14 Advances in Environmental Biology, 4(1): 14-23, 2010 ISSN 1995-0756 © 2010, American-Eurasian Network for Scientific Information

This is a refereed journal and all articles are professionally screened and reviewed ORIGINAL ARTICLE

Genetic variability and estimation of effective population sizes of the natural populations of green , formosus in Peninsular

1Shafiqur Rahman, 1Mohd Zakaria-Ismail, 3Pek Yee Tang, 1Mohd Rizman-Idid and 4Sekeran Muniandy

1Bangladesh Fisheries Research Institute, Mymensingh-2201, Bangladesh, 2Institute of Biological Sciences, Faculty of Science, University of Malaya, 50603, Kuala Lumpur, Malaysia, 3Faculty of Engineering and Science, University Tunku Abdul Rahman 4Department of Molecular Medicine, Faculty of medicine, University of Malaya, 50603, Kuala Lumpur, Malaysia,

Shafiqur Rahman, Mohd Zakaria-Ismail, Pek Yee Tang, Mohd Rizman-Idid and Sekeran Muniandy, Genetic variability and estimation of effective population sizes of the natural populations of green arowana, Scleropages formosus in , Adv. Environ. Biol., 4(1): 14-23, 2010

ABSTRACT

Microsatellite markers and mitochondrial DNA (mtDNA) sequences were used to assess the genetic variability and to estimate genetic effective population sizes of the natural populations of green arowana in Tasik Bera Lake and River. Nine microsatellite loci were polymorphic in both the Tasek Bera and Endau River populations. Results showed evidence of inbreeding in Tasik Bera and Endau River populations. These two populations also exhibited significant heterozygosity excess (p<0.05), suggesting that these two

populations have experienced a reduction in effective population size (Ne). Using mtDNA, haplotype diversity was estimated 1.000 for both the populations and nucleotide diversity was low: 0.004 for Tasik Bera and 0.006 for Endau River. The significantly (p< 0.05) negative Fu’s Fs in Tasik Bera (-4.263) indicated this population has undergone historical expansion and this is possibly the cause of the high mitochondrial gene diversity noticed. The historical and contemporary Ne of both Tasik Bera and Endau River populations based on microsatellite data suggested that the size of the arowana populations reduced drastically but these two populations has not experienced genetic bottleneck yet. Genetic differentiation based on microsatellite and mtDNA data between the arowana from Tasik Beara and Endau River was low. This observation may be resulted from isolations of these two populations due to changes of land mass configurations during glaciation and deglaciation and the accompanying lowering and rising of sea levels during the late Pleistocene era.

Key words: genetic variability, effective population sizes, natural populations, green arowana

Introduction Asia [7]. The Asian arowana’s, range was known to encompassed , , Malaysia, The Asian arowana (Scleropages formosus) is and [21]. There are three main colour also known as dragonfish, Asian Bonytongue, kelisa varieties (green, gold and red) of Asian arowana. or baju rantai. This ancient ossteoglossid is one These varieties diverged from the late Pliocene to the of the most expensive and sought after fish in late Pleistocene eras[28]. In Malaysia the distribution aquatic world. It is related to the other two of the green arowana in Peninsular Malaysia is very Australian arowana in the genus Scleropages and is wide. The green variety is relatively common in the only representative of this in Southeast some areas such as Tasik Bera in , Endau

Corresponding Author Shafiqur Rahman, Bangladesh Fisheries Research Institute, Mymensingh-2201, Bangladesh, Phone +8801730302661; E mail: [email protected] Adv. Environ. Biol., 4(1): 14-23, 2010 15

