Sly syndrome

ABSTRACT Amplified fragment length polymorphism (AFLP) and selective amplified microsatellite polymorphic loci (SAMPL) were used for a survey of genetic changes over three generations and search for sex-specific markers in a breeding program of Chinese shrimp Penaeus chinensis. For genetic survey, a total of 247 and 140 clearly defined bands from 6 AFLP and 4 SAMPL primer sets, respectively, were generated. Both estimated percentage of polymorphic loci (ranging from 41.3% to 47.8%) and average gene diversity (ranging from 0.168 to 0.190) were not significantly different from each other among generation samples, suggesting no significant change at level of genetic variation by AFLP and SAMPL analysis. Despite the frequency change of band-presence allele at all loci over generations showed no clear and traceable patterns, the values of genetic distances and identities between founder stock and sequential generations reflected the accumulation of genetic changes over generations, probably due to isolation and selection. Analysis of molecular variance (AMOVA) and pairwise [[PHI].sub.PT] statistics of AFLP and SAMPL data indicated that significant genetic variation was distributed among generation samples (P < 0.01). The use of more variable markers may help further examination of genetic change over generations in more details. Search for sex-specific markers with AFLP and SAMPL loci in this study failed to detect any putative markers, despite 2,110 bands in total were generated through extensive screening with 25 AFLP and 16 SAMPL primer pairs. The inability in detection of sex-specific markers may be due to any of several reasons such as weak correlation between the genotypic and phenotypic sex, high genetic diversity in sex-related regions, or just lack of enough number of loci for screening.

KEY WORDS: shrimp, Penaeus chinensis, AFLP, SAMPL, genetic changes, sex-specific markers

INTRODUCTION

The Chinese shrimp, Penaeus chinensis, has been an important species for the shrimp fishery for many decades in China (Yu & Chan 1986). Its aquaculture has developed rapidly since the success of artificial propagation in early 1980s and the production reached 200,000 tons per year in the early 1990s (Wang et al. 1997). Unfortunately, the extensive outbreaks of shrimp diseases (mainly white spot syndrome virus, WSSV) in 1993, and the following few years resulted in significant decline in production in those intensive production areas. The development of disease-resistant strains of Chinese shrimp represents a major task for the scientific and aquaculture community.

A selection program aimed to develop disease resistance (mainly to WSSV) strains was initiated in 1998, and mass selection has been conducted for three generations (a higher survival rate than that in control was observed). For a breeding program, it is usually important that not only the phenotypic performance of the selected strain be closely checked, but also genetic changes over generations be monitored carefully. A major concern for selected populations is possible loss of genetic variability and inbreeding (Allendorf & Ryman 1987, Hedgecock & Sly 1990, Hedgecock et al. 1992, Gaffney et al. 1992). Loss of genetic variation reduces response to selection and severe inbreeding may lead to poor survival and slow growth (Virjenhoek et al. 1990, Launey & Hedgecock 2001).

Shrimp still remains among the list of aquatic animals in which little is known about sex differentiation and determination. Although significant difference in growth rate exists between female and male, as with many other species, no sex chromosomes has been detected yet (Xiang et al. 1993), and no sex-specific genetic marker has been reported in P. chinensis.

Advances in molecular biology have provided various polymorphism techniques for study of genetic variation and search for genetic markers linked to specific traits. Amplified fragment length polymorphism (AFLP, Vos et al. 1995) is a popular polymorphism system that combines the advantages of RFLP and PCR, with no requirement of prior sequence characterization of the target genome. The number of polymorphisms detected and the level of fingerprint reproducibility per reaction is much higher than that revealed by most of the other PCR-based methods because of its simultaneous coverage of many loci in a single assay. Selective amplified microsatellite polymorphic loci (SAMPL) analysis (Witsenboer et al. 1997) is a modification of AFLP methodology, which utilizes the same template DNA as that of AFLP. However, the selective amplification uses one of the AFLP primers in combination with a specially designed SAMPL primer. The SAMPL primer essentially comprises of a compound microsatellite sequence, and such a SAMPL primer design ensures preferential amplification of microsatellite-like sequences.

In this study, AFLP and SAMPL have been used for analyzing genetic changes over generations of a selected strain of P. chinensis. At the same time, a search for sex-specific markers was conducted for potential identification of markers associated with sex differentiation and determination, using these two marker systems.

