Tor ssp.) of the family Cyprinidae are indigenous large riverine cyprinids that occur only in Southeast Asia. They are the popular freshwater fish for food, ornamental and recreational fishing. However, their wild populations are now ecologically threatened as their numbers decline drastically over the years due to over-exploitation, natural habitat degradation and water pollution. With successful hatchery production, readily accepted artificial feed and fetched high market value, Malaysian mahseer is now considered a perspective for aquaculture. Stocks were collected from various sources for broodstock development to establish an appropriate base population with desirable characteristics that harbour adequate genetic diversity. Information on the genetic status is essential to formulate appropriate strategies for genetic resources protection and its utilization. Genetic diversity of the broodfish can be assessed rapidly with high precision using polymerase chain reaction (PCR)-based DNA markers.The Malaysian mahseer  variation, genetic diversity, genetic differentiation, level of gene flow, population structure, genetic relatedness and their demographic aspects among these Tor populations, in addition to establishing their SSR profile by employing 22 SSR markers via fragment analysis. Total genomic DNA was extracted from 181 samples . Results showed the Tor spp. collection retained their genetic variation but exhibited excessive homozygosity among individuals within population. Moderate genetic differentiation was shown among the populations, with highly significant (p < 0.001) fixation indices . A low gene flow over all loci (Nm 1.548) indicates little genetic variation transfer between populations. The genetic structures of all the populations were successfully resolved into four main clusters by an unweighted pair group method with arithmetic mean (UPGMA) dendrogram generated based on Nei’s genetic distances. The population structures based on principal coordinates analysis (PCoA) and the Bayesian model also suggested four distinct clusters following geographical regions and eight closely related populations. This study provided a useful baseline reference for better genetic management and utilization of the Tor spp. stocks in their breeding and conservation programmes.In this study, a mixture of  Tor mahseer fish are generally known as kelah in Peninsular Malaysia, empurau and semah in Sarawak or pelian in Sabah [Tor mahseer comprises two valid species, Tor tambra and T. tambroides [Tor species. As such, their nomenclatures had been revised occasionally for the past few decades [Malaysian mahseer of the Cyprinidae family is an indigenous fish that occurs only in Southeast Asia ,2. Localin Sabah ,4,5. Thembroides ,6,7,8. C decades ,10. Thes decades . Wild po decades ,13.The mahseer is regarded as the most expensive freshwater food fish in Malaysia as it has high market demand and value. The price can go as high as USD 80–200 per kg though the price of cultured mahseer is not as high as that of wild-caught mahseer, which can fetch about USD 250 per kg . The retTor spp. is cultured mainly in ponds in Peninsular Malaysia and cement tanks and cages in East Malaysia. The states of Kelantan and Sarawak are the lead producers of Malaysian mahseer. The annual production of Malaysian mahseer has been approximately 20 tonnes per year since 2012 [With successful hatchery production and its ready acceptance of artificial feed, the Malaysian mahseer is now considered a good prospect for aquaculture. Lately, it has gained much attention and popularity among local farmers in Malaysia ,17. Tor nce 2012 ,20,21,22nce 2012 . It usuance 2012 ,25.T. tambroides from several natural populations in Malaysia had been examined using SSR markers in one of the studies by [The availability of polymerase chain reaction (PCR)-based microsatellites at a reasonable cost offers an easy and convenient way to generate rapid, reproducible and high throughput results for genetic diversity assessment. Microsatellites are also known as simple sequence repeat (SSR). SSR loci are hypervariable genetic markers. This feature made SSR the ideal choice for estimating genetic relatedness without prior knowledge of pedigree information ,28,29,30udies by . Still, Tor spp. as part of the conservation measure. In our research, Malaysian mahseer comprising a mixture of T. tambra and T. tambroides (and thus is addressed as Tor spp. in the study) were collected from 11 localities in Malaysia for broodstock development and sperm cryo-banking. Information on the genetic status of these Tor stocks is essential to formulate appropriate strategies for genetic resource protection and utilization in aquaculture development. However, no genetic assessment had been done on these Tor spp. stocks. Therefore, the genetic background, whether these Tor spp. stocks from different geographical regions possess different genetic makeups or whether any changes in their genetic variation over time, was unknown. It would be a waste of cost and space to maintain too many stocks of low genetic variabilities in the conservation and breeding programmes. Therefore, the main objectives of this study were to assess the genetic diversities, population structures, genetic relatedness, and their demographic aspects; and establish the genetic profiles of the Tor spp. collection by employing SSR markers.Broodstock development is the most vital element in developing a species for aquaculture. In usual practice, broodfish are collected from various sources for broodstock development. A detailed genetic background, such as the status of the genetic diversity and the population structure, including the demographic aspects (bottleneck and effective population size and number of migrants) and population assignment of the candidate broodstock, is often unknown. Very often, genetic studies will only be pursued for the collection after the collected broodstocks are established. Sperm cryo-banking was carried out for this indigenous Tor spp. samples comprised 91 cryopreserved milt samples , and 90 scale samples of live broodfish  were obtained for this study. These study samples were maintained at the Fisheries Research Institute Glami Lemi (FRIGL), Jelebu, Negeri Sembilan, Malaysia. Each broodfish was tagged with a passive integrated transponder tag. The male broodfish from which their milt samples were collected for cryopreservation in 2008 were obtained from the wild stocks of five localities caught in 2000–2008. The cryopreserved milt samples were obtained from stocks of FRIGL , Kg Esok, Jelebu, Negeri Sembilan , Aquaculture Extension Center, Perlok, Jerantut, Pahang , AgroHarvest, Raub, Pahang  and Kelah World, Hulu Langat, Selangor . FRIGL stock was collected from Kenyir Lake, Terengganu during FFRC, Batu Berendam, Melaka. KENS samples were collected from Kenaboi River, PPAP samples were collected from Pahang River, AGHR samples were collected from Keniam River, Taman Negara. In contrast, HLKW samples were obtained from a farmer who ran a farm at Hulu Langat and merely imported mahseer from Sumatra, Indonesia. The stocks from all ten localities in Malaysia were T. tambra, while samples of HLKW was T. tambroides. As claimed by the farm owner, samples of HLKW were T. tambroides. Morphologically HLKW stocks were slightly different from other stocks collected in Malaysia and most likely of T. tambroides [A total of 181 ® Blood and Tissue Kit  according to the manufacturer’s instruction.Each extraction reaction used 400 µL thawed milt and 0.04 g scale sample. Cryopreserved milt samples in 0.5 mL IMV straws  were thawed at 40 °C for 7 s. After that, both ends of the IMV straws were cut, and the thawed milt sample was drawn into a 1.5 mL centrifuge tube. The frozen-thawed milt sample was precipitated by centrifugation at 10,000 rpm for 15 min. The supernatant was discarded, and the sperm pellet was then subjected to total genomic DNA extraction by using the DNeasy® ND-1000 Microvolume Spectrophotometer . Total genomic DNA samples were homogenized at 10 ng/µL and stored at −20 °C until use.The extracted total genomic DNA samples were subjected to electrophoresis on a 1% agarose gel. Electrophoresis was carried out in 1× TAE buffer  at 80 V for 30 min to determine DNA integrity. The concentration of the extracted DNA was quantified by a NanoDropT. tambroides, according to [T. tambroides deposited in the NCBI genebank. Primer pairs were designed using Primer 3 version 0.4.0 software [DNA was amplified by PCR. A total of 24 microsatellite primer pairs  were tesrding to , and tensoftware ,40. The ® Flexi Buffer (with 1.5 mM MgCl2), 200 µM each dNTP, 10 pmol each of forward and reverse primers, 0.5 U Taq DNA Polymerase  and 3–10 ng template DNA. The PCR amplification profile was started with an initial denaturation at 94 °C for 4 min, 35 cycles of 94 °C for 35 s, annealing temperature between 48–66 °C (depending on the primer pairs) for 35 s and extension at 72 °C for 1 min, followed by a final extension at 72 °C for 10 min and finally held at +4 °C. PCR was performed using MyCyclerTM Personal Thermal Cycler . Before proceeding with the amplification of all samples, the optimal annealing temperature of each primer pair was determined via gradient PCR reaction with the range of annealing temperatures tested from 45 °C to 70 °C.The PCR reactions were performed in a total volume of 25 µL reaction mixture containing 2.5 µL 5X Go TaqTM Safe DNA Gel Stain . A volume of 5 µL of the PCR products was used for the gel electrophoresis. Agarose gel electrophoresis was carried out in 1× TAE buffer at 100 V for 30 min. The gel image was then visualized and photographed under UV illumination using the G: Box Gel Documentation System .The amplification specificity of the PCR products was determined before performing the fragment analysis via conventional gel electrophoresis on 1.8% agarose gel containing Invitrogen 1× SYBRTMLIZ-500® size standard and Hi-DiTM Formamide . After that, 2 µL of the sample mixture was loaded into the Applied Biosystems ABI3730XL Genetic Analyser  to determine the peaks. Lastly, the raw data were analyzed using the GeneMapper® Software Version 4 to determine the fragment sizes and the height of the peaks.Fragment analysis was conducted via capillary electrophoresis on the PCR products generated from primer pairs labelled with different fluorescent dye colours . Three tTor spp. samples in this study [A), number of genotypes (NG), expected heterozygosity (He), heterozygosity (Ho), inbreeding coefficient (f) and the polymorphism information content (PIC) [r), effective number of alleles (Ae), number of private alleles (Ap) and percentage of polymorphic loci [p-values following [Microsatellite loci were scored and analyzed using the Power Marker Software Version 3.25 to determine the genetic diversity and the genetic distance of the is study . Geneticnt (PIC) . The Genhic loci . Markov ollowing , with seollowing . Genotypollowing . The SSRTor spp. collection was assessed via analysis of molecular variance (AMOVA), F-statistics, pairwise population comparisons and population differentiation, determined using the