Biochemical Systematics and Ecology 60 (2015) 99e105 Contents lists available at ScienceDirect Biochemical Systematics and Ecology journal homepage: www.elsevier.com/locate/biochemsyseco Mitochondrial genetic variation and population structure of the striped snakehead, Channa striata in Malaysia and Sumatra, Indonesia M.P. Tan a, b, *, A.F.J. Jamsari d, Z.A. Muchlisin c, M.N. Siti Azizah d a School of Fisheries and Aquaculture Sciences, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia Institut Akuakultur Tropika (AKUATROP), Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia c Department of Aquaculture, Faculty Marine and Fisheries, Syiah Kuala University, Banda Aceh 23111, Indonesia d School of Biological Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia b a r t i c l e i n f o a b s t r a c t Article history: Received 15 October 2014 Accepted 5 April 2015 Available online We explored the genetic diversity and structure of the striped snakehead (Channa striata) across Malaysia and Sumatra (Indonesia) using the partial mtDNA CO1 gene. Twenty five populations (n ¼ 345) were assayed and subdivided into six regions, following the physiogeographical barriers. Populations Sega (SG), Tanjung Tambutan (TR), Kajang (KJ) and Linggi (LG) are highly diversified (Hd: 0.484e0.762, p: 0.0033e0.0059) which could serve as candidates for a selective breeding programme. The only population that contributed to the total allelic richness is Takengon (CS) as it is highly differentiated from other populations and genetically variable within population. We detected two major phylogenies: 1) northwest Peninsular Malaysia and 2) all other regions of Malaysia and Sumatra, Indonesia. They are products of the physical restriction to gene flow between the two lineages by the Bintang Mountain Range. A total of 92.4% of the population pairwise comparison FST showed significant structuring, yet several geographically distant populations showed a close genetic relationship. The discrepancy is due to ancient population dispersal and human-mediated translocation. These major findings provide an important base study for initiating a selective breeding program. The high population genetic diversity requires independent conservation as they contain most of the total diversity in this area. © 2015 Elsevier Ltd. All rights reserved. Keywords: Genetic diversity Population structure Striped snakehead Channa striata Mitochondrial DNA Cytochrome oxidase subunit 1 gene 1. Introduction The striped snakehead (Channa striata) is one of the most widely distributed snakehead species with a native range covering southern China, Pakistan, most of India, southern Nepal, Bangladesh, Sri Lanka and most of the Southeast Asian countries (Froese and Pauly, 2010). It is well-represented in the ditches, swamps, lakes, paddy fields, irrigation canals, small streams, mining pools and old ponds, showing the highest preference for muddy stagnant waters. C. striata is often utilized in the biomedical field in many local Asian communities (Mat Jais et al., 1994; Baie and Sheikh, 2000). This species is being extensively farmed. * Corresponding author. School of Fisheries and Aquaculture Sciences, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia. Tel.: þ609 6684917; fax: þ609 6685002. E-mail address: mptan@umt.edu.my (M.P. Tan). http://dx.doi.org/10.1016/j.bse.2015.04.006 0305-1978/© 2015 Elsevier Ltd. All rights reserved. 