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Population genetic structure of Etroplus suratensis Bloch, 1790 in South India: preliminary evidence of founder haplotypes shared among populations
Journal of Asia-Pacific Biodiversity 12 (2019) 376e381
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Original Article
Population genetic structure of Etroplus suratensis Bloch, 1790 in South India: preliminary evidence of founder haplotypes shared among populations Shanmugam Chandrasekar a, Rajangam Sivakumar b, Ramasamy Mathialagan b, Jayachandran Subburaj c, Muthusamy Thangaraj c, * a b c
P.G. and Research Department of Zoology, V.O.C. College, Thootukudi, India P.G. and Research Department of Zoology, Government Arts College, Kumbakonam, India Centre of Advanced Study in Marine Biology, Faculty of Marine Sciences, Annamalai University, Parangipettai, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 September 2018 Received in revised form 5 January 2019 Accepted 5 March 2019 Available online 12 March 2019
Indian estuarine and coastal water habitats have reduced in recent decades because of anthropogenic activities such as coastal development. The pearlspot cichlid Etroplus suratensis is designated as Least Concern, given its wide distribution and presumably large overall population size in South India, despite the declining trend observed in wild populations. To assess the genetic diversity and connectivity among South Indian coastal populations, mitochondrial displacement loop sequence analysis was conducted to provide fundamental information for future conservation studies and an understanding of population dynamics by calculating the haplotype diversity of local populations. The haplotype (h) and nucleotide (p) diversity were very low at most localities, with values ranging from 0.56061 to 0.87879 and from 0.0014 to 0.0046, respectively, which may have resulted from recent population bottlenecks or founder events. The results also revealed a clear genetic differentiation between East and West coast populations, suggesting the existence of a gene flow barrier between them. As the maintenance of genetic connectivity is a prerequisite for local population stability, the preservation of extant habitats and the restoration of water bodies along the coast of India may be the most effective measures for the sustainable maintenance of this species. Ó 2019 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA), Publishing Services by Elsevier. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: D-loop Genetic diversity Gene flow Isolation by distance Mitochondrial DNA
Introduction The pearlspot cichlid Etroplus suratensis Bloch, 1790 is a euryhaline fish commonly found in riverine estuaries, coastal lagoons, and in natural and man-made freshwater habitats (Pethiyagoda 1991; Bindu and Padmakumar 2014). Although generally considered native to peninsular India and Sri Lanka, some sources state that it is only native to Sri Lanka, being introduced in India during the 1950s for aquaculture purposes (Welcomme 1988). However, the earlier literature suggests that this species was found in Wayanad district, northeastern Kerala, in the 1870s (Day 1877). Most occurrences in Sri Lanka are in the Western and Northern coasts, although the species distribution limit in the Eastern
* Corresponding author. E-mail address: [email protected] (M. Thangaraj). Peer review under responsibility of National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA).
province suggests it might be widely distributed around the island (Ward and Wyman 1977). E. suratensis has also been introduced to peninsular Malaysia and Singapore, where feral populations appear to be increasing (Welcomme 1988). In India, E. suratensis fishery is mainly performed in the states of Kerala, Karnataka, and Goa on the West coast and in the states of Tamil Nadu, Andhra Pradesh, and Odisha on the East coast (Reddy and Shanbhogue 1990). Several surveys have documented the decline of E. suratensis populations after 1965 (Kurup and Thomas 2001; Padmakumar et al 2002). Despite the relative decline registered in Kerala’s wild populations, E. suratensis is classified as Least Concern in the International Union for Conservation of Nature’s Red List of Threatened Species, given its wide distribution and presumably large overall population (Abraham 2013). In 2010, the Kerala state fisheries ministry designated E. suratensis (karimeen) as the official fish of Kerala, and the year 2010e2011 was celebrated as “The Year of the Karimeen” owing to the charismatic significance of this species.
