one group except Sanmen. Significant association was found between genetic differentiation in terms of FST/(1–FST) and the natural logarithm of geographical distance (r2=0.1139, P=0.02), indicating that the genetic variation pattern closely resembled an isolation by distance model. This study supports the proposal of high genetic diversity and low genetic differentiation in S. paramamosain along the southeastern coast of China.

The mud crab (Scylla paramamosain Estampador 1949), mainly distributed along the southeastern coast of China, is a commercially important crab resource for fisheries and aquaculture. Records of S. paramamosain aquaculture date back more than 100 years in China (Shen and Lai, 1994) and more than 30 years in other Asian countries (Keenan and Blackshaw, 1999). In wild environments, adults mate inshore and the gravid females generally migrate offshore to spawn (Perrine, 1979). Because of over-exploitation and environmental deterioration, numbers in the wild have decreased quickly. In order to conserve and sustainably harvest this important crab resource, genetic studies are necessary as they enable a better understanding of genetic diversity and structure (Dickerson et al., 2010), allow investigation of phylogenetic and evolutionary history (Gvozdík et al., 2010; Van Syoc et al., 2010), and also provide constructive guidance for resource conservation and management (Ortega-Villaizan Romo et al., 2006). A mitochondrial DNA (mtDNA) study of S. paramamosain indicated a genetically homogeneous population structure and a recent population expansion event (He et al., 2010). Moreover, again using mtDNA, a high level of genetic diversity and low genetic differentiation at different locations were observed in S. paramamosain inhabiting the southeastern coast of China (Lu et al., 2009; Ma et al., 2011a).

Microsatellites are nuclear molecular markers characterized by a 1–6 bp length repeat motif, high polymorphism and co-dominant inheritance. Microsatellite markers have been widely used for investigation of genetic diversity (Dudaniec et al., 2010), determination of pedigree (Li et al., 2009a), construction of genetic maps (Ma et al., 2011b) and mapping of quantitative trait loci (Zhang et al., 2011). To date, microsatellite markers have been isolated in S. paramamosain (Takano et al., 2005; Ma et al., 2010; Ma et al., 2011c; Cui et al., 2011), but no information about population genetic diversity and differentiation has been reported for this important crab species.

In this study, a total of 397 wild specimens from 11 locations on the southeastern coast of China were sampled and genotyped using nine microsatellite markers. The purpose was to investigate the level of population genetic diversity and differentiation in S. paramamosain across these regions to provide valuable information for conservation, harvesting and management of this key fishery resource.

Sample collection and DNA extraction

A total of 397 wild specimens of S. paramamosain were collected from the following locations along the southeastern coast of China: Sanmen (SM, N=38), Ningde (ND, N=35), Zhangzhou (ZZ, N=32), Shantou (ST, N=25), Shenzhen (SZ, N=40), Zhanjiang (ZJ, N=41), Haikou (HK, N=37), Wenchang (WC, N=51), Wanning (WN, N=35), Dongfang (DF, N=30) and Danzhou (DZ, N=33) (Fig. 1; Table 1). Each specimen was killed by a lethal dose of MS-222. Genomic DNA was extracted from muscle tissue using traditional proteinase K and phenol–chloroform extraction protocols as described previously (Ma et al., 2009). The DNA was adjusted to 100 ng μl–1 and stored at –20°C until use.

Fig. 1.

Geographic map of southeastern coast of China. Filled circles, sampling location; 1, Sanmen (SM); 2, Ningde (ND); 3, Zhangzhou (ZZ); 4, Shantou (ST); 5, Shenzhen (SZ); 6, Zhanjiang (ZJ); 7, Haikou (HK); 8, Wenchang (WC); 9, Wanning (WN); 10, Dongfang (DF); and 11, Danzhou (DZ).

Fig. 1.

