Thalassas: An International Journal of Marine Sciences https://doi.org/10.1007/s41208-018-0066-1
Studies on Isozyme Variations and Morphometric Relationship among three Populations of Austruca sindensis (Alcock 1900) from Pakistan Sahir Odhano 1 & Noor Us Saher 1 & Mustafa Kamal 2 Received: 25 July 2017 # Springer International Publishing AG, part of Springer Nature 2018
Abstract The isozyme variability and morphometric analysis were examined in three populations of the fiddler crab, Austruca sindensis. The crab samples were collected from the three populations of A. sindensis (Sandspit, Sonari, and Sonmiani) along the coast of Pakistan. Three different enzymes, Catalase (CAT), Carbonate dehydratase (CD), Amylase (Amy) and a general protein pattern were investigated. Two isozymes were identified to be useful for the populations differentiation of A. sindensis along the coast of Pakistan. POPGENE software was used for the analysis of banding pattern, polymorphic loci, allelic frequency, heterozygosity and genetic distance of three populations of A. sindensis; while, Minitab and MS-Excel was used for the analysis of morphometric analysis. Four polymorphic loci, CAT-I, CAT-II, CD-I and CD-II were interpretable in muscle with Polyacrylamide Gel Electrophoresis (PAGE), the allele frequency differs significantly, detected in population of the Sonmiani Bay as compared with Sonari and Sandspit. The morphometric analysis showed low level of variability among the three studied populations when total 8 selected morphometric traits were analyzed (wet weight (WW), carapace length (CL), carapace width (CW), abdominal length (AL), abdominal width (AW), enlarged chela length (EL), enlarged chela width (EW), pleopode length (PL)). Multiple statistical approaches applied; regression analysis, ANOVA and Discriminant function analysis (DFA). Among all the statistical analysis used total three traits, showed significant variations among three populations (CW, EL and AL). The result of this study indicated that not only the morphological difference reflects the environmental conditions of habitat, but also the biochemical variations can be considered as the indicator of specific population dispersal. Keywords Electrophoresis . Isozyme . PAGE . Population structure . Austruca sindensis
Introduction Protein electrophoresis considered as a powerful and useful tool to obtain the level of genetic differentiation in different species. Sibley (1965) stated biochemical character can be more conservative than other types of characters. It was also thought that these characters would clearly reflect the evolutionary history of different groups. Electrophoretic data can be
* Noor Us Saher
[email protected] 1
Centre of Excellence in Marine Biology, University of Karachi, Karachi 75270, Pakistan
2
Department of Biotechnology, University of Karachi, Karachi 75270, Pakistan
a source of different sets of characters which can be utilized to differentiate the phylogenetic relationship among the different organisms groups (Matson 1984). Generally it is presumed that products of the gene can be examined through electrophoresis such as electro-morphs that are controlled by codominant alleles at a particular gene locus, and an assumption has been confirmed by various authors. Maeda et al. (1972) found alkaline phosphatase expressed by the co-dominant alleles in tissues; which also verified by (Grunder and Hollands 1977) adenosine de-aminase (Lucotte et al. 1978) albumin (Montag and Dahlgren 1973)and transferrin (Przytulski and Csuka 1979). There are many researchers who were attempting to determine genetic variation in populations and to distinguish between populations and/or sub species in 1970s (e.g., Brown et al. 1970; Shaughnessy 1970; Redfield 1973; Corbin et al. 1974; Morgan et al. 1977; Stephens et al. 1956; Guttman et al.