https://doi.org/10.1016/j.japb.2019.03.001 pISSN2287-884X eISSN2287-9544/Ó 2019 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA), Publishing Services by Elsevier. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
S Chandrasekar et al. / Journal of Asia-Pacific Biodiversity 12 (2019) 376e381
E. suratensis characteristics such as being euryhaline; having low oxygen demand and broad temperature, pH, and harness tolerance; being naturally omnivore; and having high fecundity and perennial brooding (Bindu and Padmakumar 2014) make it easy to recover this species in its native habitat. The creation of no-fishing zones within some of the larger estuaries, captive breeding (Padmakumar et al 2004), establishing aquatic sanctuaries, performing cage culture in Vembanad Lake and in the Vypin Islands, and introducing E. suratensis in dam reservoirs, lakes, and culture ponds (Remadevi et al 2005) are serious conservation steps that have been taken to improve these species stocks in Kerala state. No other Indian state has made such considerable efforts toward E. suratensis conservation. The present status of E. suratensis population’s genetic structure in India is crucial to define conservation milestones as only after implementing conservation steps, it will be possible to assess population expansion and compare it with baseline data. Molecular data are currently used in the conservation and management of endangered species, allowing the estimation of effective population size (Osborne et al 2010), determining levels of migration and gene flow among populations (Howes et al 2009), and estimating the effects of geographic barriers and other landscape features on populations (Boizard et al 2009). Mitochondrial DNA (mtDNA) has been the elected marker for assessing population structure and genetic variability and investigating phylogeographic groups within a species (Yue et al 2009). Very limited research on the molecular genetics of this species has been conducted in India so far. In this study, displacement loop (D-loop) marker was used to acquire baseline data on E. suratensis population in India by assessing the genetic structure of the populations along the states of Karnataka, Kerala, Tamil Nadu, and Andhra Pradesh. Material and methods Ethics statement This study does not require any ethics statement. Animal collection E. suratensis were bought from the local fish vendors in the fisheries’ landing centers. No individual fish was intentionally collected from the wild for this study. Locality, longitude, latitude, and the number of individuals are given in Table 1. The caudal fin clips were dissected out from each dead fish. After fin clip dissection, the fishes were sold for consumption. The fin clips were immediately stored in 90% ethanol. DNA isolation and polymerase chain reactions Total genomic DNA was extracted from the fin clips using a phenol-chloroform protocol (Sambrook et al 1989). The mtDNA Dloop region was amplified by polymerase chain reaction (PCR) using the primers LBSS88 50 -TTAACTCCCACCCCTAACTCC-30 and BSSH13 50 -GGGCCCATCTTAACATCTTC-30 (Santos and Quilang 2012).
Table 1. Etroplus suratensis sampling location and the number of individuals (n) used in D-loop analyses. Locality
Latitude
Longitude
D-loop (n)
Mangalore Cochin Rajakkamangalam Mudasalodai Machilipatnam
12 870 N 09 580 N 08 120 N 11 450 N 16 170 N
74 76 77 79 81
12 12 12 12 12
D-loop, displacement loop.
880 140 360 470 130
E E E E E
377
PCR amplification took place in a total volume of 20 mL, as described previously. The PCR profile comprised 35 cycles of denaturation (94 C, 30 s), annealing (50 C, 30 s), and extension (72 C, 60 s) occurring in a thermal cycler (Techgene, UK). Amplified products were checked for quality and size by loading 1 mL of PCR product onto a 1.5% agarose gel stained with 0.5 mg/mL ethidium bromide. Products w523 base pairs in size were sequenced at Macrogen, Inc. (Seoul, Korea) following the company’s protocol and used in further analyses. Newly obtained sequences were deposited in the National Center for Biotechnology Information (NCBI) GenBank database (accession numbers: KF977087eKF977106 and KT896587e KT896626). Data analysis The number of D-loop haplotypes, haplotype diversity, and nucleotide diversity were calculated for each population using Arlequin Ver. 3.1 (Institute of Ecology and Evolution, University of Bern) (Excoffier et al 2006). The structure of each population was examined by performing analysis of molecular variance (AMOVA) (Excoffier et al 1992), using Arlequin, which was also used to compute pairwise fixation index (FST) values based on uncorrected p-distance (Excoffier et al 1992; Wright 1951) as indices of genetic differentiation between populations. The significance was assessed based on 100,000 permutations using Arlequin and corrected by the false discovery rate method (Benjamini and Hochberg 1995). Population expansion and bottlenecks using Arlequin were evaluated based on Tajima’s D test (Tajima 1989a, b) and Fu’s Fs statistics (Fu 1997), and the fit of mismatch distributions were compared with that expected under the spatial expansion model. The sum of squared deviations and raggedness index (rg) between observed and expected distributions were also used as test statistics, and their significance was assessed using 1,000 bootstraps. An index regarding the age of population expansion (Ʈ) was also calculated using Arlequin. To examine if population evolved according to the model of isolation by distance, a Mantel test was performed on genetic (FST/1eFST) versus geographic distances for all sample location pairs. To illustrate the phylogenetic and geographical relationships among E. suratensis haplotypes, a median-joining haplotype network was created using Network Ver. 4.1 (University of Hamburg; Hamburg) (Röhl and Mihn 2003). Results and discussion Low genetic diversity Twenty-one D-loop haplotypes were identified from the sequenced samples (Figure 1, Table 2). Among them, H1 and H2 were the dominant and the most frequent haplotypes, which were found in at least four populations with their frequencies ranging from 0.083 to 0.167. Haplotype (h) and nucleotide (p) diversity were very low at most localities, with values ranging from 0.56061 to 0.87879 and from 0.0014 to 0.0046, respectively (Table 3). The Machilipatnam population exhibited the greatest genetic diversity (1.0000 0.0340), followed by the Cochin population (0.9565 0.0166). The median-joining haplotype network constructed for the Dloop data evidenced two major (founder) haplotypes (H1 and H2), shared by almost all populations (Figure 2). Nineteen minor haplotypes were specific to their own populations, as summarized in Table 2. AMOVA revealed significant overall population differentiation (percentage of variation among populations ¼ 31.48; percentage of variation within populations ¼ 17.04, P<0.001) (Table 4). Pairwise FST values (Table 5) revealed the West coast populations (Mangalore and Cochin) tended to be genetically
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S Chandrasekar et al. / Journal of Asia-Pacific Biodiversity 12 (2019) 376e381
Figure 1. Etroplus suratensis sampling localities and mtDNA D-loop haplotype frequencies (represented in pie charts) within each population. D-loop ¼ displacement loop; mtDNA ¼ mitochondrial DNA.