MATERIALS AND METHODS

Sample Collection and DNA Isolation

Thirty-six individuals representing four generations sample (9 from each generation randomly) were obtained from Yellow Sea Institute of Fisheries Research, Chinese Academy of Fisheries Sciences. Four generations were designated as [G.sub.0], [G.sub.1], [G.sub.2], and [G.sub.3], respectively. [G.sub.0] sample was the founder stock for selection, which was the progeny of several hundreds of wild shrimp captured in Weihai waters, the Yellow Sea, China. Mass selection was conducted with disease challenge for 3 generations ([G.sub.1] through [G.sub.3]). Briefly, about 200 mature females and males (roughly equal number of each sex) from [G.sub.0] were used to reproduce in a local hatchery. These females with an attached spermatophore were separated for egg release and fertilization to build the next generation ([G.sub.1]. Juvenile shrimp were grown in local shrimp ponds until maturation. One year later, about the same number of females and males were selected from [G.sub.1] and mated to establish [G.sub.2] in the same hatchery. The same work was repeated for the establishment of the [G.sub.3] population.

Genomic DNA was extracted from muscle using the method described by Aljanabi and Martinez (1997). DNA samples were checked by agarose gel electrophoresis, and their concentrations were determined with Beckman-spectrophotometer (Model DU 520, Beckman). For search of sex-specific markers, two separate pools consisting of DNAs from four females and five males, respectively, were used to minimize possible effects of individual variation and improve efficiency of screening process.

AFLP Analysis

AFLP procedure was performed as described by Vos et al. (1995). Genomic DNAs were digested with EcoRI and MseI, and ligated with relevant adaptors overnight at room temperature. Pre-selective amplification was performed using primers with one selective base at their 3' end (E-A and M-C). For genetic survey, 6 pairs of selective primers, each containing 3 selective nucleotides at their 3'end, were used for selective PCR. The 6 selective primer pairs were E-AAG/M-CCT, E-AAG/M-CTG, E-AAG/M-CAC, E-AAG/M-CGA, E-ACG/M-CTC, and E-ACG/M-CCT, respectively. For the search of sex-specific markers, 25 AFLP (5 EcoRI primers x 5 MseI primers) primer pairs were used. The 5 EcoRI primers included E-AAC, AAG, ACA, ACC, and ACG, and 5 MseI primers were M-CAC, CCT, CGA, CTC, and CTG, respectively.

With the addition of an equal volume of sequencing dye (98% formamide, 10 mM EDTA, 0.025% xylene cyanol, 0.025% bromophenol blue), PCR products obtained in the selective reaction were denatured at 95 [degrees]C for 5 min, and then immediately cooled on ice for at least 5 min. A 2.5 [micro]L of each sample was loaded on a denaturing polyacrylamide (6%) gel and run at 60 W. After silver staining (Bassam et al. 1991), bands were visualized under white-illumination. The developed gels were dried at room temperature for 24 h before scoring the bands.

SAMPL Analysis

SAMPL procedures used here were the same as that of AFLP, described earlier in the section of AFLP Analysis, except that SAMPL primers replaced MseI primers in the selective amplifications (Witsenboer et al. 1997). For genetic survey, 4 selective primer pairs were used, which included E-AAG/SAM01, E-AAG/ SAM02, E-ACG/SAM01, and E-ACG/SAM02, respectively (Table 1). For the search of sex-specific markers, 16 (3 EcoRI and 1 MseI primers x 4 SAMPL primers) primer pairs were used. They were E-AAC, AAG, ACG and M-CGA, and 4 SAMPL primers, respectively (see Table 1).

Data Analysis

AFLP and SAMPL profiles were scored manually as "1"s (band presence) or "0"s (band absence). Two assumptions were made: (l) bands come from independent nuclear loci and do not migrate to the same position on gel; and (2) each band represents a dominant genotype at a locus, where lack of the same band in another individual correspond to the alternative homozygous recessive genotype in the Hardy-Weinberg equilibrium (Lynch & Milligan 1994).

The unbiased estimator of Lynch and Milligan (1994) was used to estimate frequency of two alleles (1 and 0) at each locus and expected heterozygosity with combined AFLP and SAMPL data was calculated accordingly. Pairwise genetic distances and genetic identities were calculated with two data sets jointly using POPGENE (Yeh et al. 1999). AMOVA and pairwise [[PHI].sub.PT] statistics of AFLP and SAMPL data were conducted to determine genetic difference of the generations with GenA1Ex V5 (Peakall & Smouse 200 l).