100 M.P. Tan et al. / Biochemical Systematics and Ecology 60 (2015) 99e105 Although C. striata has a wide-ranging native distribution throughout Southeast Asia, there is little population genetic information on the species, particularly the strains located in remote regions. The few reports available include investigations of the genetics of Malaysian populations (Ambak et al., 2006; Tan et al., 2012) and a genetic survey of the Mekong drainage (Adamson et al., 2010). Within Peninsular Malaysia, the western populations (Perak and Perlis) are differentiated from the eastern populations (Terengganu and Johore), as inferred by the Random Amplified Polymorphic DNA (RAPD) fingerprinting method (Ambak et al., 2006) and mitochondrial DNA (mtDNA) ND5 gene (Tan et al., 2012). The study based on mtDNA cytochrome b gene and microsatellite markers in fish along the Mekong basin indicated differentiation between each population, even between adjacent locations (Adamson et al., 2010). These findings highlighted C. striata as a relatively nonmigratory species, which would necessitate independent fisheries management at different sites. The present study focused on the populations of Peninsular Malaysia and Sarawak and Sabah, the Malaysian portion of Borneo, as well as three populations from Sumatra, Indonesia. These areas form a major part of the Sundaland. This study characterized genetic diversity of each sampling locality inferred from the mtDNA cytochrome c oxidase subunit 1 (CO1) gene and defined population structuring with respect to natural physical barriers. The initial hypothesis sought to prove that adjacent populations share common haplotypes, yet populations may be significantly structured according to prominent geographical barriers. 2. Materials and methods 2.1. Human and animal rights Live specimens were collected from local fishermen and wet markets. Interviews with the procurers of the samples confirmed their origin from a single locality. Fin clips were excised from the dorsal or caudal fin rays (approximately 0.2 cm  2 cm) and preserved one set in 1.5 ml tubes containing 95% ethanol and another set in TNES-Urea (100 mM TriseHCl pH 7.5, 125 mM NaCl, 10 mM EDTA pH 7.5, 1% SDS, 3 M Urea) (modified from Valles-Jimenez et al., 2004). Samples were stored at room temperature (~25  C) until use. We returned the fish to the dealers or transported them to the Aquatic Research Centre at Universiti Sains Malaysia (USM), Penang for further research. The USM Ethics Committee approved this research. All practical steps to ameliorate suffering of specimens were taken throughout this study. 2.2. Samples collection and mtDNA extraction We conducted field sampling from 2007 to 2010. Random samples of individuals were collected from a total of 25 wild C. striata populations throughout its distribution in Peninsular Malaysia, Malaysian Borneo (Sarawak and Sabah) and Sumatra Island of Indonesia (Fig 1). Sampling locations were divided into six regions, following Tan et al. (2012): 1. Northwest Peninsular 2. Central west Peninsular 3. Southern Peninsular 4. East Peninsular 5. Malaysian Borneo and 6. Sumatra (Table 1). DNA template was isolated using an AQUAGENOMIC™ kit (MultiTarget Pharmaceuticals, Salt Lake City, Utah 84116) according to the manufacturer's protocol. 2.3. Polymerase chain reaction (PCR) optimization Genomic DNA was PCR amplified with mtDNA CO1 primer pair: L6154 (50 -AYC ARC AYY TRT TYT GRT TCT-30 ) and H6556 (50 -TGR AAR TGI GCI ACW ACR TA-30 ) (Teletchea et al., 2006). The PCR reaction mixture consisted of 50e100 ng of genomic DNA, 0.6 mM of each primer, 0.2 mM of dNTP (iNtRON), 1 PCR buffer (iNtRON), 4.2 mM MgCl2 ( iNtRON) and 0.08 U of Taq polymerase (iNtRON). We amplified each PCR in a 25 ml reaction volume in an MJ PTC-200 Thermal Cycler (MJ Research, Waltham, MA, USA). Amplification conditions were initial denaturation at 98  C (1 min); 35 cycles of 95  C (1 min), 55  C (1 min), 72  C (2 min) and a final extension at 72  C (1 min) before termination of the reaction at 10  C. PCR products were visualized on 1.7% agarose gels stained with ethidium bromide and purified (QIAGEN Sciences, Maryland 20874, USA) according to the manufacturer's instruction. Purified products were sent for DNA sequencing (First BASE Laboratories Sdn Bhd, Selangor, Malaysia) using forward primer