differentiated the East coast counterpart (Rajakkamangalam, Mudasalodai, and Machilipatnam). The demographic analyses using Tajima’s D and Fu’s Fs statistics (Table 6) showed negative values for Mangalore and Machilipatnam populations, and the P value of sum of squared deviations in these populations indicated they had undergone a sudden population expansion. Under the hypothesis of spatial expansion, the value of Ʈ obtained for Mudasalodai and Rajakkamangalam populations was much lower than the other East coast populations. This suggests that the Mudasalodai and Rajakkamangalam populations were critically affected by a bottleneck/founder effect in recent years. A significant relationship between genetic and linear geographic distances was found for D-loop data along longitudinal and latitudinal gradients, suggesting this species obeys isolation by distance (Figure 3). All the studied populations in South Indian coastal regions showed low levels of genetic diversity, as measured by haplotype and nucleotide diversities (Table 3). The values of genetic diversity found here are within the range of those obtained for Eleutheronema rhadinum populations using cytochrome oxydae subunit I (COI) data (Sun et al 2013) (mean haplotype diversity ¼ 0.759 0.035 and mean nucleotide diversity ¼ 0.00198 0.0032), and in the Australian populations of Eleutheronema tetradactylum, haplotype diversity ranged from 0.00 to 0.83 and nucleotide diversity ranged from 0.0000 to 0.0024, according to Cyt b data
(Horne et al 2011). A remarkable reduction was observed in the genetic diversity of the Zhoushan population (h ¼ 0.595 0.109, p ¼ 0.001 0.001 55) compared with the Qidong (h ¼ 0.782 0.058, p ¼ 0.00212 0.0035) and Zhuhai populations (h ¼ 0.780 0.059, p ¼ 0.00222 0.00282). Genetic variation within populations can be reduced through genetic drift or through bottlenecks (Habib et al 2011; Chang et al 2012). An earlier study (Grant and Bowen 1998) reported that overfishing and concomitant habitat loss in this area have had a deleterious effect at the population level, decreasing genetic diversity, and this might be the cause of the low genetic diversity found in the Zhoushan population in the South China Sea. Grant and Bowen (1998) classified marine fishes into four categories on the basis of different combinations of high and low values of haplotype and nucleotide diversity based on mtDNA sequence analysis. E. suratensis, having low values of haplotype and nucleotide diversity, is classified into the first category, meaning that a population bottleneck or founder event involving a single or, at the most, a limited number of mtDNA linkages might have occurred recently. The populations at the Western geographical limit showed a comparable level of genetic diversity to the populations at the Eastern geographic limit. Similar genetic relationships have been reported for E. suratensis using the COI gene (Chandrasekar et al 2013). Urbanization of coastal areas and anthropogenic activities occurring in estuaries have reclaimed tidal flats, including salt
S Chandrasekar et al. / Journal of Asia-Pacific Biodiversity 12 (2019) 376e381
379
Table 2. Number of individuals presenting each haplotype and haplotype diversity (mean SD) found within each of the five Etroplus suratensis populations. Haplotype
Mangalore (n ¼ 12)
Cochin (n ¼ 12)
Rajakkamangalam (n ¼ 12)
Mudasalodai (n ¼ 12)
Machilipatnam (n ¼ 12)
H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 Haplotype diversity
1 6 2 1 1 1 0.75758
1 1 2 2 1 1 4 0.87879
2 2 2 2 4 0.84848
1 1 8 2 0.56061
1 1 2 2 1 5 0.81818
SD, standard deviation. Table 3. Genetic diversity of Etroplus suratensis populations based on D-loop sequence analysis. Population
D-loop
p
D
H
Mangalore
0.0046 0.0028 0.0031 0.0021 0.0014 0.0011 0.0019 0.004 0.0024 0.0018
2.4293 1.3357 1.6376 1.0006 0.7375 0.5572 1.0142 0.6966 1.2878 0.8662
0.9322 0.0066 0.9565 0.0166 0.9362 0.0082 0.9429 0.0110 1.0000 0.0340
Cochin Rajakkamangalam Mudasalodai Machilipatnam
D-loop, displacement loop; D, haplotype frequency; H, shared haplotype.
