JOURNAL OF THEWORLD AQUACULTURE SOCIETY

Vol. 43, No. 1February, 2012

Genetic Diversity and Population Structure in the HeavilyExploited Korean Rockfish, Sebastes schlegeli, in Korea

Hyesuck An1, Mi-Jung Kim, Kwangjae Park, Keechae Cho, Bongseong Bae,Jaewoo Kim and Jeong-In Myeong

Genetics and Breeding Research Center, National Fisheries Research and DevelopmentInstitute, Gyeongsangnamdo 656-842, Korea

AbstractThe Korean rockfish, Sebastes schlegeli, is a valuable and intensively exploited species in Korea.

We discuss the genetic diversity and genetic structure of four Korean rockfish populations usingeight microsatellite loci. In total, 161 different alleles from 138 individuals were observed. Averageallele number per locus ranged from 2.5 to 23 and allelic richness varied from 13.38 to 14.63within a population. Despite a long history of stocking practices, we found very high levels ofpolymorphism (mean heterozygosity = 0.810), which is comparable to other congeneric species. Nosignificant difference in genetic diversity and molecular genetic variance (F ST and RST) was observedamong four local samples (P > 0.1). Little indication of contemporary inbreeding (F IS= 0.051) orpopulation structure (K = 1 ) was detected. This absence of differentiation may reflect high levelsof gene flow along the coast of Korea. Our study demonstrates that rockfish in Korea should bemanaged as a single unit. Currently, the species does not appear to be genetically threatened, but thepotential for a rapid loss of genetic diversity remains. This information on the genetic characteristicsof Korean rockfish populations has important implications for fisheries management and conservationefforts, and will aid in the sustainable exploitation of the fishing resources and the preservation ofbiodiversity.

The Korean rockfish, Sebastes schlegeli,of the live-bearing genus Sebastes belongsto the most species-rich genus of the fam-ily Scorpaenidae (Nelson 1994). It inhabitscoastal rocky reefs and feeds on benthic ani-mals and is generally known as a nonmigra-tory marine species. After a 2- to 3-monthpelagic stage, juveniles settle and adults arerelatively sedimentary, traveling limited dis-tances within their home reefs (Kim and Han1991). This species provides commerciallyvaluable recreational and commercial fisheriesin Pacific Asia. In Korea, while the produc-tion of the Korean rockfish fishery has notchanged or declined, aquaculture production ofKorean rockfish increased continuously sincethe early of 1990s, reaching a historical maxi-mum of approximately 35,500 tons in the year2007 (MOMAFK 2008), and Korean rockfishcomprised approximately 30% (nearly 27,500

1 Corresponding author.

tons) of the total annual average aquacultureproduction in 2006, making it an importantaquaculture species in Korea (Park 2007). Inaddition to increased Korean rockfish farming,stock enhancement programs which the Koreangovernment has sponsored for natural resourcerestoration have been introduced throughoutthe coastal areas of Korea since the late1980s. In 2007, approximately 2 million arti-ficial Korean rockfish juveniles were released.Although mass releases of cultured Koreanrockfish are expected to have an immediateeffect on stock abundance, they raise con-cerns that can potentially lead to changes inthe genetic structure of wild populations. Fur-thermore, in recent years, many impedimentshave hindered the production from aquacultureand economic success of this species, such asslow juvenile growth rates and low larval sur-vival rates (pers. comm.). This situation hasfostered a need for a basic understanding ofpopulation genetic characteristics in practical

© Copyright by the World Aquaculture Society 2012

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74 AN ET AL.

management. However, despite more than 20 yrof stocking practices in Korea, no informationis currently available on genetic diversity ofKorean rockfish populations. Although we can-not obtain genetic information regarding naturalpopulations before the commencement of stock-ing, knowledge regarding the present popula-tion structure, levels of gene flow, and geneticdiversity within and among populations thatare harvested for commercial purposes can pro-vide useful information for developing conser-vation and management plans. Understandingthe processes and the organization of geneticdiversity and genetic resources is essential forthe sustainable management of exploited fishpopulations (FAO 1993).