Geographic map of southeastern coast of China. Filled circles, sampling location; 1, Sanmen (SM); 2, Ningde (ND); 3, Zhangzhou (ZZ); 4, Shantou (ST); 5, Shenzhen (SZ); 6, Zhanjiang (ZJ); 7, Haikou (HK); 8, Wenchang (WC); 9, Wanning (WN); 10, Dongfang (DF); and 11, Danzhou (DZ).

Microsatellite genotyping

Nine polymorphic microsatellite loci were selected for genotyping, of which eight were developed using the 5′ anchored PCR method (Cui et al., 2011), and the remaining one was developed using PCR-based isolation of microsatellite arrays (PIMA) (Ma et al., 2010) in our laboratory (Table 2). The criteria for selection were as follows: annealing temperature of 50–63°C, expected product size between 110 and 320 bp, observed heterozygosity value >0.5 and no stuttering bands. PCR reactions were conducted in a total volume of 25 μl and included 0.4 μmol l–1 each primer, 0.2 mmol l–1 each dNTP, 1× PCR reaction buffer, 1.5 mmol l–1 MgCl2, 0.75 U Taq polymerase and approximately 100 ng template DNA, under the following conditions: one cycle of denaturation at 94°C for 4 min; 30 cycles of 30 s at 94°C, 50 s at a primer-specific annealing temperature (Table 2), and 50 s at 72°C. As a final step, products were extended for 7 min at 72°C.

Table 1.

Characteristics of 11 locations of Scylla paramamosain

Characteristics of 11 locations of Scylla paramamosain
Characteristics of 11 locations of Scylla paramamosain

Several methods, including agarose gel electrophoresis, denaturing polyacrylamide gel electrophoresis and automated DNA sequencing, were employed for detecting differences in nucleotide sequence, of which the second is a very effective and practical technique for genotyping of microsatellites and has been used in a wide range of organisms, as it has many advantages: a high resolution (about 1 bp) and large output (100 samples each), low expense and easily mastered. In this study, the PCR products were separated on 6% denaturing polyacrylamide gels as described previously (Ma, 2009). The microsatellite fragments were visualized by silver staining, which was performed as follows. The gel was soaked in 1.0 l staining solution (1.5 g AgNO3) for about 10 min; this solution was then removed and the gel was washed in ddH2O for 5 s. Then the gel was soaked in 1.0 l coloured solution (20 g NaOH and 4 ml formaldehyde) for about 10 min. Finally, the gel was cleaned with ddH2O. The size of alleles was estimated according to the pBR322/Msp I marker.

Data analysis

Observed and expected heterozygosity, departure from Hardy–Weinberg equilibrium (HWE), linkage disequilibrium (LD) and inbreeding coefficient (FIS) were obtained using ARLEQUIN version 3.01 software (Excoffier et al., 2005). Genetic differentiation among locations was estimated using the analysis of molecular variance (AMOVA) approach by GENAlEX version 6.41 software (Peakall and Smouse, 2006). The significance levels were tested by 10,000 permutations for LD and by 1000 permutations for fixation index (FST) values. Observed number of alleles (Na), effective number of alleles (Ne) and genetic distance were estimated using POPGENE version 1.31 software (Yeh et al., 1999). An unweighted pair-group mean analysis (UPGMA) tree was constructed based on Nei's genetic distance (Nei, 1978) of pairwise locations using MEGA version 4.0 software (Tamura et al., 2007). The association between genetic differentiation and geographic distance (isolation by distance) among locations was estimated by the Mantel test (Mantel, 1967) with 1000 permutations.

All nine microsatellite loci used in this study were polymorphic in each location, showing a high level of genetic diversity (Table 3). In total, 104 alleles were detected from 397 individuals in 11 locations across nine loci. Na ranged from six (Scypa1) to 16 (Scypa8 and Scpa03) per locus and from 7.8 (ST) to 9.6 (WC) per location. HO and HE ranged from 0.32 to 1.00 and from 0.31 to 0.93 per locus–location combination, and from 0.62 (SM) to 0.77 (HK) and from 0.66 (ST) to 0.76 (ND and DZ) per location, respectively. FIS ranged from –0.278 to 0.440 per locus–location combination and from –0.137 (ST) to 0.136 (SM) per location, with an average of 0.001 as a whole.