River in [19,25] and Trengganu drainage[6] and Biology laboratory, Faculty of Science, (Fig. 1). University of Malaya and were reared individually in Genetic analysis of arowana is of conservation . Scales, opercula and fin clips were interest, because it is a declining species. collected form live specimens while muscles were alteration, over exploitation and other human collected from dead fish. These samples were activities are threatening arowana populations in preserved in 70% ethanol at 4°C until genomic DNA Malaysia [33]. Low fecundity rate, oralbrooding habit was extracted. and openwater spawning further threaten the survivability of the arowana [13]. The species is DNA Extraction considered to be vulnerable by the International Union for Conservation of Natural Resources Approximately 20-30 mg of sample was lysed (IUCN)[1,2], and is currently listed in Appendix I of with 260 µl TNES-Urea buffer (Asahida et al., 1996) the Convention on International Trade of Endangered and 0.2 mg to 0.8 mg of Proteinase K. The mixture 0 Species of Wild Fauna and Flora (CITES) as was incubated for 12 hours to 15 hours at 55 C . following conventional phenol-chloroform extraction. Genetic assessment of the arowana has been undertaken using various kinds of molecular markers. Microsatellite Analyses The capability of Restriction fragment length polymorphism (RFLP) and random amplified Genetic variation within and between these polymorphic DNA (RAPD) to study the genetic populations was assessed using nine microsatellite variability of arowana is low [10]. Analysis using loci. Among these markers four were described by Yue et al. [34], while five loci were isolated by amplified fragment length polymorphism (AFLP) Tang et al.[28]. Details of all the microsatellite loci showed significant genetic differentiation between the and PCR conditions are given in Table 1. The green, red and gold arowana [35,36]. The use of Polymerase chain reaction (PCR) procedure was microsatellites is well documented in fish [24,30,8]. performed on a Hybaid Omnigene thermal cycler in It is a powerful technique to detect genetic variability total a volume of 25 µl. Reactions contained 1x PCR between and within strains of arowana [35,36]. buffer (Promega), 1.5 mM MgCl2, 200mM of each Molecular markers have been used successfully dNTP, 0.2 mM of each primer (Table 1), 1U Taq for monitoring in captive stocks of polymerase (Promega) and 20 ng of genomic DNA. arowana. However, the lack of consensus regarding Amplifications for the six loci described by Yue et the population structure of the wild arowana suggests al.[34], were carried out using 4 min of initial the need for population genetic studies to provide denaturation followed by 30 cycles of 30 s of insight into the status of the wild populations. In this denaturation at 94.5°C, 30 s annealing at the study, we used microsatellite markers and temperature detailed in Table 1, and 30 s extensions mitochondrial sequences to assess the genetic at 72°C, with a final extension of 5 min at 72°C. variability and to estimate genetic effective The other five loci were amplified with 3 min of population sizes of two wild populations of green initial denaturation followed by 40 cycles of 10 s of arowana in Tasik Bera and Endau River. This study denaturation at 950C, annealing at specific will provide a genetic background for the temperature (Table 2) for 10 s and 30 s extensions at conservation of wild arowana in the Malaysian river 720C with a final extension of 5 min. at 720C. PCR systems. products were run on a 10% nondenaturing polyacrylamide gel (16cm x 20cm) at 250 V for 4-5 Materials and methods hours. A 20-bp DNA marker (Cambrex BioScience) was used to estimate the PCR fragment size. Gels Samples were visualized using a DNA silver staining system (Promega) and analyzed using GelCompar the II Two populations of green arowana were used in Software (Applied Maths). this study. Ninety-seven green arowana were collected from Tasik Bera, Pahang (Fig. 1) and Mitochondrial DNA Sequencing thirty-eight green arowana were sampled from the Endau River (Fig. 1). Tasik Bera, in central Ten individuals from Tasik Bera and 5 Peninsular Malaysia, lies within the catchments of individuals from Endau River were chosen for . This is the first RAMSAR mitochondrial DNA sequence analysis. Three target site in Malaysia. The Endau-Rompin area is situated regions of the arowana mitochondrial DNA were at the boundary of Johor and Pahang States. It selected for sequencing: 1044bp encompassing the encompasses the watershed of the Endau and Rompin complete ND2, 628 bp of cytb gene region and 72 rivers. Green individuals were caught by fishermen bp of tRNA-Thr. The positions for the amplifications using net. The fish were then transferred the Ecology are shown in Fig. 2 and Fig. 3 respectively. Adv. Environ. Biol., 4(1): 14-23, 2010 16

Fig. 1: Major River Drainages and Major of Arowana (Scleropages formosus) in Peninsular Malaysia.