Many studies have been conducted on thegenetic features of marine fishes using sev-eral kinds of molecular markers (Sugiyamaet al. 1986; Alcivar-Warren et al. 1997; Ricoet al. 1997; Sekino and Hara 2001; Higuchiand Kato 2002; Sekino et al. 2002; Palm et al.2003). In particular, microsatellite DNA mark-ers have been used extensively to detect geneticdiversity and to evaluate population structurein marine species because of their high poly-morphism, ease of use with polymerase chainreaction (PCR) amplification, and codominantMendelian inheritance, as compared to manynuclear loci (Liu et al. 2005; Lundrigan et al.2005; Sekino et al. 2005). However, the geneticfeatures of wild Korean rockfish populationshave not been examined using high-resolutionDNA markers.

The aim of this study was to assess geneticdiversity within and among the major wildKorean rockfish populations around Korea andto examine the genetic population structureamong these populations using microsatelliteDNA markers.

Materials and Methods

Sample Collection and DNA Extraction

We collected a total of 138 wild adultS. schlegeli from four localities at east (Dong-hae, 40 individuals), west (Buan, 30), andsouth (Yeosu, 37) coast of Korean Peninsulaand at Jeju Island (31) between February and

October 2006 using local fishing boats (Fig. 1).Fin clips were preserved in 100% ethanolbefore being transported to the lab. Total DNAwas extracted using a MagExtractor-genomicDNA purification kit (Toyobo, Osaka, Japan).DNA extraction was performed according tothe manufacturer’s recommendations for anautomated DNA extraction system, MagExtrac-tor MFX–2100 (Toyobo). Extracted genomicDNA was stored at −20 C until PCR.

Microsatellite Genotyping

In total, 138 Korean rockfish from the fourpopulations were genotyped. Eight highly vari-able microsatellite loci from 14 published rock-fish microsatellite loci (KSs2A, KSs3, KSs6,KSs8, KSs11B, KSs16, KSs20A, and KSs27A)were used to investigate the genetic relation-ships among the four wild Korean rockfishpopulations distributed around Korea. Primersequences, microsatellite repeat sequences, andthe optimal annealing temperature for eachlocus are provided in An et al. (2009b). Theforward primer from each primer set was5′-fluorescent labeled with one of three dyes: 6-FAM, HEX, or NED (Applied Biosystems, Fos-ter City, CA, USA). PCR amplification of eightmicrosatellite loci was carried out using anRTC 200 instrument (MJ Research, Waltham,MA, USA) in 10 μL of solution containing10–50 ng DNA, 1× ExTaq buffer, 0.2 mMdNTPs, 10 pmol of each primer, and 0.25U Taq DNA polymerase (TaKaRa BiomedicalInc., Shiga, Japan). The amplification protocolincluded an initial denaturation for 11 min at95 C followed by 35 cycles of 1 min at 94 C,1 min at the optimal annealing temperature, and1 min at 72 C, with a final extension step of5 min at 72 C. For genotyping, 1 μL of PCRproduct was added to each reaction contain-ing formamide with a size standard, GeneScan-400HD (ROX) (Applied Biosystems), and elec-trophoresed using an ABI3130 DNA sequencer(Applied Biosystems). The fragment lengthsof the PCR products were determined usingGeneMapper software version 4.0 (AppliedBiosystems).

GENETIC DIVERSITY AND STRUCTURE OF KOREAN ROCKFISH IN KOREA 75

130°125° 127.5°122.5°

130°125° 127.5°122.5°

40°

35°

37.5°

40°

35°

37.5°

KOREA

CHINA

JAPAN

YELLOW SEA

N

E

0 50 100 km

Yeosu

Donghae

Buan

Jeju

EAST SEA

Buan

Jeju

Figure 1. Sampling sites for four rockfish populations in Korea.