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1980; Parker et al. 1981; Tegelstrom and Ryttman 1981; Barrett and Vyse 1982; Matson 1984). These researchers compute the values of loci variations by expressing them in the form of percentage of polymorphic loci (P), average heterozygosity (Hav), Genetic Distance and Wright’s F-statistic (F) (Manwell and Baker 1975; Fleischer 1983; Zink and Winkler 1983). Various distance and similarity coefficients were also calculated following Nei (1972) and Rogers (1972). Therefore electrophoresis techniques have been used to identify interspecific level to study systematic relationships (Angeles 1984). Indus Fiddler crab A. sindensis (Fig. 6) is the most abundantly found species which occurs along the coast of Pakistan (Alcock 1900). Along with the A. sindensis total four species have been reported along the coast of Pakistan (A. iranica, A. annulipes and T. urvillei) (Saher 2008). They are typically small, highly social and noticeable population that play some important environmental roles in coastal ecosystems by their burrowing and feeding activities (Saher 2008). These species play an important role as ecosystem engineer for the nutrient recycling and energy flow in coastal ecosystem and trophic level within the intertidal area by converting organic matter into small sized round packs for other species specially predators (Teal 1958; Saher and Qureshi 2012). Koch and Madden (2001) suggested that such direct conversion of debris material into a biomass may be a major cause of energy that transfers to other populations such as predators. Fiddler crabs are also known as detritivore organisms and surface deposit feeders as they are important consumers of detritus, bacteria, fungi and benthic micro-algae in coastal regions such as mangrove, sand flat and mud flat habitats (Backwell et al. 2006; Mokhlesi et al. 2010). Therefore, their distribution and abundance is largely dependent on the type of sediment where they live because sediment is a provider of space and food for fiddler crabs (Saher and Qureshi 2012). The organic matter is the major source of sediment from which they sort out endofauna of the substrate (Murai et al. 1982) and remaining unwanted material formed into interconnected masses termed as mud balls or food pallets dropped at the surface sediment near the burrow openings (Saher and Qureshi 2014). The relative growth of family Ocypodidae was first studied by (Huxley 1924a, 1924b, 1927); Cori (1929) then subsequently (Barnes 1968; Haley 1972; Frith and Brunenmeister 1983; Von Hagen 1987; Rosenberg Jörg 2001; NegreirosFransozo et al. 2003; Qureshi and Saher 2012; Saher and Qureshi 2011; Saher 2008; Saher and Qureshi 2010) research conducted by various authors on the basis of their speciesspecific or sex ratios of selected appendages and body parts dimensions. (Barnes 1968; Siddiqui and Qasim 1988; Miller 1973), Whereas few studies were conducted on intra-species variations such as Teissier (1960) worked on relative growth of crustacean with reference to their regional populations and forms (Castiglioni and Negreiros-Fransozo 2004).
Besides their important ecological role, previous literature reveals no detailed work on the population genetics of this speciesalong the coast of Pakistan. The purpose of this study is to analyze andcompare the morphological and isozyme variation in the population of Austruca sindensis.This work is carried out on a single species of fiddler crabs (family Ocypodidae) to observe the effectiveness of electrophoretic applications and to test the efficacy of various enzymes for their species identification and population genetics analysis. This work is projected first time to observe the comparative relationship between morphometric measurement and isozyme variation of A. sindensis from the coast of Pakistan.
Materials Method Site Selection Three sites Sandspit, Sonari and Sonmiani were selected for the study area along the coast of Pakistan during the PreMonsoon seasons of two year 2012 and 2013. These three sites represent their own environmental conditions (Physical and chemical). The Sandspit (24°49′41.0^N 66°56′26.0″ E) and Sonari (24°53′00.0^N 66°42′00.0″E) are situated in Karachi coastal beaches. The distance between Sandspit and Sonari is about 27.5 km. Whereas Sonmiani beach (25°26′ 00.0^N 66°35′00.0″E) is situated in the Baluchistan coastal area, which is about 90 km away from Karachi (Fig. 1).
Collection and Preservation Three populations of A. sindensis; representative of the subfamily Ucinae were selected for comparative materials from three selected sites of Pakistan (Table 1), together with collection data and number of individuals examined. A total of 513 samples male, female and barried female crab specimen were collected by digging the burrows from three selected sites (Sandspit, 172; Sonari, 170; Sonmiani, 171) through random collection method. The random collection method is involved for uniform procedures and such random collection of the members of same species in the field can also remove the possible influence of external variables and establish the generalized results (Kelley et al. 2003). The collected samples were frozen through ice in the ice box (Colman, Japan) and carried to the laboratory and stored at −20 °C.
