DOI QR코드

DOI QR Code

Genetic diversity of wild and farmed black sea bream populations in Jeju

  • An, Hye-Suck (Biotechnology Research Division, National Fisheries Research and Development Institute) ;
  • Hong, Seong-Wan (Jeju Province Fisheries Resources Research Institute) ;
  • Lee, Jung-Uie (Aquaculture Management Division, National Fisheries Research and Development Institute) ;
  • Park, Jung-Youn (Biotechnology Research Division, National Fisheries Research and Development Institute) ;
  • Kim, Kyung-Kil (Biotechnology Research Division, National Fisheries Research and Development Institute)
  • Received : 2009.09.29
  • Published : 2010.03.31

Abstract

Black sea bream, Acanthopagrus schlegelii, is a commercially important fish in Korea. As a preliminary investigation into the effect of hatchery rearing for stock enhancement, we examined genetic diversity between wild and farmed black sea bream populations from Jeju using six microsatellite markers. High levels of polymorphism were observed between the two populations. A total of 87 different alleles were found at the loci, with some alleles being unique. Allelic variability ranged from 8 to 22 in the wild population and from 7 to 17 in the farmed one. Average observed and expected heterozygosities were estimated at 0.87 and 0.88 in the wild sample. The corresponding estimates were 0.83 and 0.86 in the farmed sample. Although a considerable loss of rare alleles was observed in the farmed sample, no statistically significant reductions were found in heterozygosity or allelic diversity in the farmed sample, compared with the wild one. Significant genetic heterogeneity was found between the wild and farmed populations. These results suggest that more intensive breeding practices for stock enhancement may have resulted in a further decrease of genetic diversity. Thus, it is necessary to monitor genetic variation in bloodstock, progeny, and target populations and control inbreeding in a commercial breeding program for conservation. This information may be useful for fisheries management and the aquaculture industry.

