Mitochondrial Markers Identify a Genetic Boundary of the Green Tiger Prawn (Penaeus semisulcatus) in the Indo-Pacific Ocean

© 2021 Academia Sinica, Taiwan Open Access Mitochondrial Markers Identify a Genetic Boundary of the Green Tiger Prawn (Penaeus semisulcatus) in the Indo-Pacific Ocean Siti Amalia Aisyah Abdul Halim1,*, Ahmad Sofiman Othman1, Noor Adelyna Mohammed Akib2, Noorul-Azliana Jamaludin3, Yuzine Esa4,5 , and Siti Azizah Mohd Nor1,6 1School of Biological Sciences, Universiti Sains Malaysia, 11800 Minden, Pulau Pinang, Malaysia. *Correspondence: E-mail: [email protected] (Halim). Tel: +60142214807 E-mail: [email protected] (Othman) 2Centre for Global Sustainability Studies, Universiti Sains Malaysia, Penang, Malaysia. E-mail: [email protected] (Akib) 3Marine Capture Fisheries Division, FRI Kampung Acheh, 32000 Sitiawan, Perak, Malaysia. E-mail: [email protected] (Jamaludin) 4Department of Aquaculture, Faculty of Agriculture, Universiti Putra Malaysia, 43400 Universiti Putra Malaysia, Serdang, Selangor, Malaysia. E-mail: [email protected] (Esa) 5International Institute of Aquaculture and Aquatic Sciences, Universiti Putra Malaysia, Port Dickson, Negeri Sembilan, Malaysia 6Institute of Marine Biotechnology, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu, Malaysia. E-mail: [email protected] (Nor) Received 25 September 2020 / Accepted 31 December 2020 / Published 18 March 2021 Communicated by Ka Hou Chu A population genetics study of the commercially important Green Tiger Prawn (Penaeus semisulcatus) was conducted in the Indo-Pacific Ocean with a focus on the Indo-Malay Archipelago waters of the South China Sea (SCS), Sulu Sea (SLS), Celebes Sea (CLS) and the Strait of Malacca (SOM), the latter being the main waterway that connects the Indian Ocean with the Pacific Ocean. A 548-base-pair region of mitochondrial COI and 571 base pairs of the control region (CR) were analysed in 284 specimens from 15 locations. Genetic divergences (Tamura 3-parameter) for COI ranged from 0.1% to 7.2% and CR 2.3% to 21.7%, with Bagan Pasir (BGP) in central SOM being the most genetically different from other populations (COI: 3.3–4.2%; CR: 7.1–16.5%). All populations were differentiated into two lineages with a genetic break in the vicinity of BGP; Lineage I comprised populations south of this site (SCS, SLS, CLS and part of SOM) and Lineage II comprised populations north of BGP (part of the SOM). Specifically, most individuals of Bagan Pasir (BGP) and another site just south of it, Batu Pahat (BPT), clustered in Lineage I, while all SOM populations to the north of these sites clustered in Lineage II. The BGP population is believed to be a mixed gene pool between the two lineages. The results could be attributed to the fluctuations of Pleistocene sea levels and a possible influence of the One Fathom Bank in SOM. High genetic diversity was recorded, π (Lineage I: COI: 3.4%; CR: 7.4%) (Lineage II: COI: 3.8%; CR: 12.6%) and, h (Lineage I: COI: 0.81; CR: 1.0) (Lineage II: COI: 0.57; CR: 0.99). Demographic statistics revealed that both lineages underwent a sudden expansion and consequent stabilisation in genetic variability. The findings of this study have wide implications for fisheries in the Indo-Pacific. The increased sampling effort within a narrower geographical scale by the current study permitted a precise locality of the genetic break for this species within the Indo-Pacific Ocean to be identified. The substantial genetic diversity within both lineages should be considered in fishery management and aquaculture development programs of this species in this region. Key words: Penaeus semisulcatus, Cytochrome oxidase subunit I (COI), Control region (CR), Population genetics, Indo-Pacific. Citation: Abdul Halim SAA, Othman AS, Akib NAM, Jamaludin NA, Esa Y, Nor SAM. 2021. Mitochondrial markers identify a genetic boundary of the Green Tiger Prawn (Penaeus semisulcatus) in