RESULTS

In genetic survey, six AFLP primer combinations and four SAMPL primer pairs generated 247 and 140 clearly defined bands, respectively, averaging 41.2 bands per primer pair for AFLP and 35.0 bands for SAMPL. Most amplified profiles were highly specific and reproducible, and ambiguous bands were excluded from further analysis. The size of most scored bands ranged from 100 to 400 bp. The percentage of polymorphic loci and average gene diversity (Nei et al. 1975) with combined AFLP and SAMPL data ranged from 41.3 to 47.8% and from 0.168 to 0.190, respectively (Table 2), which were not significantly different from each other (Chi-test, P = 0.56 and 0.99, respectively), suggesting no significant change in the level of genetic variation by AFLP and SAMPL. The frequency change of band-presence allele at all loci over generations showed no clear and traceable patterns.

The genetic distances and genetic identities with combined data sets among generations are shown in Table 3. Clearly, the values of distances or identities between Go and other generations increased or decreased over successive order accordingly, reflecting the accumulation of genetic changes over generations. AMOVA results from both data sets showed that significant genetic variation was distributed among generation samples (P < 0.01), with percentages of total variance of 17% and 26%, respectively, among generations for AFLP and SAMPL data (Table 4). Furthermore, pairwise [[PHI].sub.PT] statistics in both data sets indicate that significant genetic difference occurred between any neighbor generation pair and increased over sequential generation order (Table 5).

With respect to the search of sex-specific marker, 2,110 bands in total were generated with AFLP and SAMPL, but unfortunately, analysis and comparison showed that no putative sex-specific band was identified for both sexes in the two marker systems.

DISCUSSION

Genetic Changes over Generations

While AFLP has been extensively used in the studies of genetic diversity of populations, germplasms, cultivars, and strains for plants, it has recently been applied to similar researches in aquatic animals (Seki et al. 1999, Moore et al. 1999, Miller et al. 2000, David et al. 2001). AFLP is considered very efficient at revealing genetic difference due to its ability to screen polymorphism on genome scale despite lower average heterozygosity (Vos et al. 1995, Maguire et al. 2002). SAMPL is a novel approach that emerged recently for genetic studies and shown useful in plants. Although based on small sample sizes, the similar estimation of average percentage of polymorphic loci and gene diversity of four samples indicated that no significant change at level of genetic variation was observed among generations by AFLP and SAMPL analysis. This maintenance of genetic variation level is likely due to the large size of founder population and the reproduction populations used in the following generations. It could help reduce the adverse effects of genetic drift, selection, and inbreeding that may occur in a breeding program. This result should be contributed by the fact that AFLP's advantage of comprehensive evaluation of multi polymorphic loci on genome range compensated the effect of the small sample size. With AFLP, Seki et al. (1999) detected significant and clear genetic difference among three Ayu Plecoglossus altivelis populations (8 fish per sample) by using 19 primer combinations; and significant difference in average heterozygosity for three samples were also found. Similarly, it was confirmed that multilocus RAPD (6 random primers) detected very similar molecular differentiation among blacklip abalone Haliotis rubra populations in small sample size (10 animals per sample) as revealed by microsatellites (Huang et al. 2000).

Usually, heterozygosity level and allele diversity shift are considered as indicators for genetic changes of populations under selection or culture. Sbordoni et al. (1986) examined genetic diversity with 20 allozyme loci for sequential hatchery generations in P. japonicus, noticing progressive reduction of heterozygosity from 0.102 down to 0.039 in samples from generation F1 through F6. However, Cruz et al. (2004) found that high heterozygosities (in 2 microsatellite loci) were still maintained through two generations of the Pacific white shrimp Litopenaeus vannamei under selection. Nevertheless, three studies of penaeids species have reported lower numbers of alleles at microsatellite loci in cultured populations than in wild or founder stocks (Wolfus et al. 1997, Bierne et al. 2000, Xu et al. 2001). In molluscan, similarly, several studies showed that no association was observed between selection or culture and loss of heterozygosity in the Pacific oyster Crassostrea gigas (Hedgecock & Sly 1990), hard clam Mercenaria mercenaria (Dillon & Manzi 1987) and American oyster C. virginica (Vrijenhoek et al. 1990, Yu & Guo 2004). However, the reduction of allele number in these selected populations was commonly observed (Dillon & Manzi 1987, Vrijenhoek et al. 1990, Yu & Guo 2004). Obviously, loss of genetic variation resulted from genetic drift, bottlenecks, selection, and inbreeding caused by a reduced effective population size.

