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Genetic differences between broodstock and offspring of seven-band grouper in a hatchery

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Abstract

The seven-band grouper (Epinephelus septemfasciatus) is an important fishery resource of a target for prospective aquaculture diversification and maintenance of stock quality is thus important. To explore the sustainability of fry production, genetic variations in 83 seven-band groupers from two broodstock and offspring populations of a hatchery strain were analyzed using 13 polymorphic nuclear microsatellite DNA loci; 133 alleles were identified. Allelic variability ranged from 4 to 18 in the broodstock and from 3 to 11 in the offspring. The average observed and expected heterozygosities were 0.669 and 0.734 in broodstock and 0.674 and 0.649 in offspring, respectively. Although no statistically significant reductions in heterozygosity or allelic diversity were evident in offspring, considerable loss of rare alleles was apparent. The broodstock and offspring populations exhibited significant genetic differences (F ST = 0.033, P < 0.001) indicating that genetic drift has likely promoted differentiation between the two populations, which may have negative effects on sustainable fry production. Therefore, genetic variations between broodstock and offspring should be monitored, and inbreeding should be controlled, to ensure the success of commercial breeding programs. Our data provide a useful genetic basis for future planning of sustainable culture and management of E. septemfasciatus in fisheries.

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References

  • Allendorf FW, Ryman N (1987) Genetic management of hatchery stocks. In: Ryman N, Utter F (eds) Population genetics and fishery management. Washington Sea Grant, Seattle, pp 141–159

    Google Scholar 

  • Amos W, Wilmer JW, Fullard K, Burg TM, Croxall JP, Bloch D, Coulson T (2001) The influence of parental relatedness on reproductive success. Proc R Soc Lond B 268:2021–2027

    Article  CAS  Google Scholar 

  • An HS, Byun SG, Kim YC, Lee JW, Myeong JI (2011a) Wild and hatchery populations of Korean starry flounder (Platichthys stellatus) compared using microsatellite DNA marker. Int J Mol Sci 12:9189–9202

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  • An HS, Hong SW, Kim EM, Myeong JI (2011b) Comparative genetic diversity of wild and hachery populations of Korean threadsail filefish Stephanolepis cirrhifer using cross-species microsatellite markers. Genes Genomics 33:605–611

    Article  Google Scholar 

  • An HS, Kim JW, Lee JH, Kim SK, Lee BI, Kim DJ, Kim YC (2012a) Development and characterization of microsatellite markers for an endangered species, Epinephelus bruneus, to establish a conservation program. Anim Cells Syst 16:50–56

    Article  CAS  Google Scholar 

  • An HS, Lee JW, Dong CM (2012b) Population genetic structure of Korean pen shell (Atrina pectinata) in Korea inferred from microsatellite marker analysis. Genes Genom 34:681–688

    Article  Google Scholar 

  • An HS, Lee JW, Park JY, Jung HT (2013) Genetic structure of the Korean black scraper Thamnaconus modestus inferred from microsatellite marker analysis. Mol Biol Rep 40:3445–3456

    Article  CAS  PubMed  Google Scholar 

  • An HS, Cho JK, Kim KM, Son MH, Myeong JI, An CM (2014) Characterization of 22 polymorphic microsatellite markers for seven-band grouper Epinephelus septemfasciatus developed using a 454 pyrosequencing approach. Conserv Genet Resour. doi:10.1007/s12686-014-0176-x

    Google Scholar 

  • Blanco Gonzalez E, Aritaki M, Taniguchi N (2012) Microsatellite multiplex panels for population genetic analysis of red sea bream Pagrus major. Fish Sci 78:603–611

    Article  CAS  Google Scholar 

  • Callen DF, Thompson AD, Shen Y, Phillips HA, Mulley JC, Sutherl GR (1993) Incidence and origin of “null” alleles in the (AC)n microsatellite markers. Am J Hum Genet 52:922–927

    PubMed Central  CAS  PubMed  Google Scholar 

  • De Sousa SN, Finkeldey R, Gailing O (2005) Experimental verification of microsatellite null alleles in Norway spruce (Picea abies [L.] Karst.): implications for population genetic studies. Plant Mol Biol Rep 23:113–119

    Article  Google Scholar 

  • DeWoody JA, Avise JC (2000) Microsatellite variation in marine, freshwater and anadromous fishes compared with other animals. J Fish Biol 56:461–473

    Article  CAS  Google Scholar 

  • Excoffier L, Smouse PE, Quattro JM (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131:479–491

    PubMed Central  CAS  PubMed  Google Scholar 

  • Excoffier L, Laval G, Schneider S (2005) ARLEQUIN version 3.0. An integrated software package for population genetics data analysis. Evol Bioinform Online 1:47–50

    PubMed Central  CAS  Google Scholar 

  • Goudet J, Raymond M, De Meiis T, Rousset F (1996) Testing differentiation in diploid populations. Genetics 144:933–940

    Google Scholar 

  • Heemstra PC, Randall JE (1993) FAO Species Catalogue. Vol. 16. Groupers of the World (Family Serranidae, Subfamily Epinephelinae). FAO Fisheries Synopsis No. 125, vol 16, Food and Agriculture Organization of the United Nations, Rome