Identification and Relative Growth Measurements The crabs were identified and sorted out by available keys (Crane, 1975; Tirmizi and Ghani 1996; Saher 2008) and then morphometric measurements were carried out before electrophoresis. During morphometric measurements about 8 traits
Thalassas Fig. 1 Pakistan map representing the three collected sites of A. sindensis
were selected for the measurement i.e., carapace length, carapace width, wet weight, enlarged chela length sinistral, enlarged chela length dextral, abdominal length, abdominal width and small chela length (Table 1) to observe the phenotypic variations. The morphometric variables were measured to nearest 0.1 mm using the Vernier calliper. For isozyme electrophoresis crab samples were selected by collecting discriminating samples such as adult male crabs, which were found visibly different in their chela structure and color.
Table 1 Comparative morphostudy of three populations of Austruca sindensis from three different sites of Pakistan coastline
Tissue Extraction, Electrophoresis and Staining Frozen muscle from the ambulatory legs of each individual extracted and used for Polyacrylamide gel electrophoresis (PAGE-Native). Total three enzymes and a general protein were investigated, and the discontinuous buffer system was used.The staining procedures for specific enzymes were similar to those of Shaw and Prasad (1970), Ayala et al. (1972); Harris and Hopkinson (1976);
S. no.
Variable
Site
Count
Mean ± StDev
Minimum
Maximum
1
Wet weight (W.wt.) grams
Sandspit
171
516.3 ± 525.1
11.2
2355.6
2
Carapace Width (CW) mm
Sonari Sonmiani Sandspit Sonari Sonmiani
171 171 171 171 171
437.1 ± 316.2 126.90 ± 1.17 11.37 ± 3.63 10.42 ± 2.67 8.34 ± 0.89
11.0 11.0 3.5 5.0 6.0
1370.0 290.0 20.0 17.0 10.0
3
Carapace Length (CL) mm
4
Abdominal length (AL) mm
5
Abdominal width (AW) mm
6
Right chela length (RCL) mm
7
Left chela length (LCL) mm
Sandspit Sonari Sonmiani Sandspit Sonari Sonmiani Sandspit Sonari Sonmiani Sandspit Sonari Sonmiani Sandspit Sonari Sonmiani
171 171 171 171 171 171 171 171 171 171 171 171 171 171 171
7.42 ± 2.22 7.35 ± 1.66 6.33 ± 0.74 6.43 ± 2.19 6.11 ± 1.18 5.31 ± 0.91 3.61 ± 1.07 4.58 ± 0.65 3.31 ± 0.89 8.0 ± 6.4 13.7 ± 10.4 6.6 ± 1.8 7.76 ± 6.35 10.24 ± 8.26 8.12 ± 2.04
3.0 4.0 5.5 1.5 3.25 3.0 0.5 3.25 2.0 1.5 3.0 5.0 0.5 2.5 5.0
13.0 11.0 9.0 12.0 9.0 7.0 7.0 6.0 5.0 28.0 26.0 12.0 29.5 29.0 10.0
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Fig. 2 Correlation between carapace length and carapace width within three (Sandspit, Sonari and Sonmiani) populations of A. sindensis from the coastline of Pakistan
Murphy et al. (1996). Alleles at each locus were designated by letters in alphabetical order, starting with the allele encoding the most anodally migrating isozymes. Fig. 3 The mean (carapace width) difference through one-way ANOVA from three of different sites of Pakistan
In the present study, we followed the Shaklee et al. (1990) for enzyme nomenclature system proposed by the asterisks, coma and italicizing the name of the locus.
Interval Plot of carapace width vs Site1 95% CI for the Mean 12
carapace width
11
10
9
8 Sandspit
Sonari
Site1 The pooled standard deviation was used to calculate the intervals.