marshes, throughout the Indian coast. As a result, estuarinespecific population ranges have reduced, with the majority of such populations inhabiting India’s major estuaries now being
Table 4. Analysis of molecular variance (AMOVA) performed for the partial D-loop sequences of Etroplus suratensis populations. Source of variation
Degrees of freedom
Sum of squares
Variance Percentage of components variation
Among groups (West coast vs. East coast) Among populations within group Within populations Total
1
228.62
1.40
31.48
3
211.30
2.28
51.48
175 179
132.66 572.58
0.75 4.44
17.04
D-loop, displacement loop.
threatened. The unimodal mismatched nucleotide frequency distribution and haplotype network configuration of the present study supported the occurrence of a recent population bottleneck, followed by population expansion in most of the populations. However, positive selection can also result in an excess of lowfrequency haplotypes in many populations, making it difficult to
Figure 2. Median-joining network constructed for the D-loop haplotypes found in Etroplus suratensis populations. Each circle represents a unique haplotype, with its size being proportional to its frequency. Colors represent the different populations. D-loop ¼ displacement loop.
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Table 5. Pairwise FST (above diagonal) and Kimura two parameter genetic distance (below diagonal) values between Etroplus suratensis populations. Population
Mangalore
Mangalore Cochin Rajakkamangalam Mudasalodai Machilipatnam
0.028 0.026 0.026 0.028
Cochin
Rajakkamangalam
Mudasalodai
Machilipatnam
0.76110*
0.78159* 0.41056*
0.82629* 0.45944* 0.47693*
0.80808* 0.42935* 0.47643* 0.50225*
0.010 0.009 0.010
0.007 0.009
0.007
*
Significant values at P<0.01. FST, fixation index.
Table 6. Neutrality test (Tajima’s D and Fu’s Fs) values and demographic estimates for mismatch distributions under the spatial expansion model (SSD, rg, and Ʈ). Population
Mangalore Cochin Rajakkamangalam Mudasalodai Machilipatnam
Neutrality
Demographic
Tajima D
Fu’s Fs
SSD
rg
Ʈ
e0.5620 0.6465 1.1473 0.1261 e0.0973
e2.2337 e7.9943 e10.9853 e9.5543 e17.7877
0.0146 0.0076 0.0121 0.3693 0.0086
0.0651 0.0279 0.0415 0.1418 0.0344
1.0253 4.8652 0.4062 0.0000 1.3125
Rg, raggedness index; SSD, sum of squared deviations.
open estuarine and marine environment often effectively reduces genetic heterogeneity among populations, making it difficult to differentiate discreet regional populations (Han et al 2008). Conclusion Similar to other estuarine fishes, E. suratensis have a short larval stage and reduced dispersal ability. The genetic homogeneity found in marine and estuarine fish populations is generally attributed to the high dispersal potential of the species during the planktonic egg and larval stages, coupled with the absence of physical barriers between ocean basins and adjacent continental margins. Previous studies have revealed that the oceanic currents in the China Sea facilitate the dispersal of marine larvae among distant locations (Shui et al 2009; Xiao et al 2009). Furthermore, the low genetic diversity and the results of the demographic analysis performed for these distant populations suggested they might have been established coincidently through the introduction of founder individuals from unknown habitats, and founder haplotypes shared between populations might have resulted from naturally occurring genetic drift. However, the present data is insufficient for inferring population connectivity. The use of multiple genetic marker systems can increase the resolving power of genetic studies. Microsatellite is a useful marker for estimating contemporary gene flow among populations. Thus, such markers should be considered in future studies aiming to elucidate the metapopulation structure of E. suratensis in India.
Figure 3. Isolation by distance in Etroplus suratensis populations. Genetic distances (FST/1eFST) based on D-loop data were plotted against geographical distances between the five localities. D-loop ¼ displacement loop; FST ¼ fixation index.
Conflict of interest
unambiguously distinguish between natural selection and demographic population expansion. To distinguish these scenarios, it is necessary to analyze several unlinked genomic loci as selection would only affect specific loci (Grant et al 2006). Still, historical factors, anthropogenic activity, habitat destruction and occupancy, and a low rate of mitochondrial evolution are known to influence genetic population structure (Avise 2004; Kumar et al 2012) and need to be taken into account.
Acknowledgments
Low gene flow D-loop AMOVA revealed significant overall population differentiation, and FST analysis showed a clear differentiation between East and West coast populations. The D-loop isolation by distance analysis (Figure 3) revealed a significant relationship between genetic and linear geographic distances within the longitudinal gradient examined, that is, between East and West coast populations. Marine and estuarine species are generally characterized by metapopulations, which have a large population size, high dispersal capacity during the pelagic larval stages, and extensive distribution (Palumbi 1992). The apparent lack of barriers to dispersal in the
The authors declare that there is no conflict of interest.