Data Analysis

Statistical genetic analyses were conductedfor four populations of S. schlegeli. PCRerrors as a result of null alleles, stuttering, orallele dropout were tested using Micro-Checker(version 2.2.3; 1000 randomizations) (VanOosterhout et al. 2004). Scoring and humanerror were estimated by duplicating analyses.As genetic diversity parameters, the number ofalleles per locus (NA), allele size range (S),frequency of the most common allele (F), andnumber of unique alleles (U) were determinedfor each local sample at each locus using theprogram Genepop version 4.0, which is avail-able on the Internet (http://kimura.univ-montp2.fr/∼rousset/Genepop.htm). Allelic richness(AR) was corrected (using the rarefactionmethod of FSTAT version 2.9.3.2 [Goudet

2002]) to the smallest sample (n = 30). Anallelic richness can be directly comparedamong populations, irrespective of samplesize (El Mousadik and Petit 1996). Fixationindex values that estimate inbreeding withinindividuals in a population (calculated asFIS, the “inbreeding coefficient”) were alsocalculated, and the significance of positive ornegative values was tested by using FSTAT.For analysis of molecular variance (AMOVA,Excoffier et al. 1992), components of variancewithin and between populations based on theinfinite allele model (IAM) were estimatedusing the program Arlequin 3.0 (Excoffier et al.2005). The significance of AMOVA compo-nents was tested using 1000 permutations.To estimate genetic heterozygosity among theentire set of pairwise population samples,unbiased expected and observed heterozygosity

76 AN ET AL.

values (He and Ho, respectively) (Nei 1987)were calculated. Deviations from Hardy–Weinberg equilibrium (HWE) for each locusand globally across populations and loci weretested using probability tests or exact tests bythe Markov chain procedure using Arlequin.

The extent of population subdivision wasexamined by calculating global multilocusFSTvalues (1000 permutations) (Weir and Cock-erham 1984) and RSTestimates (Slatkin 1995;Rousset 1996) using Arlequin. RST incorporatesthe correlation of the weighted mean allele size,expressed as the number of tandem repeats. Sig-nificance levels were adjusted for multiple testsusing the sequential Bonferroni correction tech-nique (Rice 1989). Patterns of population struc-ture were further investigated using the modelbased Bayesian clustering procedure in Struc-ture version 2.2 (Pritchard et al. 2000; Falushet al. 2003), which assigns individuals based ontheir multilocus genotypes into K populations.We performed five runs for each value of K

(number of putative populations) from 1 to 5and employed the Markov chain method with10,000 iterations (burn-in) and 50,000 Markovchain Monte Carlo repetitions. The simulationwas performed under the admixture model withcorrelated allele frequencies (default parame-ters). We then chose the most appropriate clus-ter number (K) using the criterion of Evannoet al. (2005), which is based on �K .

Genetic distances between populationswere estimated based on Cavalli-Sforza andEdwards’s chord distance DCE (Cavalli-Sforzaand Edwards 1967). A phylogenetic tree wasconstructed based on pairwise genetic distancesfor all samples using the neighbor-joining(NJ) method of the program Population ver-sion 1.2.30 (http://bioinformatics.org/∼tryphon/populations/) to examine genetic relationshipsbetween populations.

Results

Genetic Diversity

The allele frequencies of eight microsatelliteloci were analyzed from 138 individuals fromfour Korean rockfish populations that were cap-tured along the Korean coast (Fig. 1). Genetic

variability, reflected in the degree of heterozy-gosity and the number of alleles, was highexcept at one locus, KSs20A. A summary of thegenetic diversity in each population is shownin Table 1. In total, 161 different alleles werescored at the eight loci. Each population hadsome unique alleles and no population had adiagnostic allele. Among the loci, the num-ber of alleles varied greatly and ranged from3 (KSs20A) to 34 (KSs11B), with an averageof 20.1 alleles across all loci.