only. 2.4. Genetic diversity Multiple CO1 sequences were aligned and all unambiguous operational taxa units were compiled for editing using ClustalW implemented in MEGA v. 4.0 (Tamura et al., 2007). DNA sequences were translated into protein to ensure accurate alignment and detection of nuclear mitochondrial DNA (numt), if present. The aligned sequences were exported to Collapse v. 1.2 (Posada, 2004) to construct a haplotype datasheet. The complete aligned dataset were analyzed for nucleotide variable sites, parsimony informative sites and number of haplotypes in MEGA v. 4.0. Using the same program, genetic divergence within population based on Kimura 2-parameter genetic distance was calculated. We calculated three estimations of diversity measurement to describe DNA polymorphism at each sampling site using Arlequin v. 3.1 (Excoffier et al., 2005). The first, haplotype/gene diversity (Hd), measures the probability of uniqueness of a haplotype in a given population. The second, nucleotide diversity (p), is the mean number of pairwise nucleotide differences among M.P. Tan et al. / Biochemical Systematics and Ecology 60 (2015) 99e105 101 Fig. 1. Clustering of C. striata populations into two major phylogenies, as defined in SAMOVA: Group 1, discontinuous round circle and Group 2, the rest of the populations. a) Map of Malaysia and populations from Sumatra, Indonesia. b) Enlarged map of Malaysia: 1-Timah Tasoh (TT) 2-Kuala Nerang (KN) 3-Jeniang (JN) 4-Seberang Prai (SP) 5-Teluk Kumbar (TK) 6-Kerian (KR) 7-Tanjung Rambutan (TR) 8-Tapah (TP) 9-Kajang (KJ) 10-Linggi (LG) 11- Yong Peng (YP) 12-Mersing (MS) 13-Kota Bahru (KB) 14-Binjai (BJ) 15-Kubang Bujuk (KT) 16-Kuala Krau (KK) 17-Sega (SG) 18-Tanjung Lumpur (TL) 19-Kota Belud (SB) 20-Kampung Kesapang (KS) 21-Sungai Sibuti (SS) 22-Serian (SW) and Sumatra populations: 23-Takengon (CS) 24-Sibreh (AB) 25-Kampar (KP). A indicates Titiwangsa Mountain Ranges, B indicates Bintang Mountain Range. individuals in a sample. The third, theta S (qs) (Watterson, 1975), is a measure of the number of segregating sites among haplotypes in a sample. To evaluate the contribution of each population to the total diversity, as measured by the allelic richness with rarefaction technique (CTR), we used CONTRIB v. 1.02 (Petit et al., 1998; Kalinowski, 2005). Rarefaction technique was used to standardize Table 1 Sampling locality, coordinate, collection date and sample size of C. striata populations in this study. Region Population Latitude (North) Longitude (East) Date collected Sample size (N) Northwest Peninsular 1) Timah Tasoh (TT), Perlis 2) Kuala Nerang (KN), Kedah 3) Jeniang (JN), Kedah 4) Seberang Prai (SP), P. Pinang 5) Teluk Kumbar (TK), P. Pinang 6) Kerian (KR), Perak 7) Tanjung Rambutan (TR), Perak 8) Tapah (TP), Perak 9) Kajang (KJ), K. Lumpur 10) Linggi (LG), N. Sembilan 11) Yong Peng (YP), Johor 12) Mersing (MS), Johor 13) Kota Bahru (KB), Kelantan 14) Binjai (BJ), Terengganu 15) Kubang Bujuk, Marang (KT), Terengganu 16) Kuala Krau, Mentakap (KK), Pahang 17) Sega, Raub (SG), Pahang 18) Tanjung Lumpur, Kuantan (TL), Pahang 19) Kota Belud (SB), Sabah 20) Kampung Kesapang (KS), Sabah 21) Sungai Sibuti, Miri (SS), Sarawak 22) Serian (SW), Sarawak 23) Takengon (CS), Aceh 24) Sibreh (AB), Aceh Besar 25) Kampar (KP), Riau 6 350 0800 6 140 3800 5 480 3900 5 220 0800 5 170 0400 4 590 2200 4 400 2300 4 110 5000 2 590 4200 2 350 0700 2 140 3900 2 300 2100 6 070 0500 4 130 4300 5 160 3800 3 370 1700 4 000 5800 3 470 4600 6 210 0300 6 210 5500 4 000 4300 1 020 4300 4 360 5300 5 240 5100 0 180 1200 100 130 1400 100 360 2200 100 370 2700 100 230 0300 100 140 2700 100 320 4900 101 080 5200 101 150 4800 101 470 5100 102 020 1500 103 020 2800 103 490 0600 102 140 2300 103 220 0300 103 020 5500 102 230 0700 101 530 5500 103 200 0900 116 250 5800 116 260 5000 113 460 3100 110 450 0300 96 500 4500 95 250 2000 