An exact probability test of HWE was performed among 99 locus–location combinations, and it revealed a significant deviation at 19 loci (P<0.05). These 19 loci were Scypa1 (in ZZ and HK), Scypa2 (in SM and ZJ), Scypa3 (in ND and ST), Scypa4 (in DF), Scypa8 (in ND, ZZ, HK and WN), Scypa13 (in SM, ST, ZJ and WN) and Scpa03 (in SM, SZ, ZJ and WC). Two loci (Scypa5 and Scypa11) were in keeping with HWE in all locations. Probability tests of genotypic LD for all pairs of loci within each location suggested significant non-random associations in only one of 396 possible pairwise comparisons after sequential Bonferroni correction (Scypa2 and Scypa13 in DF, P<0.00139) (Rice, 1989). When each location was analysed separately, there was no evidence of stuttering and large allelic dropout in any of the loci, as confirmed by MICRO-CHECKER version 2.2.3 software (Van Oosterhout et al., 2004).

Table 2.

Characterization of the nine microsatellite markers used in this study

Characterization of the nine microsatellite markers used in this study
Characterization of the nine microsatellite markers used in this study
Table 3.

Summary statistics of nine microsatellite markers in 11 locations of S. paramamosain

Summary statistics of nine microsatellite markers in 11 locations of S. paramamosain
Summary statistics of nine microsatellite markers in 11 locations of S. paramamosain
Fig. 2.

The unweighted pair-group mean analysis (UPGMA) tree of 11 locations of Scylla paramamosain. SM, Sanmen; ND, Ningde; ZZ, Zhangzhou; ST, Shantou; SZ, Shenzhen; ZJ, Zhanjiang; HK, Haikou; WC, Wenchang; WN, Wanning; DF, Dongfang; and DZ, Danzhou.

Fig. 2.

The unweighted pair-group mean analysis (UPGMA) tree of 11 locations of Scylla paramamosain. SM, Sanmen; ND, Ningde; ZZ, Zhangzhou; ST, Shantou; SZ, Shenzhen; ZJ, Zhanjiang; HK, Haikou; WC, Wenchang; WN, Wanning; DF, Dongfang; and DZ, Danzhou.

The AMOVA showed that genetic variation existed mainly within locations, rather than among locations, as the percentage of variance was 98.17% within locations and 1.83% among locations. Although the overall FST value for all locations and loci was statistically significant (FST=0.0183, P<0.05), the genetic differentiation was still low, because the FST value was much lower than 0.05 (Tables 4, 5). Multi-locus estimates of FST for all possible pairwise locations ranged from 0.002 (ZJ and DZ) to 0.067 (SM and ST). The highest differentiation was between SM and ST (FST=0.067), and the lowest differentiation was between ZJ and DZ (Table 5). Thirty-nine out of 55 pairwise locations showed significant differentiation (P<0.05). Nei's genetic distances between pairwise locations ranged from 0.0121 (ZZ and SZ) to 0.2036 (SM and ST), and were lower than 0.1 in 43 out of the 55 pairwise locations. Of the 11 locations, SM was the most distinctive, as it showed significant differentiation in relation to all the other 10 locations (FST values ranged from 0.024 to 0.067). In contrast, DZ was the most representative as it significantly differed from only four locations (FST values ranged from 0.012 to 0.029).

Cluster analysis of 11 locations using the UPGMA approach revealed two groups: one contained 10 locations and the other contained only one location (SM) (Fig. 2). Mantel tests for isolation by distance among locations detected a significant positive correlation between pairwise FST/(1–FST) and the natural logarithm of geographic distance (km) (r2=0.1139, P=0.02), while there was no significant correlation between pairwise FST and geographic distance (km) (r2=0.1230, P=0.06) (Fig. 3)

Table 4.