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Journal of Asia-Pacific Biodiversity journal homepage: http://www.elsevier.com/locate/japb
Original Article
Population genetic structure of Etroplus suratensis Bloch, 1790 in South India: preliminary evidence of founder haplotypes shared among populations Shanmugam Chandrasekar a, Rajangam Sivakumar b, Ramasamy Mathialagan b, Jayachandran Subburaj c, Muthusamy Thangaraj c, * a b c
P.G. and Research Department of Zoology, V.O.C. College, Thootukudi, India P.G. and Research Department of Zoology, Government Arts College, Kumbakonam, India Centre of Advanced Study in Marine Biology, Faculty of Marine Sciences, Annamalai University, Parangipettai, India
a r t i c l e i n f o
a b s t r a c t
Article history: Received 10 September 2018 Received in revised form 5 January 2019 Accepted 5 March 2019 Available online 12 March 2019
Indian estuarine and coastal water habitats have reduced in recent decades because of anthropogenic activities such as coastal development. The pearlspot cichlid Etroplus suratensis is designated as Least Concern, given its wide distribution and presumably large overall population size in South India, despite the declining trend observed in wild populations. To assess the genetic diversity and connectivity among South Indian coastal populations, mitochondrial displacement loop sequence analysis was conducted to provide fundamental information for future conservation studies and an understanding of population dynamics by calculating the haplotype diversity of local populations. The haplotype (h) and nucleotide (p) diversity were very low at most localities, with values ranging from 0.56061 to 0.87879 and from 0.0014 to 0.0046, respectively, which may have resulted from recent population bottlenecks or founder events. The results also revealed a clear genetic differentiation between East and West coast populations, suggesting the existence of a gene flow barrier between them. As the maintenance of genetic connectivity is a prerequisite for local population stability, the preservation of extant habitats and the restoration of water bodies along the coast of India may be the most effective measures for the sustainable maintenance of this species. Ó 2019 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA), Publishing Services by Elsevier. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: D-loop Genetic diversity Gene flow Isolation by distance Mitochondrial DNA
Introduction The pearlspot cichlid Etroplus suratensis Bloch, 1790 is a euryhaline fish commonly found in riverine estuaries, coastal lagoons, and in natural and man-made freshwater habitats (Pethiyagoda 1991; Bindu and Padmakumar 2014). Although generally considered native to peninsular India and Sri Lanka, some sources state that it is only native to Sri Lanka, being introduced in India during the 1950s for aquaculture purposes (Welcomme 1988). However, the earlier literature suggests that this species was found in Wayanad district, northeastern Kerala, in the 1870s (Day 1877). Most occurrences in Sri Lanka are in the Western and Northern coasts, although the species distribution limit in the Eastern
* Corresponding author. E-mail address: [email protected] (M. Thangaraj). Peer review under responsibility of National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA).
province suggests it might be widely distributed around the island (Ward and Wyman 1977). E. suratensis has also been introduced to peninsular Malaysia and Singapore, where feral populations appear to be increasing (Welcomme 1988). In India, E. suratensis fishery is mainly performed in the states of Kerala, Karnataka, and Goa on the West coast and in the states of Tamil Nadu, Andhra Pradesh, and Odisha on the East coast (Reddy and Shanbhogue 1990). Several surveys have documented the decline of E. suratensis populations after 1965 (Kurup and Thomas 2001; Padmakumar et al 2002). Despite the relative decline registered in Kerala’s wild populations, E. suratensis is classified as Least Concern in the International Union for Conservation of Nature’s Red List of Threatened Species, given its wide distribution and presumably large overall population (Abraham 2013). In 2010, the Kerala state fisheries ministry designated E. suratensis (karimeen) as the official fish of Kerala, and the year 2010e2011 was celebrated as “The Year of the Karimeen” owing to the charismatic significance of this species.