Acknowledgement

Supported by : NFRDI

References

  1. Alarcon JA, Magoulas A, Georgakopoulos T, Zouros E, Alvarez MC. 2004. Genetic comparison of wild and cultivated European populations of the gilthead sea bream (Sparus aurata). Aquaculture. 230:65-80. https://doi.org/10.1016/S0044-8486(03)00434-4
  2. An HS, Kim MJ, Hong SW. 2008. Genetic diversity of rock bream Oplegnathus fasciatus in Southern Korea. Genes Genomics. 30:451-459.
  3. Ardren WR, Borer S, Thrower F, Joyce JE, Kapuscinski AR. 1999. Inheritance of 12 microsatellite loci in Oncorhynchus mykiss. J Hered. 90:529-536. https://doi.org/10.1093/jhered/90.5.529
  4. Banks MA, Blouin MS, Baldwin BA, Rashbrook VK, Fitzgerald HA, Blankenship SM, Hedgecock D. 1999. Isolation and inheritance of novel microsatellites in Chinook salmon (Oncorhynchus tschawytscha). J Hered. 90:281-288. https://doi.org/10.1093/jhered/90.2.281
  5. Coughlan JP, Imsland AK, Galvin PT, Fitzgerald RD, Naevdal G, Cross. 1998. Microsatellite DNA variation in wild populations and farmed strains of turbot from Ireland and Norway: a preliminary study. J Fish Biol. 52:916-922. https://doi.org/10.1111/j.1095-8649.1998.tb00592.x
  6. Desvignes JF, Laroche J, Durand JD, Bouvet Y. 2001. Genetic variability in reared stocks of common carp (Cyprinus carpio L.) based on allozymes and microsatellites. Aquaculture. 194:291-301. https://doi.org/10.1016/S0044-8486(00)00534-2
  7. DeWoody JA, Avise JC Microsatellite variation in marine, freshwater and anadromous fishes compared with other animals. J Fish Biol. 56:461-473 https://doi.org/10.1111/j.1095-8649.2000.tb00748.x
  8. Elliott NG, Reilly A. 2003. Likelihood of a bottleneck even in the history of the Australian population of Atlantic salmon (Salmo salar L.). Aquaculture. 215:31-44. https://doi.org/10.1016/S0044-8486(02)00055-8
  9. Goudet J. 2002. FSTAT: a computer program to calculate F-statistics. J Hered. 86:485-486.
  10. FAO. 1993. Report of the expert consultation on utilization and conservation of aquatic genetic resources. FAO Fish Rep. 491:1-58.
  11. Hara M, Sekino M. 2003. Efficient detection of parentage in a cultured Japanese flounder Paralichthys olivaceus using microsatellite DNA marker. Aquaculture. 217:107-114. https://doi.org/10.1016/S0044-8486(02)00069-8
  12. Hoarau G, Rijnsdrop AD, Van der Veer HW, Stam WT, Olsen JL. 2002. Population structure of plaice (Pleuronectes platessa L.) in northern Europe: microsatellites revealed largescale spatial and temporal homogeity. Mol Ecol. 11:1165-1176. https://doi.org/10.1046/j.1365-294X.2002.01515.x
  13. Holland BS. 2001. Invasion without a bottleneck: microsatellite variation in natural and invasive populations of the brown mussel Perna perna (L). Mar Biotechnol. 3:407-415. https://doi.org/10.1007/s1012601-0060-Z
  14. Jackson TR, Martin-Robichaud DJ, Reith ME. 2003. Application of DNA markers to the management of Atlantic halibut (Hippoglossus hippoglossus) broodstock. Aquaculture. 220:245-259. https://doi.org/10.1016/S0044-8486(02)00622-1
  15. Jeong DS, Umino T, Kuroda K, Hayashi M, Nakagawa H, Kang JC, Morishima K, Arai K. 2003. Genetic divergence and population structure of black sea bream Acanthopagrus schlegeli inferred from microsatellite analysis. Fish Sci. 69:896-902. https://doi.org/10.1046/j.1444-2906.2003.00705.x
  16. Jeong DS, Gonzalez EB, Morishima K, Arai K, Umino T. 2007. Parentage assignment of stocked black sea bream Acanthopagrus schlegelii in Hiroshima Bay using microsatellite DNA markers. Fish Sci. 73:823-830. https://doi.org/10.1111/j.1444-2906.2007.01402.x
  17. Kimura M, Crow JF. 1964. The number of alleles that can be maintained in a finite population. Genetics. 49:725-738.
  18. Li Q, Park C, Endo T, Kijima A. 2004. Loss of genetic variation at microsatellite loci in hatchery strains of the Pacific abalone (Haliotis discus hannai). Aquaculture. 235:207-222. https://doi.org/10.1016/j.aquaculture.2003.12.018
  19. Liu N, Chen L, Wang S, Oh S, Zhao H. 2005. Comparison of single-nucleotide polymorphisms and microsatellites in inference of population structure. BMC Genetics 30(6 Suppl 1):S26.
  20. Michalakis Y, Excoffier L. 1996. A genetic estimation of population subdivision using distances between alleles with special reference for microsatellite loci. Genetics. 142:1061-1064.
  21. Nei M. 1987. Molecular evolutionary genetics. New York: Columbia University Press.
  22. Norris AT, Bradley DG, Cunningham EP. 2000. Parentage and relatedness determination in farmed Atlantic salmon (Salmo salar) using microsatellite markers. Aquaculture. 182:73-83. https://doi.org/10.1016/S0044-8486(99)00247-1
  23. Nugrohoa E, Taniguchi N. 2004. Daily change of genetic variability in hatchery offspring of red sea bream during spawning season. Fish Sci. 70:638-644. https://doi.org/10.1111/j.1444-2906.2004.00851.x
  24. Porta J, Porta JM, Martınez-Rodrıguez G, Alvarez MC. 2006. Genetic structure and genetic relatedness of a hatchery stock of Senegal sole (Solea senegalensis) inferred by microsatellites. Aquaculture. 251:46-55. https://doi.org/10.1016/j.aquaculture.2005.05.019
  25. Primmer CR, Aho T, Piironen J, Estoup A, Cornuet JM, Ranta E. 1999. Microsatellite analysis of hatchery stocks and natural populations of Arctic charr, Salvelinus alpinus, from the Nordic region: implications for conservation. Hereditas. 130:277-289.
  26. Rice WR. 1989. Analyzing tables of statistical tests. Evolution. 43:223-225. https://doi.org/10.2307/2409177
  27. Rousset F, Raymond M. 1995. Testing heterozygote excess and deficiency. Genetics. 140:1413-1419.
  28. Schneider S, Kueffer JM, Roessli D, Excoffier L. 2000. ARLEQUIN version 2.0: a software for population genetic data analysis. Geneva: Genetics and Biometry Laboratory, University of Geneva.
  29. Sekino M, Hara M, Taniguchi N. 2002. Loss of microsatellite and mitochondrial DNA variation in hatchery strains of Japanese flounder Paralichthys olivaceus. Aquaculture. 213:101-122. https://doi.org/10.1016/S0044-8486(01)00885-7
  30. Skaala O, Hoyheim B, Glover K, Dahle G. 2004. Microsatellite analysis in domesticated and wild Atlantic salmon (Salmo salar L.): allelic diversity and identification of individuals. Aquaculture. 240:131-143. https://doi.org/10.1016/j.aquaculture.2004.07.009
  31. Slatkin M. 1995. A measure of population subdivision based on microsatellite allele frequencies. Genetics. 139: 457-462.
  32. Stahl G. 1987. Genetic population structure of Atlantic salmon. In: Ryman N, Utter F, editors. Population genetics and fishery management. Seattle: University Washington Press. p. 121-140.
  33. Taniguchi N, Sumantadinata K, Iyama S. 1983. Genetic change in the first and second generations of hatchery stock of black sea bream. Aquaculture. 35:309-320. https://doi.org/10.1016/0044-8486(83)90103-5
  34. Tessier N, Bernatchez L, Wright JM. 1997. Population structure and impact supportive breeding inferred from mitochondrial and microsatellite DNA analyses in landlocked Atlantic salmon Salmo salar L. Mol Ecol. 6: 735-750. https://doi.org/10.1046/j.1365-294X.1997.00244.x
  35. Waldman B, McKinnon JS. 1993. Inbreeding and outbreeding in fishes, amphibians and reptiles. In: Thornbel NW, editor. The natural history of inbreeding and outbreeding. Chicago: University of Chicago Press. p. 250-282.
  36. Weir BS, Cockerham CC. 1984. Estimating F-statistics for the analysis of population structure. Evolution. 38: 1358-1370. https://doi.org/10.2307/2408641