Sonmiani
Thalassas Table 2
Summary of canonical discriminant function
Function
Eigenvalue
% of variance
Cumulative %
Canonical correlation
1
1.125
80.1
80.1
.728
2
.279
19.9
100.0
.467
Data Analysis Ecological observations typically generate a large and complex amount of data to analyse and interpreted it because of the complex interrelationship between the variables. For such complex variables, multivariate techniques can be used to support the analysis of complicated measurements. For morphometric measurement analysis, MS Excel (2013), Minitab vr. 17 and SPSS vr. 16 were used to observe the descriptive analysis, regression, correlation, one-way ANOVA and discriminate function analysis. Discriminant function analysis (DFA) is used to interpret the various morphological measurements (Walker and Frison 1982; Morey 1986; Benecke 1987, 1994; Crockford 1997; Clark 1998) of A. sindensis for comparative purpose of three coastal sites. The descriptive analysis was employed for all three populations’ data to investigate the basic difference between all three populations of A. sindensis. The regression analysis (y = a + b x) was used for the study of the relative growth of each population (male and female) where (b) designates the slope and (a) as a Y – intercept. The correlation was observed between the variables of three different sites. The one-way ANOVA that was carried Fig. 4 The three different patches of individuals A. sindensis
out with the supporting null hypothesis that expresses that the populations of Austruca sindensis from three different sites is same. Finally DFA can be determined through quantitative variables which can discriminate numerous recognized groups and produces linear functions of quantitative variables that can be greatly separated into two or more groups of individuals. Statistical analyses of genetic data for isozyme were accomplished using the POPGENE 1.31 program (Yeh et al. 1999). Allele and genotype frequencies, percent polymorphic loci, mean expected heterozygosity, unbiased genetic distance D and a dendrogram constructed using the unweighted pair group method with arithmetic means UPGMA of Sneath and Sokal (1973) were calculated. Genotype frequencies were verified for abnormality from frequencies which were likely in HardyWeinberg equilibrium by means of random mating using the algorithm Levene (1949) and perform chi-square (χ2) at each locus; whereas a single locus expresses more than two alleles. Each locus was calculated for the percentage polymorphic loci for each population, one by using no standard (loci were designated to be polymorphic if that locus expresses more than one allele), and other a 0.95 standard (locus was designated as polymorphic if that allele’s frequency does not exceed 0.95). Each locus was also calculated for the mean expected heterozygosity under the random mating,by using Nei’s (1973) heterozygosity and unbiased heterozygosity (Nei 1978). For estimation of three different populations, the Nei’s (1978) mean unbiased genetic identity (I) and distance (D) were calculated and a dendrogram was constructed based on Nei’s genetic distance using UPGMA. Further, F- statistics (FST) were calculated (Hartl and Clark 1997) for each locus and all loci combined in order.
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Results
Table 4 The significance of discriminant function as indicated by wilks’ lambda
Morphometric Analysis
Test of function(s)
Wilks’ lambda
Chi-square
df
Sig.
The descriptive analysis showed that the maximum number of all the morphological characters was observed higher from the Sandspit coastal area while minimum numbers of morphological characters are observed higher from Sonmiani beach (Table 1). During regression analysis total 8 morphometric traits were selected from which only (3) showed the interpopulation variation (name of three variables carapace width, Enlarged cheliped length and abdominal width) (Table 1). The carapace length and carapace width showed positive correlation while carapace width (R2, 87%) and the small chela length showed negative correlation (R2 49%) (Fig. 2a–c). The one way ANOVA shows significant difference (p < 0.001) between the mean of carapace length from three different sites (Fig. 3). Two canonical discriminant functions were acquired having the Eigenvalue of 1.125 and 0.279. Function 1 describes the 80.1% of the variance (Table 2). The greater the Eigen value, the additional of the variance in the dependent variable is described by that function. The canonical correlation of function 1 (0.728) was also higher than function 2 (0.467). It is also reported that higher the canonical correlation value, the higher the strength of the canonical correlation. The plot of canonical discriminant function 1 and 2 of the morphometric measurements showed that individuals were divided into three different groups collected from three different sites and distinguished along the first function (Fig. 4). The Fisher’s linear discriminant function analysis (DFA) determines the discriminating characters which are contributing significantly in the populations; these characters are: carapace width, enlarged Chela length and width and abdominal length (Table 3). The carapace width and enlarged Chela length were considered as the most significant characters for discriminating populations.
1 through 2
.368
506.658
16
.000
2
.782
124.808
7
.000
Wilks’ lambda text indicated that discriminating function 1 was highly significant (p < 0.001) through function 2 and function 2 was also highly significant (p < 0.001) (Table 4). The significance of the discriminant functional analysis through wilks’ lambda test revealed that the models in function 1 and 2 were efficient and had the strength of differentiating between the groups. The classification result showed that 71.3% of the crabs were correctly classified into 3 groups. Crabs in group Sonmiani were classified with better accuracy of 77.2% than the crabs in group Sonari 69.4% and Sandspit 67.4% (Table 5).
Isozyme Analysis Collectively total 19 loci were observed among three populations; Sonari population showed total 13 loci monomorphic which is higher than Sandspit (10) and Sonmiani (11) populations (Table 6) among themCAT3 and Amy3 and two general protein with coomassie brilliant blue stain Com3 and Com4 found monomorphic throughout all three populations of A. sindensis (Fig 6). Whereas CD3, CD4, CAT5 found polymorphic in the Sandspit population, CD3, CAT1, Amy1 observed as polymorphic in Sonari population and Sonmiani population revealed CD2, CD3 and CAT1as polymorphic loci also, the general protein (amido stain) (Gp2 and Gp3) in Sandspit population, (Gp2) in Table 5 Classification resultsa,b in which the rows are dependent variables and the columns are predicted categories
Table 3 The Fisher’s linear discriminant functions of morpho-variables found from three study sites S. no.
1 2 3 4 5 6 7 8
Variables
Wet. Weight Carapace Length Carapace Width Enlarged Chela Length Enlarged Chela Width Abdominal Length Abdominal Width Small Chela length
Classification resultsa
Site
Site
Sandspit
Sonari
Sonmiani
−.001 1.595 .555 −.105 −.107 .015 2.657 .700
.005 1.817 −.166 −.133 .180 −.653 4.435 1.108
.000 1.557 −.200 −.118 −.016 .235 2.755 1.127
Original
Count
%
Sandspit Sonari Sonmiani Sandspit Sonari Sonmiani
Predicted group membership Sandspit
Sonari
Sonmiani
116 29 18 67.4 17.1 10.5
8 118 21 4.7 69.4 12.3
48 23 132 27.9 13.5 77.2
a
71.3% of original grouped cases correctly classified
b
70.8% of cross-validated grouped cases correctly classified
Total
171 171 171 100.0 100.0 100.0
Thalassas Table 6 The allele frequency, percentage of polymorphic loci and mean number of alleles per locusof 19 loci in 3 populations of Austruca sindensis from three different locations of Pakistan
S. no.
Locus
Allele
Population examined and allele frequency
Sandspit
Sonari
Sonmiani
Cd1
A
–
1.000
1.000
2
Cd2
B A
1.000 –
– 1.000
– 0.500
B
1.000
–
0.500
3
Cd3
A B
0.500 0.500
0.500 0.500
0.700 0.300
4
Cd4
A
0.700
1.000
1.000
5
Cat1
B A
0.300 1.000
– –
– –
6
Cat2
B A
– 1.000
1.000 –
1.000 –
B
–
1.000
1.000
7 8
Cat3 Cat4
A A
1.000 1.000
1.000 1.000
1.000 –
9
Cat5
B A
– 0.500
– 1.000
1.000 1.000
B A B A
0.500 1.000 – 1.000
– 0.500 0.500 1.000
– – – 1.000
A A B A
1.000 1.000 – 0.600
1.000 1.000 – 0.200
1.000 0.500 0.500 0.300
B A B A B
0.400 0.500 0.500 0.500 0.500
0.800 1.000 – 0.500 0.500
0.700 0.500 0.500 1.000 –
A B A B A B A B
0.500 0.500 1.000 1.000 1.000 0.500 52.6% 15.8 36.8%
0.500 0.500 1.000 – 1.000 – 63.2% 10.5% 26.3%
0.500 0.500 1.000 – 1.000 – 47.4% 15.8% 31.6%
1.473 0.756 ± 0.265 0.232 ± 251
1.368 0.839 ± 0.248 0.153 ± 0.235 0.232 ± 0.251
1.42 0.811 ± 0.256 0.180 ± 0.254
1
10
Amy1
11
Amy2
12 13
Amy3 Gp1
14
Gp2
15
Gp3
16
Com1
17
Com2
18
Com3
19
Com4
Frequency of Alleles Percent of polymorphic loci
Mean number of alleles per locus Mean observed heterozygosity Mean expected heterozygosity Nei (1973) Overall expected heterozygosity Nei (1973)
Sonari and (Gp1, Gp2, Gp3) found polymorphic. The percentage of Polymorphic loci ranged from 31.58–47.37%, while the average expected heterozygosity ranged from 0.167 to 0.553 and mean average heterozygosity value
was 0.188 ± 0.191 observed. Mean value of Nei’s (1978) expected heterozygosity of Austruca sindensis 0.232 ± 0.251, 0.153 ± 0.235 and 0.180 ± 0.244 was calculated from the allele frequencies of the 19 loci among the