https://doi.org/10.1016/j.japb.2019.03.001 pISSN2287-884X eISSN2287-9544/Ó 2019 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA), Publishing Services by Elsevier. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
S Chandrasekar et al. / Journal of Asia-Pacific Biodiversity 12 (2019) 376e381
E. suratensis characteristics such as being euryhaline; having low oxygen demand and broad temperature, pH, and harness tolerance; being naturally omnivore; and having high fecundity and perennial brooding (Bindu and Padmakumar 2014) make it easy to recover this species in its native habitat. The creation of no-fishing zones within some of the larger estuaries, captive breeding (Padmakumar et al 2004), establishing aquatic sanctuaries, performing cage culture in Vembanad Lake and in the Vypin Islands, and introducing E. suratensis in dam reservoirs, lakes, and culture ponds (Remadevi et al 2005) are serious conservation steps that have been taken to improve these species stocks in Kerala state. No other Indian state has made such considerable efforts toward E. suratensis conservation. The present status of E. suratensis population’s genetic structure in India is crucial to define conservation milestones as only after implementing conservation steps, it will be possible to assess population expansion and compare it with baseline data. Molecular data are currently used in the conservation and management of endangered species, allowing the estimation of effective population size (Osborne et al 2010), determining levels of migration and gene flow among populations (Howes et al 2009), and estimating the effects of geographic barriers and other landscape features on populations (Boizard et al 2009). Mitochondrial DNA (mtDNA) has been the elected marker for assessing population structure and genetic variability and investigating phylogeographic groups within a species (Yue et al 2009). Very limited research on the molecular genetics of this species has been conducted in India so far. In this study, displacement loop (D-loop) marker was used to acquire baseline data on E. suratensis population in India by assessing the genetic structure of the populations along the states of Karnataka, Kerala, Tamil Nadu, and Andhra Pradesh. Material and methods Ethics statement This study does not require any ethics statement. Animal collection E. suratensis were bought from the local fish vendors in the fisheries’ landing centers. No individual fish was intentionally collected from the wild for this study. Locality, longitude, latitude, and the number of individuals are given in Table 1. The caudal fin clips were dissected out from each dead fish. After fin clip dissection, the fishes were sold for consumption. The fin clips were immediately stored in 90% ethanol. DNA isolation and polymerase chain reactions Total genomic DNA was extracted from the fin clips using a phenol-chloroform protocol (Sambrook et al 1989). The mtDNA Dloop region was amplified by polymerase chain reaction (PCR) using the primers LBSS88 50 -TTAACTCCCACCCCTAACTCC-30 and BSSH13 50 -GGGCCCATCTTAACATCTTC-30 (Santos and Quilang 2012).
Table 1. Etroplus suratensis sampling location and the number of individuals (n) used in D-loop analyses. Locality
Latitude
Longitude
D-loop (n)
Mangalore Cochin Rajakkamangalam Mudasalodai Machilipatnam
12 870 N 09 580 N 08 120 N 11 450 N 16 170 N
74 76 77 79 81
12 12 12 12 12
D-loop, displacement loop.
880 140 360 470 130
E E E E E
377
PCR amplification took place in a total volume of 20 mL, as described previously. The PCR profile comprised 35 cycles of denaturation (94 C, 30 s), annealing (50 C, 30 s), and extension (72 C, 60 s) occurring in a thermal cycler (Techgene, UK). Amplified products were checked for quality and size by loading 1 mL of PCR product onto a 1.5% agarose gel stained with 0.5 mg/mL ethidium bromide. Products w523 base pairs in size were sequenced at Macrogen, Inc. (Seoul, Korea) following the company’s protocol and used in further analyses. Newly obtained sequences were deposited in the National Center for Biotechnology Information (NCBI) GenBank database (accession numbers: KF977087eKF977106 and KT896587e KT896626). Data analysis The number of D-loop haplotypes, haplotype diversity, and nucleotide diversity were calculated for each population using Arlequin Ver. 3.1 (Institute of Ecology and Evolution, University of Bern) (Excoffier et al 2006). The structure of each population was examined by performing analysis of molecular variance (AMOVA) (Excoffier et al 1992), using Arlequin, which was also used to compute pairwise fixation index (FST) values based on uncorrected p-distance (Excoffier et al 1992; Wright 1951) as indices of genetic differentiation between populations. The significance was assessed based on 100,000 permutations using Arlequin and corrected by the false discovery rate method (Benjamini and Hochberg 1995). Population expansion and bottlenecks using Arlequin were evaluated based on Tajima’s D test (Tajima 1989a, b) and Fu’s Fs statistics (Fu 1997), and the fit of mismatch distributions were compared with that expected under the spatial expansion model. The sum of squared deviations and raggedness index (rg) between observed and expected distributions were also used as test statistics, and their significance was assessed using 1,000 bootstraps. An index regarding the age of population expansion (Ʈ) was also calculated using Arlequin. To examine if population evolved according to the model of isolation by distance, a Mantel test was performed on genetic (FST/1eFST) versus geographic distances for all sample location pairs. To illustrate the phylogenetic and geographical relationships among E. suratensis haplotypes, a median-joining haplotype network was created using Network Ver. 4.1 (University of Hamburg; Hamburg) (Röhl and Mihn 2003). Results and discussion Low genetic diversity Twenty-one D-loop haplotypes were identified from the sequenced samples (Figure 1, Table 2). Among them, H1 and H2 were the dominant and the most frequent haplotypes, which were found in at least four populations with their frequencies ranging from 0.083 to 0.167. Haplotype (h) and nucleotide (p) diversity were very low at most localities, with values ranging from 0.56061 to 0.87879 and from 0.0014 to 0.0046, respectively (Table 3). The Machilipatnam population exhibited the greatest genetic diversity (1.0000 0.0340), followed by the Cochin population (0.9565 0.0166). The median-joining haplotype network constructed for the Dloop data evidenced two major (founder) haplotypes (H1 and H2), shared by almost all populations (Figure 2). Nineteen minor haplotypes were specific to their own populations, as summarized in Table 2. AMOVA revealed significant overall population differentiation (percentage of variation among populations ¼ 31.48; percentage of variation within populations ¼ 17.04, P<0.001) (Table 4). Pairwise FST values (Table 5) revealed the West coast populations (Mangalore and Cochin) tended to be genetically
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Figure 1. Etroplus suratensis sampling localities and mtDNA D-loop haplotype frequencies (represented in pie charts) within each population. D-loop ¼ displacement loop; mtDNA ¼ mitochondrial DNA.