AMOVA design and results for 11 locations of S. paramamosain

AMOVA design and results for 11 locations of S. paramamosain
AMOVA design and results for 11 locations of S. paramamosain

The results of this study suggest a high level of population genetic diversity of S. paramamosain along the southeastern coast of China (Na, HO and HE in the range 7.8–9.6, 0.62–0.77 and 0.66–0.76 per location, respectively), in accordance with previous studies that showed a high level of mtDNA genetic diversity in S. paramamosain (Lu et al., 2009; Ma et al., 2011a). High population genetic diversity has also been observed in other marine animals, such as scallop (Chlamys farreri) (Zhao et al., 2009), Atlantic salmon (Salmo salar) (Karlsson et al., 2010) and silver pomfret (Pampus argenteus) (Zhao et al., 2011). Three factors including the life history characteristics, environmental heterogeneity and large population size may help to maintain a high level of genetic diversity (Perrine, 1979; Nei, 1987; Avise, 1998). On the whole, the level of genetic diversity of S. paramamosain from the southern regions was higher than that from the northern regions (Table 3), which may be due to the different environments. A similar finding was observed in a previous study, which indicated a trend for a reduction in genetic diversity of S. paramamosain from south to north, step by step using mtDNA (Lu et al., 2009).

Fig. 3.

Relationship between genetic differentiation and geographic distance among the 11 locations. (A) Relationship between pairwise FST/(1–FST) (where FST is the fixation index) and the natural logarithm of geographic distance. (B) Relationship between pairwise FST and geographic distance.

Fig. 3.

Relationship between genetic differentiation and geographic distance among the 11 locations. (A) Relationship between pairwise FST/(1–FST) (where FST is the fixation index) and the natural logarithm of geographic distance. (B) Relationship between pairwise FST and geographic distance.

Generally, marine fishes are considered to have a low level of genetic differentiation among different geographic populations because of the high dispersal capabilities, large population sizes and relatively small barriers in the marine environment (Beheregaray and Sunnucks, 2001). For the fish Nibea albiflora, there was little difference in the population genetic structure between the Yellow Sea and East China Sea observed using mtDNA (Han et al., 2008). For the shrimp Fenneropenaeus chinensis, no significant population genetic differentiation between the Yellow Sea and Bohai Sea was found using both microsatellite DNA and mtDNA (Liu et al., 2006; Li et al., 2009b). For the crab S. paramamosain, a genetically homogeneous population structure with high gene flow was observed among most localities along the coasts of the East China Sea and South China Sea using mtDNA (He et al., 2010). In the current study, statistically significant genetic differentiation was detected across 11 locations along the southeastern coast of China (FST=0.0183, P<0.05), but the FST value was still low (<0.05), suggesting a low level of genetic differentiation (Wright, 1978). A similar finding was reported in earlier studies, which suggested a low differentiation in S. paramamosain using mtDNA (Lu et al., 2009; He et al., 2010; Ma et al., 2011a). The above information indicates that all locations of S. paramamosain should be a single genetically homogeneous population. The low FST value indicates a relatively high gene flow among locations. There are three probable explanations for this: (1) the unique reproductive habit in which adults and juveniles migrate between ocean basins and adjacent continental margins; (2) the high dispersal capabilities of larvae; and (3) the relatively small physical barriers in the marine environment.

Table 5.

Pairwise FST (below diagonal) and genetic distance (above diagonal) among the 11 locations of S. paramamosain

Pairwise FST (below diagonal) and genetic distance (above diagonal) among the 11 locations of S. paramamosain
Pairwise FST (below diagonal) and genetic distance (above diagonal) among the 11 locations of S. paramamosain

Among these 11 locations, SM was the most genetically distinctive in two main ways: (1) it has the lowest genetic diversity (the overall HO was 0.62) and the highest FST values (between 0.024 and 0.067) compared with other locations; and (2) it has the greatest overall FIS value (FIS=0.136, P<0.05) compared with other locations. These findings indicate that the gene exchange is relatively low between SM and other locations compared with that between other location pairs. The optimum temperature range of this crab is 18–27°C for growth, and a higher temperature is needed for spawning. However, SM is the most northern of these locations, so the seawater temperature is the lowest in the same period. Low temperature may limit the effective population size and the high dispersal capabilities of S. paramamosain. Over-fishing by humans may be another potential explanation. A significant positive correlation between genetic differentiation and geographic distance was found, suggesting an isolation by distance model of genetic variation.