the Indo-Pacific Ocean. Zool Stud 60:8. doi:10.6620/ZS.2021.60-08. Zoological Studies 60: 8 (2021) doi:10.6620/ZS.2021.60-08 1 © 2021 Academia Sinica, Taiwan BACKGROUND Knowledge of the population genetics of a species—including its distribution and changes in genotype and phenotype frequencies and the underlying causes—provide information that can answer various biological questions. Understanding population genetic diversity and structure is essential for the management and conservation of genetic resources in marine organisms and for productive fisheries conservation and sustainable population harvesting (Park and Moran 1994; Hillis et al. 1996; Thorrold et al. 2002; Xiao et al. 2012; Cui et al. 2018). Such population genetic data can contribute additional information for taxonomic and evolutionary historical analyses (Benzie et al. 1995; Uthicke and Benzie 2003; Cheng et al. 2018), as well as information on demographic history, such as effective population size (Fu 1997) and changes in population size (Rogers and Harpending 1992), critical for fisheries and aquaculture management, particularly of ecologically and commercially important groups such as the penaeids. Identification of reproductively isolated and genetically differentiated populations of existing resources within an exploited species is critical for planning conservation strategies (Brooker 2009; Schröder and Walsh 2010). Due to their ecological and economic importance, the family Penaeidae has been the subject of considerable biological and genetic research. Dall et al. (1990) hypothesised that the genus Penaeus within family Penaidae, which is comprised of some of the most economically important species, arose in the Indo-Pacific based on the principle that biogeographic centres of origin have the highest species diversity and the deepest morphological differentiation (Briggs 1999). This was supported by the study of Baldwin et al. (1998), which showed that the highest mtDNA diversity and deepest mtDNA lineages for Penaeus are found in this region, based on 14 species. They further postulated that the genus Penaeus radiated westward into the eastern Atlantic and eastward into the eastern Pacific/western Atlantic. This bidirectional migration theory has received considerable support. Phylogenetic studies of P. kerathurus (eastern Atlantic) (Lavery et al. 2004) and P. japonicus (Indo-Pacific) (Tzong et al. 2004; Tsoi 2006; Shih et al. 2011) corroborated the hypothesis of the westward movement from the Indian Ocean into the eastern Atlantic. Similarly, several studies have documented a close relationship between the P. monodon lineages of the eastern Pacific/western Atlantic and the Indo-Pacific region, indicating the eastward radiation across the Pacific (Benzie et al. 2002; You et al. 2008; Waqairatu et al. 2012; Munasinghe 2014; Abdul‐Aziz et al. 2015). The green tiger prawn or grooved tiger prawn, Penaeus semisulcatus De Haan, 1844, is one of the commercially important species in the family Penaeidae. It is widely distributed in the Indo-West Pacific from the Red Sea, east and southeast Africa to Japan, Korea, the Malay Archipelago and northern Australia (Holthius 1980; Dall et al. 1990; Chan 1998). The species is widely distributed in the seas of the Indo-Malay Archipelago (IMA); Strait of Malacca, (the main channel connecting the Indian Ocean with the Pacific Ocean), South China Sea, Celebes Sea and Sulu Sea, the latter three are within the Pacific Ocean. A number of population genetic investigations of penaeids prawn in the Indo-Pacific region have been done—e.g., for the tiger prawn, P. monodon (Duda and Palumbi 1999; Benzie et al. 2002; You et al. 2008; Waqairatu et al. 2012; Abdul‐Aziz et al. 2015); kuruma prawn, P. japonicus (Tzong et al. 2004; Tsoi et al. 2007); brown tiger prawn, P. esculentus (Ward et al. 2006); banana prawn, P. merguiensis (Hualkasin et al. 2003; Wanna et al. 2004); and