  • Kalinowski ST, Taper ML, Marshall TC (2007) Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Mol Ecol 16:1099–1106

    Article  PubMed  Google Scholar 

  • Kim WJ, Shin EH, Kong HJ, Nam BH, Kim YO, Jung H, An CM (2013) Development of polymorphic microsatellite markers suitable for genetic linkage mapping of olive flounder Paralichthys olivaceus. Fish Aquat Sci 16:303–309

    CAS  Google Scholar 

  • Kime DE, Van Look KJW, McAllister BG, Huyskens G, Rurangwa E, Ollevier F (2001) Computer assisted sperm analysis (CASA) as a tool for monitoring sperm quality in fish. Comp Biochem Physiol 130:425–433

    CAS  Google Scholar 

  • Kohlmann K, Kersten P, Flajshans M (2005) Microsatellite-based genetic variability and differentiation of domesticated, wild and feral common carp (Cyprinus carpio L) populations. Aquaculture 247:26–253

    Article  Google Scholar 

  • Koljonen ML, Tahtinen J, Saisa M, Koskiniemi J (2002) Maintenance of genetic diversity of Atlantic salmon (Salmo salar) by captive breeding programmes and the geographic distribution of microsatellite variation. Aquaculture 212:69–92

    Article  CAS  Google Scholar 

  • Korean Fisheries Resources Agency (2012) Evaluation of a stock enhancement programme effectiveness. Korean Fisheries Resources Agency, Seoul in Korean

    Google Scholar 

  • Liu F, Xia JH, Bai ZY, Fu JJ, Li JL, Yue GH (2009) High genetic diversity and substantial population differentiation in grass carp (Ctenopharyngodon idella) revealed by microsatellite analysis. Aquaculture 297:51–56

    Article  CAS  Google Scholar 

  • Reily A, Elliott NG, Grewe PM, Clabby C, Powell R, Ward RD (1999) Genetic differentiation between Tasmanian cultured Atlantic salmon (Salmo salar L.) and their ancestral Canadian population: comparison of microsatellite DNA and allozyme and mitochondrial DNA variation. Aquaculture 173:459–469

    Article  Google Scholar 

  • Rice WR (1989) Analyzing tables of statistical tests. Evolution 43:23–225

    Article  Google Scholar 

  • Rousset F (1996) Equilibrium values of measures of population subdivision for stepwise mutation processes. Genetics 142:1357–1362

    PubMed Central  CAS  PubMed  Google Scholar 

  • Rousset F (2008) Genepop`007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour 8:103–106

    Article  PubMed  Google Scholar 

  • Schlötterer C (2000) Evolutionary dynamics of microsatellite DNA. Chromosoma 109:365–371

    Article  PubMed  Google Scholar 

  • Slatkin M, Excoffier L (1996) Testing for linkage disequilibrium in genotypic data using the EM algorithm. Heredity 76:377–383

    Article  PubMed  Google Scholar 

  • Spencer CC, Neigel JE, Leberg PL (2000) Experimental evaluation of the usefulness of microsatellite DNA for detecting demographic bottlenecks. Mol Ecol 9:1517–1528

    Article  CAS  PubMed  Google Scholar 

  • van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) MICRO-CHECKER: software for identifying and correcting genotyping errors in microsatellite data. Mol Ecol Notes 4:535–538

    Article  Google Scholar 

  • Wang L, Meng Z, Liu X, Zhang Y, Zhang Y, Lin H (2011) Genetic diversity and differentiation of the orange-spotted grouper (Epinephelus coioides) between and within cultured stocks and wild populations inferred from microsatellite DNA analysis. Int J Mol Sci 12:4378–4394

    Article  PubMed Central  PubMed  Google Scholar 

  • Weir BS, Cockerham CC (1984) Estimating F-statistics for the analysis of population structure. Evolution 38:1358–1370

    Article  Google Scholar 

  • Wilcoxon F (1945) Individual comparisons by ranking methods. Biom Bull 1:80–83

    Article  Google Scholar 

Download references

Acknowledgments

This work was funded by a grant from the National Fisheries Research and Development Institute (NFRDI; contribution number RP-2014-BT-004). The views expressed herein are those of the authors and do not necessarily reflect the views of NFRDI.

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Authors declare no conflict of interest on this article contents.

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Authors and Affiliations

  1. Biotechnology Research Division, National Fisheries Research and Development Institute, Busan, 619-705, Korea

    Hye Suck An & Chul Min An

  2. Aquaculture Management Division, Southwest Sea Fisheries Research Institute, National Fisheries Research and Development Institute, Yeosu, 556-823, Korea

    Jae Kwon Cho, Kyong Min Kim, Maeng Hyun Son & Jeong In Myeong

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  1. Hye Suck An
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  2. Jae Kwon Cho
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  3. Kyong Min Kim
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  4. Maeng Hyun Son
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  5. Jeong In Myeong
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  6. Chul Min An
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Correspondence to Hye Suck An.

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An, H.S., Cho, J.K., Kim, K.M. et al. Genetic differences between broodstock and offspring of seven-band grouper in a hatchery. Genes Genom 36, 661–669 (2014). https://doi.org/10.1007/s13258-014-0213-x

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  • DOI: https://doi.org/10.1007/s13258-014-0213-x

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