In conclusion, a high level of population genetic diversity and low differentiation were found in the mud crab (S. paramamosain) from 11 locations along the southeastern coastal regions of China by microsatellite analysis, which showed a genetically homogeneous population structure for S. paramamosain in these 11 locations. In the future, more population genetic studies should be carried out in this crab species. The findings in this study will provide valuable information for conservation, harvesting and artificial selective breeding of this important fishery resource.

     
  • AMOVA

    analysis of molecular variance

  •  
  • FIS

    inbreeding coefficient

  •  
  • FST

    fixation index

  •  
  • HE

    expected heterozygosity

  •  
  • HO

    observed heterozygosity

  •  
  • HWE

    Hardy–Weinberg equilibrium

  •  
  • LD

    linkage disequilibrium

  •  
  • Na

    observed number of alleles

  •  
  • Ne

    expected number of alleles

FUNDING

This research was supported by the National Non-Profit Institutes (East China Sea Fisheries Research Institute) [grant no. 2011M05], the National Natural Science Foundation of China [grant no. 31001106], and the Science and Technology Commission of Shanghai Municipality [grant no. 10JC1418600].

We thank Dr Keji Jiang for assistance in partial sample collection.

Avise
J.
(
1998
).
Phylogeography
.
Cambridge, MA
:
Harvard University Press
.
Beheregaray
L. B.
,
Sunnucks
P.
(
2001
).
Fine-scale genetic structure, estuarine colonization and incipient speciation in the marine silverside fish Odontesthes argentinensis
.
Mol. Ecol.
10
,
2849
-
2866
.
Cui
H. Y.
,
Ma
H. Y.
,
Ma
L. B.
,
Ma
C. Y.
,
Ma
Q. Q.
(
2011
).
Development of eighteen polymorphic microsatellite markers in Scylla paramamosain by 5′ anchored PCR technique
.
Mol. Biol. Rep.
38
,
4999
-
5002
.
Dickerson
B. R.
,
Ream
R. R.
,
Vignieri
S. N.
,
Bentzen
P.
(
2010
).
Population structure as revealed by mtDNA and microsatellites in northern fur seals, Callorhinus ursinus, throughout their range
.
PLoS ONE
5
,
e10671
.
Dudaniec
R. Y.
,
Storfer
A.
,
Spear
S. F.
,
Richardson
J. S.
(
2010
).
New microsatellite markers for examining genetic variation in peripheral and core populations of the coastal giant salamander (Dicamptodon tenebrosus)
.
PLoS ONE
5
,
e14333
.
Excoffier
L.
,
Laval
G.
,
Schneider
S.
(
2005
).
ARLEQUIN (version 3.0): an integrated software package for population genetics data analysis
.
Evol. Bioinform. Online
1
,
47
-
50
.
Gvozdík
V.
,
Moravec
J.
,
Klütsch
C.
,
Kotlík
P.
(
2010
).
Phylogeography of the Middle Eastern tree frogs (Hyla, Hylidae, Amphibia) as inferred from nuclear and mitochondrial DNA variation, with a description of a new species
.
Mol. Phylogenet. Evol.
55
,
1146
-
1166
.
Han
Z. Q.
,
Gao
T. X.
,
Yanagimoto
T.
,
Sakurai
Y.
(
2008
).
Genetic population structure of Nibea albiflora in the Yellow Sea and East China Sea
.
