Fisheries Science

, Volume 72, Issue 3, pp 556–567 | Cite as

Genetic population evaluation of two closely related flatfish species, the rare barfin flounder and spotted halibut, along the Japanese coast

  • María Del Mar Ortega-Villaizán Romo
  • Masato Aritaki
  • Shigenori Suzuki
  • Minoru Ikeda
  • Takashi Asahida
  • Nobuhiko Taniguchi
Article

Abstract

Barfin flounder and spotted halibut have been selected as target species for stock enhancement in Japan. Understanding the genetic condition of the wild stock is a principal requirement in any stock enhancement program. The genetic variability of barfin flounder and spotted halibut, and the population structure of spotted halibut were evaluated using microsatellite DNA markers (msDNA) and the control region of the mitocondrial DNA (mtDNA). Barfin flounder and spotted halibut showed high genetic variability at the msDNA level. Barfin flounder A was 16.7 and H e was 0.860; spotted halibut A n ranged from 7.7 to 10.2 and H e ranged from 0.710 to 0.774. At the mtDNA level, high haplotype (h=0.922) and low nucleotide (π=0.002) diversities were observed for barfin flounder; however, low haplotype and nucleotide diversities (h=0.603–0.620 and π=0.001–0.002), and very low haplotype and nucleotide diversities (h=0.193 and π=0.0003) were observed for spotted halibut in the north and south locations, respectively. Slight genetic differentiation among spotted halibut sampling locations was observed from the msDNA. MtDNA analyses showed genetic differentiation between north and south locations, but not within them. The designation of north-specific and south-specific management units in the future stock enhancement activities of spotted halibut is recommended.

Key Words

barfin flounder control region genetic variability microsatellite DNA population structure related species spotted halibut 