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Sandspit, Sonari and Sonmiani populations respectively. The expected heterozygosity mean value was 0.244 ± 0.265, 0.161 ± 0.248 and 0.189 ± 0.257 from the allele frequencies of the 19 loci of three populations respectively. During (χ2) test for HW-Equilibrium, total 3 loci CD2, GP-1, and CAT5 found HW – equilibrium while 16 loci deviated from HW equilibrium. The level of differentiation through the fixation index (FST = 0.50) 50% which is very high. The overall population heterozygosity revealed through the Wright’s fixation index (FIS) which showed a deficiency in overall heterozygosity (−0.493) (Table 7). Nei’s unbiased genetic distance values (Nei 1972) among the three populations of Austruca sindensis, calculated from 19 loci, are given in Table 8. The pairwise genetic distance measurement values between Sonari, and Sonmiani Populations of A. sindensis revealed (D = 0.19) and conforming genetic identity with (I = 0.82) which indicates the population of Sandspit is somewhat diverged from twoother populations (Sonari and Sonmiani). Dendrogram Based on Nei’s (1978) Genetic distance by using Method UPGMA (Modified from Neighbor procedure of Phylip Version 3.5 by using PopGene 3.2 shows the Sonari and Sonmiani are in same clade while Sandspit showed in different clad (Fig. 7).
Table 7 The overall expected chi-square test of HW-equilibrium, level of genetic differentiation (Fixation index) in three populations of Austruca sindensis gene flow estimation
Enzyme locus
Sample size
Table 8 Nei’s Unbiased Measures of Genetic Identity and Genetic distance (1978). Nei’s unbiased measures of genetic identity and genetic distance [See Nei (1978) Genetics 89:583–590] Pop ID
Sandspit
Sonari
Sonmiani
Sandspit
–
0.5703
0.5647
Sonari Sonmiani
0.5616 0.5715
– 0.1892
0.8276 –
Discussion The selected three sites found physically different and isolated from each other (geographically); the Sandspit site consists of Sandy-cum muddy habitat and its substratum is soft as compared to other two selected sites. While the Sonari and Sonmiani beaches possess a purely muddy habitat for the selected species and substratum is so hard to dig their burrows. During the developmental stage of brachyuran crabs from fertilized egg to its sexual maturity, some gradual or sudden changes take place in their body parts, such as chelipeds, abdomen and pleopods. Therefore, allometric statistical analysis is used for the biological practical applications to study the
Chi-Square Chi-
P-value
CD1 CD2 CD3
60 60 60
31.30 3.68 3.43
0.000 0.055 0.063
CD4 GP1 GP2 GP3 CM1 CM2 CM3 CM4 AMY1 AMY2 AMY3 CAT1 CAT2 CAT3 CAT4 CAT5 Mean
60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60
35.45 1.065 31.02 7.064 22.89 29.00 – 59.00 59.25 31.30 0.000 29.00 31.30 0.000 31.30 1.065
0.00 0.302 0.000 0.008 0.000 0.000 – 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.302
Nm = Gene flow estimated from Fst = 0.25(1 - Fst)/Fst
Fis
Fit
Fst
Nm
−1.000 0.296
1.000 0.333 0.3213
1.000 0.667 0.0362
0.000 0.125 6.656
1.000 −1.000 1.000 −1.000 −1.000 −1.000 – −1.000 −0.200
1.000 −0.2000 1.000 −0.5000 −0.0909 −1.000 – 0.333 0.333 1.000
0.875 0.375 1.7596 0.7500 0.3000
−0.807
−0.6014 1.000
2.222 0.4000 0.1244 0.2500 0.4545 0.000 0.000 0.667 0.667 1.000 0.000 0.1139 1.000 0.000 1.000 0.4000 0.500
−1.000 −0.493
1.000 −0.2000 0.254
– 0.1250 0.1250 0.000 1.9453 0.0000 1.000 0.3750 0.250
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different growth patterns of body parts such as carapace length, Carapace width, enlarge cheliped and gonopod length. For allometric growth analysis of crabs, the carapace width used as an independent factor because it shows all the physiological changes that occurred in their life history (Castiglioni and Negreiros-Fransozo 2004). During current study, mean carapace width was 11.379 ± 3.633 from the Sandspit area which was higher from other two populations. This result can be compared with the previous study which shows slightly higher carapace width (13.5) from the current study (Lavajoo et al. 2013).The positive correlations observed between the carapace length and carapace width. Such allometric analysis have been studied in many Austruca species, where small change in overall body size may lead to increase in correlation determination between carapace length and carapace width which usually describes that when carapace width increases