Despite no significant change in the level of genetic variation was observed through AFLP and SAMPL analysis, it is risky to say that no significant change at level of genetic variation occurred at all. Because allele diversity change, which is another indicator of genetic changes, could not be detected via these two methods. From the literature mentioned above, one can see that the two indicators do not match in many cases. Therefore, for more details of genetic change over generations, further studies using microsatellite or allozyme markers will be helpful and necessary. Recently, some microsatellites have been developed for Chinese shrimp (Liu et al. 2004) and could be used for further analysis of this breeding program.

Because isolation and selection of stocks may lead to deterioration via inbreeding and reduction of effective population size, genetic changes should be monitored carefully following operation of selection. Despite complicated frequency change of bandpresence allele and unavailability of traceable patterns of polymorphic loci over generations in this study, AFLP and SAMPL did screen out occurrence of difference over generation samples. As indicated by genetic distances, identities and result of AMOVA, isolation and selection caused the accumulation of genetic changes over sequential generations.

From AMOVA of SAMPL data, it was noted that estimation of percentage of total variance distributed among generations was higher than that in AFLP data (26% vs. 17%), so was from pair-wise [[PHI].sub.PT] statistics of SAMPL. This difference was very likely due to the characters of polymorphism from SAMPL. Theoretically, SAMPL screens 4 types of polymorphisms: (1) codominant microsatellite polymorphisms, which resulted from the number variation of repeat units within microsatellites targeted by the microsatellite-anchor primers; (2) presence/absence-style polymorphisms arising from variation of the annealing sites for the microsatellite-anchor primer; (3) codominant polymorphisms originating from insertion/deletions in amplified fragments; and (4) presence/absence-style polymorphisms originating from variation in restriction sites (Yang et al. 2001). Whereas type 2 and 4 could be detected as dominant polymorphism, type 1 and 3 may cause incorrect scoring information due to their codominant nature, and then magnified the difference among samples involved to some extent. In addition, another reason responsible for this difference could be the smaller data size (140 bands) in SAMPL than that in AFLP (247 bands).

Search for Sex-specific Markers

Understanding the mechanism of sex determination and differentiation is important for study of shrimp biology and aquaculture practices. Although recently Li et al. (2003) mapped sex-linked markers on the maternal linkage map in Kuruma prawn P. japonicus and implied that the female may be the heterogametic sex in this species, search for sex-specific markers with AFLP and SAMPL loci in current study has failed to detect any putative markers, despite extensive screening with 25 AFLP and 16 SAMPL primer pairs (2,110 bands in total were generated). Previously, attempts to detect sex-specific markers in Atlantic salmon (Salmo salar) and green spotted pufferfish (Tetraodon nigroviridis) with RAPD, AFLP, and RDA (representational difference analysis) were made, but were not successful (McGowan & Davidson 1998, Li et al. 2002). Sex determination in crustacean has been studied for the last 2 decades (Malecha 1983, Legrand et al. 1987, Benzie 1998, Hulata 2001), with the exception of decapods. Lack of sex chromosome differentiation in penaeids has been observed, and no environmental factors of sex determination have ever been reported (Korpelainen 1990). As mentioned earlier, karyotype analysis detected no dimorphic pair of chromosomes, and it may imply absence of sex chromosomes or their weak differentiation in P. chinensis genome. The inability to detect of sex-specific markers in this kind of limited search could be due to any of the following reasons: very weak correlation between the genotypic and phenotypic sex due to modifiers, high genetic diversity in sex-related regions on genome among the individuals studied, or biallelic and autosomal nature of sex-determining genes (Li et al. 2002, McGowan & Davidson 1998). Of course, it could not be ruled out that the number of loci used in this search may not be enough to screen out the sex-specific markers, if there is any. More work is needed before we come to any conclusion.

ACKNOWLEDGMENTS

The authors thank Mr. B.W. Liu and D. R. Hu for their assistance with DNA extraction and Mr. Sean Boyd for English review. This work was supported by an 863 project of Ministry of Science and Technology of China (2001 AA620105) and funded by the Key Laboratory of Mariculture of Ministry of Education, Ocean University of China.

LITERATURE CITED

Aljanabi, S. M. & I. Martinez. 1997. Universal and rapid salt-extraction of high quality genomic DNA for PCR-based techniques. Nucleic Acids Res. 25:4692-4693.