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References

  1. 1.
    Masuda H, Amaoka K, Araga C, Uveno T, Yoshino T. The Fishes of the Japanese Archipelago. Tokai University Press, Kanagawa, Japan. 1984; 351–352.Google Scholar
  2. 2.
    Minami T. Matsukawa. In: Fisheries Agency (eds). Basic Data About Rare Japanese Wild Aquatic Organisms (Marine Fishes). Japan Fisheries Resource Conservation Association, Tokyo, Japan. 1994; 284–288.Google Scholar
  3. 3.
    Sasaki M. Barfin flounder fisheries and ecology in Hidaka and Iburi (Pacific Ocean). Hokusuishi Dayori 1997; 38: 7–12.Google Scholar
  4. 4.
    Primack RB. Essentials of Conservation Biology. Sinauer Associates, Massachusetts, USA. 1993.Google Scholar
  5. 5.
    Aritaki M, Ohta K, Hotta Y, Tanaka M. Morphological development and growth of laboratory-reared spotted halibut Verasper variegatus. Nippon Suisan Gakkaishi 2001; 67: 58–66.Google Scholar
  6. 6.
    Watanabe K, Suzuki S, Nishiki A. Migration, growth and stock enhancement effects of hatchery-reared barfin flounder, Verasper moseri, juveniles released in Akkeshi bay. Saibai Giken 2001; 28: 93–99.Google Scholar
  7. 7.
    JASFA (Japan Sea Farming Association), ed. Annual Technical Report of the Japan Sea Farming Association. JASFA, Tokyo. 1989–2002. (in Japanese).Google Scholar
  8. 8.
    Taniguchi N. Broodstock management for stock enhancement programs of marine fish with assistance of DNA markers (a review). In: Leber KM, Kitada S, Blankenship HL, Svåsand T (eds). Stock Enhancement and Sea Ranching. Developments, Pitfalls and Opportunities. Blackwell, MA. 2004; 329–338.Google Scholar
  9. 9.
    O’Reilly P, Wright JM. The evolving technology of DNA fingerprinting and its application to fisheries and aquaculture. J. Fish Biol. 1995; 47: 29–55.CrossRefGoogle Scholar
  10. 10.
    Avise JC, Arnold J, Ball M, Bermingham E, Lamb T, Neigel JE, Reeb CA, Saunders NC. Intraespecific phylogeography: the mitochondrial DNA bridge between population genetics and systematics. Annu. Rev. Ecol. Syst. 1987; 18: 489–522.Google Scholar
  11. 11.
    Hoarau G, Piquet AMT, Van der Veer HW, Rijnsdorp AD, Stam WT, Olsen JL. Population structure of plaice (Pleuronectes platessa L.) in northern Europe: a comparison of resolving power between microsatellites and mitochondrial DNA data. J. Sea Res. 2004; 51: 183–190.CrossRefGoogle Scholar
  12. 12.
    Tsuzaki T. Present status and problems of seedling production of spotted halibut, Verasper variegatus. Suisanzoshoku 1995; 43: 273–276.Google Scholar
  13. 13.
    Aritaki M. Metamorphosis and morphological abnormalities of the flatfish. Kaiyo Monthly 1995; 27: 732–739.Google Scholar
  14. 14.
    Asahida T, Kobayashi T, Saitoh K, Nakayama I. Tissue preservation and total DNA extraction from fish stored at ambient temperature using buffers containing high concentration of urea. Fish. Sci. 1996; 62: 727–730.Google Scholar
  15. 15.
    Ortega-Villaizán Romo M, Nakajima M, Taniguchi N. Microsatellite DNA markers isolation and characterization in the rare species barfin flounder (Verasper moseri) and its close related species spotted halibut (Verasper variegatus). Mol. Ecol. Notes 2003; 3: 629–631.CrossRefGoogle Scholar
  16. 16.
    Lee WJ, Conroy J, Howell WH, Kocher TD. Structure and evolution of teleost mitochondrial control regions. J. Mol. Evol. 1995; 41: 54–66.PubMedCrossRefGoogle Scholar
  17. 17.
    Raymond M, Rousset F. Genepop (Version 3.4): Population genetics software for exact test and ecumenicism. J. Hered 1995; 86: 248–249.Google Scholar
  18. 18.
    Rice RW. Analyzing tables of statistical tests. Evolution 1989; 43: 223–225.CrossRefGoogle Scholar
  19. 19.
    Crow JF, Kimura M. Evolution in sexual and asexual populations. Am. Nat. 1965; 99: 439–473.CrossRefGoogle Scholar
  20. 20.
    Goudet J. FSTAT, a Program to Estimate and Test Gene Diversities and Fixation Indices (version 2.9.3) [cited 3 March 2005.] Available from URL: http://www.unil.ch/izea/softwares/fstat.html.2001.Google Scholar
  21. 21.
    Excoffier L, Smouse P, Quattro J. Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 1992; 131: 479–491.PubMedGoogle Scholar
  22. 22.
    Schneider S, Roessli D, Excoffier L. Arlequin: A Software for Population Genetics Data Analysis. Ver 2.000. Genetics and Biometry Laboratory, Department of Anthropology. University of Geneva. Geneva, Switzerland. 2000.Google Scholar
  23. 23.
    Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure. Evolution 1984; 38: 1358–1370.CrossRefGoogle Scholar
  24. 24.
    Saitou N, Nei M. The neighbour-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 1987; 4: 406–425.PubMedGoogle Scholar
  25. 25.
    Cavalli-Sforza LL, Edwards WF. Phylogenetic analysis: models and estimation procedures. Am. J. Hum. Genet 1967; 19: 233–257.PubMedGoogle Scholar
  26. 26.
    Felsenstein J. PHYLIP (version 3.6) Phylogeny Inference Package. Department of Genetics, University of Washington, Seattle, WA, USA. 2000.Google Scholar
  27. 27.
    Tamura K. TreeExplorer software v2.12 [cited 3 March 2005.] Available from URL: http://evolgen.biol.metro-u.ac.jp/TE/TE_man.html). 1999.Google Scholar
  28. 28.
    Takezaki N, Nei M. Genetic distances and reconstruction of phylogenetic tress from microsatellite DNA. Genetics 1996; 144: 389–399.PubMedGoogle Scholar
  29. 29.