101 220 0100 7.10.2008 13.5.2008 21.7.2008 8.8.2008 18.9.2008 Sept 2007 Sept 2007 Oct 2007 24.9.2008 5.4.2008 5.4.2008 6.5.2008 10.1.2009 13.6.2008 31.7.2009 30.7.2009 30.7.2009 1.8.2009 1.2.2009 23.8.2009 30.10.2009 13.5.2009 18.2.2009 18.2.2009 17.2.2009 Total 7 15 10 21 15 31 20 20 14 13 15 14 16 14 16 12 7 7 14 13 18 15 7 2 18 345 Central west Peninsular Southern Peninsular East Peninsular Malaysian Borneo Sumatra 102 M.P. Tan et al. / Biochemical Systematics and Ecology 60 (2015) 99e105 the allelic richness across populations by correcting variation in sample sizes, ensuring that the rarefaction size should not be larger than the smallest sample size (Petit et al., 1998). The contribution of each population to the total diversity was divided into two categories: 1) due to the variation of the population (Crs) and 2) due to the differences to other populations (Crd) (Petit et al., 1998). 2.5. Population structure and phylogenetic study A spatial analysis of molecular variance was conducted using Spatial Analysis of Molecular Variance (SAMOVA) SAMOVA v. 1.0 (Dupanloup et al., 2002) to identify similar groups of populations and to evaluate the amount of genetic variation among the partitions. The optimal number of groups (k) was determined based on the highest value of variances among groups (FCT) in the analysis, incorporating information on haplotype divergence and geographical proximity. Population pairwise comparison FST that calculates genetic differentiation within and among sites based on the k was determined in Arlequin v. 3.1, to evaluate the level of differences among populations and spatial population structuring. The analysis used the Kimura 2Parameter distance method and statistically significant pairwise comparisons were tested with 10,000 permutations procedure. Significant probability values were adjusted by performing the False Discovery Rate Procedure (FDR) at a ¼ 0.05, which controls the family wise error rate (FWER), a conservative type I error rate that originates from multiplicity (Benjamini and Hochberg, 1995). Phylogenetic relationships among haplotypes were constructed using Neighbor-Joining (NJ) (Saitou and Nei, 1987) and Maximum Parsimony (MP) (Eck and Dayhoff, 1966) in MEGA v. 4.0. The phylogenetic trees were produced with the least evolutionary steps or with the least total branch length. Kimura 2-Parameter (Kimura, 1980) evolutionary distance was implemented for the NJ method and confidence level at each node was assessed by 1000 bootstrap replications (Felsenstein, 1985). The close-neighbor-interchange (CNI) search option with search level of three and an initial tree by random addition of sequences at 20 replicates was used to search for maximum parsimony tree. We calculated the MP consensus tree, with 50% cut-off value, in the same program to view the most frequently occurring topology. 3. Results 3.1. Genetic diversity The 369 bp segment of the 345 CO1 gene sequences from 25 localities revealed 14 segregating sites defining 18 haplotypes. All unique sequences have been deposited in GenBank with accession number HQ384435eHQ384452. Of the 14 variable sites occurring at only the first and third codon positions with a ratio of 1:6, eight (57.1%) were parsimony informative. Population SG recorded the highest mean genetic divergence within population (0.6%), followed by TR (0.6%), KJ (0.4%), LG (0.3%) and KK (0.3%), while the rest recorded < 0.3% divergence (Table 2). Ten populations proved to be monomorphic. Within each population, the number of nucleotide variable sites varied from 0 to 7, generating 1 to 6 haplotypes in each population with an average of 2.12 haplotypes per population. The three diversity estimations consistently showed SG, TR and LG among the populations that harbored the highest genetic variation. No specific region showed extreme low or high genetic diversity. We excluded