Indian prawn, P. indicus (De Croos and Pálsson 2010; Alam et al. 2015); these have displayed strong phylogeographic structuring among populations in the Indo-West Pacific region that have revealed a clear distinction between populations in the Indian Ocean and Pacific Ocean. This suggests that a similar pattern of population structuring may also occur in the widespread P. semisulcatus species. However, population genetics studies of the Penaeus are limited, particularly in the region. Most penaeid studies in the region have focused on the giant tiger prawn, P. monodon, and banana prawn, P. merguiensis (Daud 1995; Aziz 2011; Aziz et al. 2011; Nahavandi et al. 2011a b). Indeed, broad-scale phylogeographic division of this species between the Indian Ocean and Pacific Ocean has also been shown, but the genetic boundary remains obscure, primarily due to the lack of detailed coverage of the connecting populations between the two oceans (Alam et al. 2016). Thus, the aim of this study was to identify the potential location of this genetic break in the IndoPacific Ocean, based on the mitochondrial cytochrome c oxidase I (COI) and control region (CR) genes, on a narrower geographical scale in the IMA. The COI gene (Folmer et al. 1994) is widely used because it is robust, is efficiently amplified using a universal primer, and has been successfully applied to reconstruct phylogenetic relationships among several Penaeus species, including the Indian white prawn, P. indicus (De Croos and Pálsson 2010; Alam et al. 2015); banana prawn, P. merguiensis (Hualkasin et al. 2003); kuruma prawn, P. japonicus (Tsoi 2006); and Chinese white prawn, P. chinensis (Li et al. 2009). The mitochondrial control region (CR) or D-loop is a non-coding protein and page 2 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan commonly used for population studies due to its highly variable and rapid evolution (Upholt and Dawid 1977; Walberg and Clayton 1981; Chu et al. 2003). This gene has also found applicability when elucidating population variability and relationships in several Penaeus species: giant tiger prawn, P. monodon (Zhou et al. 2009; Alam et al. 2016); kuruma prawn, P. japonicus (Tsoi 2006; Tsoi et al. 2007); Chinese white prawn, Penaeus chinensis (Cui et al. 2007; Xiao et al. 2010); and pink prawn, Penaeus duorarum (McMillen-Jackson and Bert 2004b). Although several population genetic studies have been reported on P. semisulcatus based on mitochondrial DNA and nuclear markers (Munasinghe and Senevirathna 2015; Alam et al. 2017; Jahromi et al. 2019), none have been within the IMA waters. Thus, the present study aimed to characterize the genetic diversity and population structure of P. semisulcatus populations within the IMA (Strait of Malacca, South China Sea, Sulu Sea and Celebes Sea) inferred from mtDNA COI and control region (CR) genes. This represents the first detailed population genetics study of the green tiger prawn, P. semisulcatus, in IMA waters. The combined application of the COI (DNA barcoding) gene and control region could provide useful insights into potential cryptic diversity and population structuring. MATERIALS AND METHODS Sample collection and species identification Specimens of P. semisulcatus were collected from landing sites of 15 locations in the IMA, focusing on the Strait of Malacca, South China Sea, Celebes Sea and Sulu Sea in 2016 and early 2017 (Table 1 and Fig. 1). The prawn specimens were identified through assistance of a taxonomist and were identified using the following references; A guide to the Australian penaeid prawns (Grey et al. 1983), A guide to penaeid shrimps found in Thai waters (Chaitiamvong and Supongpan 1992) and FAO Species Identification Guide for Fishery Purposes (Chan 1998). All specimens were immediately iced or frozen after collection and later stored at -20°C or preserved in 99% ethanol until DNA extraction. DNA Extraction and PCR