Fig. 2: Position of primers for amplification and/or sequencing of ND2 gene. The tRNA genes are indicated by the single letter amino acid codes (I= Isoleucine tRNA; Q=Glutamine tRNA; M= Methionine; W=Tryptophan tRNA; A=Alanine tRNA; N=Asparagine tRNA; C= Cysteine tRNA; Y= Tyrosine tRNA).

Fig. 3: Position of primers for amplification and/or sequencing of cyt-b gene. The tRNA genes are indicated by the single letter amino acid codes (E= Glutamic Acid tRNA; T= Threonine tRNA; P= Proline tRNA).

PCR amplification was carried out in a 25-µl followed by 40 cycles of denaturation at 940C for 40

containing 1x PCR buffer (Promega), 1.5 mM MgCl2, s, annealing at specific temperatures (Table 2) for 1, 200mM of each dNTP, 0.2 mM of each primer extension at 720C for 2 min followed by a final (Table 2), 1U Taq polymerase (Promega) and 20 ng extension at 720C for 10 min. of genomic DNA, on a Hybaid Omnigene Thermocycler. Amplification conditions were as follows: initial denaturation at 940C for 4 min, Adv. Environ. Biol., 4(1): 14-23, 2010 17

Table 1: Primers sequences of nine microsatellite loci. Locus Repeat motif Primer sequences (5’-3’) GenBank accession nos. Optimized Annealing Temperature (0C)

D92 (GT)13 F AGTCGCACACCACCACCTCAG R TCAGCGATAACCCCACACCT AF219969 55°C

D27 (CA)17 F GTGTCAGTATAGTGAATCTGTAG R TGACAATGGCAGCATAATGAGAT AF219958 55°C

D85 (CA)10 F GTTCCACAGGGGCTGAGAAAAT R GAGGACGGAACAAAAGCATTGG AF219967 55°C

D11 (GT)16 F TGGTTTCCACCTACAGTCCAAAGA R GTTACGAGTATCTGGCCCAATGG AF219953 55°C

K10 (CA)20 F GCACCTAACTGAAGAGCATT R AAAATTACCTGCTTGTGTGC AY173130 57°C

K13 (CA)5CG(CA)3 F GCACTGTTAAGTTCTGGTGTC R GATACGCATGACATTCTGTG AY173131 51°C

K16 (TG)5 F CAGTGGTTGCACACTTACAG R AAAGTCGGCATGATGAAATA AY173136 50°C

K27 (CA)16 F CCATTAACCCCTTGTCCTCA R AAGGATGCAGGAGAGCAAAA AY173135 50°C

K37 (CA)4 F CCATTAGCAAACCCATGCTT R TGGAAATGTGTCATCCTTCAG AY173132 51°C

Table 2: Primers used for PCR and sequencing (Kumazawa et al., 1999. Mitochondrial gene Primers Primer sequences (5’-3’) Annealing Temperature (0C) ND2 L4296 F CGTAGGGATCACTTTGATAG H5540 R CCGCTGAGGGCTTTGAAGGC 50°C fND2-3 F TCMACCTGACARAAACT (Internal sequencing primer) 50°C Cytb Fcytb-3 F TMGTMCAATGAATCTGAGG H15990 R GTTTAATTTAGAATCYTGGCTTTGG 51°C