the length of carapace also increases (Lavajoo et al. 2013). In the present study,the overall expected heterozygosity (Detto et al. 2006; Nei 1973) observed higher between the three populations of Austruca sindensis(0.232 ± 0.251). This value is higher than other species of fiddler crabs such as U. rosea (0.071), U. forciptata (0.025), U. vocans (0.023), U. triangularis (0.031) and Austruca lactea (0.111) (Suzawa et al. 1993) U. musica (0.097); U. princeps (0.028); U. speciosa (0.031) and U. spinicarpa (0.029) other brachyuran species like Norway lobsters (0.180–0.187) (Stamatis et al. 2006); Portunid crabs (0.015–0.0225) (Saher et al. 2016). This value is also higher than the average heterozygosity of other crustaceans such as coconut crab (0.018); Penaeid shrimps (0.006–0.03) (Lavery and Fielder 1993; Mulley and Latter 1980) and invertebrates (0.110) (Nevo 1978) as well as group mean of decapods (0.07) (Hedgecock et al. 1982) while the current study shows exactly equals to (Huang and Shih 1995) results when working on U. arcuata (0.232). This high level of genetic variation can be the cause of abundant gene flow or by randomly matting individuals within a site (Huang and Shih 1995; Wright 1946, 1978). Whereas Albrecht and von Hagen (1981) did not find any intraspecific variation among various species of family Ocypodidae collected from different localities from the muscle protein. The overall expected heterozygosity observed in total population found higher than the values of expected heterozygosity of three populations (0.232 ± 0.251 vs Sandspit = 0.232 ± Fig. 5 The allele description modified from Bader 1998
251, Sonari = 0.153 ± 0.235 and Sonmiani = 0.180 ± 0.254). Therefore, this shows substantial lack of heterozygotes across all the loci that are produced by the Wahlund effect (Huang and Shih 1995). Our result is suggestive for more than two unmixed sub-populations of the genus Austruca. Hedgecock et al. (1982) suggested Wahlund effect may be cause of population sub-division during the study of Homarus americanus genetic structure. The sexual selection or genetic drift may lead to heterogeneity of gene frequency among populations. The chi-square test used to determine the existence or extent of any heterogeneity among the population by using the genetic structure of the population. The main benefit of this technique is its easy calculation but this technique cannot analyze the forces involved in any observed heterogeneity. The chi-square heterogeneity test analysis showed similar results for each locus in overall three populations with FST (Table 7). This showed the significant deficiency of heterozygotes in number of loci. Such results are may be the product of non-random matting such as inbreeding (the degree of differentiation between the populations) or affected by Wahlund effect (Table 7). The same results (significant deficiency in number of heterozygotes) were obtained by Huang and Shih (1995) in Uca arcuata populations. Deviation from HW-Equilibrium was measured among all the six populations for each locus. The HW-Equilibrium explains that the certain forms of nonrandom mating are produced and sustained in HWproportions among unstructured populations (Stark 2008). Chi-square test showed 13 loci with significant value deviation from HW-Equilibrium. Three loci found monomorphic in all populations (CM-3, AMY-3 and CAT-3). Three loci were in HW-Equilibrium (CD-3, GP-1 and CAT-5). This result justifies the result of genetic differentiation and genetic distances in current study. The alleles of each locusis designated with A, B or C (Figs. 5 and 7) depending on allele position modified by (Bader 1998). The current study shows that frequency of allele A was higher in 12 loci out of 19 loci (63.16%) in two populations (Sandspit and Sonari) and 9 out of 19 loci (47.37%) in Sonmiani as compared to two other alleles B and C. The level of genetic differentiation of A. sindensis of three populations is about 50% (FST = 0.50) which is higher than the recorded values for U. arcuata (0.085); Horseshoe crab (Limulus, FST = 0.076) and Drosophila aequinoxialis (FST = 0.109). FST values greater than 0.25 are considered as
Thalassas Fig. 6 The frontal view of Austruca sindensis