ARLEQUIN software version 3.5.2.2 [ST) between populations based on the distance method, with the significance level set at p = 0.05 [Tor spp. collection was determined using a variant of the Mantel test, with the genetic distance matrix constructed based on the shared allele distance for each pair of individuals. Principal coordinates analysis (PCoA) for the distribution of each individual in all populations and estimation of gene flow (Nm) was performed using GenAleX 6.51b2 software [The genetic structure of the  3.5.2.2 . AMOVA w 3.5.2.2 . F-stati 3.5.2.2 . Populatp = 0.05 . Populatsoftware . PCoA wasoftware .Tor samples studied. The distance-based method through Nei’s genetic distance implemented in Power Marker Software Version 3.25 was performed to construct an Unweighted Pair Group Method with Arithmetic Mean (UPGMA) dendrogram and viewed using the TreeView v 1.6.6 program [Both distance-based and Bayesian model-based clustering methods were used to determine the population structures of the  program ,51,52. T program . In the  program . The out program .Genetic relatedness between and among individuals within each population was assessed by seven relatedness estimators implemented in the COANCESTRY Version 1.0.1.9 software based on an individual’s multilocus genotype data . The relEvidence of a recent bottleneck for each population except EMS was tested for using BOTTLENECK version 1.2.02 . Three mLDNE Software version 1.31 [crit) was defined at 0.01, i.e., all alleles with frequencies less than 0.01 were excluded from the analysis. The 95% confidence intervals for Ne were determined by the JackKnife method. Population assignment was also performed using GenAleX 6.51b2 software [The effective population size (Ne) was estimated based on linkage disequilibrium data at unlinked loci according to the Burrows method with a bias correction using the ion 1.31 ,68. The software  to detecsoftware ,70.A (146), Ar (6.6818), allele numbers per locus (1–20), and the number of genotypes (7.8182), while EMS generated the lowest NA (28), Ar (1.2727), allele numbers per locus (1–2) and the number of genotypes (1.0000)  to 0.8636 (EMS) and with a mean value of 0.6495. The number of effective alleles (Ae) generated varied from 1.273 to 3.792, with a mean of 2.543. The highest Ae was seen in the AgroHarvest, Raub, Pahang (AGHR) population, while the lowest Ae was in the EMS population. A total of 87 private alleles unique to a single population were produced from the Tor samples, with the highest number from the HLKW population , followed by the Aquaculture Extension Center, Perlok, Jerantut, Pahang (PPAP) population . Private alleles were generated in nine populations, i.e., 81.8% of the populations, while they were absent in the AGHR and HLS populations. The list of private alleles generated in each population is shown in Among the eleven populations studied, Kelah World, Hulu Langat, Selangor (HLKW) produced the highest N(1.0000) . The meaThe percentages of polymorphic loci ranged from 27.27% in the EMS population to 95.45% in PPAP, HLKW and TGN populations, with an average of 76.45%. The lowest genetic variation was in the EMS population due to its small sample size. The highest He (0.5970), Ho (0.4545) and PIC (0.5711), respectively, were shown in HLKW, while the lowest He (0.0682), Ho (0.2727) and PIC (0.1023), respectively, were seen in EMS. The mean values of He, Ho and PIC, were 0.4189, 0.4083 and 0.3966, respectively. In this study, six out of the eleven populations with He < Ho were conforming to HWE.f) ranged from −0.6226 (BS08) to 0.9238 (NY13) and with an average f at 0.2259  was in the range of −0.003 to 0.234, with a mean of 0.015  for most allele size classes might be present in sixteen loci (72.7%), suggesting the presence of null alleles. For those loci with null alleles, the total observed homozygotes appeared higher than the total expected homozygotes and exhibited positive f values . Null alf values . The nulf values . The AGHMeanwhile, stuttering, which is indicated by a highly significant shortage of heterozygous genotypes with alleles of one repeat unit difference, might have occurred in thirteen loci (59.1%) in this study. The HLKW population showed the highest occurrence of null alleles and stuttering. Nevertheless, the results showed no evidence for large allele dropout in all loci. Large allele dropout occurs when large alleles do not amplify as efficiently as small alleles.a) was 14.92%, variation among individuals within populations (Vb) was 9.00%, and variation within individuals was 76.09%. These indicated that the Tor spp. collection was highly variable, and, statistically, all these variations were highly significant (p < 0.001)  .ST, FIS, and FIT of 0.149, 0.106, and 0.239, respectively. All the three indices exhibited statistically highly significant differences (p < 0.001) from zero among and within all populations indicating the phenomenon of inbreeding. Inbreeding was resulting in a loss of heterozygosity among populations (FST), among individuals relative to the subpopulation (FIS), as well as within individuals relative to the total population (FIT).The estimates of fixation indices from the F-statistics analysis were with mean values of overall FST values ranged from 0.016 to 0.237 among populations, indicating mixed levels (from low to high) of genetic differentiation among the populations  was between the MSJ and HLS populations. The highest value (0.237) was between the GPRK and KENS populations. Significantly higher (p < 0.05) genetic differentiation than all other populations was observed in three populations, i.e., HLKW, GPRK, and KENS. The pairwise FST values ranged from 0.135 to 0.235 between the HLKW population and other populations, ranged from 0.092 to 0.237 between the GPRK population and other populations, and ranged from 0.090 to 0.237 between the KENS population and other populations. For EMS (T. tambra from Sarawak), significant population differentiation was observed between EMS and HLKW, GPRK and KENS populations. Still, it was not significant between the EMS population and seven other populations . Besides the HLKW population, high population differentiation, with pairwise FST greater than 0.2, was also observed between the KENS and EMS populations (pairwise FST 0.235), between the EMS and PHG populations (pairwise FST 0.227), between the AGHR and PHG populations (pairwise FST 0.211), and between the GPRK and PHG populations (pairwise FST 0.210). Pairwise populations with FST < 0.05 indicated that the genetic differentiation was small and insignificant between them. For them, the allele frequencies within each population pair were very similar. These were seen in the pairwise populations of HLS-MSJ (FST 0.016), FFRC-TGN (FST 0.050), and AGHR-TGN (FST 0.036).Pairwise Fulations . The lowGenetic divergence among the populations, as revealed by pairwise Nei’s (1983) genetic distances, ranged from 0.062 to 0.423 among the populations . The low1) consisted of three populations . The second sub-group (D2) comprises five populations , of which four populations were the localities from which the cryopreserved milt samples were obtained. Based on the population structure dendrogram generated, it was evident that the populations within subgroups D1 and D2 were closely related, as revealed by the small Nei’s genetic distances (1983) (Based on the UPGMA dendrogram generated based on the Nei’s genetic distance (1983), as shown in s (1983) .Tor spp. samples. The results showed that the first, second and third component axes accounted for 28.50%, 11.88% and 6.99%, respectively, of the total variance, and the eigenvalues were 190.80, 79.50 and 46.79, respectively. The PCoA plot showed that the Tor spp. samples were in four distinct groupings, with the first principal component differentiating the HLKW population from the rest of the samples on the left quadrant. In contrast, the remaining populations formed three distinct groups on the right quadrant (Tor spp. samples studied. These groups were: (I) EMS and GPRK; (II) PHG and KENS; (III) AGHR, TGN, FFRC, PPAP, MSJ and HLS; (IV) HLKW.The principal coordinates analysis (PCoA) plot was also generated to show the genetic structure among all the quadrant . SamplesTor spp. population structure was four. Another peak was also observed at K = 6. From the plot of mean likelihood L(K) and variance per K value generated, the likelihood L(K) values over 20 runs were consistent without showing significant variance for the same K value  statistics generated the highest K value at K = 4 . Therefo K value . Tor spp. individuals estimated by the STRUCTURE software at varying K values from K = 2 to K = 7 are shown in Comparisons of the proportional membership of the Tor spp. were unambiguously divided into four groups with unique and distinct genetic compositions corresponding to the respective geographical regions. The four different groups were: (I) EMS, GPRK (Northern); (II) PHG, KENS ; (III) PPAP, AGHR, FFRC, TGN, HLS, MSJ ; and (IV) HLKW (Indonesia). All members in EMS, GPRK (group I), PHG, KENS (group II), and AGHR, FFRC, and TGN (group III) were correctly assigned to their respective populations. Nevertheless, some of the individuals in both the HLS and MSJ populations of group III were assigned to group I . Individuals in the PPAP and TGN populations, 76.9% and 92.9%, respectively, were assigned to group III. Some members in the PPAP population had admixed ancestry with group II and group IV, while 7.1% of the members in the TGN population had admixed ancestry with group IV. Meanwhile, some members in the HLKW population were found assigned to group I and showed admixed ancestry  with the Tor spp. from Northern Peninsular Malaysia.At K = 4, the eleven populations of At K = 6, it was observed that population differentiation occurred in groups II and III. PHG and KENS populations of group II were differentiated into two distinct groups. HLS and MSJ populations were differentiated from group III to form another separate group.The genetic relatedness among individuals in all populations was successfully generated from seven relatedness estimators implemented in the COANCESTRY program. Tor populations. Overall, the relatedness estimators were positively correlated with correlation coefficients ranging from 0.531 to 0.986 among all populations. The range of correlation coefficients in each population is summarized in The correlation coefficients between each pair of the seven relatedness estimators were calculated to compare different estimators in all the The results from bottleneck analysis using IAM suggested that there were occurrences of bottlenecks in six populations, i.e., FRIGL stock (FFRC), GPRK, HLKW, Kg Esok, Jelebu, Negeri Sembilan (KENS), MSJ and PHG . AnalysiThe estimates of effective population size (Ne) within each population determined from the linkage disequilibrium data are listed in The outcome of the population assignment showed that 90% (163) of the individuals from the eleven populations were assigned correctly to the self-population, i.e., their original sampling locality. In comparison, only 10% (18) individuals of four populations