Statistical Analysis Population differentiation was measured by

calculating pairwise weighted FST [31] values over all Microsatellites loci. The ARLEQUIN programme was used for

computations. RST values were also calculated as sum The observed (Ho) and expected heterozygosities of squared size differences based on number of (He), of the polymorphic loci of each strain were repeats [26]. The probability associated with the FST estimated using the ARLEQUIN version 2.000 [23] and RST values was estimated through random software. Hardy-Weinberg equilibrium (HWE) at each permutation procedure (1000 permutation). locus was assessed using the ARLEQUIN Effective population sizes for the two populations programme. A Markov-chain method with 1000 were estimated based on two methods: the linkage steps, 1000 dememorizations was used to calculate an disequilibrium method [12] to estimate contemporary unbiased estimate of the P value. The inbreeding Ne and the unbiased expected heterozygosity under coefficient, FIS [31] was estimated to measure the Stepwise Mutation Model (SMM) according to HWE departures for each population using Nei[17] to calculate long-term Ne. The contemporary GENEPOP version 3.1c [22]. The software estimates of Ne and 95% confidence intervals were MICROCHECKER [29] was used to identify the estimated using the programme NeEstimator [20]. presence of null alleles. MICROCHECKER was also used to test for another source of errors in mis- Mitochondrial DNA scoring due to stuttering and allelic dropout. All sequences were edited using the programme The micorsatellite data were examined for CHROMAS version 1.4 [16]. The ESEE programme evidence of a population bottleneck using [4] was used to align multiple sequences to identify BOTTLENECK version 1.2.02 [5]. The two-phased polymorphic nucleotide sites and assign haplotypes. model (TPM) was used as it is intermediate to the Sequence variation was assessed estimating Stepwise Mutation Model (SMM) and the Infinite nucleotide diversity [17] and haplotypic diversity [18] Allele Model (IAM), and most microsatellite loci using the ARLEQUIN package version 2.0[23]. evolve under this model [5]. This model was tested Analysis of molecular variance (AMOVA) [9] was using the Wilcoxon sign-rank test with default performed on the mtDNA sequence data. The settings and 1000 iterations. A graphical method [15] ARLEQUIN was also used to estimate thr ФST (an was used to look for further evidence of a mtDNA analogue for FST; Excoffier [9]. The ФST bottleneck. analysis was performed using a matrix Tamura and Adv. Environ. Biol., 4(1): 14-23, 2010 18

Table 3: Number of alleles (N), heterozygosity observed (Ho), heterozygosity expected (He), and inbreeding coefficient (FIS) at nine microsatellite loci for two populations of arowana. Locus Genetic variability indices Tasik Bera Endau River D92 N 43

Ho 0.918 0.737 He 0.639 0.512 Fis -0.438 -0.448 D27 N 43

Ho 0.495 0.658 He 0.427 0.501 Fis -0.161 -0.318 D85 N 22

Ho 0.000 0.000 He 0.327 0.419 Fis 1.000 1.000 D11 N 22

Ho 0.000 0.000 He 0.501 0.498 Fis 1.000 1.000 K10 N 22

Ho 0.464 0.447 He 0.366 0.372 Fis -0.297 -0.276 K13 N 33

Ho 0.320 0.342 He 0.289 0.373 Fis -0.140 0.084 K16 N 22

Ho 0.000 0.000 He 0.127 0.392 Fis 1.000 1.000 K27 N 22

Ho 0.515 0.553 He 0.420 0.448 Fis -0.250 -0.239 K37 N 22

Ho 0.000 0.000 He 0.212 0.127 Fis 1.000 1.000 Mean N 2.56 2.33

Ho 0.301 0.304 He 0.368 0.405 Fis 0.302 0.311

Table 4: Observed gene diversity (He, Hardy-Weinberg heterozygosity) and equilibrium gene diversity (Heq) of two populations of arowana under two-phased model. Tasik Bera Endau River ------

He Heq PHe Heq P D92 0.639 0.477 0.148 0.512 0.400 0.326 D27 0.427 0.473 0.320 0.501 0.390 0.322 D85 0.327 0.186 0.269 0.419 0.235 0.269 D11 0.501 0.181 0.052 0.498 0.215 0.133 K10 0.366 0.191 0.231 0.372 0.218 0.281 K13 0.289 0.360 0.340 0.373 0.401 0.391 K16 0.127 0.183 0.501 0.392 0.223 0.268 K27 0.420 0.178 0.148 0.448 0.212 0.168 K37 0.212 0.186 0.394 0.127 0.221 0.382