Amplification Total DNA were extracted from the pleopod tissue of the preserved samples based on the 2xCTAB method (Doyle 1991). The COI and CR gene fragments were amplified using a penaeid-specific primer COIf (5'- TAA CCT GCA GGA GGA GGA GAY CC-3') (Palumbi and Benzie 1991) and COI-P4 (5'-AGG AAA TGT TGA GGG AAG AAA GTA A-3) (Tong et al. 2000) for COI gene and 12S (5'-AAG AAC CAG CTA GGA TAA AAC TTT-3') and PCR-1R (5'-GAT CAA AGA ACA TTC TTT AAC TAC-3') (Chu et al. 2003) for the control region. The PCR amplifications for each of the two gene fragments were performed in a reaction mixture containing 1.5 μL DNA template, 0.5 μL of each primer, 2.5 μL of 10x i-TaqTM plus PCR Buffer, 2.0 of 25 mM MgCl2, 1.0 μL of dNTP, 0.25 μL of i-TaqTM plus DNA Polymerase and 16.75 μL of distilled water (ddH2O), adding up to 25 µL. The PCR cycling conditions for COI and CR was conducted according to the following thermal cycling profile: 4 min at 94°C, 35 cycles of 30 s at 94°C for denaturation, 50 s at 50°C (COI) and 48.8°C (CR) for annealing and 1 min at 72°C for extension followed by a final step of 7 min at 72°C for the complete fragment extension. The PCR products were sent to the service provider, First BASE Laboratories Sdn. Bhd., for sequencing in both the forward and reverse directions with an automated sequencer (ABI3730XL, Applied Biosystems USA). Data Analysis Nucleotide alignment Both forward and reverse COI and CR sequences were aligned using ClustalW in MEGA 7 (Nei and Kumar, 2000; Kumar et al. 2016). The aligned sequences for COI were translated into proteins to ensure accurate alignment and to detect stop codons, if present. The haplotype distribution for sampled data was summarized using DnaSP 5.10 (Librado and Rozas 2009). Sequence data for both genes were analysed based on the Maximum Likelihood (ML) method in MEGA 7 (Kumar et al. 2016) to produce phylogenetic trees with a confidence level of 1000 bootstrap replicates. Prior to this, the Model Test was conducted to determine the best model for tree construction using MEGA 7 (Kumar et al. 2016). The Bayesian Information Criterion method was run to construct a Bayesian Inference tree phylogeny with the Markov Chain Monte Carlo (MCMC) algorithm (Ronquist et al. 2012). PartitionFinder2 (Lanfear et al. 2017) was used to determine the best-fit partitioning schemes and models of molecular evolution for phylogenetic analysis. The Bayesian Inference (BI) tree was run in MrBayes 3.2.6 (Ronquist et al. 2012) on CIPRES Science Gateway (Miller et al. 2010) together with gene partitions, 1 million MCMC chains and 50% burn in. The output files generated from the analyses were examined in Tracer v.1.6 (Rambaut et al. 2014) to assess the MCMC chain. The generated tree was displayed in FigTree v.1.4.3 (Rambaut 2016) and the complete page 3 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan Fig. 1. Sampling locations of fifteen Penaeus semisulcatus populations amplified for mtDNA COI and control region gene analysed in the present study. N Table 1. Sampling location, sample size and number of haplotypes of 15 Penaeus semisulcatus populations based on mtDNA COI and CR No Population Abbreviation N No. of haplotypes COI CR COI CR Group 1: Straits of Malacca (SOM), West Coast of Peninsular Malaysia 1. Kuala Perlis KPE 18 17 3 16 2. Kuala Kedah KKE 19 19 7 16 3. Kuala Muda KMU 19 17 10 17 4. Batu Maung BMA 18 14 5 14 5. Bagan Panchor BPA 15 15 8 14 6. Bagan Pasir BGP 23 20 11 20 7. Batu Pahat BPT 23 20 7 20 Group 2: South China Sea (SCS), East Coast of Peninsular Malaysia and Sabah and Sarawak, Malaysian Borneo 8. Tumpat TPT 20 19 13 18 9. Pulau Kambing PKA 19 16 13 16 10. Endau END 20 17 13 17 11. Tanjung Sedili TSE 20 20 10 20 12. Santubong SAN 11 11 511 13. Kota Kinabalu KKI 20 20 11 20 Group 3: Sulu Sea (SLS), Sabah, Malaysian Borneo 14. Sandakan SDK 19 18 11 18 Group 4: Celebes Sea (CLS), Sabah, Malaysian Borneo 15. Tawau TWU 20 20 