were mismatched and assigned to other populations . Out of Tor spp. produced identical SSR loci with the expected sizes (Coregonus lavaretus L.) using DNA from adipose fins and cryopreserved milt [In this study, the total genomic DNA extracted from both the frozen milt and scale samples of ed sizes . Similarved milt . SSR allved milt . TherefoTor collection in this study still retained a reasonable amount of genetic variation, with allele richness of 1 to 33 alleles per locus, polymorphic loci 76.45%, and an average PIC of 0.4942. Compared to studies on the same species by [The ecies by ,34,36, tecies by ,74. GeneT. tambroides, was quite similar to the allelic richness, i.e., 5–21 alleles per locus obtained on the same species in the study by [T. tambra in all the other populations that we studied, the allelic richness ranged from 1–2 alleles per locus to 1–17 alleles per locus, but with most populations  having the allelic richness of around ten alleles per locus. The reported allelic richness for T. tambra was ten alleles per locus in several studies [Allelic richness is an essential element in conservation programmes, as it is indicative of a population’s long-term potential for adaptability and persistence ,76. The study by . For T.  studies ,34,36.Most SSR loci (90.9%) revealed a significant deviation from HWE after the Bonferroni correction. Departures from HWE in most SSR loci are plausible and have been commonly reported in studies of natural populations in a wide range of fish species ,79,80,81The small sample size in both EMS and AGHR populations has resulted in low genetic variation. In populations with small sample sizes, rare genotypes are likely to be included in the samples. The small population size also increases inbreeding and genetic drift, thus reducing genetic variability over the long term . When inp < 0.001) heterozygosity loss among and within the populations was also revealed in the present study, as revealed in the AMOVA and F-statistics analysis. For populations with null alleles in the present study, the null alleles’ frequencies were relatively high in general . These populations showed highly significant genetic differentiation, with low gene flow among the populations as shown from the AMOVA.Heterozygosity deficit in the present study could also be the consequence of null alleles or stuttering among the SSR loci. Both null alleles and stuttering were detected in nine populations in this study. Of the nine populations with null alleles, five populations, i.e., HLKW, MSJ, HLS, FFRC and PPAP, showed heterozygote deficits. A highly significant (Donax trunculus), the presence of unusually high frequency of null alleles (>10%) did not appear to affect the FST estimates significantly [Each locus that deviated from HWE can amplify at least one allele in all the samples. Thus, the low frequencies of null alleles were not enough to affect the analysis . Generalficantly .The presence of null alleles in microsatellite data and their consequences on population genetic parameters had been tested using various analytical and simulation tools  and actuST, FIS and FIT indicated a significant reduction in heterozygosity within and among the populations due to non-random mating. FIS values significantly higher or lower than zero reveal inbreeding or outbreeding, respectively [Tor spp. collection (FST = 0.149), as evidenced by the low level of gene flow estimate (Nm = 1.548 per generation) and highly significant level (p < 0.001) of inbreeding among individuals within population (FIS = 0.106). Generally, it was observed in this study that the inter-population differentiation was low among the Tor spp. populations in Malaysia. Similar findings were also reported in the previous study by [Tor populations, with the pairwise population FST values ranging from low (0.016) to very high genetic differentiation (0.237) following the FST classification by [p < 0.05) were detected in 83.6% of the pairwise comparisons among populations. These confirmed their population divergence.In the present study, the fixation indices Fectively . As reflstudy by  on the sation by . SignifiTor spp. collection. The proportional membership of Tor spp. individuals with low genetic admixtures , as shown in Tor spp. populations. From the pairwise FST generated for the Tor spp. populations, results presented relatively higher differentiation between HLKW and all other populations, indicating that the population is most likely a separate species (T. tambroides). The same observation was also seen in the EMS population, which revealed significantly higher differentiation between HLKW, KENS and GPRK populations but no significant differentiation from other remaining populations. For AGHR and EMS, a small sampling size looks likely to be the main cause of population differentiation. For other populations, it seems more likely that the Wahlund effect due to geographic distances or habitat fragmentation may have caused the local genetic differentiation among the Tor spp. by limiting the gene flow among the populations [Genetic differentiation can be attributed to migration, geographical barriers, genetic drift and gene mutation ,104. Lowulations ,106. Habulations .Tor spp. populations ranged from 6.2% to 42.3% in this study. A great genetic distance was observed between the HLKW population and the other populations, with a pairwise genetic coefficient ranging from 31.8% to 42.3%. This finding again supported the idea that the HLKW population was from a different Tor species than the other populations because there was no sexual selection between different species. The pairwise genetic coefficient of the T. tambra populations ranged from 6.2% to 29.3%. T. tambra from EMS of Sarawak also showed a higher genetic distance from other T. tambra populations in Peninsular Malaysia, ranging from 27.5% to 35.3%. The distinct population clusterings were further supported by the results of the population assignment tests, using both PCoA analysis and Bayesian cluster analysis. A high percentage of correctly assigned individuals indicated substantial genetic divergence among the populations [Tor spp. samples obtained. Moreover, the genetic admixture of all the Tor stocks was relatively low , indicating that individuals in each population were weakly differentiated. These genetically uncontaminated populations served as ideal sources of fresh alleles for future aquaculture and restocking programmes [Genetic distance among the ulations . The patTor populations could also be explained according to their geographical distribution. Populations in cluster D , as illustrated in the UPGMA dendrogram, had small genetic distances which ranged from 6.2% to 18.3%, indicating that these populations were closely related and had a recent common ancestor. It was apparent that these closely related populations were from the same source and origin. Similar clustering was also observed in the previous study by [Similar to the genetic structures revealed in both the PCoA plot and the model-based cluster analysis at K = 4, the UPGMA clustering of study by , i.e., sSamples of the FFRC population were obtained from Kenyir Lake, while samples of the TGN population were collected from the Terengganu River, originating in Kenyir Lake. Samples of population PPAP were collected from the Pahang River. In contrast, the samples of the KENS population were obtained from the Kenaboi River, which is one of the tributaries of the Pahang River. However, the close relationship between samples of the HLS population from the Hulu Langat River and samples of the MSJ population from Mersing Johor could not be explained according to their geographical locations because these two river systems were not from the same origin. The Hulu Langat River flowed westwards of Peninsular Malaysia and ended at the Straits of Malacca, while the Mersing River flowed to the southeast of Peninsular Malaysia and ended at the South China Sea. Tor individuals from both the HLS and MJS populations comprise a mixture of Tor with distinct genetic contributions from the North (GPRK) at ≈35% and East Coast  of Peninsular Malaysia at ≈65%. Generally, the samples of populations HLS and MSJ were more closely related genetically to population GPRK. This observation was also supported in the population assignment test, by which 25% and 33.3% of the HLS and MSJ populations respectively mismatched one another and mismatched with the GPRK population or populations from the East Coast (TGN and AGHR) of Peninsular Malaysia. The admixture percentages were low among individuals in the HLS and MSJ populations, indicating that they did not interbreed. Therefore, it looked more likely that the local fish traders who supplied the HLS and MSJ stocks had obtained their fish stocks from the same source.Based on the population structure derived from the STRUCTURE analysis at K = 4, it was noticed that individuals in populations HLS and MSJ had similar genetic compositions. On the other hand, the samples of AGHR, which originated from the Keniam River, were found to be more closely related to the stocks from FFRC and TGN. In the meantime, both the GPRK and EMS were found to cluster in the same grouping in both PCoA plot and Bayesian cluster analysis, indicating that samples from Perak and Sarawak were closely related. These results again highlighted the possibility of mislabeling the EMS sample by the fish trader who supplied the fish. The so-called EMS broodfish was most probably from the local source in north Peninsular Malaysia. Unfortunately, no other samples from the same population were available for verification.Tor samples revealed by different relatedness estimators in the present study were not significantly (p > 0.05) different among all Tor populations across all estimators. It was also observed that mean Rxy based on the moment estimators showed negative values in most populations. A negative Rxy value indicates that the individuals are less related than the average relatedness. It also reflected how much lower the probability of recent coalescence is for the individuals relative to the average probability for all considered individuals from the reference population [Lates calcarifer), in which the Rxy estimates for wild and hatchery stocks did not differ significantly (p > 0.05). However, a significant increase of genetic relatedness with a high correlation coefficient and a decline in Ne estimates were detected within a selectively bred population from the hatchery stocks. Therefore, selective breeding has caused a significant loss of genetic variation, allelic diversity and overall heterozygosity compared to the parental generation.Genetic relatedness shows the relationship between individuals in a population . Knowledpulation . Meanwhipulation  on seabaTor spp. collection for cross breeding in the future to avoid a rapid increase in genetic relatedness and reduction in Ne.The pattern of genetic relatedness has a direct functional relationship with the Ne of the population . The nexIn the present study, a recent population bottleneck was detected in FFRC, GPRK, HLKW, KENS, MSJ and PHG populations and a mode-shift in allele