Allendorf, F. W. & N. Ryman. 1987. Genetic management of hatchery stocks. In: N. Ryman & F. Utter, editors. Population genetics and fishery management. Seattle: University of Washington Press. pp. 141-159.

Bassam, B. J., G. Caetano-Anolles & P. M. Gresshoff. 1991. Fast and sensitive silver staining of DNA in polyacrylamide gels. Anal. Biochem. 196:80-83.

Benzie, J. A. H. 1998. Penaeid genetics and biotechnology. Aquaculture 164:23-47.

Bierne, N., I. Beuzart, V. Vonau, F. Bonhomme & E. Bedier. 2000. Microsatellite-associated heterosis in hatchery-propagated stocks of the shrimp Penaeus stylirostris. Aquaculture 184:203-219.

Cruz, P., A. M. Ibarra, H. Mejia-Ruiz, P. M. Gaffney & R. P6rez-Enrfquez. 2004. Genetic variability assessed by microsatellites in a breeding program of Pacific white shrimp (Litopenaeus vannamei). Mar. Biotech. 6:157-164.

David, L., P. Rajasekaran, J. Fang, J. Hillel & U. Lavi. 2001. Polymorphism in ornamental and common carp strains (Cyprinus carpio L.) as revealed by AFLP analysis and a new set of microsatellite markers. Mol. Genet. Genomics 266:353-362.

Dillon, R. T. & J. J. Manzi. 1987. Hard clam, Mercenaria mercenaria, broodstocks: genetic drift and loss of rare alleles without reduction in heterozygosity. Aquaculture 60:99-105.

Gaffney, P. M., C. V. Davis & R. O. Hawes. 1992. Assessment of drift and selection in hatchery population of oysters (Crassostrea virginica). Aquaculture 105: 1-20.

Hedgecock, D. & F. Sly. 1990. Genetic drift and effective population sizes of hatchery-propagated stocks of the Pacific oyster, Crassostrea gigas. Aquaculture 88:21-38.

Hedgecock, D., V. Chow & R. S. Waples. 1992. Effective population numbers of shellfish broodstocks estimated from temporal variance in allelic frequencies. Aquaculture 108:215-232.

Korpelainen, H. 1990. Sex ratios and conditions required for environmental sex determination in animals. Biol. Rev. 65: 147-184.

Huang, B. X., R. Perkall & P. J. Hanna. 2000. Analysis of genetic structure of blacklip abalone (Haliotis rubra) populations using RAPD, minisatellite and microsatellite markers. Mat: Biol. 136:207-216.

Hulata, G. 2001. Genetic manipulations in aquaculture: a review of stock improvement by classical and modern technologies. Genetica 111:155-173.

Launey, S. & D. Hedgecock. 2001. High genetic load in the Pacific oyster Crassostrea gigas. Genetics 159:255-265.

Legrand, J. J., E. Legrand-Hamelin & P. Juchault. 1987. Sex determination in crustacea. Biol. Rev. 62:439-470.

Li, Y., K. Byrne, E. Miggiano, V. Whan, S. Moore, S. Keys & P. Crocos. 2003. Genetic mapping of the kuruma prawn Penaeus japonicus using AFLP markers. Aquaculture 219: 143-156.

Li, Y., J. A. Hill, G. H. Yue, F. Chert & L. Orban. 2002. Extensive search does not identify genomic sex markers in Tetraodon nigroviridis. J. Fish Biol. 61:1314-1317.

Liu, P., X. Meng, J. Kong & H. Gao. 2004. Selection of polymorphic microsatellites from random shearing DNA clones in Fenneropenaeus chinensis. Hightech. Comm. 2:87-90.

Lynch, M. & B. G. Milligan. 1994. Analysis of population genetic structure with RAPD markers. Mol. Ecol. 3:91-99.

Maguire, T. L., R. Peakall & P. Saenger. 2002. Comparative analysis of genetic diversity in the mangrove species Avicennia marina (Forsk.) Vierh. (Avicenniaceae) detected by AFLPs and SSRs. Theor. Appl. Genet. 104:388-398.

Malecha, S. R. 1983. Crustacean genetics and breeding: an overview. Aquaculture 33:395-413.

McGowan, C. & W. S. Davidson. 1998. The RAPD technique fails to detect a male-specific genetic marker in Atlantic salmon. J. Fish Biol. 53:1134-1136.