AB population from the evaluation on the contribution to the total allelic richness (CTR) due to the small sample size (n ¼ 2), as specifying rarefaction size at 2 yields the same estimation as Nei's gene diversity (Nei, 1973), and thus did not permit standardization of allelic richness across unequal-sized samples (Petit et al., 1998). Only CS contributed significantly to CTR as it is strongly differentiated from other populations and genetically diversified within population. Although it exhibited a low percentage, it indicated a positive contribution. Other populations fell into two categories; a) differentiated from other populations but not genetically diverse within (SW, SP and TP) and b) not differentiated but genetically diversified (TR, LG, SG, KK and KJ). 3.2. Population structure and phylogenetic study By defining groups of populations that are geographically homogenous and maximally differentiated with SAMOVA, important insights of genetic barriers between these groups could be identified (Dupanloup et al., 2002). The NeighborJoining tree in the previous section had revealed two lineages. Using this information, we initially set SAMOVA analysis at k ¼ 2. This resulted in the six northwest Peninsular populations grouping together (labeled as group 1) while all the rest formed group 2 (k ¼ 2, FCT ¼ 59.9%) (Fig 1). Further simulations revealed that FCT increased proportionately with k (2 < k < 20) (data not shown). The SAMOVA simulations attempted to maximize the contribution of total genetic variance among groups of populations. Increasing FCT values with higher k suggested that C. striata is a non-migratory species. Each disconnected population differentiated from each other. We accepted the optimal number of groups for SAMOVA at k ¼ 2, based on the phylogenetic NJ tree analysis in the earlier section. We excluded AB population from the population pairwise comparisons for genetic differentiation estimates due to its very small sample size (n ¼ 2). The population pairwise FST analysis showed an average high genetic differentiation, ranging from 0 to 100%. A total of 92.4% of the population pairwise comparisons FST showed significant structuring after FDR correction at a ¼ 0.05 (data not shown). The results demonstrated several unexpected findings, yet are consistent with the SAMOVA analysis. Several geographically distant populations proved to be genetically closely related. For instance, we found KP to be M.P. Tan et al. / Biochemical Systematics and Ecology 60 (2015) 99e105 103 Table 2 Genetic diversity for CO1 sequences in C. striata showing sample size (N), number of variable sites (#V), number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (p) and theta (S) for each population and each group. No 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Group 1 Group 2 Pop TT KN JN TK SP KR TR TP KJ LG YP MS BJ KB TL SG KT KK SW SS SB KS CS KP AB N 7 15 10 15 12 31 20 20 14 13 15 14 14 16 7 7 16 12 15 18 14 13 7 18 2 90 255 #V 1 0 3 0 1 5 7 5 4 4 0 1 0 2 1 4 0 3 0 2 0 0 1 0 0 7 10 H 2 1 2 1 2 5 6 2 3 4 1 2 1 3 2 3 1 3 1 2 1 1 2 1 1 8 13 Genetic diversity Hd p Theta(S) 0.286 0 0.200 0 0.167 0.299 0.737 0.100 0.484 0.756 0 0.528 0 0.242 0.476 0.762 0 0.546 0 0.425 0 0 0.476 0 0 0.615 0.794 0.0008 0 0.0016 0 0.0005 0.0027 0.0056 0.0014 0.0038 0.0033 0 0.0014 0 0.0007 0.0013 0.0059 0 0.0030 0 0.0023 0 0 0.0013 0 0 0.0026 0.0042 0.408 0 1.060 0 0.331 1.252 1.973 1.409 1.258 1.289 0 0.314 0 0.603 0.408 1.633 0 0.993 0 0.581 0 0 0.408 0 0 1.380 1.798 not differentiated from BJ, KT and KB (FST: 0.000e0.008). Similarly, we found KJ to be not differentiated from SS, SB and KS (FST: 0.107e0.180). Both neighbor-joining and maximum parsimony returned the same tree topology (MP tree not shown). A weak NJ tree still revealed two lineages (Fig 2). Clade I represented haplotypes common throughout all regions except the northwest Peninsular. We found clade II clustered haplotypes solely in the northwest Peninsular populations except Hap02 and 05. Hap02 was found in all regions in Malaysia but mainly in Malaysian Borneo and the central west Peninsular. Hap05 was found in TP and TR in the central west Peninsular. 