frequencies in AGHR population. Sampling error in GPRK and small sample size in AGHR and EMS populations have resulted in negative effective population size (Ne) estimates in these populations. Ne measures the rate of inbreeding and genetic drift in the population . PopulatTor spp. collection. The percentage has doubled the previous study  by [The accuracy of the population assignment test did not seem to affect much by null alleles in the present study. In the population assignment test, a high percentage  of individuals correctly assigned to respective populations were observed for the 2.8%) by . As repo2.8%) by . Therefo2.8%) by . Thus, t2.8%) by .Tor spp. and for their utilization in aquaculture development, especially for selective breeding programmes. The high percentages of departures from HWE as the consequences of excessive homozygosities among the SSR loci showed an urgent need for proper management strategies of these Tor stocks. It was evident from the genetic structures obtained that the Tor spp. collected for the establishment of the hatchery population comprised the natural gene pool of four distinct genetic sources. Understanding the connectivity among the populations provides a useful tool to determine appropriate strategies for fisheries conservation, effective management and genetic improvement of the Malaysian mahseer.An appropriate base population containing selected fish with desirable characteristics that harbour adequate genetic diversity is a prerequisite for successful broodstock development and effective genetic management. Therefore, the genetic information obtained from this study is essential to formulate appropriate strategies for genetic resource protection of Analysis of genetic relationships is an essential component in a genetic improvement programme. It provides information about genetic diversity, and it also offers the platform for the stratified sampling of breeding populations ,117,118.Tor spp. collection, it should serve as a valuable germplasm resource and a suitable base population to start with for future utilization and genetic improvements of this species. Excessive homozygosity caused the departures from HWE we observed, highlighting the need for better management and planned breeding programmes of these Tor stocks.Proper knowledge of stock structure is necessary to preserve genetic diversity and ensure sustainable exploitation of the broodstocks. With reasonable variability, which ranged from intermediate to high levels in the current Tor spp. stock from east Malaysia (Sabah and Sarawak) and northern Peninsular Malaysia (Kelantan) shall be included in future studies to best characterize the Tor spp. in Malaysia, which could better understand the current genetic status of Malaysian mahseer in the whole country. Future samples shall be obtained from more reliable sources for the stocks of Hulu Langat River and Mersing Johor populations. In genetic conservation programmes, milt samples of the Tor stocks from the GPRK, PHG and east Malaysia populations should be prioritized for sperm cryo-banking. Besides that, the polymorphic SSR loci with considerable genetic variations used in this study and those with private alleles are potentially useful for pedigree and parentage analyses of the new breeds from the stocks, as well as in the development of marker-assisted selection technology (MAS) for Tor spp. in this region. The SSR markers used in the study are expected to be useful for the ongoing inter-population diallel cross-breeding and growth performance assessments of the fingerlings produced from the same pool of candidate broodstocks. These SSR markers are also of potential use in monitoring the genetic impacts of restocking activities on the wild populations of Tor spp. The levels of genetic variation, which included measures of allelic diversity, overall heterozygosity, Ne and genetic relatedness, should be monitored continuously for the breeds resulting from these broodstocks.For better prospects, Tor spp. collection obtained from 11 populations using 22 SSR loci. The information on SSR polymorphism and diversity, gene flow, population differentiation, genetic structure, genetic relatedness and their demographic aspects of the Tor spp. collection is obtained from the study. This finding facilitated the reliable classification of the Tor spp. stocks and provided excellent information on genetic variabilities and population genetic structures of the Malaysian mahseer stocks obtained from various geographical locations. The Tor spp. collection still retained their genetic variation but exhibited excessive homozygosity among individuals within population and little genetic variation transfer between the populations. Generally, the levels of genetic variation and the population structures corresponded to the geographical origins of the Tor spp. The private alleles we found to be present in the different populations could serve as specific markers for the respective populations. The results on the genetic diversity, genetic structure and relationships, and the methodology used in the study may be utilized in the future for constructing genetic linkage maps for marker-assisted breeding and for identifying growth trait-associated markers in Tor spp.The SSR genotyping in this study has successfully established the SSR profile for the


Rhodeus pseudosericeus, a bitterling species  endemic to the Korean Peninsula, are only found in some limited areas of three rivers, Daecheon, Han and Muhan, that flow into the west coast. Here, we genotyped 24 microsatellite loci and two loci (DAB1 and DAB3) of MHC class II peptide-binding β1 domain for 222 individuals collected from seven populations. Our microsatellite analysis revealed distinctive differentiation between the populations of Daecheon and Muhan Rivers and the Han River populations, and populations were structured into two subgroups within the Han River. Apparent positive selection signatures were found in the peptide-binding residues (PBRs) of the MHC loci. The allelic distribution of MHC showed a degree of differentiation between the populations of Daecheon and Muhan Rivers and the Han River populations, partially similar to the results obtained for microsatellites, however showed rather complex patterns among populations in the Han River. Considering the apparent differences in the distribution of supertypes obtained based on the physicochemical differences induced by the polymorphisms of these PBRs, the differentiation in DAB1 between the two regional groups may result in the differences in immune function. No differentiation between these two regions was observed in the supertyping of DAB3, probably indicating that only DAB1 was associated with the response to locally specialized antigenic peptides.Given the fact that threatened species are often composed of isolated small populations, spatial continuity or demography of the populations may be major factors that have shaped the species’ genetic diversity. Thus, neutral loci have been the most commonly-used markers in conservation genetics. However, the populations under the influence of different environmental factors may have evolved in response to different selective pressures, which cannot be fully reflected in neutral genetic variation.  The main reason for the contemporary loss of freshwater fish diversity is that freshwater ecosystems are particularly sensitive to the effects of anthropogenic activities, including habitat loss, alien species introduction and pollution, primarily due to their insular and fragmented nature5. No matter how global wildlife conservation efforts are underway, it seems impossible to stop the widespread decline in freshwater fish diversity6. Considering this situation, it is effective to focus more on the conservation of species specifically vulnerable to extinction, for example species with small native ranges.Freshwater fish species, which make up nearly a quarter to half of the world's vertebrate diversity9. Given that threatened species are often composed of small fragmented populations10, spatial continuity or demography of the populations may be major factors that have shaped the species’ current genetic diversity and characteristics12. Thus, neutral loci with signatures of such spatio-temporal histories are the most commonly used markers in conservation genetics13. However, the populations under the influence of different environmental factors may have evolved in response to different selective pressures18, which cannot be fully reflected in neutral genetic variation19.One of the most important steps to consider before establishing management strategies for a species is to understand its genetic diversity and population structure21. MHC molecules are divided into class I and class II23. All types of nucleated cells express MHC class I, whereas MHC class II molecules are only found on specialized antigen-presenting cells23. MHC class I presents a peptide fragment of cytoplasmic proteins or pathogens to the receptor of cytotoxic T cells that express CD823. A peptide fragment loaded by MHC class II is derived from the lysosomal process of proteins or pathogens internalized by endocytosis and presented to the receptor of helper T cells that express CD423. An enormous polymorphism is found in the domain to which a peptide bind24. The diversity of this domain confers a variety of peptide-binding repertoire, and is known to be the historical consequences of co-evolutionary arms race with the local pathogens27. Local populations living under distinct composition of pathogens are thus expected to have a different MHC allelic composition27.The peptide-binding region in the major histocompatibility complex (MHC) molecules has been considered as one of the widely used genetic marker in the context of local adaptationRhodeus pseudosericeus, a bitterling species  endemic to the western Korean Peninsula, is legally designated as an endangered species (class II) under the Protection Act of Wild Fauna and Flora by the Ministry of Environment, South Korea28. Like other bitterling species, R. pseudosericeus spawns only into living unionid mussels28. Populations of this species are only found in some limited areas of three rivers, Daecheon, Han and Muhan that flow into the west coast28  would have worked between Han and Daecheon-Muhan. Only a single genetic analysis for this species, using the mitochondrial cytochrome b gene, has been performed to date28. In that study, the populations in the Han River showed a slightly distinct haplotype composition from the Daecheon and Muhan Rivers that were genetically similar to each other28.t28 Fig. . AlthougR. pseudosericeus individuals collected from seven populations  of MHC class II β1 domain (peptide-binding domain) for 222  and DAB3TS27) to 24 (TS76), and the expected heterozygosity ranging from 0.233 (TS27) to 0.751  deviated significantly from the expectation of HWE  were genetically close with each other, whereas these two river populations were genetically distinct from the Han River populations (Table FST and -RST of 0.286 (0.112–0.533) and 0.234 (0.102–0.431), respectively  was significantly high only in DAB3 , the populations of the Han River in DAB3 were structured similarly to those revealed in the microsatellite loci. More importantly, the allelic structure in DAB3 was rather different from the pattern revealed by MHC supertyping. This may reflect a history of isolation among population groups within the Han River. As such, being able to measure the relative importance of neutral change and adaptation to the environment can be an important benefit of investigating adaptive loci. Considering these points, caution is required during the conservation management of the populations in the Han River.Overall, the MHC and microsatellite loci we investigated in Taken together, two main parts should be considered in the perspective of conservation and management. First, it should be noted that the genetic diversity of the Han River populations is relatively lower than that of the populations DC or MH. In addition, genetic features that appear to have been formed under the influence of genetic drift or demographic fluctuation were also revealed. A more detailed ecological survey of these species in the future will be beneficial for establishing conservation strategies. Second, our findings support that the populations of the Han River and the populations of the Daecheon and Muhan Rivers likely have specialized immune adaptations to different types of pathogens, based on the results of MHC supertyping. Therefore, these two regional groups need to be established as separate conservation units.Rhodeus pseudosericeus samples used for the genetic analysis were the fin clips removed from the specimens stored in the Department of Life Sciences at Yeungnam University, which were also used in a previous study28. These specimens were collected in accordance with the Inland Water Fisheries Act and Wildlife Protection and Management Act in the South Korea from seven populations of the Daecheon River (DC), Muhan River (MH) and Han River .All R. pseudosericeus, we tested the microsatellite loci known from other species in Acheilognathidae and then selected those with high PCR success rate and variability. We tested 13 and 110 microsatellites developed from R. sinensis (series RU)48 and Tanakia somjinensis (series TS)37, respectively. Through the tests using eight randomly selected R. pseudosericeus individuals, a total of 24 loci that showed good polymerase chain reaction (PCR) amplification efficiency and polymorphism visually observed in electrophoresis were selected to be used for genotyping in this study (Supplementary Table To determine the population diversity and genetic structure of Taq buffer (containing 2.5 mM MgCl2), 0.25 mM dNTPs, 1 μM of each primer and 0.25 units of Taq DNA polymerase . Thermal cycling using GenePro  was performed under the profile consisting of an initial denaturation at 95 °C for 5 min, 35 cycles of a denaturation at 95 °C for 30 s, an annealing at 58 °C for 30 s, an extension at 72 °C for 45 s, and a final extension at 72 °C for 10 min. The amplified products were genotyped on an ABI 3730xl Genetic Analyzer by Macrogen Inc .One of four different types of fluorescence, FAM, PET, VIC or NED was labelled at the 5′ end of each forward primer . PCR was performed using a 10 μl mixture comprising 1 μl of DNA extraction, 1 × FIS) using Arlequin 3.549, Fstat 2.9.3.250 and Genepop 4.251. The deviation of observed genotype frequencies from the expectation of Hardy–Weinberg equilibrium (HWE) was tested for each locus and each population using the Fisher’s exact test based on Markov chain parameters with 1000 batches and 10,000 iterations per batch52 in Genepop. Fisher’s exact test was also used in testing the existence of linkage disequilibrium between pairs of loci based on the Markov chain algorithm under the null hypothesis of independence using Genepop. Micro-Checker 2.2.353 was used to check the likelihood of genotyping errors caused by the presence of null alleles or allele dropout.Genetic variability per locus and population was estimated with the number of alleles, allelic richness, observed heterozygosity, expected heterozygosity and fixation index  with a setting of 90% stepwise mutations model (SMM) and 10% infinite alleles model (IAM). Second, mode-shift was examined to check if the distribution of allelic class deviated from the typical L shape56. The probability of a historical population size reduction was examined by whether the M-ratio, which is the mean ratio of the number of alleles to the range in allele size, was significantly lower than the commonly used threshold, 0.6857.For each population, two different methods were used to determine whether there was a signature of recent reduction in population size using Bottleneck 1.2.1R. pseudosericeus populations. First, global FST and RST as well as pairwise-FST and pairwise-RST were estimated using Arlequin and Genepop. GenAlEx 6.558 was applied to evaluate the relationship between pairwise genetic divergence and the geographic distance along the water way. The interpopulation geographic distance was estimated using Googlemap’s ‘Measure Distance’ function. Second, the pattern of population structuring was examined based on Bayesian framework using the software Structure 2.3.459. The reliable numbers of genetically distinguishable clusters (K) were predicted by ΔK60 implemented in Structure Harvester v0.6.9461. Bayesian Structure analysis was performed for each K, with ten independent MCMC runs, each consisting of 4 × 105 generations after a burn-in of 105. Finally, principal component analysis (PCA) was performed using GenAlEx to visualize the relationship among populations at the individual level. Critical significance values of all statistics used were adjusted for multiple comparisons based on the Bonferroni procedure.Three different methods were used to identify the genetic structure among 21. DAB1 (212 bp) and DAB3 (227 bp) were amplified using the primer pairs RPMHCD1E2  and RPMHCD3E2 , respectively, designed based on the relatively conserved sequences at both ends of the peptide-binding domain (β1 domain). Draft sequences of DAB1 and DAB3 obtained from four R. pseudosericeus individuals of population DC, which was known to show the highest genetic diversity among the populations28, were used for the comparison with other species21 and the design of this primer set. Primers designed in a closely related species, R. sinensis21 were used to analyze this full DAB sequences. The forward and reverse primers of both RPMHCD1E2 and RPMHCD3E2 carried 5′ end overhang extension to provide a primer binding site for the second PCR and the pair-end sequencing on MiSeq platform . The first PCR amplification was performed in a 25 μl reaction volume containing 2.5 μl template, 12.5 μl 2 × NEBNext Ultra II Q5 Mater Mix , 1.25 μl of each primer (10 μM) and 7.5 μl distilled H2O. The thermal cycling profile was as followed: an initial denaturation at 98 °C for 30 s, 30 cycles of a denaturation at 98 °C for 10 s, an annealing at 60 °C for 30 s and an extension at 72 °C for 30 s, and a final extension at 72 °C for 5 min. The first amplicons were sent to GenoTech Inc  for the next steps including the second PCR for library preparation, MiSeq sequencing and data processing.We employed a two-step tailed PCR approach to construct the paired-end libraries for high throughput sequencing of MHC using MiSeq platform. As with most cypriniform species, MHC class IIB of bitterlings can be assigned into two evolutionarily distinct loci, DAB1 and DAB32O using the following settings: an initial denaturation at 98 °C for 30 s, 10 cycles of a denaturation at 98 °C for 10 s, an annealing at 55 °C for 30 s and an extension at 65 °C for 45 s, and a final extension at 65 °C for 5 min. The final PCR products were pooled in equal volumes, purified using AMPure XP beads , and subjected to TapeStation HSD5000  to check the purity, concentration and fragment size. The final library preparation was subjected to the pair-end sequencing mode of 300 bp read length in the Illumina MiSeq platform .In the second PCR, the first amplicons were amplified using the forward and reverse primers tagged with a unique combination of 8 bp index sequence allowing the identification of each individual and an adaptor sequence allowing the final amplicons to hybridize to the MiSeq flowcells  were quality-filtered with CLC genomics workbench v6.5  to remove the sequences having a Phred score less than Q30 or ambiguous nucleotides and the sequences more than five bp longer or shorter in length than expected. The 3,343,997 (DAB1) and 5,419,573 (DAB3) reads that passed these criteria were mapped to the draft DAB sequences obtained from four individuals in the population DC. Sequences that were completely mapped  were demultiplexed, and their adaptors and primer sequences were trimmed. During this process, sequences with incorrect adapters or primer sequences were manually removed. The sequences were subjected to two additional steps of validation. First, an amplicon must appear in more than one individual in the population to be recognized as an allele. The only exception was permitted for the amplicons that appeared only in one heterozygote individual. Second, a single amplicon should be supported with more than 1000 reads or more than the frequency of 0.1. This validation protocol can prevent chimeric sequences or PCR artifacts from being included in our analysis, although the possibility exists to slightly underestimate the diversity of MHC.We validated MHC alleles according to the protocol proposed in a previous studySince amplification was not successful for the DAB1 of many individuals from populations GD and HC, the DAB1 data of these two populations were excluded from the analysis. This may be due to the presence of mutations in the priming sites, and it is also possible that the presence of adaptor sequences for two-step PCR significantly lowered the efficiency of amplification in these populations. However, considering that the possibility of amplification of different loci cannot be ruled out if different primer sequences are used for different populations, the same primer sets had to be used. We finally obtained reliable MHC genotyping data from 97 individuals for DAB1 and 192 individuals for DAB3. Average number of reads per amplicon was 8569 ± 5495, ranging from 1040 to 22,155, in DAB1 and 9042 ± 8365, ranging from 311 to 78,094, in DAB3. The MHC sequences obtained in this study were deposited in NCBI GenBank under the accession numbers from MT943022 to MT943047.Rhodeus sinensis21. The strength of historical selection pressure acting on DAB was determined by the ratio of non-synonymous (dN) to synonymous (dS) substitutions (ω) based on Nei-Gojobori method63 with 2000 bootstrap replicates and modified under Juke–Cantor corrections. Tests of the positive selection signature for each of the codons were performed in two ways. First, codons were tested using CODEML implemented in PAMLX package65. The Bayes empirical Bayes (BEB) method was used to estimate Bayesian posterior probability (BPP). If the BPP was greater than 95%, the codon was considered to show significance. To obtain the phylogenetic tree included in the