Miller, M. P., L. E. Stevens, J. D. Busch, J. A. Sorensen & P. Keim. 2000. Amplified fragment length polymorphism and mitochondrial sequence data detect genetic differentiation and relationships in endangered southwestern USA amber snails (Oxyloma spp.). Can. J. Zool. 78: 1845-1854.

Moore, S. S., V. Whan, G. P. Davis, K. Byrne, D. Hetzel & N. Preston. 1999. The development and application of genetic markers for the Kuruma prawn Penaeus japonicus. Aquaculture 173:19-32.

Nei, M. 1973. Analysis of gene diversity in subdivided populations. Proc. Natl. Acad. Sci. USA. 70:3321-3323.

Nei, M., T. Maruyama & R. Chakraborty. 1975. The bottleneck effect and genetic variability in populations. Evolution 29:1-10.

Peakall, R. & P. E. Smouse. 2001. GenA1Ex V5: Genetic Analysis in Excel. Population genetic software for teaching and research. Canberra, Australia: Australian National University.

Sbordoni, V., M. De Metthaeis, M. Cobolli Sbordoni, G. La Rosa & M. Mattoccia. 1986. Bottleneck effects and the depression of genetic variability in hatchery stocks of Penaeus japonicus (Crustacea, Decapoda). Aquaculture 57:239-251.

Seki, S., J. J. Agresti, G. A. E. Gall, N. Taniguchi & B. May. 1999. AFLP analysis of genetic diversity in three populations of ayu Plecoglossus altivelis. Fish. Sci. 65:888-892.

Vos, P., R. Hongers, M. Bleeker, M. Reijans, T. Lee, M. Hornes, A. Frijters, J. Pot, J. Peleman & M. Kuiper. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23:4407-4414.

Virjenhoek, R. C., S. E. Ford & H. H. Haskin. 1990. Maintenance of heterozygosity during selective breeding of oysters for resistance to MSX disease. J. Hered. 81:418-423.

Vos, P., R. Hongers, M. Bleeker, M. Reijans, T. Lee, M. Hornes, A. Frijters, J. Pot, J. Peleman & M. Kuiper. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23:4407-4414.

Wang, Q. Y., S. L. Cai & J. Li. 1997. The shrimp farming industry in China. World Aquaculture. 3:23-29.

Witsenboer, H., J. Vogel & R. W. Michelmore. 1997. Identification, genetic localization, and allelic diversity of selectively amplified microsatellite polymorphic loci in lettuce and wild relatives (Lactuca spp.). Genome 40:923-936.

Wolfus, G. M., O. K. Garcia & A. Alcivar-Warren. 1997. Application of the microsatellite technique for analyzing genetic diversity in shrimp breeding programs. Aquaculture 152:35-47.

Xiang, J. H., R. Y. Liu & L. H. Zhou. 1993. Chromosome of marine shrimps with special reference to different techniques. Aquaculture 111:321-328.

Xu, Z., J. H. Primavera, L. D. de la Pena, P. Pettit, J. Belak & A. Alcivar-Warren. 2001. Genetic diversity of wild and cultured black tiger shrimp (Penaeus monodon) in the Philippines using microsatellites. Aquaculture 199:13-40.

Yang, H., M. W. Sweetingham, W. A. Cowling & P. M. C. Smith. 2001. DNA fingerprinting based on microsatellite-anchored fragment length polymorphisms, and isolation of sequence-specific PCR markers in lupin (Lupinus angustifolius L.). Mol. Breeding 7:203-209.

Yeh, F., R. Yang & T. Boyle. 1999. POPGENE version 1.31, Microsoft Window-based Freeware for Population Genetic Analysis.

Yu, H. P. & T. Y. Chart. 1986. The illustrated penaeid prawns in Taiwan. Taipei, Taiwan: South Material Center. pp. 183.

Yu, Z. & X. Gut. 2004. Genetic analysis of selected strains of the Eastern oyster (Crassostrea virginica Gmelin) using AFLP and microsatellite markers. Mar. Biotechnol. (in press).

LIUSUO ZHANG, (1) XIAOYU KONG, (1) ZINIU YU, (1) * JIE KONG, (2) AND LIMEI CHEN (1)

* Corresponding author. E-mail: carlzyu@ouc.edu.cn

(1) The Key Laboratory of Mariculture of Ministry of Education, Ocean University of China, Qingdao 266003, People's Republic of China and (2) Yellow Sea Institute of Fisheries Research, Chinese Academy of Fisheries Science, Qingdao 266071, People's Republic of China

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