Fish. Sci.
74
,
544
-
552
.
He
L.
,
Zhang
A.
,
Weese
D.
,
Zhu
C.
,
Jiang
C.
,
Qiao
Z.
(
2010
).
Late Pleistocene population expansion of Scylla paramamosain along the coast of China: a population dynamic response to the last interglacial sea level highstand
.
J. Exp. Mar. Biol. Ecol.
385
,
20
-
28
.
Karlsson
S.
,
Moen
T.
,
Hindar
K.
(
2010
).
Contrasting patterns of gene diversity between microsatellites and mitochondrial SNPs in farm and wild Atlantic salmon
.
Conserv. Genet.
11
,
571
-
582
.
Keenan
C.
,
Blackshaw
P. A.
(
1999
).
Mud Crab Aquaculture and Biology
.
ACAIR Proceedings No. 78
.
Australia
:
Watson Ferguson & Co.
Li
M. H.
,
Välimäki
K.
,
Piha
M.
,
Pakkala
T.
,
Merilä
J.
(
2009a
).
Extrapair paternity and maternity in the three-toed woodpecker, Picoides tridactylus: insights from microsatellite-based parentage analysis
.
PLoS ONE
4
,
e7895
.
Li
Y. L.
,
Kong
X. Y.
,
Yu
Z. N.
,
Kong
J.
,
Ma
S.
,
Chen
L. M.
(
2009b
).
Genetic diversity and historical demography of Chinese shrimp Fenneropenaeus chinensis in Yellow Sea and Bohai Sea based on mitochondrial DNA analysis
.
Afr. J. Biotechnol.
8
,
1193
-
1202
.
Liu
P.
,
Meng
X. H.
,
Kong
J.
,
He
Y. Y.
,
Wang
Q. Y.
(
2006
).
Polymorphic analysis of microsatellite DNA in wild populations of Chinese shrimp (Fenneropenaeus chinensis)
.
Aqua. Res.
37
,
556
-
562
.
Lu
X. P.
,
Ma
L. B.
,
Qiao
Z. G.
,
Zhang
F. Y.
,
Ma
C. Y.
(
2009
).
Population genetic structure of Scylla paramamosain from the coast of the Southeastern China based on mtDNA COI sequences
.
J. Fish. China.
33
,
15
-
23
. (
In Chinese with English abstract.
)
Ma
H. Y.
(
2009
).
Development of sex-specific markers and ssr markers and construction of genetic linkage maps of three important cultured marine fish species
.
PhD thesis
,
Ocean University of China
,
Qingdao, China
.
Ma
H. Y.
,
Yang
J. F.
,
Su
P. Z.
,
Chen
S. L.
(
2009
).
Genetic analysis of gynogenetic and common populations of Verasper moseri using SSR markers
.
Wuhan Univ. J. Nat. Sci.
14
,
267
-
273
.
Ma
H. Y.
,
Ma
C. Y.
,
Ma
L. B.
,
Cui
H. Y.
(
2010
).
Novel polymorphic microsatellite makers in Scylla paramamosain and cross-species amplification in related crab species
.
J. Crustac. Biol.
30
,
441
-
444
.
Ma
H. Y.
,
Ma
C. Y.
,
Ma
L. B.
(
2011a
).
Population genetic diversity of mud crab (Scylla paramamosain) in Hainan Island of China based on mitochondrial DNA
.
Biochem. Syst. Ecol.
39
,
434
-
440
.
Ma
H. Y.
,
Chen
S. L.
,
Yang
J. F.
,
Chen
S. Q.
,
Liu
H. W.
(
2011b
).
Genetic linkage maps of barfin flounder (Verasper moseri) and spotted halibut (Verasper variegatus) based on AFLP and microsatellite markers
.
Mol. Biol. Rep.
38
,
4749
-
4764
.
Ma
H. Y.
,
Ma
C. Y.
,
Ma
L. B.
(
2011c
).
Identification of type I microsatellite markers associated with genes and ESTs in Scylla paramamosain
.
Biochem. Syst. Ecol.
39
,
371
-
376
.
Mantel
N.
(
1967
).
The detection of disease clustering and a generalized regression approach