12 20 TOTAL 284 263 90 246 page 4 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan mitochondrial sequence of the giant tiger prawn, P. monodon (AF217843), sequence was selected from GenBank as an outgroup to root the phylogenetic trees. In addition, the Minimum Spanning Network (MSN) version 5.0.0.3 (Polzin and Daneshmand 2018) was used to display the haplotype relationships based on median joining or MJ network algorithm (Bandelt et al. 1999) together with reduction options. Genetic diversity and Demographic history The genetic diversity of these populations were examined using two estimators: haplotype diversity (Hd) and nucleotide diversity (p) in Arlequin 3.1 (Excoffier et al. 2005). Tajima’s D (Tajima 1989) and Fu’s Fs (Fu 1997) analyses were examined to evaluate the deviation from neutrality of the observed variation in the same software. Mismatch distribution analysis and goodness of fit assessed by the Harpending’s raggedness index, Hri (Harpending 1994), were performed to evaluate demographic patterns in the major regional groups as identified by the median joining network and phylogenetic trees using DnaSP 5.10 (Librado and Rozas 2009). A non-significant result of Hri index analysis indicates an expanding population (Harpending 1994). Population structure analysis Analysis of Molecular Variance (AMOVA) was conducted to evaluate the genetic variation at different hierarchical levels using Arlequin 3.1 (Excoffier et al. 2005). Isolation by Distance (IBD) analysis (Mantel Test) was also tested to assess any significance in isolation by distance relationships (Bohonak 2002) using the same software. To determine groups of populations that are geographically homogenous and maximally differentiated from each other, and the genetic barriers between these groups a Spatial Analysis of Molecular Variance (SAMOVA) was performed in SAMOVA 2.0 (Dupanloup et al. 2002). The optimal number of groups, k (with maximum was k = 12), was chosen based on the number that has the highest among group (FCT) variance. Significant values were adjusted for family-wise error rate using the False Discovery Rate Procedure at α = 0.05 (Verhoeven et al. 2005). RESULTS A total of 284 individuals for COI and 263 individuals for CR specimens from 15 localities were successfully amplified. Sample size per site ranged from 11 to 23, with an average of 19 individuals per population available for further genetic analysis (Table 1). Nucleotide composition The sequence analysis for COI generated a 548-base-pair region from the 284 specimens with 89 variable sites—58 parsimony informative and 31 singleton—generating 90 haplotypes (Table 1). The average nucleotide composition for the COI gene was A: 27.7%, T: 37%, G: 17.4%, C: 17.9%. Sequence analyses for CR generated a 571 base pair region from the 263 specimens with 252 variable sites, 194 parsimony informative and 58 singleton sites, generating 247 haplotypes. The average nucleotide composition was, A: 41.7%, T: 41.6%, G: 7.7%, C: 9%. Most unique sequences have been deposited in GenBank with accession numbers for COI (MG020144–MG214725) and CR (MG214707–MG544283). Haplotype distribution Haplotypes 1 (22.9%) and 27 (27.8%) were the most dominant for the COI gene. Haplotype 1 was represented by all populations from the Strait of Malacca (SOM) except for BPT (southern SOM), and a few specimens from BGP. Haplotype 27 represented specimens from the South China Sea (SCS), Sulu Sea (SLS) and Celebes Sea (CLS), and included the SOM population of BPT and several individuals of BGP (SOM). Sixty-three haplotypes were private or population-specific, while the other 27 haplotypes were shared by more than one population. However, in CR gene, apart from a few exceptions, each of the 247 mtCR haplotype generated was restricted to only a single population with none being dominant. Of these 247 haplotypes, only seven are shared between two or more populations, which