    Thompson JD, Higgins DG, Gibson TJ, Clustal W. Improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position specific gap penalties, and weight matrix choice. Nucleic Acids Res. 1994; 22: 4673–4680.PubMedCrossRefGoogle Scholar
  30. 30.
    Nei M. Molecular Evolutionary Genetics. Columbia University Press, New York, USA. 1987.Google Scholar
  31. 31.
    Tajima F. Evolutionary relationship of DNA sequences in finite populations. Genetics 1983; 105: 437–460.PubMedGoogle Scholar
  32. 32.
    Nei M, Li WH. Mathematical model for studying genetic variation in terms of restriction endonucleases. Proc. Natl. Acad. Sci. USA 1979; 76: 5269–5273.PubMedCrossRefGoogle Scholar
  33. 33.
    Templeton AR, Crandall KA, Sing CF. A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping and DNA sequence data III. Cladogram estimation. Genetics 1992; 132: 619–633.PubMedGoogle Scholar
  34. 34.
    Clement M, Posada D, Crandall KA. TCS: a computer program to estimate gene genealogies. Mol. Ecol. 2000; 9: 1657–1659.PubMedCrossRefGoogle Scholar
  35. 35.
    Sekino M, Hara M. Application of microsatellite markers to population genetics studies of Japanese flounder. Paralichthys olivaceus. Mar. Biotechnol. 2001; 3: 572–589.CrossRefGoogle Scholar
  36. 36.
    Sekino M, Saitoh K, Yamada T, Kumagai A, Hara M, Yamashita Y. Microsatellite-based pedigree tracing in a Japanese flounder Paralichthys olivaceus hatchery strain: implications for hatchery management related to stock enhancement program. Aquaculture 2003; 221: 255–263.CrossRefGoogle Scholar
  37. 37.
    Hoarau G, Rijnsdorp D, Van der Veer HW, Stam WT, Olsen JL Population structure of plaice (Pleuronectes platessa L.) in northern Europe: microsatellites revealed large-scale spatial and temporal homogeneity. Mol. Ecol. 2002; 11: 1165–1176.PubMedCrossRefGoogle Scholar
  38. 38.
    Pérez-Enríquez R, Taniguchi N. Use of microsatellite DNA as genetic tags for the assessment of a stock enhancement program of red sea bream. Fish. Sci. 1999; 65: 374–379.Google Scholar
  39. 39.
    Tabata K, Taniguchi N. Differences between Pagrus major and Pagrus auratus through mainly mtDNA control region analysis. Fish. Sci. 2000; 66: 9–18.CrossRefGoogle Scholar
  40. 40.
    Takagi M, Shoji E, Taniguchi N. Microsatellite DNA polymorphism to reveal genetic divergence in ayu, Plecoglossus altivelis. Fish. Sci. 1999; 65: 507–512.Google Scholar
  41. 41.
    Matsuda T, Matsukawa, Verasper moseri, Jordan and Gilbert. In: Ueda Y, Maeda K, Shimada H, Takami T (eds). Fisheries and Aquatic Life in Hokkaido. The Hokkaido Shimbun Press, Hokkaido, Japan. 2003; 242–245.Google Scholar
  42. 42.
    JASFA (Japan Sea Farming Association). Investigation promotion of hoshigarei sea farming technology development. Japan Sea Farming Association Report 2002; 81: 49–84.Google Scholar
  43. 43.
    Pope TR. Genetic variation in remnant populations of the woolly spider monkey (Brachyteles arachoides). Int. J. Primatol. 1998; 19: 95–109.CrossRefGoogle Scholar
  44. 44.
    Grant WS, Bowen BW. Shallow populations histories in deep evolutionary lineages of marine fishes: insights from sardines and anchovies and lessons for conservation. J. Hered 1998; 89: 415–426.CrossRefGoogle Scholar
  45. 45.
    Bouza C, Presa P, Castro J, Sánchez L, Martínez P. Allozyme and microsatellite diversity in natural and domestic populations of turbot (Scophthalmus maximus) in comparison with other Pleuronectiformes. Can. J. Fish. Aquat. Sci. 2002; 59: 1460–1473.CrossRefGoogle Scholar
  46. 46.
    Birky CW, Maruyama T, Fuerst P. An approach to population and evolutionary genetic theory for genes in mitochondria and chloroplasts, and some results. Genetics 1983; 103: 513–527.PubMedGoogle Scholar
  47. 47.
    Sato A, Takezaki N, Tichy H, Figueroa F, Mayer WE, Klein J. Origin and speciation of haplochromine fishes in east African crater lakes investigated by the analysis of their mtDNA, Mhc genes, and SINEs. Mol. Biol. Evol 2003; 20: 1448–1462.PubMedCrossRefGoogle Scholar
  48. 48.
    García de León FJ, Chikhi L, Bonhomme F. Microsatellite polymorphism and population subdivision in natural population of European sea bass, Dicentrarchus labrax. Mol. Ecol. 1997; 6: 51–62.CrossRefGoogle Scholar
  49. 49.
    Hansen MM, Mensberg KLD, Berg S. Postglacial recolonization patterns and genetic relationships among whitefish (Coregonus sp.) populations in Denmark, inferred from mitochondrial DNA and microsatellites. Mol. Ecol. 1999; 8: 239–252.CrossRefGoogle Scholar
  50. 50.
    Pardini AM, Jones CS, Noble LR, Kreiser B, Malcom H, Bruces BD, Stevens JD, Cliff G, Scholl MC, Francis M, Duffy CAJ, Martin AP. Sex-biased dispersal of great white sharks. Nature 2001; 412: 139–140.PubMedCrossRefGoogle Scholar
  51. 51.
    Moritz C. Defining ‘evolutionary significant units’ for conservation. Trends Ecol. Evol 1994; 9; 373–375.CrossRefGoogle Scholar

Copyright information

© The Japanese Society of Fisheries Science 2006

Authors and Affiliations

  • María Del Mar Ortega-Villaizán Romo
    • 1
  • Masato Aritaki
    • 2
  • Shigenori Suzuki
    • 3
  • Minoru Ikeda
    • 1
  • Takashi Asahida
    • 4
  • Nobuhiko Taniguchi
    • 1
  1. 1.Laboratory of Population Genetic Informatics, Graduate School of Agricultural ScienceTohoku UniversityMiyagiJapan
  2. 2.Miyako StationNational Center for Stock EnhancementIwateJapan
  3. 3.Akkeshi StationNational Center for Stock EnhancementHokkaidoJapan
  4. 4.School of Fisheries ScienceKitasato UniversityIwateJapan

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