Nei [27]. Fu’s test Fs [11] was performed to indicate accession numbers DQ 864661- DQ864676 and whether the mutations are neutral or under the tRNA- Threonine accession numbers DQ147903-

influence to selection. Significance of Fs was DQ147905; DQ864687-DQ864699). evaluated by using 1,000 random permutations in ARLEQUIN. Results Sequences generated from the two-mitochondrial genes and tRNA-Thr were submitted to Genbank Genetic variability (ND2 gene sequences accession numbers DQ 864677-DQ864686; DQ147901- DQ147902; All nine microsatellite loci were polymorphic in DQ147906- DQ147909, Cyt-b gene sequences both the Tasik Bera and Endau River populations Adv. Environ. Biol., 4(1): 14-23, 2010 19

(Table 3). A total of 24 alleles were detected in 135 the FST and RST values were 0.022. The фST of -0.037 individuals. The average number of alleles per locus did not reveal significant difference between the two ranged from 2.33 in the Endau River population to populations (Table 6). 2.56 in the Tasik Bera population. Three alleles were Population Expansion and Effective Population

unique to Tasik Bera while one was unique to Endau Size Fu’s Fs of Tasik Bera and Endau River were - River. 4.263 and -0.286 respectively. However only the Fu’s

The Endau River population showed higher Fs of Tasik Bera was significantly (p<0.05) different average observed and expected heterozygosity than from zero which indicated population expansion. For

the Tasik Bera (0.315) population (Table 3). Positive microsatellite data, contemporary Ne estimates for values of average inbreeding coefficients (FIS) were Tasik Bera and Endau River were 28.0 (95% estimated for both of the populations, where the confidence interval [CI] = 20.1-39.9) and 14.6 (95%

Endau River population showed the higher value CI = 10.9-19.5) respectively. Historical Ne showed (Table 3). that the Tasik Bera population had an Ne of 1514 Seven loci significantly deviated (p<0.05) from which was higher than that of the Endau River Hardy-Weinberg equilibrium, K10 and K27 in the population (995). The estimates were slightly Tasik Bera population and D92, D85, D11, K16 and changed after correcting the allele frequencies for

K37 in both populations. MICROCHECKER null alleles. The contemporary Ne for Tasik Bera was indicated that departure from HWE in these two 26.7 (95% CI = 19.8-36.6) while Ne for Endau River populations was not due to stuttering or large allele was 21.4 (95% CI = 16.2-28.5). drop out. Null alleles were detected at loci D11 and K37 in the Tasik Bera and Endau River populations. Discussion The frequencies of null alleles were 0.33 for D11, 0.17 for K37 in the Tasik Bera population and 0.32 Our microsatellite data suggest the genetic for D11, 0.09 for K37 in the Endau River population. variation within and between the two populations was After adjusting allele frequencies for the null alleles, low. Previous genetic work on the arowana indicated these two loci were still deviated from HWE. higher genetic variability [34-36]. The discrepancy The Endau River has experienced significant between our results and these earlier studies may be heterozygosity excess (p< 0.05) (Table 4) but not the explained by the unequal representation of Tasik Bera population. The allelic distribution shows populations in different geographical regions and time a significant ‘mode-shift’ (lack of low frequency frame. The stock in previous studies was either alleles) in the former population while the latter pooled from numerous farms or established from showed normal L-shaped distribution (Fig. 4). Using wild stock collected in the early 1980s [34,35]. This allele frequencies adjusted for null alleles, both of might not represent the recent natural populations. the populations exhibited significant heterozygosity The deviation from Hardy Weinberg observed in excess (p< 0.05) and L-shape in the distribution of the present study might result from the territorial allele frequencies (results not presented). behavior of arowana. The entire population may be Among 1041 bp of ND2 gene sequenced, 9 sites divided into several subpopulations and only matings were variable. Five unique haplotypes were detected between related individuals is likely to happen. The