Micro-Checker analysis showed that lociKSs16 in the Buan population and KSs6 inthe Yeosu population could be affected by anull allele. However, we used these loci in thisstudy because null alleles could affect only onepopulation and no indications of allele scoringerrors due to stuttering and large allele dropoutwere observed.

Mean allelic richness numbers (for compar-ing the number of alleles between different sam-ple sizes) varied from 2.5 for KSs20A to 21.8for KSs11B. The highest value was observedwith KSs11B in the Buan sample, with valuesof up to 24 alleles. However, no significant dif-ference was found among the four local samplesat most loci.

Mean observed and expected heterozygosi-ties ranged from 0.272 in KSs20A to 0.906 inKSs11B with a mean of 0.770, and from 0.287in KSs20A to 0.938 in KSs11B with a meanof 0.810, respectively. Observed heterozygos-ity varied greatly for a given locus among thesamples, except at two loci, KSs3 and KSs11B.When heterozygosity was pooled over loci foreach sample, differences in mean observed het-erozygosity among samples were observed thatranged from 0.737 in the Yeosu sample to0.806 in the Jeju sample. However, despitethese differences, no clear difference in averageheterozygosity was observed among samples.

In total, 27 alleles were found to be uniqueto the local samples examined, and ranged fromfive in the Yeosu sample to eight in the Buansample. As the number of individuals analyzeddiffered among the samples, the results shouldbe interpreted with caution.

Of the 32 independent loci examined byHardy–Weinberg tests, five (15.6%) were found

GENETIC DIVERSITY AND STRUCTURE OF KOREAN ROCKFISH IN KOREA 77

Table 1. Allelic variability observed at eight microsatellite loci in four Sebastes schlegeli populations.a

Microsatellite loci

Population (No) KSs2A KSs3 KSs6 KSs8 KSs11B KSs16 KSs20A KSs27A Mean

Captured Buan (30)NA 16 12 10 19 24 22 3 11 14.63AR 16.00 12.00 10.00 19.00 24.00 22.00 3.00 11.00 14.63S 110–166 136–184 140–160 176–230 106–182 108–168 232–254 208–232 —F 0.233 0.283 0.433 0.267 0.15 0.217 0.883 0.233 —U 1 1 1 0 3 2 0 0 1.00He 0.879 0.851 0.780 0.893 0.951 0.923 0.213 0.859 0.794Ho 0.933 0.833 0.667 0.733 0.900 0.833 0.233 0.933 0.758FIS −0.064 0.021 0.147 0.181 0.054 0.099 −0.097 −0.088 0.045— (0.981) (0.916) (0.166) (0.000) (0.054) (0.012) (1.000) (0.933) —P 1.000 0.912 0.208 0.000 0.074 0.066 1.000 0.916 —

Captured Yeosu (37)NA 14 13 9 23 23 22 2 9 14.38AR 13.35 12.3 8.96 21.60 21.48 20.55 2.00 8.77 13.63S 132–166 134–170 140–156 176–230 120–176 110–166 250–252 210–230 —F 0.216 0.284 0.230 0.162 0.189 0.176 0.838 0.230 —U 0 3 0 0 0 1 0 1 0.63He 0.884 0.848 0.858 0.937 0.934 0.936 0.275 0.852 0.816Ho 0.892 0.892 0.514 0.865 0.865 0.865 0.216 0.784 0.737FIS −0.008 −0.052 0.405 0.078 0.075 0.077 0.217 0.081 0.098— (0.945) (0.080) (0.000) (0.027) (0.046) (0.136) (0.0217) (0.678) —P 0.945 0.108 0.000 0.109 0.040 0.164 0.213 0.643 —