input (nekwick format) files for CODEML, Bayesian inference (BI) analysis was performed for the DAB1 or DAB3 sequences without consideration of outgroups using MrBayes 3.2.3 under the options of four heated chains, 40,000,000 generations and sampling tree at each 1000 generation66. GTR + I + G was chosen as the best-fit model for the BI analysis using jModelTest 2.067 under Akaike Information Criterion (AIC)68. In CODEML, the likelihood ratio tests (LRT) were performed to compare the codon-based models, between M1a  and M2a (positive selection), between M7 (beta distribution) and M8 (beta distribution and positive selection), and between M0 (one-ratio) and M3 (discrete). Second, the signature of positive selection was detected for each codon using the HyPhy package69 implemented in DataMonkey web server (http://www.datamonkey.org/), where three different codon-based maximum likelihood tests, FEL (Fixed Effects Likelihood), FUBAR (Fast Unconstrained Bayesian AppRoximation) and MEME (Mixed Effects Model of Evolution), were used. Phylogenetic relationship was reconstructed under the default setting in DataMonkey.The putative peptide-binding residues (PBRs) in the β1 domain region were identified based on the comparison with the sequences characterized in Hd) and nucleotide diversity (π) with DnaSP 5.1070. Pairwise ϕST values were calculated among populations as an estimate of genetic differentiation using DnaSP70. The significance of the estimated ϕST values was tested using 1000 permutations. Bayesian Structure analysis was performed for the K = 3 that was predicted to be the most reliable by ΔK60 implemented in Structure Harvester61, with ten independent MCMC runs, each consisting of 4 × 105 generations after a burn-in of 105. The input file for Structure analysis was constructed in a way that the corresponding alleles or supertypes for each individual were present (1) or not (0), or data was missing (− 1).MHC allelic diversity at the intra-population level was quantified by estimating the allele number, haplotype diversity , z2 (steric bulk), z3 (polarity), z4 and z5 (electronic effects). A matrix was created for each of DAB1 and DAB3 with rows representing alleles and columns representing the physiochemical descriptors of z1–z5 for each PBR. The matrix for each DAB was used for the input in clustering of alleles by discriminant analysis of principle components (DAPC) implemented in the R package adagenet 1.4-074. The optimal number of supertypes were estimated using R package NbClust 3.0 (https://cran.rstudio.com/bin/windows/contrib/3.5/NbClust_3.0.zip) under the majority rule.The DAB1 and DAB3 alleles were assigned into functional supertypes by analyzing amino acid polymorphism at the PBRs in the β1 domain regionSupplementary Information.


Littorina brevicula , on artificial structures along the coast of the Yangtze River Delta (YRD) using mitochondrial ND6 sequences and microsatellite data. Clear phylogeographic and genetic differentiation were detected between natural rocky populations south and north of the YRE, which resulted from the lack of hard substrate for rocky invertebrates in the large YRD coast. For the newly colonized populations on the coast of YRD, most individuals (98%) to the south of ~33.5°N were from natural rocky populations to the south of the YRE and most of those (94%) to the north of ~33.5°N were from the northern natural rocky populations, which demonstrated strong ecological connectivity between the inner southwestern Yellow Sea and the YRE in winter time. We presented the first genetic evidence that demonstrated a northward wintertime coastal current in the inner southwestern Yellow Sea, and precisely illustrated the boundary of the coastal current recently proposed by numerical experiment. These results indicated that the YRE serves as an important source of materials and energy for the inner southwestern Yellow Sea in winter, which can be crucial for the function of the Yellow Sea ecosystem.Understanding connectivity over different spatial and temporal scales is fundamental for managing of ecological systems. However, controversy exists for wintertime ecological connectivity between the Yangtze River Estuary (YRE) and inner southwestern Yellow Sea. Here, we investigated ecological connectivity between the YRE and inner southwestern Yellow Sea in wintertime by precisely pinpointing the source of the newly colonized populations of a winter‐spawning rocky intertidal invertebrate,  The study addressed a consequential question regarding the ecological connectivity between the Yangtze River Estuary and inner southwestern Yellow Sea. For the first time, we provided clear genetic evidence for strong ecological connectivity between the southwestern Yellow Sea and Yangtze River Estuary in winter season. The strong wintertime ecological connectivity indicated that the Yangtze River Estuary serves as an important source of materials and energy for the inner southwestern Yellow Sea in winter, which can be crucial for the function of the Yellow Sea ecosystem. It exteLittorina brevicula    is an alluvial plain created by activities of the Yangtze River, Old Yellow River, and other rivers and is characterized by muddy coastline that is inappropriate for settlement of rocky intertidal species from the Yangtze River mouth (c. 30°N) to Lianyungang, Jiangsu (c. 34.5°N)  Figure . The spa Kojima, . The egg Kojima, . The dur Kojima, . Within L. brevicula on the artificial structures along coastal areas of the YRD. By using complete mitochondrial ND6 gene sequences and microsatellite markers, we inferred the source of the newly colonized populations by investigating spatial genetic structure among the newly colonized populations on coasts of YRD and natural rocky intertidal populations south and north to the YRD. For the first time, our results clearly demonstrated that most of the individuals of the newly colonized populations to the south of ~33.5°N were from natural populations to south of the YRE and those to the north of 33.5°N were from natural populations to north of the YRD. These results suggested a strong ecological connectivity between the inner southwestern Yellow Sea and the YRE in winter, which can be crucial for the function of the Yellow Sea ecosystem and have general interest to marine ecologist working in this area.The aim of the present work was to clarify the ecological connectivity between the inner southwestern Yellow Sea and the YRE in winter monsoon season by precisely pinpointing the source of the newly colonized populations of 22.1L. brevicula is not protected by Chinese law. Procedures were performed in accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals of the Institute of Oceanology, Chinese Academy of Sciences.The field studies did not involve any endangered or protected species. 2.2L. brevicula were collected from 12 geographic localities covering the YRD coast artificial structures and nearby natural rocky intertidal areas from 2018 to 2019  and Lbnd‐R (5’‐GTG TGC GCA TGA AAT GTA T‐3’)]   gene was performed by PCR in a 25‐μl reaction mixture containing template DNA (1 μl), ddH2O (10.5 μl), 2X PCR Mix (12.5 μl), and a pair of “For the development of microsatellite loci, a de novo genomic library with insert size ~350bp was constructed following a standard Illumina protocol. Sequencing was performed to generate 150‐bp paired‐end reads on the HiSeq X Ten platform (Illumina) at Novogene Bioinformatics Technology . Then, de novo assembly was carried out using MEGAHIT using default settings , nucleotide diversity (π), number of polymorphic sites, haplotypes, transversions, and transitions were obtained using the program DnaSP 5 .The complete mt ND6 sequences were edited and aligned using the DNASTAR software . Molecular diversity indices such as haplotype diversity (2.5Na), allelic richness (AR), and inbreeding coefficient (FIS) for each population were calculated using FSTAT 2.9.3 , expected heterozygosity (HE), and polymorphic information content (PIC) were calculated using Excel Microsatellite Toolkit  and nucleotide diversity (π) in the northern natural populations were much lower than in the southern natural populations, which was also consistent with results of the number of polymorphic sites and haplotypes. For the newly colonized populations, both h and π were also lower in the two northern populations than in the four populations on the coastline of the Subei Shoal  were singletons represented by a single individual. Of the remaining nine haplotypes, eight were shared among populations and one was found in two individuals but in one population Table . For theFST and genetic distances  separated from each other by only a single mutational step. A total of 129 individuals with 22 haplotypes were detected in clade A, and 161 individuals with 32 haplotypes were found in clade B. Network of clade A was star‐like with a dominant haplotype H1  in the center Figure . In clad3.3ΦST values of mt ND6 between the five populations north of 33.5°N (hereafter Northern Populations) and the seven populations south of 33.5°N (hereafter Southern Populations) were strong (ΦST = 0.426–0.572) and were all statistically significant after Bonferroni's correction (Table ΦST among pairs of the Northern Populations and pairs of the Southern Populations (ΦST = −0.027–0.052). For microsatellite data, the pairwise FST values between the Northern Populations and Southern Populations ranged from 0.069 to 0.123 and were all statistically significant after Bonferroni's correction  plot of pairwise y Figure . Consisty Figure ) clustery Figure . The DAPy Figure .3.4Although simulation studies showed that bias in assignment tests caused by null alleles lead to a slight reduction in the power to correctly assigned individuals (2.4 percent units for GENECLASS‐based assignment tests), microsatellite loci affected by null alleles would not alter the overall outcome of assignment testing and could therefore be included in the analysis , their distinct spatial distribution in natural rocky populations south and north of the YRE, and the cyclic nature of the Pleistocene glaciations, the phylogeographic divergence of the two mitochondrial lineages could have occurred after populations of L. brevicula recolonized the natural rocky habitats from a common glacial refugia after the last glacial maximum when the sea level rose. Indeed, the great drainages of the world produce genetic partitions in coastal marine organisms, such as the Yangtze River outflow ) exists from the YRE all the way along the Subei Coast until reaching ∼33.5°N; thereafter, it converges with southward coastal current from Haizhou Bay and turns offshore gradually in the vicinity of the Old Yellow River Delta ; Formal analysis (lead); Writing‐original draft . Meng‐Yu Li: Data curation (supporting); Formal analysis (supporting); Writing‐original draft (supporting). Teng‐Fei Xing: Investigation ; Resources . Jin‐Xian Liu: Conceptualization (lead); Funding acquisition (lead); Investigation ; Project administration (lead); Resources (lead); Supervision (lead); Writing‐review & editing (lead).Supplementary MaterialClick here for additional data file.