(Fig. 5). Of these, 2 unique haplotyes were found in presence of positive FIS values showed further Tasik Bera whereas 3 were found in Endau River. evidence of inbreeding. Although null allele For cytb, 4 variable sites were detected out of 628 frequencies were taken into consideration, the results aligned nucleotides (Fig. 6). Of 72 aligned tRNA-Thr did not change. Thus, null alleles seemed unlikely to

nucleotides, 2 were variables (Fig. 7). Haplotype cause the positive FIS values. The observation of diversity was 1.000 for both populations and deviation from HWE might result from sampling nucleotide diversity was low, 0.004 for Tasik Bera error. Adult male arowana are territorial mouth and 0.006 for Endau River (Table 5). brooder and frys can be found near the adults. So, collections in the same location might be composed Population Differentiation of siblings produced by a relatively few adults. This could prevent the detection of high genetic variation.

FST of Tasik Bera and Endau River (0.020) was Both Tasik Bera snd Endau River exhibited significantly different from zero (p<0.05). This heterozygote excess, suggesting that these two showed that there was pronounced genetic populations have experienced a reduction in effective differentiation between these two populations. population size (Ne). This is because allelic richness Significant (p<0.05) pairwise RST value of 0.021 is lost faster than heterozygosity after a population were observed between these two populations. After reduction. Both populations showed L-shaped adjusting the allele frequencies for null alleles, the distribution of allele frequencies. Thus these two

FST and RST values were still significantly (p<0.05) populations have not experienced bottleneck yet differentiated between the two populations. Both of because the low frequency alleles are still conserved. Adv. Environ. Biol., 4(1): 14-23, 2010 20

Fig 4: Allele Frequency Distributions from Two Populations of Arowana (Tb; Tasik Bera and Er; Endau River).

Fig. 5: Variable sites of the ND2 gene. Dots indicate identity to the sequences of TB19. TB03-10, TB19 and TB79 indicate Tasek Bera Individuals green variety); ER04-05, 06, 16 and 17 indicates Endau River Individuals (green variety).

Table 5: MtDNA sequence variable for green arowana from Tasik Bera and Endau River: number of individuals (n), number of haplotypes (nh), haplotype diversity (h) and nucleotide diversity (π). nnhhπ Tasik Bera 10 10 1.000 0.004 Endau River 5 5 1.000 0.006

Table 6: Amova table of genetic variation of green arowana form Tasik Bera and Endau River. Source of variation d.f. Sum of square Variance components % of total variance Among populations 1 3.267 -0.154 -3.72 Within populations 13 55.800 4.292 103.72 Total 14 59.067 4.138

Fixation index ФST= -0.037 Adv. Environ. Biol., 4(1): 14-23, 2010 21

Fig. 6: Variable sites for cyt-b gene. Dots indicate identity to the sequences of TB19. TB03-10, TB19 and TB79 indicate Tasek Bera Individuals (green variety); ER04-05, 06, 16 and 17 indicates Endau River Individuals; (green variety).

Fig. 7: Variable sites for tRNA-Thr gene. Dots indicate identity to the sequences of TB19. TB03-10, TB19 and TB79 indicate Tasek Bera Individuals (green variety); ER04-05, 06, 16 and 17 indicates Endau River Individuals; (green variety). Adv. Environ. Biol., 4(1): 14-23, 2010 22

Mitochondrial markers which have a 4-fold 5. Cornuet, J.M. and G. Luikart, 1996. Description smaller effective population size than nuclear markers and power analysis of two tests for detecting are expected to lose variation faster due to genetic recent population bottlenecks from allele drift [32]. Surprisingly, in the present study, frequency data. Genetics, 144: 2001-2014. mitochondrial gene diversity (h) was high. The 6. Cramphorn, J., 1983. Sungai Trengganu fish