Captured Donghae (40)NA 13 11 9 25 25 24 2 9 14.75AR 11.66 10.62 8.88 21.57 21.93 21.36 2.00 9.00 13.38S 132–172 138–170 140–156 174–236 120–186 110–176 250–252 214–232 —F 0.275 0.238 0.325 0.188 0.150 0.150 0.825 0.200 —U 2 0 0 3 1 1 0 0 0.88He 0.823 0.864 0.827 0.917 0.936 0.935 0.292 0.877 0.809Ho 0.800 0.825 0.775 0.875 0.925 0.950 0.250 0.825 0.778FIS 0.028 0.046 0.064 0.046 0.012 −0.016 0.147 0.060 0.039— (0.699) (0.693) (0.355) (0.569) (0.485) (0.693) (0.325) (0.708) —P 0.617 0.699 0.343 0.614 0.241 0.762 0.324 0.731 —

Captured Jeju (31)NA 12 12 10 24 20 20 3 10 13.88AR 11.93 11.93 9.97 23.64 19.80 3.00 10.00 13.76 —S 132–166 138–170 140–158 160–246 124–180 114–170 250–254 214–232 —F 0.274 0.242 0.355 0.161 0.161 0.161 0.774 0.306 —U 0 1 1 3 1 1 0 0 0.88He 0.857 0.871 0.824 0.935 0.932 0.932 0.368 0.847 0.821Ho 0.774 0.839 0.806 0.968 0.935 0.935 0.387 0.806 0.806FIS 0.098 0.038 0.022 −0.035 −0.004 −0.004 −0.053 0.048 0.018— (0.054) (0.267) (0.419) (0.518) (0.972) (0.975) (1.000) (0.340) —P 0.044 0.303 0.384 0.221 0.934 0.985 1.000 0.379 —

Mean wild populationsNA 13.75 12.00 9.50 22.75 23.00 22.00 2.50 9.75 14.41AR 13.24 11.71 9.45 21.45 21.80 20.93 2.50 9.69 13.85U 0.75 1.25 0.5 1.5 1.25 1.25 0 0.25 0.84He 0.861 0.859 0.822 0.921 0.938 0.932 0.287 0.859 0.810Ho 0.850 0.847 0.691 0.860 0.906 0.896 0.272 0.837 0.770FIS 0.013 0.013 0.017 0.065 0.035 0.037 0.069 0.031 0.051

No = Number of samples; NA = number of alleles per locus; AR = allellic richness; S = size in bp of alleles;F = frequency of the most common allele; U = number of unique alleles; He = expected heterozygosity; Ho = observedheterozygosity; FIS = inbreeding coeficient; P = probability of significant deviation from Hardy–Weinberg equilibriumare given for each population and locus.

aCalculations assume that individuals with one microsatellite band are homozygous for the allele. Number in parenthesesbelow FIS indicates the probability of significant heterozygosity excess or deficit.

78 AN ET AL.

to deviate significantly from equilibrium (P <

0.05), and three (9.4%) of these deviationsremaining significant after Bonferroni correc-tion (Rice 1989) for multiple observationsacross the eight loci. Significant deviationswere not evenly distributed among samples orloci. They were not associated with a particu-lar locus or sample. One deviation from equi-librium was observed within the Buan sam-ple at the KSs8 locus and two deviationswere observed within the Yeosu sample attwo loci, KSs6 and KSs11B. These deviationsreflected a deficit in heterozygosity. Inbreedingcoefficients were low over all polymorphic loci(FIS = 0.051; 95% confidence interval, 0.025–0.089) and at each locus (Table 1).

Locus KSs20A was tri-allelic and hence theleast variable. Allele frequency distributions forthe eight selected loci are shown in Figure 2.These data reveal differences among locations.Differences in allele frequencies are indicativeof genetic divergence among samples.