A new 16 X-short tandem repeat (STR) multiplex PCR system has recently been developed for Sr Lankans, though its applicability in evolutionary genetics and forensic investigations has not been thoroughly assessed. In this study, 838 unrelated individuals covering all four major ethnic groups  in Sri Lanka were successfully genotyped using this new multiplex system. The results indicated a high forensic efficiency for the tested loci in all four ethnicities confirming its suitability for forensic applications of Sri Lankans. Allele frequency distribution of Indian Tamils showed subtle but statistically significant differences from those of Sinhalese and Moors, in contrast to frequency distributions previously reported for autosomal STR alleles. This suggest a sex biased demographic history among Sri Lankans requiring a separate X-STR allele frequency database for Indian Tamils. Substantial differences observed in the patterns of LD among the four groups demand the use of a separate haplotype frequency databases for each individual ethnicity. When analysed together with other 14 world populations, all Sri Lankan ethnicities except Indian Tamils clustered closely with populations from Indian Bhil tribe, Bangladesh and Europe reflecting their shared Indo-Aryan ancestry. Their overpowering impact have confined the original inhabitants of the country to a few dry zone areas, forming a tribal group known as the Veddahs 2, represented by about 10,000 individuals3.Sri Lanka is an island country in South Asia, located in the Indian Ocean, close to India. Due to its strategic position at middle of the maritime silk route from China to Europe, it was well known to the outside world from ancient times as a trading hub. The diverse ethnicities that compose the 20 million population inhabiting the island as per the last population census1. The Sinhalese make a unique population in the world as the only ethnic group that speaks Sinhala, a branch of the Indo-European (Indo-Aryan) language family4. According to historical chronicles, the Bengali prince Vijaya and his seven hundred followers, who are descendants from the Indo-Aryans natives of the northern Indian subcontinent laid the foundation to the Sinhalese in 543 BCE4. They vanquished the aboriginal Veddas and converted Sri Lanka to a Sinhalese territory until the Dravidian rulers from South India invaded the northern part of the island in the fifth century AD4. Since then, there had been frequent migrations by South Indians into the country, which gave rise to the second largest ethnic group in Sri Lanka known as the “Ceylon Tamil” (2.27 million people representing 11.2%)1.Today, the Sinhalese make the largest ethno-cultural group in Sri Lanka, having a population of 15.17 million 4. The group now known as Moors comprise 9.2%1 (1.86 million) of the Sri Lankan population and maintain unique sociocultural features which are based largely on the Islamic faith. They speak a Dravidian language that contains large number of Arabic words that is generally referred to as ‘‘Arabic Tamil’’5. However, some scholars attribute the origin of Moors to South Indian traders, who later settled in Sri Lanka5. This view in part is based on the similarities shared by Sri Lankan Moors with the Tamil Muslims of Tamil Nadu. Indian Tamils make the 4th largest ethnic group in Sri Lanka and comprise the descendants from plantation workers brought to Sri Lanka from South India by the English rulers who colonized Sri Lanka in nineteenth century4. Comprising a relative minority of 0.84 million people 1, Indian Tamils are chiefly confined to the central hills in Sri Lanka with a relatively low admixture with other ethnic groups due to socio cultural reasons associated with their more recent immigrant status.A third ethnic group was established in the country when Arab traders visiting the country for commercial purposes settled in Sri Lanka in 1000 AD, leading to intermarriages with the Sinhalese and the Sri Lankan TamilsIn addition to these ethnicities, around 0.5% of the Sri Lankan population comprises other minor ethnic groups belonging to numerous descents. They include Malays (descendants from island of Java) Burghers  and other Chinese and African migrants who came to the island in the eighteenth and nineteenth centuries.6, Y chromosomal7 and mitochondrial markers9, none has utilized those present on the X chromosome. X-chromosome markers, particularly short tandem repeats (STRs), with the advantageous features of both autosomal and uniparental biomarkers, play an important role in evolutionary studies11 as well as in forensic genetics12.They assist in the interpretation of complex kinship cases on its own or in conjunction with other marker like autosomal STRs. Analysis of X chromosome STRs (X-STRs) is specially advantageous in complex cases, where at least one female is involved, such as in a deficient paternity case of a female child, cases involving female siblings sharing a common biological father, questioned relationships between paternal grandmother-granddaughter or other distant female relatives13. Additionally, at some rare instances, they can also serve in forensic case work in which female traces are to be identified in male background contamination14. The use of clusters of tightly linked X-STRs forming highly informative haplotypes is particularly effective in such cases14. In addition, X-chromosome markers have a proven utility in tracing the sex biased demographic history among populations with complex admixture and geneflow patterns. Consequently, X-chromosome markers have gained significant importance in population and forensic genetic studies in the past 2 decades. However, the routine practice of molecular genetics in Sri Lanka presently comprise only of autosomal, Y-chromosomal and mitochondrial DNA analyses. The scope of X-chromosome markers is yet to be investigated for Sri Lankans.Because of the demographic history and geneflow, the genetic position occupied by each of these ethnic groups, both at local and global scales is not clear. The wide array of genetic markers currently available provide an opportunity for reliably elucidating their genetic affinities. However, depending on the type of genetic markers used, the ancestral information of populations deduced from the analyses could be quite different. On the other hand, each of these different approaches can complement each other with their characteristic genetic information. Although a few previous studies that had been conducted to understand the genetic substructure and underlying heterogeneity of Sri Lankan ethnicities using autosomal15 with the aim of incorporating X-STR analysis in to molecular forensic and evolutionary genetics investigations in the country. Thirteen of these STR markers are in four closely linked clusters (each spanning < 3 cM) that are likely to produce stable haplotypes , Cluster II; DXS7132-DXS10079-DXS10074-DXS10075 (Xq12), Cluster III: DXS6801-DXS6809-DXS6789 (Xq21), Cluster IV; DXS7424-DXS101-DXS7133 (Xq22)). Additional three unlinked markers were also included from both p (DXS9902 at Xp22) and q (HPRTB at Xq26 and DXS7423 at Xq28) arms to have a better coverage of the X chromosome. The assay was validated for the Sinhalese using 200 unrelated individuals of which 120 were males. In the present study, we extended the analysis to evaluate the forensic efficiency of this novel 16 X-STR assay to all four major ethnicities in Sri Lanka  and constructed an allele and haplotype frequency database for Sri Lankans for forensic and kinship analysis purposes. Further, we have conducted a comprehensive analysis of the possible linkage disequilibrium (LD) among the selected X-STR markers. Here, we report for the first time, the X-STR based population genetic information of all four main ethnicities in Sri Lanka. In addition, Pairwise genetic distances based on Fst were also calculated between the Sri Lankan population and populations from South, South East and East Asia, Europe, Africa and Brazil based on the data extracted from literature to elucidate the genetic substructure between Sri Lankan and other global populations.Recognizing this vital need exist in the field of molecular genetics in Sri Lanka, we recently developed a multiplex X-STR system with 16 X-STR markers  , mean exclusion chance for trios and duos (MECtrio and MEC duo) calculated for the 16 individual loci based on the allele frequency data , polymorphism information content (PIC), power of discrimination for males and females (PDP > 0.05) though a subtle, but statistically significant variation was detected among populations within groups . The global AMOVA results as a weighted average over loci showed that most of the variance in the samples is attributable to within-individual variation (97.97%) and between ethnic group variation is around 0.18%. To better understand this observed population structure, pairwise comparisons  were carried out among all four ethnicities (Table P = 0.0000) and Moors  while Sinhalese, Sri Lankan Tamils and Moors are highly panmictic (P > 0.05). Further, the two Tamil ethnicities were shown to share a common genetic background (P > 0.05).A locus-by-locus analysis of molecular variance (AMOVA) was carried out including all 16 loci, grouping the four ethnicities based on their linguistic origins  DNA studies are also of much relevance to the present context. Despite that the number of mt DNA studies conducted on Sri Lankan ethnicities are very limited, the available reports closely agree with our observations and indicated a very fine genetic structure with a more closer genetic relationship among Sinhalese and Sri Lankan Tamils, in comparison to that among Sinhalese and Indian Tamils19, Bangladesh20 and Pakistan22), two from South East Asia , three from East Asia , five from Europe  two from Africa  and Brazil45 were compared  out of the nine common loci compared.These results suggest that allele distribution of the four ethnic groups of Sri Lanka is very similar to the two tested Indian populations and the Bangladesh population. Pakistani population also exhibit substantial similarity to Sri Lankan ethnic groups, though not to the same extent of Indian and Bangladesh populations. On the contrary, allelic distribution of many X-STR loci in Sri Lankan ethnic groups differ from Southeast Asian, East Asian, European and African populations. Among them, East Asian and African populations are the most genetically distant populations to Sri Lankans.18, Bangladesh20, Malaysia23, Thailand24, China25, Japan25, Taiwan30, Germany32, Italy36, Sweden41, Denmark42, North Portugal43, Somalia42, and Ivory Coast44). According to the results observed, Sri Lankans were clustered together not only with Indians and Bangladeshi, but also with Europeans. Indian Tamils were placed towards the periphery of this main cluster, while Southeast Asians, East Asians and Africans were placed at a distant, outside the main cluster.To further clarify the relationship between Sri Lankans and the world populations, pairwise Fst values were averaged over eight of the 16 studied X-STR loci  and were represented in a multidimensional scaling (MDS) plot  LD between the two marker pairs, DXS10074-XS10075  and DXS7132-DXS10075 . However, there was no LD detected between DXS10079 and DXS10074 among Sinhalese in contrast to the results obtained for our initial study, which was conducted with 120 Sinhalese males15. This disparity of observations might have caused by the limitations in the initial study with respect to the sample size requirements specified for LD analysis50. In cluster III, none of the markers showed a significant LD (corrected P = 0.0167), although there was a marginal LD (P = 0.0174) detected between DXS6801 and DXS6809 for Sinhalese population. Further, in addition to the pairwise LD analysis within separate clusters, pairwise LD was also analyzed between markers belonging to cluster III and IV, due to their relative close physical proximity (6.78 cM) compared to the other clusters. However, LD was not detected between any of the marker pairs (P > 0.05 for eight out of nine marker pairs) as shown in Table Population studies of various countries have illustrated that the LD is population specificm and PDf values for all these haplotypes were greater than 0.9 while MEC values ranged above 0.8.Since the haplotypes defined by those loci which are found to be in LD tend to behave as alleles, forensic efficiency parameters were calculated based on their observed haplotype frequencies and are given in Table 48. Indian Tamils who are tea estate workers, restricted mostly to central part of the country fits well into this description. In Sri Lanka, there are about 850,000 Indian Tamils, which had very limited genetic mixing with other populations due to social and cultural reasons. Nevertheless, only one loci pair among Indian Tamils showed LD according to our results. As pointed out by Kling et al.50, to acquire adequate power to detect LD in X-STR analysis, sample sizes over 200 are often needed. When considering the limited number of Indian Tamil samples used in the present study in calculating LD , it is possible that the low sample number to have masked the actual existence in LD among Indian Tamils. The same limitation is also valid for Sri Lankan Tamil and Moor ethnicities in which similarly low level of LD were detected. On the other hand, analysing a small sample from a large population can create LD, even among loci which are in linkage equilibrium, due to the under-representation of haplotypes51. In this light, it is advisable to increase the number of Sinhalese samples used for LD calculations , considering that there are about 15 million Sinhalese in the country. On the other hand, the high level of LD observed within Sinhalese might have resulted from its largely admixed nature. All these facts highlight the requirement of a more exhaustive data set with increased power to detect LD, before concluding on the true pattern of LD among Sri Lankan ethnicities.LD is generally expected to be high in populations, which are either small, reproductively isolated or having low population growth20, Indian Bhil tribe18 and Malaysians23 was quite low; i.e. no LD was reported among cluster I  or in cluster II markers . The marker, DXS10075, in which LD was detected with DXS7132 for Sinhalese was not investigated in any of these populations to make a comparison. However, it is noteworthy that all these studies were conducted with male samples between 100 and160, which might have posed a limitation in detecting true LD in these populations. On the other hand, LD was not observed for cluster III or cluster IV in a study that investigated 302 Pakistan males21, the only Asian population for which LD data are available for these clusters. These data are suggestive of the existence of a complex pattern of LD among Asians. In contrast, a high level of LD was reported within these four clusters for Europeans like Swedish52 and German55 populations, in studies conducted with 450–800 male individuals.In general, the LD reported earlier for South Asian and South East Asian populations like Bangladeshi56. However, a linkage analysis was not conducted for the 16 X-STR markers investigated in the current study. Nevertheless, a previous research conducted for three generation families of Chinese origin has reported a significant linkage with maximum LOD scores > 2.0 for all pairwise markers in the cluster II, III and IV indicating their tightly linked nature57.The genetic stability of the linked clusters and the degree of dependence between them can have a major influence on most forensic and kinship applications. The classical approach of studying such linkage between selected markers is via analysis of three generation pedigrees using LOD scores59. Likewise, the four markers included in the cluster II had been analyzed in two different combinations; i.e. DXS7132-DXS10079-DXS10074 (Argus X-12 kit) and DXS10079-DXS10074-DXS1007554. Therefore, to allow comparisons with these previous studies, the haplotype frequencies of above combinations are also listed in Supplementary Tables The haplotype frequencies obtained for the four ethnic groups for all four clusters are listed in Supplementary Tables As shown in Supplementary Table 25. Cluster II, on the other hand carries four markers compared to the other clusters, which consists of three markers each. This increased number of markers may have generated higher haplotype diversity with respect to cluster II among the studied populations. On the contrary, cluster III and cluster IV are equally informative (HD = 0.9873–0.9908 and 0.9882–0.9923 respectively), though not to the same extent as the clusters I and II. Nevertheless, in general, all four clusters showed a high haplotype diversity for all four ethnicities.Among the four clusters, both clusters I and II proved relatively more informative for all four ethnicities as reflected by the haplotype diversity (HD = 0.9964–0.9987 and 0.9935–0.9973 respectively). In cluster I, this observation may have caused by the two highly polymorphic markers, DXS10135 and DXS10148 as described above and is consistent with other previously published population datam > 0.999999991334440) and females (CPDf > 0.999999999999996) as well as combined MEC indices calculated for deficiency (CMECKru > 0.999999242880176), normal trio (CMECDes-trio > 0.999999984443189) and duo cases (CMECDes-duo > 0.999999435330137) were equally high for all four ethnicities  and data analysis allele designation was performed using GeneMapper IDX software .The study was conducted with the approval of the Ethics Review Committee, Institute of Biology, Sri Lanka (ERC IOBSL 135 11 15) and the study was performed in line with the principles of the Declaration of Helsinki. Written informed consent was obtained from all individual participants included in the study. Finger pricked blood samples were collected from 838 unrelated individuals from the four ethnic groups in the Sri Lankan population; 426 samples from Sinhalese , 154 samples from the Sri Lankan Tamils , 128 samples from Indian Tamils , and 130 samples from Sri Lankan Moors . Genomic DNA was extracted using Chelex-100 methodKruger), mean exclusion chance in Duos (MECDesmaris duo), mean exclusion chance in trios (MECDesmaris trio), power of discrimination for females (PDf), power of discrimination for males (PDm) were calculated using chromosome X web (http://www.chrx-str.org) for all X-STR loci and haplotypes defined by the four clusters using MATLAB software (version R2017a) for all four ethnic groups. For those loci under LD, the parameters were also evaluated based on frequencies of haplotypes defined by them using the latter software.All population genetic parameters were calculated using ARLEQUIN 3.5. Allele and haplotype frequencies, exact test of differentiation for male and female allele frequencies, conformity of female subsamples to Hardy–Weinberg equilibrium and pairwise test of LD between pairs of markers within clusters of linked loci in the male sub samples were analysed separately for all four ethnic groups. LD between the markers of cluster III and IV was also analysed, considering the close physical proximity of the two clusters (6.78 cM). Forensic parameters, i.e. polymorphism information content (PIC), expected heterozygosity (He), mean exclusion chance in deficiency 62 software using the Unweighted Pair Group Method with Arithmetic mean (UPGMA) method. The reliability of phylograms was estimated by bootstrapping 2000 replicates over loci and the extended majority rule consensus trees were inferred. To compare the Sri Lankan ethnicities with populations from other countries in the world, locus by locus pairwise genetic distances (Fst) were generated based on data available in the literature. Resulting Fst values were averaged over loci and represented in a multidimensional scaling (MDS) plot using IBM SPSS Statistics Version 21 statistical package63.Locus-by-locus analysis of molecular variance (AMOVA) was conducted by grouping the four ethnicities based on their linguistic origin; i.e. Indo-Aryan origin  versus Dravidian origin (Tamils and Moors) to create a hierarchical structure. Nei’s average number of pairwise differences within and between populations was used to detect pairwise differences among the four ethnic groups. The null distribution of pairwise Fst values was obtained by permuting haplotypes between populations for 1000 times. The significance level was kept at 0.05 and all analyses were conducted using Arlequin software v.3.5.1.2Supplementary Information.