indicative of high genetic differentication (Wright 1971). However, during present study analysis, all the populations were sampled from a separate location therefore, the level of differentiation among three populations (0.50) is very high. Such high level of genetic differentiation may be cause by habitat selection since larval placement is influenced by two stimuli one is adult crab and other sediment presence of properties (O’Connor 1991; Huang and Shih 1995)described that free swimming crab larvae have ability to travel all over the estuarine habitat during high tide level. However, the study about free swimming larvae on A. sindensis is scarce there is dire need of work on free swimming larvae to understand how far the crab larvae can travel. Besides this, gene flow, regarding migration, can happen at different developmental stages of fiddler crabs (Huang and Shih 1995). Therefore, this is important to study on mating system of A. sindensis to evaluate the influence of matting system on genetic structure. Genetic drift and bottleneck effect may also effect on population if population is small in size (less than 100) Wright (1971). However, this does not influence on the current study because the population size is larger than the 100 samples. The Nei’s measure of genetic identity between the population of Sonari and Sonmiani is 0.82, corresponding to Nei’s genetic distance of 0.19, Hedgecock et al. (1982) established the mean genetic identity for the congeneric crustacean species as 0.59 to 0.17, following 40 comparisons between various crustacean species. The genetic identity value between these two populations is somewhat higher but similar to the average value between decapod crustacean species. These two population possess similar loci and no any divergent loci was observed therefore these two populations are not genetically divergent therefore these are closely related species.
The genetic distance along with the dendrogram (UPGMA)represents similar forms of population assemblage which shows that genetic distances are correlated with geographic distances. In dendrogram Sonari and Sonmiani populations formed single clad while Sandspit population formed separate populations. Such cladogram formation shows that Sandspit population is quite different from other two populations this just because Sonari and Sonmiani populations are closely related with other while Sandspit population is covered in a backwaters area. Therefore, it can be assumed that larval distribution is limited in that area and the flow is not possible from Sandspit to other two studied populations because of a large barrier of Hawksbay beach. While larval mixing is quite possible between two other populations because there is no any barrier between them. So, it can be assumed that, there might be gene flow and natural selection interaction between the populations to observe the patterns of genetic differentiation. The habitat selection could be the evolutionary forces which may be involved in higher genetic differentiation. This study reveals the importance of difference in habitat quality and status (includes physico- chemical factors, quality of available food and intraspecific as well as interspecific interaction in an area) that can also determine through the isozyme variations among the different population of species. The high level of genetic differentiation obtained from current study may be,because of gene flow with higher rates. This higher genetic differentiation is suggestive among the A. sindensis population; there might be an impact of habitat selection, gene flow and geographical isolation. These preliminary results indicated the need of more work on species habitat influential factor, larval migration and habitat selection pressure. Acknowledgements This research was supported by Pakistan Science Foundation Project No. 456 to NUS.
Compliance with Ethical Standards Fig. 7 Dendrogram Based Nei’s (1978) Genetic distance: Method using UPGMA (Modified from Neighbor procedure of Phylip Version 3.5 by using PopGene 3.2
Conflict of Interest On behalf of all authors, the corresponding author states that there is no conflict of interest.
Thalassas
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