Population Genetic Differentiation

The population genetic relationship accord-ing to DCE’s chord distance (Cavalli-Sforza andEdwards 1967) showed two regional groups:the first group was composed of two localsamples (Donghae and Jeju) and the secondgroup was composed of the others (Buanand Yeosu) (data not shown). However, thedegree of allelic differentiation through allelicand genotypic frequencies of all polymor-phic loci was not significantly heterogeneousamong populations after sequential Bonferronicorrection for multiple tests. Genetic differ-entiation among Korean rockfish populationsinhabiting Korean waters were estimated bycomparing DCE and mean pairwise FST andRST values between each pair (Table 2). Wefound that overall pairwise FSTandRST valueswere low. RST values were similar but gen-erally higher than FSTvalues. Slatkin demon-strated that FST tends to underestimate the truelevel of genetic differentiation when applied tomicrosatellite data (Slatkin 1995). However, theAMOVA results corroborated that no signifi-cant molecular genetic variance (FST and RST)

was associated with subdivisions among thefour localities (0.0028 and 0.0085, respectively;P > 0.05).

We found evidence for a single populationcluster in Structure. For K = 1, estimates ofposterior probabilities approached 1, whereasfor K = 2–5, high variance was observedamong α values, and all individuals wereroughly symmetrical and admixed over K

populations (i.e., no strong population assign-ments), which is consistent with a lack ofpopulation structure.

Discussion

Genetic variability estimates for the eightmicrosatellites suggested that these loci wouldprovide more genetic information than allozy-mic loci and sequence variability in themitochondrial DNA control region (Sugiyamaet al. 1986; Higuchi and Kato 2002). Intotal, 161 alleles were found at polymorphicloci (average per locus = 20.1), although notall loci were equally variable. Specifically,KSs8, KSs11B, and KSs16 displayed greaterallelic diversity as well as higher levels ofheterozygosity.

In the present study, the number of alle-les per locus and the levels of genetic diver-sity did not differ among four local sam-ples and were slightly higher relative to thosereported in other Sebastes species and in othermarine fish species. This results (average allele= 20.1; average He = 0.81) are not atypi-cal. Molecular genetic diversity in fish hasbeen found to be associated with life historytraits reflecting habitat types. Marine speciesgenerally possess significantly higher levelsof genetic diversity (average He = 0.79) thanfreshwater (average He = 0.46) or anadro-mous (average He = 0.68) species (DeWoodyand Avise 2000). For example, other studiesusing microsatellite markers have demonstratedexpected heterozygosities of 72–75% and aver-ages of 17.3, 11.8, and 13.5 alleles per locusfor Sebastes rastrelliger (six loci) (Buonac-corsi et al. 2004), Sebastes caurinus (nineloci) (Buonaccorsi et al. 2002), and Sebastesmacdonaldi (seven loci) (Rocha-Olivares et al.

GENETIC DIVERSITY AND STRUCTURE OF KOREAN ROCKFISH IN KOREA 79

0.000

0.100

0.200

0.300

0.400

0.500

0.600

0.700

0.800

0.900

232

208210214216218220222224226228230232234

KSs3

KSs2A

KSs6

KSs11B

KSs16

KSs20A

KSs27A

Observed frequency

0.000

0.050

0.100

0.150

0.200

0.250

1101321341361381401421461481521541561581601621641661720.000

0.050

0.100

0.150

0.200

0.250

0.300

1341361381401441461481501541561581601621641661681701840.000

0.050

0.100

0.150

0.200

0.250

0.300

0.350

0.400

1401421441461481501521541561581600.000

0.020

0.040

0.060

0.080

0.100

0.120

0.140

0.160

0.180

0.200 160

174178182186190194198202206210214218222226230236

0.000

0.020

0.040

0.060

0.080

0.100

0.120

0.140 106

120124128132136140144148152156160164168172176180186

0.000

0.020

0.040

0.060

0.080

0.100

0.120

0.140

0.160

0.180 108

112118122126130134138142146150154158162166170

250

252

254

0.000

0.050

0.100

0.150

0.200

0.250

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80 AN ET AL.