differentiated the East coast counterpart (Rajakkamangalam, Mudasalodai, and Machilipatnam). The demographic analyses using Tajima’s D and Fu’s Fs statistics (Table 6) showed negative values for Mangalore and Machilipatnam populations, and the P value of sum of squared deviations in these populations indicated they had undergone a sudden population expansion. Under the hypothesis of spatial expansion, the value of Ʈ obtained for Mudasalodai and Rajakkamangalam populations was much lower than the other East coast populations. This suggests that the Mudasalodai and Rajakkamangalam populations were critically affected by a bottleneck/founder effect in recent years. A significant relationship between genetic and linear geographic distances was found for D-loop data along longitudinal and latitudinal gradients, suggesting this species obeys isolation by distance (Figure 3). All the studied populations in South Indian coastal regions showed low levels of genetic diversity, as measured by haplotype and nucleotide diversities (Table 3). The values of genetic diversity found here are within the range of those obtained for Eleutheronema rhadinum populations using cytochrome oxydae subunit I (COI) data (Sun et al 2013) (mean haplotype diversity ¼ 0.759 0.035 and mean nucleotide diversity ¼ 0.00198 0.0032), and in the Australian populations of Eleutheronema tetradactylum, haplotype diversity ranged from 0.00 to 0.83 and nucleotide diversity ranged from 0.0000 to 0.0024, according to Cyt b data
(Horne et al 2011). A remarkable reduction was observed in the genetic diversity of the Zhoushan population (h ¼ 0.595 0.109, p ¼ 0.001 0.001 55) compared with the Qidong (h ¼ 0.782 0.058, p ¼ 0.00212 0.0035) and Zhuhai populations (h ¼ 0.780 0.059, p ¼ 0.00222 0.00282). Genetic variation within populations can be reduced through genetic drift or through bottlenecks (Habib et al 2011; Chang et al 2012). An earlier study (Grant and Bowen 1998) reported that overfishing and concomitant habitat loss in this area have had a deleterious effect at the population level, decreasing genetic diversity, and this might be the cause of the low genetic diversity found in the Zhoushan population in the South China Sea. Grant and Bowen (1998) classified marine fishes into four categories on the basis of different combinations of high and low values of haplotype and nucleotide diversity based on mtDNA sequence analysis. E. suratensis, having low values of haplotype and nucleotide diversity, is classified into the first category, meaning that a population bottleneck or founder event involving a single or, at the most, a limited number of mtDNA linkages might have occurred recently. The populations at the Western geographical limit showed a comparable level of genetic diversity to the populations at the Eastern geographic limit. Similar genetic relationships have been reported for E. suratensis using the COI gene (Chandrasekar et al 2013). Urbanization of coastal areas and anthropogenic activities occurring in estuaries have reclaimed tidal flats, including salt
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379
Table 2. Number of individuals presenting each haplotype and haplotype diversity (mean SD) found within each of the five Etroplus suratensis populations. Haplotype
Mangalore (n ¼ 12)
Cochin (n ¼ 12)
Rajakkamangalam (n ¼ 12)
Mudasalodai (n ¼ 12)
Machilipatnam (n ¼ 12)
H1 H2 H3 H4 H5 H6 H7 H8 H9 H10 H11 H12 H13 H14 H15 H16 H17 H18 H19 H20 H21 Haplotype diversity
1 6 2 1 1 1 0.75758
1 1 2 2 1 1 4 0.87879
2 2 2 2 4 0.84848
1 1 8 2 0.56061
1 1 2 2 1 5 0.81818
SD, standard deviation. Table 3. Genetic diversity of Etroplus suratensis populations based on D-loop sequence analysis. Population
D-loop
p
D
H
Mangalore
0.0046 0.0028 0.0031 0.0021 0.0014 0.0011 0.0019 0.004 0.0024 0.0018
2.4293 1.3357 1.6376 1.0006 0.7375 0.5572 1.0142 0.6966 1.2878 0.8662
0.9322 0.0066 0.9565 0.0166 0.9362 0.0082 0.9429 0.0110 1.0000 0.0340
Cochin Rajakkamangalam Mudasalodai Machilipatnam
D-loop, displacement loop; D, haplotype frequency; H, shared haplotype.