were mainly limited to the coast of the Straits of Malacca. Phylogenetic relationships among haplotypes The best-fit Model Selection for ML for both genes was Tamura 3-parameter (T92+G) with a discrete gamma distribution. Two lineages were generated, Lineage I and Lineage II, in both COI (Fig. 2A) and CR (Fig. 2B) (only selected representative haplotypes are shown) genes with high support (BP > 92%). Lineage I is composed of the SCS, SLS and CLS populations and the unexpected inclusion of BPT (southern SOM) and most of the BGP specimens (central SOM). Lineage II is composed of all SOM populations to the north of BGP and the rest of the BGP specimens (of SOM) that were not clustered in Lineage I. page 5 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan Fig. 2. (A) Maximum Likelihood tree of P. semisulcatus rooted with P. monodon (AF217843) from GenBank and Bayesian Inference (BI) analyses of mtDNA COI gene. (B) Maximum Likelihood tree of P. semisulcatus rooted with P. monodon (AF217843) from GenBank and Bayesian Inference (BI) analyses of mtDNA CR gene. The bootstrap support and posterior probability values are presented at the nodes. Population abbreviations are as defined in table 1. H ap89 H ap143 H ap127 H ap185 H ap120 H ap142 H ap106 H ap75 H ap193 H ap72 H ap109 H ap164 H ap99 H ap226 H ap234 H ap210 H ap157 H ap247 H ap201 H ap215 H ap82 H ap177 Hap46 Hap58 Hap22 Hap10 Hap80 Hap14 Hap45 Hap68 Hap36 Hap76 Hap28 Hap57 Hap18 Hap31 Hap86 Hap01 Hap13 Penaeus monodon (AF217843) 0.5 99/0.98 99/1.0 (BPT) (END) (PKA) (SAN) (TPT) (PKA) (BPT) (BGP) (KKI) (BGP) (TPT) (TSE) (BPT) (SDK) (TWU) (KKI,TWU) (END) (TWU) (BGP) (TSE) (BGP) (KMU) (SDK) (KKI) (BPA) (KPE,KKE,KMU) (BGP) (KKE,BPA) (KKE) (BPA) (BMA) (KMU) (KPE,KMU) (KPE) (BGP) (KMU) (KKE,BMA) (BMA) (KKE,BPA) Lineage I Lineage II Lineage I Lineage II H ap25-H ap90 (BGP,BPT,TPT,PKA,END, TSE,SAN,KKI,SDK,TWU) Hap01-Hap29 (KPE,KKE,KMU,BMA,BPA,BGP) (PKA) (BPA) (KMU) (A) (B) page 6 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan The minimum spanning network (MSN) generated two discrete groups (Lineage I and Lineage II) (Fig. 3) for COI and CR haplotypes (only representative haplotypes are shown) (Fig. 4), with a reticulate pattern within each lineage in the latter, concordant with the phylogenetic tree analysis. The data shows the genetic isolation of the SOM populations from SCS, SLS and CLS populations with two distinct exceptions as in the earlier analyses, supporting a strong population structure of this species, except for the admixed gene pool at BGP. Genetic diversity within and among populations Based on COI, BGP had the highest withinpopulation genetic diversity (4%), while KPE had the lowest (0.1%). Between-population genetic diversity ranged from 0.1% to 7.2% (Table 2). The BGP population of SOM was genetically differentiated from the northern populations (KPE, KKE, KMU, BMA and BPA) of SOM at a mean of 4%, while its genetic distance from the eastern seas of SCS, SLS and CLS populations was 3%. The BPT population of SOM was most genetically distant from the northern SOM populations, with an average of 7%. However, the BPT population was genetically similar to the SCS, SLS and CLS populations, with an average of 0.3%. As in COI, a parallel trend was observed in CR (Table 2), although with higher absolute values. Withinpopulation genetic diversity ranged from 2.3% to 9.7, while between-population diversity ranged from 2.3% to 21.7%. The BGP population of SOM was the highly differentiated from the northern SOM populations (KPE, KKE, KMU, BMA and BPA) at an average distance of 16%, while its distance from the eastern seas of SCS, SLS and CLS populations was only 7%. The BPT population was even more genetically distant from the northern populations of SOM, at a mean of 21%, while it was genetically similar to SCS, SLS and CLS populations at a mean of 3%. Thus, in summary, the genetic diversity between the SCS, SLS and CLS populations (Lineage I) and the northern SOM Fig. 3. Median joining-network of mtDNA COI haplotypes in Penaeus semisulcatus. The sizes of the circles are proportional to haplotype frequencies, colour coded corresponding to locations and black squares on the lines linking haplotypes represent the number of mutations. page 7 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan populations (Lineage II) were high for both genes; COI (7%) and CR (21%). However, the two more southern populations of SOM—BGP and BPT—were more genetically close to SCS, SLS and CLS. As derived from COI gene, the within population haplotype diversities were high for most populations (h: 0.307–0.911), except for KPE, KKE and BMA (all in SOM) at (h < 0.5) (Table 3). The nucleotide diversity was moderate, at 0.4% to 2.7%, except in the BGP population, with very high value of (p: 22%). Based on the lineages, the combined populations had high haplotype and nucleotide diversities ranging from (h: 0.567–0.813) and (p: 3.4%–3.8%), respectively. On the other hand, based on the CR gene, the haplotype and nucleotide diversities were high: (h: 0.965–1.000) and (p: 2%–8%), respectively. Based on lineages, haplotype and nucleotide diversities were also very high ranging from (h: 0.993–1) and (p: 7.4– 12.6%), respectively. Thus, according to the four basic classifications of demographic history by Grant and Bowen (1998), both Lineages I and II in general fall into category 4, with high haplotype (h > 0.5) and nucleotide (p > 0.5%) diversities, indicating a long evolutionary history in a large stable population or high level of divergence among haplotypes that may be attributed to secondary contact between differentiated lineages. Historical demographic pattern Tajima’s D and Fu’s Fs revealed negatively significant deviations from the mutation drift equilibrium in Lineage I and Lineage II (except the Tajima’s D for CR in Lineage II), thus making it consistent with the molecular response to population expansion (Table 3 and Fig. 5). Overall, most of the sites fit a sudden population expansion model, with negatively significant Fu’s Fs and Tajima’s D for COI. However, the Tajima’s D for CR was not significant, which is not consistent with Fu’s Fs. The discrepancy between Tajima’s D and Fu’s Fs is likely due to the superiority of Fu’s Fs over Tajima’s D in detecting significant changes in population (Fu 1997). A unimodal peak and non-significant Harpending’s raggedness index were observed in both lineages (Fig. 5), which strengthen the evidence that both lineages underwent sudden expansion. Fig. 4. Median joining-network of mtDNA CR haplotypes in Penaeus semisulcatus. The sizes of the circles are proportional to haplotype frequencies, colour coded corresponding to locations and black squares on the lines linking haplotypes represent the number of mutations. page 8 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan Population genetic structure In agreement with the earlier analyses, the SCS, SLS and CLS populations (Lineage I) were found to be genetically distinct from the SOM populations (Lineage II), except for the BGP and BPT populations (COI: FST = 0.912–0.984, CR: FST = 0.816–0.846, p < 0.05) (Table 4). The majority of non-significant values after FDR corrections were confined to within individual seas. Mantel tests indicated statistically non-significant correlation between genetic differentiation (FST) and geographical distance among populations within both lineages, for both genes: Lineage I (COI: r = 0.051, P = 0.585; CR: r = 0.227, P = 0.117) and Lineage II (COI: r = 0.317, P = 0.849; CR: r = 0.265, P = 0.837), which indicate gene flow, were not restricted by distance. In SAMOVA, the best population configuration is defined by the highest FCT. However, in this study, SAMOVA revealed that FCT increased with partitioning of populations into the maximum group in all analyses. It