Table 2. DCE distances (below the diagonal), mean F ST estimates, and mean RST estimates (above the diagonal)between each pairing of four Sebastes schlegeli populations.a

Population Captured Buan Captured Yeosu Captured Donghae Captured Jeju

Captured Buan — 0.0066NS (0.0302NS) 0.0070NS (0.0012NS) 0.0081 (−0.0032NS)Captured Yeosu 0.2718 — 0.0006NS (0.0205NS) −0.0036NS (−0.0094NS)Captured Donghae 0.2800 0.2358 — −0.0013NS (−0.0069NS)Captured Jeju 0.3027 0.2570 0.2405 —

aDCE distance (Cavalli-Sforza and Edwards 1967) and pairwise FST (Cavalli-Sforza and Edwards 1967) and RST

(Rousset 1996) are measures of genetic distance and genetic differentiation between populations, respectively. Number inparenthesis indicates RST. NS is nonsignificant after sequential Bonferroni correction.

∗P < 0.05 from a multilocus test that there is no genetic differentiation in population pair after corrections for multiplecomparisons.

2003), respectively. Eight microsatellite locidescribed for four North Atlantic redfish(Sebastes fasciatus, Sebastes mentella, Sebastesmarinus, and Sebastes viviparus) were alsohighly polymorphic (0.5 ≤ He ≤ 0.96) and atleast half the loci had He > 0.8 in all species(Roques et al. 1999). Our microsatellite surveyprovided no evidence that the long history ofstocking practices in Korea have significantlyaffected the genetic variability of wild popula-tions to date and indicated genetic diversity inKorean rockfish around Korea appears to havebeen maintained at a high level.

Microsatellite analysis of four Korean rock-fish populations revealed homogeneous geneticvariability with a slight tendency for deficien-cies in heterozygous genotypes. In large pan-mictic and isolated populations, neutral geneticmarkers are expected to show no change inallele frequency through generations on a shortevolutionary timescale. However, in the presentstudy, we found departures from HWE, whichwere mainly caused by heterozygote deficien-cies at three loci. The observed deficit in het-erozygotes as compared with HWE could becaused by natural selection, phenotypic assor-tative mating, inbreeding, and/or null alleles.As no other loci except three loci showedany significant HWE departures, the significantdepartures from HWE were likely caused byassortative mating, or inbreeding. One may rea-sonably believe that a locus-dependent effect,such as null alleles, created the deficiencies inheterozygotes. Null alleles, frequently found atmicrosatellite loci, are the most likely causesfor the Hardy–Weinberg disequilibrium (Callen

et al. 1993). In fact, Micro-Checker analysisrevealed the presence of null alleles at locusKSs16 in the Buan population and at locusKSs6 in the Yeosu population. The presenceof null alleles has been reported in many otherfish species (Banks et al. 1999; An et al. 2009a,2010; Kim et al. 2010). Alternatively, randomvariation and/or the small sample size mightaccount for the HWE departures.

None of the eight loci showed significantgenetic heterogeneity among the four popula-tions in terms of allele frequency distributionsand pairwise FST values. Bayesian clusteringanalysis indicated that the four Korean rockfishpopulations were composed of a single clus-ter. The absence of genetic differences in thisstudy suggests that sufficient gene flow existsamong the populations to prevent detectablegenetic differentiation and that these popula-tions are probably a single population. Likeother benthic marine organisms, the life cycle ofS. schlegeli includes a relatively long pelagiclarval and early juvenile stage that lasts from2 to 6 months (Kim and Han 1991). Althoughthe mode and extent of larval dispersal is notclear, the existence of separation-floating-typeeggs has often been assumed to facilitate large-scale larval dispersal, which can result in highlevels of gene flow between populations, par-ticularly when they are geographically close.Currents or gyres may effectively mix geneticcomponents among populations throughout theKorean coast and lead to reduced genetic differ-entiation. Therefore, efficient passive larval dis-persal by oceanic currents may act to homoge-nize the genetic composition of Korean rockfish

GENETIC DIVERSITY AND STRUCTURE OF KOREAN ROCKFISH IN KOREA 81

populations around Korea, even if the extent ofadult movement is limited.