marshes, throughout the Indian coast. As a result, estuarinespecific population ranges have reduced, with the majority of such populations inhabiting India’s major estuaries now being
Table 4. Analysis of molecular variance (AMOVA) performed for the partial D-loop sequences of Etroplus suratensis populations. Source of variation
Degrees of freedom
Sum of squares
Variance Percentage of components variation
Among groups (West coast vs. East coast) Among populations within group Within populations Total
1
228.62
1.40
31.48
3
211.30
2.28
51.48
175 179
132.66 572.58
0.75 4.44
17.04
D-loop, displacement loop.
threatened. The unimodal mismatched nucleotide frequency distribution and haplotype network configuration of the present study supported the occurrence of a recent population bottleneck, followed by population expansion in most of the populations. However, positive selection can also result in an excess of lowfrequency haplotypes in many populations, making it difficult to
Figure 2. Median-joining network constructed for the D-loop haplotypes found in Etroplus suratensis populations. Each circle represents a unique haplotype, with its size being proportional to its frequency. Colors represent the different populations. D-loop ¼ displacement loop.
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Table 5. Pairwise FST (above diagonal) and Kimura two parameter genetic distance (below diagonal) values between Etroplus suratensis populations. Population
Mangalore
Mangalore Cochin Rajakkamangalam Mudasalodai Machilipatnam
0.028 0.026 0.026 0.028
Cochin
Rajakkamangalam
Mudasalodai
Machilipatnam
0.76110*
0.78159* 0.41056*
0.82629* 0.45944* 0.47693*
0.80808* 0.42935* 0.47643* 0.50225*
0.010 0.009 0.010
0.007 0.009
0.007
*
Significant values at P<0.01. FST, fixation index.
Table 6. Neutrality test (Tajima’s D and Fu’s Fs) values and demographic estimates for mismatch distributions under the spatial expansion model (SSD, rg, and Ʈ). Population
Mangalore Cochin Rajakkamangalam Mudasalodai Machilipatnam
Neutrality
Demographic
Tajima D
Fu’s Fs
SSD
rg
Ʈ
e0.5620 0.6465 1.1473 0.1261 e0.0973
e2.2337 e7.9943 e10.9853 e9.5543 e17.7877
0.0146 0.0076 0.0121 0.3693 0.0086
0.0651 0.0279 0.0415 0.1418 0.0344
1.0253 4.8652 0.4062 0.0000 1.3125
Rg, raggedness index; SSD, sum of squared deviations.
open estuarine and marine environment often effectively reduces genetic heterogeneity among populations, making it difficult to differentiate discreet regional populations (Han et al 2008). Conclusion Similar to other estuarine fishes, E. suratensis have a short larval stage and reduced dispersal ability. The genetic homogeneity found in marine and estuarine fish populations is generally attributed to the high dispersal potential of the species during the planktonic egg and larval stages, coupled with the absence of physical barriers between ocean basins and adjacent continental margins. Previous studies have revealed that the oceanic currents in the China Sea facilitate the dispersal of marine larvae among distant locations (Shui et al 2009; Xiao et al 2009). Furthermore, the low genetic diversity and the results of the demographic analysis performed for these distant populations suggested they might have been established coincidently through the introduction of founder individuals from unknown habitats, and founder haplotypes shared between populations might have resulted from naturally occurring genetic drift. However, the present data is insufficient for inferring population connectivity. The use of multiple genetic marker systems can increase the resolving power of genetic studies. Microsatellite is a useful marker for estimating contemporary gene flow among populations. Thus, such markers should be considered in future studies aiming to elucidate the metapopulation structure of E. suratensis in India.
Figure 3. Isolation by distance in Etroplus suratensis populations. Genetic distances (FST/1eFST) based on D-loop data were plotted against geographical distances between the five localities. D-loop ¼ displacement loop; FST ¼ fixation index.
Conflict of interest
unambiguously distinguish between natural selection and demographic population expansion. To distinguish these scenarios, it is necessary to analyze several unlinked genomic loci as selection would only affect specific loci (Grant et al 2006). Still, historical factors, anthropogenic activity, habitat destruction and occupancy, and a low rate of mitochondrial evolution are known to influence genetic population structure (Avise 2004; Kumar et al 2012) and need to be taken into account.
Acknowledgments
Low gene flow D-loop AMOVA revealed significant overall population differentiation, and FST analysis showed a clear differentiation between East and West coast populations. The D-loop isolation by distance analysis (Figure 3) revealed a significant relationship between genetic and linear geographic distances within the longitudinal gradient examined, that is, between East and West coast populations. Marine and estuarine species are generally characterized by metapopulations, which have a large population size, high dispersal capacity during the pelagic larval stages, and extensive distribution (Palumbi 1992). The apparent lack of barriers to dispersal in the
The authors declare that there is no conflict of interest.
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