.
Cancer Res.
27
,
209
-
220
.
Nei
M.
(
1978
).
Estimation of average heterozygosity and genetic distance from a small number of individuals
.
Genetics
89
,
583
-
590
.
Nei
M.
(
1987
).
Molecular Evolutionary Genetics
.
New York, NY
:
Columbia University Press
.
Ortega-Villaizan Romo
M.
,
Suzuki
S.
,
Nakajima
M.
,
Taniguchi
N.
(
2006
).
Genetic evaluation of interindividual relatedness for broodstock management of the rare species barfin flounder Verasper moseri using microsatellite DNA markers
.
Fish. Sci.
72
,
33
-
39
.
Peakall
R.
,
Smouse
P. E.
(
2006
).
GENALEX 6: genetic analysis in excel. Population genetic software for teaching and research
.
Mol. Ecol. Notes
6
,
288
-
295
.
Perrine
D.
(
1979
).
The Mangrove Crab on Ponape.
88
pp.
Ponape Eastern Caroline Islands
:
Marine Resources Division
.
Rice
W. R.
(
1989
).
Analyzing tables of statistical tests
.
Evolution
43
,
223
-
225
.
Shen
Y.
,
Lai
Q.
(
1994
).
Present status of mangrove crab (Scylla serrata (Forskål)) culture in China
.
NAGA: the ICLARM Quarterly
,
January 1994, 28-29
.
Takano
M.
,
Barinova
A.
,
Sugaya
T.
,
Obata
Y.
,
Watanabe
T.
,
Ikeda
M.
,
Taniguchi
N.
(
2005
).
Isolation and characterization of microsatellite DNA markers from mangrove crab, Scylla paramamosain
.
Mol. Ecol. Notes
5
,
794
-
795
.
Tamura
K.
,
Dudley
J.
,
Nei
M.
,
Kumar
S.
(
2007
).
MEGA4: molecular evolutionary genetics anlysis (MEGA) software version 4.0
.
Mol. Biol. Evol.
24
,
1596
-
1599
.
Van Oosterhout
C.
,
Hutchinson
W. F.
,
Wills
D. P. M.
,
Shipley
P.
(
2004
).
MICRO-CHECKER: software for identifying and correcting genotyping errors in mirosatellite data
.
Mol. Ecol. Notes
4
,
535
-
538
.
Van Syoc
R. J.
,
Fernandes
J. N.
,
Carrison
D. A.
,
Grosberg
R. K.
(
2010
).
Molecular phylogenetics and biogeography of Pollicipes (Crustacea: Cirripedia), a Tethyan relict
.
J. Exp. Mar. Biol. Ecol.
392
,
193
-
199
.
Wright
S.
(
1978
).
Evolution and the Genetics of Populations, Vol. 4, Variability Within and Among Natural Populations
.
Chicago
:
The University of Chicago Press
.
Yeh
F. C.
,
Yang
R. C.
,
Boyle
T.
(
1999
).
POPGENE version 1.31. Microsoft window-based freeware for population genetic analysis
.
University of Alberta and the Centre for International Forestry Research
. .
Zhang
Y.
,
Xu
P.
,
Lu
C.
,
Kuang
Y.
,
Zhang
X.
,
Cao
D.
,
Li
C.
,
Chang
Y.
,
Hou
N.
,
Li
H.
, et al. 
. (
2011
).
Genetic linkage mapping and analysis of muscle fiber-related QTLs in common carp (Cyprinus carpio L.)
.
Mar. Biotechnol. (NY)
13
,
376
-
392
.
Zhao
C.
,
Li
Q.
,
Kong
L.
(
2009
).
Inheritance of AFLP markers and their use for genetic diversity analysis in wild and farmed scallop (Chlamys farreri)
.
Aquaculture
287
,
67
-
74
.
Zhao
F.
,
Dong
Y.
,
Zhuang
P.
,
Zhang
T.
,
Zhang
L.
,
Shi
Z.
(
2011
).
Genetic diversity of silver pomfret (Pampus argenteus) in the Southern Yellow and East China Seas
.
Biochem. Syst. Ecol.
39
,
145
-
150
.