should be noted that population structure analysis with one or more single population groups cannot deduce the group structure (Heuertz et al. 2004). Thus, the best population configuration with the highest FCT was selected when the analysis had more than a single population (Tsukagoshi et al. 2011). Based on the SAMOVA, k = 2 was selected for both genes as the best population configuration defined by the highest FCT (COI: 90.05%, p-value: 0.0000; CR: 82.34%, p-value: 0.0000) for AMOVA analysis (Table 5). Two analyses were conducted for the AMOVA. For the COI, the first AMOVA analysis—which divided the 15 populations into four groups based on the seas (Group 1: KPE, KKE, KMU, BMA, BPA, BGP, BPT (SOM); Group 2: TPT, PKA, END, TSE, SAN, KKI (SCS); Group 3: SDK (Sulu Sea); Group 4: TWU (Celebes Sea)—showed significant difference among groups/ seas (FCT: 55.41%, p < 0.05). In the second approach, populations were divided into two groups based on SAMOVA, k = 2) (Group 1: BGP, BPT, TPT, PKA, END, TSE, SAN, KKI, SDK, TWU; Group 2: KPE, KKE, KMU, BMA, BPA) and resulted in even higher Table 2. Genetic diversity within (bold) and among populations of P. semisulcatus based on COI (below diagonal) and CR (above diagonal) genes Populations KPE KKE KMU BMA BPA BGP BPT TPT PKA END TSE SAN KKI SDK TWU KPE 0.028 0.001 0.026 0.029 0.025 0.031 0.163 0.211 0.211 0.212 0.214 0.213 0.214 0.214 0.211 0.215 KKE 0.001 0.025 0.002 0.028 0.023 0.030 0.162 0.210 0.211 0.211 0.213 0.213 0.213 0.213 0.210 0.215 KMU 0.002 0.002 0.028 0.003 0.026 0.032 0.166 0.213 0.213 0.213 0.216 0.215 0.215 0.215 0.213 0.217 BMA 0.001 0.001 0.002 0.023 0.001 0.029 0.162 0.211 0.211 0.211 0.213 0.212 0.213 0.213 0.210 0.215 BPA 0.002 0.003 0.004 0.003 0.035 0.004 0.165 0.212 0.213 0.213 0.215 0.214 0.215 0.215 0.212 0.217 BGP 0.041 0.041 0.042 0.041 0.042 0.097 0.040 0.072 0.072 0.073 0.072 0.072 0.073 0.073 0.071 0.074 BPT 0.070 0.070 0.071 0.070 0.070 0.033 0.027 0.002 0.027 0.028 0.026 0.026 0.027 0.026 0.026 0.028 TPT 0.071 0.071 0.072 0.071 0.071 0.034 0.003 0.027 0.004 0.028 0.027 0.027 0.028 0.027 0.026 0.029 PKA 0.068 0.068 0.068 0.068 0.068 0.033 0.004 0.005 0.030 0.007 0.027 0.028 0.028 0.028 0.027 0.030 END 0.070 0.070 0.071 0.070 0.070 0.034 0.003 0.004 0.006 0.026 0.004 0.026 0.027 0.026 0.025 0.028 TSE 0.070 0.070 0.070 0.070 0.070 0.033 0.002 0.003 0.005 0.003 0.026 0.002 0.027 0.026 0.026 0.028 SAN 0.069 0.069 0.070 0.069 0.069 0.033 0.002 0.003 0.004 0.003 0.002 0.028 0.002 0.028 0.027 0.029 KKI 0.071 0.071 0.071 0.070 0.071 0.034 0.003 0.004 0.005 0.004 0.003 0.003 0.026 0.004 0.026 0.028 SDK 0.071 0.070 0.071 0.070 0.071 0.034 0.003 0.004 0.005 0.004 0.003 0.003 0.003 0.025 0.003 0.028 TWU 0.070 0.070 0.070 0.069 0.070 0.033 0.003 0.004 0.005 0.004 0.003 0.002 0.003 0.003 0.030 0.003 page 9 of 19Zoological Studies 60: 8 (2021) © 2021 Academia Sinica, Taiwan differentiated populations. Acknowledgments: We thank the Universiti Sains Malaysia for funding this project under the FRGS research grant (203/PBIOLOGI/6711455) - ‘Elucidating the molecular taxonomy and phylogenetics of the shrimp, Superfamily Penaeoidea and population genetic structure of the banana prawn, Penaeus merguensis in Malaysia’. We are grateful to SEAFDEC and the Department of Fisheries, Malaysia, for assisting us with the sampling and also our colleagues and their respective institutions—Norli Fauzani binti Mohd Abu Hassan Alshari, Siti Zuliana binti Ahmad, Mohamad Firdaus bin Mohamad Ridzwan, Dr Nur Fadli and Dr Jamsari Amirul Firdaus bin Jamaluddin (members of Molecular Ecology Lab 308)—for helping with the collection of specimens, and Mr Abdul Rahman Abdul Majid (Al Hana Enterprise) for sharing his vast experience with species identification. Authors’ contributions: SAAAH collected and processed the samples, performed the molecular analysis and drafted the manuscript. 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