4. Discussion 4.1. Genetic diversity We observed a relatively high haplotype diversity in some of the C. striata populations (Hd ¼ 0.000e0.762), a phenomenon often noted in freshwater fish inhabiting non-glaciated regions (during past glaciations era) or temperate regions (Bernatchez and Wilson, 1998; Roos, 2004). Various diversity measurements consistently indicated SG, TR, KJ and LG to be the most highly diversified populations and significantly contributed to the total genetic diversity within the studied regions, in agreement with our earlier works (Tan et al., 2012). Thus, these populations are highly recommended as potential broodstock for selective breeding programs in Malaysia. In contrast, ten populations showed a total absence of genetic variation, possibly due to a small effective population size. This could be a consequence of one or several likely factors, such as inbreeding possibly caused by a genetic bottleneck (Newman and Pilson, 1997), sample overexploitation (Hauser et al., 2002), habitat fragmentation (Luikart et al., 1998) or habitat loss due to environmental perturbation, including human activities (Wang et al., 2006), which threatened the genetic variability of this species. We found population and regional specific haplotypes, respectively, in 38.9 and 66.7%, suggesting local adaptation and independent evolutionary paths due to the limited connectivity between populations/regions. 4.2. Population structure and phylogenetic study We observed two genetically distinct clusters of C. striata in this study, separated significantly by the Bintang Mountain Range which lies at Perak state, suggesting it as an effective geographical barrier to gene flow between these two Peninsular regions. In our earlier study (Tan et al., 2012), we found three genetic clusters, inferred from the mtDNA ND5 gene. Two separate clusters formed group 2 in the current study, where populations from the central west Peninsular (TR, TP and KJ) and populations from Malaysian Borneo (SB, KS and SS) combined (Tan et al., 2012). The partial mtDNA CO1 gene used in this 104 M.P. Tan et al. / Biochemical Systematics and Ecology 60 (2015) 99e105 Fig. 2. The evolutionary tree of C. striata inferred from CO1 gene using NJ method. MP/NJ bootstrap value denoted at each branch (value < 50% not shown). study proved less informative in elucidating phylogenetic signals in this species. The probable cause is its relatively low mutation rate compared to the ND5 gene, where the former, more conservative (Miya et al., 2006), accumulated less genetic differentiation between individuals and populations. A high level of genetic structuring appeared among the C. striata populations in this study, based on the population pairwise FST analysis. We expected high genetic structuring, particularly in freshwater fish, as their distribution ability depends solely on waterway connections. We observed several unexpected results when genetic closeness appeared in geographically distant populations. KP proved to be similar to populations of the east Peninsular. Unexpectedly, KJ showed no genetic differentiation from populations of Malaysian Borneo. We observed these aberrant results in our earlier study, inferred from the mtDNA ND5 gene (Tan et al., 2012). The genetic proximity between KP and populations of the east Peninsular is most likely due to ancient long-range dispersal, through palaeo-river connectivity, of both regions through the last deglaciation period, when sea level rise submerged the river interconnectivity. To explain the lack of genetic differentiation between KJ and populations from Malaysian Borneo, after evaluating C. striata's native range and ancient river connectivity, we believe the genetic similarities are due to human-mediated translocation, either intentional or unintentional. C. striata did not occur originally in the eastern part of Malaysian Borneo (USGS, 2011). Additionally, there was no river connection between these two regions (Voris, 2000). C. striata is commonly transported inter-regionally due to its high economic value (Schuster, 1952) and its ability to air-breathe and stay alive during shipping (Courtenay et al., 2004). The landscape highly influenced the genetic diversity of C. striata in the Sundaland, suggesting independent evolutionary paths of respective regions in concordance with the disconnected geographical relationship. Our most significant finding is the segregation of this obligate freshwater species into two highly structured and significant phylogenetic groups, limited by effective geographical barriers and, thus, low gene flow between each population/phylogenetic region. Anthropogenic activity possibly played a major part in the probable translocation of this species from the central west Peninsular to as far as Malaysian Borneo, as detected by the maternal lineage markers. Ancient dispersal, through the palaeo river system running across two presently isolated regions, indicates the Pleistocene glacial signature of the typical genetic structure of freshwater fishes in the Sundaland. This indirectly revealed the dispersal power of C. striata, given dispersal limitations and its high adaptability into a newly colonized area. The current population genetics study has provided a good platform for future projection of an aquaculture programme and the conservation and management of this species. Acknowledgements Thanks are due to Dr Geoffrey K Chambers from Victoria University of Wellington, New Zealand, Prof Peter Mather and Dr David Hurwood from Queensland University of Technology, Australia for their helpful guidance and advice. Our appreciation also goes to Dr Muchlisin Zainal Abidin for his help in getting samples from Sumatra. Universiti Sains Malaysia funded this project under Research University Grant (1001/PBIOLOGI/8150123). References Adamson, E.A.S., Hurwood, D.A., Mather, P.B., 2010. A reappraisal of the evolutionary of Asian snakehead fishes (Pisces, Channidae) using molecular data from multiple genes and fossil calibration. Mol. Phylogenetics Evol. 56 (2), 707e717. M.P. Tan et al. / Biochemical Systematics and Ecology 60 (2015) 99e105 105 Ambak, M.A., Ambok, B.A.M., Ismail, P., Bui, M.T., 2006. Genetic variation of snakehead (Channa striata) populations using random amplified polymorphic DNA. Biotechnology 5 (1), 104e110. Baie, S.H., Sheikh, K.A., 2000. The wound healing properties of Channa striatus cetrimide cream: tensile strength measurement. J. Ethnopharmacol. 71 (1e2), 93e100. Benjamini, Y., Hochberg, Y., 1995. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57 (1), 289e300. Bernatchez, L., Wilson, C.C., 1998. Comparative phylogeography of Neartic and Paleartic fishes. Mol. Ecol. 7 (4), 431e452. Courtenay Jr., W.R., Williams, J.D., Britz, R., Yamamoto, M.N., Loiselle, P.V., 2004. Identity of introduced snakeheads (Pisces, Channidae) in Hawai'i and Madagascar, with comments on ecological concerns. Bish. Mus. Occas. Pap. 77, 13. Dupanloup, Schneider, S., Excoffier, L., 2002. A simulated annealing approach to define the genetic structure of populations. Mol. Ecol. 11, 2571e2581. Eck, R.V., Dayhoff, M.O., 1966. Atlas of Protein Sequence and Structure. National Biomedical Research Foundation, Silver Springs, Maryland. Excoffier, L., Laval, G., Schneider, S., 2005. Arlequin ver. 3.0: an integrated software package for population genetics data analysis. Evol. Bioinforma. Online 1, 47e50. Felsenstein, J., 1985. Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39, 783e791. Froese, R., Pauly, D. (Eds.), 2010. FishBase. World Wide Web electronic publication. www.fishbase.org. version (01/2010). Hauser, L., Adcock, G.J., Smith, P.J., Bernal Ramirez, J.H., Carvalho, G.R., 2002. Loss of microsatellite diversity and low effective population size in an overexploited population of New Zealand snapper (Pagrus auratus). Proc. Natl. Acad. Sci. U. S. A. 99 (18), 11742e11747. Kalinowski, S.T., 2005. HP-RARE 1.0: a computer program for performing rarefaction on measures of allelic richness. Mol. Ecol. Notes 5, 187e189. Kimura, M., 1980. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. J. Mol. Evol. 16, 111e120. Luikart, G., Sherwin, W.B., Steele, B.M., Allendorf, F.W., 1998. Usefulness of molecular markers for detecting population bottlenecks via monitoring genetic change. Mol. Ecol. 7, 963e974. Mat Jais, A.M., McCulloch, R., Croft, K., 1994. Fatty acid and amino acid composition in haruan as a potential role in wound healing. General Pharmacol. 25 (5), 947e950. Miya, M., Saitoh, K., Wood, R., Nishida, M., Mayden, R.L., 2006. New primers for amplifying and sequencing the mitochondrial ND4/ND5 gene region of the Cypriniformes (Actinopterygii: Ostariophysi). Ichthyol. Res. 53, 75e81. Nei, M., 1973. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. U. S. A. 70 (12), 3321e3323. Part I. Newman, D., Pilson, D., 1997. Increased probability of extinction due to decreased genetic effective population size: experimental populations of Clarkia pulchella. Evolution 51 (2), 354e362. Petit, R.J., El Mousadik, A., Pons, O., 1998. Identifying populations for conservation on the basis of genetic markers. Conserv. Biol. 12, 844e855. Posada, D., 2004. Collapse Ver. 1.2. A Tool for Collapsing Sequences to Haplotypes [Online] Available from: http://darwin.uvigo.es. Roos, H., 2004. Genetic Diversity in the Anabantids Sandelia capensis and S. bainsii: a Phylogeography and Phylogenetic Investigation. MSc thesis. University of Pretoria. Saitou, N., Nei, M., 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4 (4), 406e425. Schuster, W.H., 1952. A Provisional Survey of the Introduction and Transplantation of Fish throughout the Indo-Pacific Region. Third IPFC Fisheries Symposium, pp. 187e196. Tamura, K., Dudley, J., Nei, M., Kumar, S., 2007. MEGA4: molecular evolutionary genetics analysis (MEGA) software version 4.0. Mol. Biol. Evol. http://dx.doi. org/10.1093/molbev/msm092. Tan, M.P., Jamsari, A.F.J., Siti Azizah, M.N., 2012. Phylogeography pattern of the striped snakehead, Channa striata in Sundaland: ancient river connectivity, geographical and anthropological signatures. PLoS One 7 (12), e52089. http://dx.doi.org/10.1371/journal.pone.0052089. Teletchea, F., Laudet, V., H€ anni, C., 2006. Phylogeny of the Gadidae (sensu Svetovidov, 1984) based on their morphology and two mitochondrial genes. Mol. Phylogenetics Evol. 38, 189e199. USGS, 2011. Channa striata (Bloch, 1793) Chevron snakehead (Online), (accessed 19.02.11.). Available from: World Wide Web. http://fl.biology.usgs.gov/ Snakehead_circ_1251/html/channa_striata.html. Valles-Jimenez, R., Cruz, P., Perez-Enrique, R., 2004. Population genetic structure of Pacific white shrimp (Litopenaeus vannamei) from Mexico to Panama: microsatellite DNA variation. Mar. Biotechnol. 6, 475e484. Voris, H.K., 2000. Map of Pleistocene sea levels in Southeast Asia: shorelines, river systems and time duration. J. Biogeogr. 27, 1153e1167. Wang, Z.W., Zhou, J.F., Ye, Y.Z., Wei, Q.W., Wu, Q.J., 2006. Genetic structure and low genetic diversity suggesting the necessity for conservation of the Chinese longsnout catfish, Leiocassis longirostris (Pisces: Bagriidae). Environ. Biol. Fish 75 (4), 455e463. Watterson, G.A., 1975. On the number of segregating sites in genetic models without recombination. Theor. Popul. Biol. 7, 256e276. View publication stats