significantly negative Fu’s Fs in Tasik Bera indicated survey, 1980. Malayan Naturalist, 3: 16-20. this population has undergone historical expansion 7. Dawes, J., L.C. Lim and L. Cheong, 1999. The and this might be the cause of the high mitochondrial Dragon Fish. Kingdom Books, England. gene diversity. However, this expansion was followed 8. Elliott, N.G. and A. Reily, 2003. Likelihood of by a more recent population decline. The historical bottleneck event in the history of the Australian and contemporary Ne of both Tasik Bera and Endau population of Atlantic salmon (Slamo salar L.). River based on microsatellite data suggest that the Aquiculture, 215: 31-44. size of the arowana populations reduced drastically. 9. Excoffier, L., P.E. Smouse and J.M. Quattro, Genetic differentiation based on microsatellite and 1992. Analysis of molecular variance inferred mtDNA data between the arowana from Tasik Beara from metric distances among DNA haplotypes: and Endau River was low. This observation may be application of human mitochondrial DNA result from changes of land mass configurations due restriction data. Genetics, 131: 479-491. to glaciation and deglaciation and the accompanying 10. Fernando, A.A., 1997. DNA fingerprinting: lowering and rising of sea levels during the late application to conservation of the CITES-listed Pleistocene. During glacial maxima (17, 000 years dragon fish, Scleropages formosus before present), extensive land bridges connected (Osteoglossidae). Aquarium Sci. Conserv., 1: 91- Peninsular Malaysia, the Indonesian island and 104. mainland Asia to form a huge continental shelf called 11. Fu, Y.X., 1997. Statistical tests of neutrality of Sundaland. The Endau, Pahang, Trengganu and mutations against population growth, hitchhiking Rivers of Peninsular Malaysia joined and background selection. Genetics, 147: 915- Thailand’s Chao Phraya River to form the Siam 925. River System. The Pahang and Endau River 12. Hill, W.G., 1981. Estimation of effective disconnected 13, 000 yr BP when sea level rose to population size from data on linkage 75 m below present level. disequilibrium. Genet. Res., 38: 209-216. Acknowledgments 13. Khan, M.S., P.K.Y. Lee, J. Cramphorn and M. Zakaria-Ismail, 1996. Freshwater of the The research was partly funded by a research Pahang River Basin. International-Asia grant from the Ministry of Science, Technology and Pacific, Malaysia, Kuala Lumpur. Innovation (05-01-03-SF0172) and University’s short- 14. Kumazawa, Y., M. Yamaguichi and M. Nishida, term research grants 0139/2002A, 0142/2003A and 1999. Mtochondrial molecular clocks and the 0131/2004A. The authors wish to express sincere region of euteleostean biodiversity: familial thank to the Government of Malaysia for granting the radiation of perciforms may have predated the sponsorship through the Malaysian Technical Co- Cretaceous/ tertiary boundaary. Pages 35-52 in operation Programme (MTCP) for the study. M. Kato, editor. The biology of biodiversity, Springer- Verlag, Tokyo. References 15. Luikart, G. and J.M. Cornuet, 1998. Empirical evaluation of a test for identifying recently 1. Alfred, E.R., 1964. The fresh-water food fishes bottlenecked populations from allele frequency of Malaya. I. Scleropages formosus (Müller and data. Conserv. Biol., 12: 228-237. Schlegel). Fed. Mus. J., 9: 80-83. 16. McCarthy, C., 1997. Chromas v1.4 computer 2. Alfred, E.R., 1969. Conserving Malayan fresh- package. Griffith University, Australia. water fishes. Malay. Nat. J., 22: 69-74. 17. Nei, M., 1987. Molecular evolutionary genetics. 3. Asahida, T., T. Kobayashi, K. Saitoh and I. Columbia University Press, New York. Nakayama, 1996. Tissue preservation and total 18. Nei, M. and F. Tajima, 1981. DNA DNA extraction from fish at ambient temperature polymorphism detectable by restriction using buffers containing high concentration of endonucleases. Genetics, 97: 145-163. urea. Fisheries Science, 62: 727-730. 19. Ng, H.H. and H.H. Tan, 1999. The fishes of the 4. Cabot, E.L. and A.T. Beckebach, 1989. Endau Drainage, Peninsular Malaysia with Simultaneous editing of multiple nucleic acid description of two new species of catfishes and protein sequences with ESEE. Comput. (Teleostei: Akysidae, Bagridae). Zool. Stu., 38: Appl. Biosci., 5: 233-234. 350-366. Adv. Environ. Biol., 4(1): 14-23, 2010 23