Additionally, more than 20 yr of stockingpractices in Korea may be one of the majorfactors influencing patterns of geographic distri-bution and population structure in this species.Translocations of Korean rockfish within andamong the coastal regions have considerablyoccurred in recent decades and “unofficial”cross-regional stocking still takes place (weinformed by three hatchery managers). Further-more, Korean rockfish aquaculture is extensivein the country, and these activities may intro-duce juveniles and/or adults into other coastalregions. Therefore, it is possible that the trans-portation of Korean rockfish within and amongthe coastal regions and cross-regional stock-ing may account for some gene flow of thesecoastal regions. This scenario and these con-ditions might support our results. The findingof high genetic diversity does not necessar-ily suggest that there is no impact from 20yr of intensive stocking. Heterozygosity is notsensitive to genetic changes, and the stockingis not expected to reduce genetic diversity ofthe wild population short-term unless the wildpopulation is largely replaced. On the otherhand, population structure is sensitive to geneflow. Cross-regional stocking, if significant,may have contributed to the lack of populationstructure. Similar results have been shown for afew other Sebastes species. An early allozymestudy found no evidence of stock structurein chilipepper rockfish (Sebastes goodei ) col-lected from the coasts of California, Oregon,and Washington (Wishard et al. 1980). Mexicanrockfish, the southernmost of the northeasternPacific rockfishes, also shows no evidence ofgenetic differentiation. Despite reasonable lev-els of polymorphism, population samples fromthroughout the Mexican rockfish’s range werenot distinct when analyzed using both mtDNAsequence information (Bernardi et al. 2003) andseven microsatellite loci (Rocha-Olivares et al.2003). With 16 microsatellite loci, kelp rockfish(Sebastes atrovirens) specimens collected froman 800-km stretch along the central Californiacoastline exhibited apparent genetic homogene-ity (Gilbert-Horvath et al. 2006). Furthermore,

Sugiyama et al. (1986) examined S. schlegeliusing allozyme analysis, and their data showthat local populations in the northern partof the Sea of Japan were not geneticallydivergent. Oceanographic features can stronglyaffect population structure, but conclusions ofgenetic homogeneity should be drawn caution,even when geographically distinct samples areincluded. The occurrence of geographically dis-tinct spawning groups increases the probabilitythat these groups are also genetically different.Therefore, other possibilities should be takeninto consideration; the population homogene-ity revealed in this study may have been dueto insufficient information and future geneticinvestigation need to be based on larger sam-ple size, potentially more microsatellite loci (ifavailable), and a temporal design.

As discussed above, Korean rockfish pop-ulations do not appear to be well structured,which seems to indicate near panmixia eventhough adult migrations and movement mightbe extremely limited. Therefore, rockfish inKorea should be managed as a single unit. Cur-rently, the species does not appear to be genet-ically threatened, but the potential for a rapidloss of genetic diversity remains. In terms ofconservation, monitoring genetic variation andcontrolling inbreeding is desirable in a com-mercial breeding program. Such a low levelof migration would be useless for rebuildingstocks depleted through overfishing, at least ontimescales of interest to fishery managers. Sub-stantial rebuilding periods would be requiredbefore immigrations of juveniles could return astock to its former size.

In summary, the results of this study found nogenetic structuring among the four wild rock-fish populations in Korea. Such findings haveimportant implications for the preservation andfurther genetic management of Korean rockfish.

Acknowledgments

This work was funded by a grant from theNational Fisheries Research and DevelopmentInstitute (NFRDI), contribution number RP-10-BT-036. The views expressed herein are those

82 AN ET AL.

of the authors and do not necessarily reflectthose of the NFRDI.

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