20. Peel, D., J.R. Ovenden and S.L. Peel, 2004. Ne 29. Van Oosterhout, C., W.F. Hutchinson, D.P.M. Estimator: software for estimating effective Wills and P. Shipley, 2004. Micro-checker: population size, Version 1.3. Queensland Software for identifying and correcting Government, Department of Primary Industries genotyping errors in microsatellite data. Mol. and Fisheries. Ecol. Notes, 4: 535-538. 21. Pouyaud, L., G.G. Sudarto, G.G. Teugels, 2003. The different colour varieties of the Asia 30. Was, A. and R. Wenne, 2002. Genetic arowana Scleropages formosus (Osteoglossidae) differentiation in hatchery and wild sea trout are distinct species: morphology and genetic (Slamo trutta) in the Southern Baltic at evidences. Cybium, 27: 287-305. microsatellite loci. Aquaculture, 204: 493-506. 22. Raymond, M. and F. Rousset, 1995. GENEPOP 31. Weir, B.S. and C.C. Cockerham, 1984. (v 3. 1c): A population genetics software for Estimating F-statistics for the analysis of exact tests and ecumenicism. J. Hered., 86: 248- population structure. , 38: 1358-1370. 249. 32. Wilson, A.C., R.L. Cann, S.M. Carr, M. George, 23. Schneider, S., J.M. Kueffer, D. Roessli and L. U.B. Gyllensten, K.M. Helm-Bychowski, R.G. Excoffier, 2001. ARLEQUIN (version 2.000) - A Software for Population Genetic Data Analysis. Higuchi, S.R. Palumbi, E.M., Prager, R.D. Sage, Genetics and Biometry Laboratory, University of and M. Stoneking, 1985. Mitochondrial DNA Geneva, Switzerland. and two perspectives on evolutionary genetics. 24. Sekino, M., M. Hara and N. Taniguchi, 2002. Biol. L. Linn. Soc., 26: 375-400. Loss of microsatellite and mitochondrial DNA 33. Ismail, M.Z., 1989. Systematics, Zoogeography, variation in hatchery strains of Japanese flounder and Conservation of the Freshwater Fishes of Paralichthys olivaceus. Aquaculture, 213: 101- Peninsular Malaysia. Unpublished Ph. D. 122. Dissertation, Colorado State University, USA. 25. Sim, C.H., 2002. A Field Guide to the Fish of 34. Yue, G.H., F. Chen and L. Orban, 2000. Rapid Tasek Bera Ramsar site, Pahang, Malaysia. Kuala Lumpur: Wetland International-Malaysia isolation and characterization of microsatellites Programme. from the genome of Asian arowana (Scleropages 26. Slatkin, M., 1995. A measure of population formosus, Osteoglossidae, Pisces). Mol. Ecol., 9: subdivision based on microsatellite allele 993-1011. frequencies. Genetics, 139: 457-492. 35. Yue, G.H., Y. Li, F. Chen, S. Cho and L. 27. Tamura, T. and M. Nei, 1993. Estimation of the Orban, 2002. Comparision of three DNA marker number of nucleotide substitutions in the control systems for assessing genetic diversity in asian region of mitochondrial DNA in humans and arowana (Scleropages formosus). Electrophoresis, chimpanzees. Mol. Biol. Evol., 10: 512-526. 23: 1025-1032. 28. Tang, P.Y., J. Sivananthan, S.O. Pillay and S. Muniandy, 2004. Genetic structure and 36. Yue, G.H., Y. Li, L.C. Lim and L. Orban, 2004. biogeography of Asian arowana (Scleropages Monitoring the genetic diversity of three Asian formosus) determined by microsatellite and arowana (Scleropages formosus) captive stocks mitochondrial DNA analysis. Asian Fish. Sci., using AFLP and microsatellites. Aquaculture, 17: 81-92. 237: 89-102.