doi: 10.15389/agrobiology.2018.2.348eng

UDC 639.3/.5:574.5:591.1

 

GENETIC STRUCTURE OF NATURAL POPULATIONS OF STERLET
(Acipenser ruthenus L.) IN THE CATCHMENT BASINS OF THE KAMA
AND OB RIVERS BASED ON POLYMORPHIC ISSR MARKERS

L.V. Komarova1, 2, N.V. Kostitsyna1, S.V. Boronnikova1, A.G. Melnikova2

1Perm State National Research University, 15, ul. Bukireva, Perm, 614990 Russia, e-mail  lidie.komarova@mail.ru (✉ corresponding author);
2State Research Institute of Limnetic and River Fishery, Perm Department, 3, ul. Chernishevskogo, Perm, 614002 Russia, e-mail melnikova_ag@list.ru

ORCID:
Komarova L.V. orcid.org/0000-0002-7021-0017
Boronnikova S.V. orcid.org/0000-0002-5498-8160
Kostitsyna N.V. orcid.org/0000-0002-8681-2135
Melnikova A.G. orcid.org/0000-0003-2717-5188

Received January 11, 2018

 

Starlet (Acipenser ruthenus L.) is included in the Red Data Books of the Russian Federation, Perm Krai and Kirov Province. Inter-microsatellite DNA polymorphism analysis of sterlet populations of the Kama and Ob rivers has not been performed until now. This paper reports on genetic diversity and genetic structure of five natural sterlet populations of the Kama, Ob and Vyatka rivers based on polymorphism of ISSR-PCR markers. The study was carried out in 2015-2916. DNA was extracted from fragments of pectoral fins of fishes aged 3 to 4 years. DNA samples from 195 individuals were analyzed with five effective ISSR primers. POPGENE 1.31 and GenAlEx6 software was used for statistical processing. Basic genetic parameters were proportion (P95) of polymorphic loci, expected (He) heterozygosity, number of alleles per locus (Na), effective number of alleles per loci (Ne), and number of rare alleles (R). The Bayesian method of population structure analysis was performed using STRUCTURE 2.3.4 software. Genetic structure of a population was characterized by proportion of heterozygous genotypes (HT) in the entire population, the expected proportion of heterozygous genotypes (HS) in the subpopulation, and the proportion of interpopulation genetic diversity (GST). As a result, a total of 128 ISSR-PCR markers were identified. The number of amplified ISSR-PCR markers ranged from 7 to 23 depending on the ISSR primer. It was found that the portion of polymorphic loci in A. ruthenus populations was high and amounted to 0,938. Genetic diversity was the highest in the Vyatka sterlet population (P95 = 0.876; = 0.232; Ne = 1.402; R = 10) and the lowest in the Ob sterlet population (P95 = 0.634; = 0.100; Ne = 1.175; R = 3). A total of 23 rare ISSR-PCR markers were identified for all the samples studied, and 10 of these markers were characteristic of the Vyatka river sterlets. This indicates the possibility of successful identification of these sterlets by population-specific markers. Genetic structure analysis showed that the expected proportion of heterozygous genotypes (HT) for the total sample was 0.283, whereas HS index was much lower making 0.173, therefore, GST value was high and amounted to 0.386. The studied populations were highly differentiated. The interpopulation component accounted for 38.6 % of genetic diversity, while intrapopulation component was responsible for 61.4 %. In each of the studied populations, the rare ISSR-PCR markers have been determined that can be used for identification of studied populations of this species. Thus, the efficiency of ISSR analysis for the identification of sterlets at population level has been proved. It has been established that polylocus ISSR-PCR markers can be used both for characterizing gene pools and for molecular genetic identification of populations and breeds, including sterlet populations and replacement broodstocks. Recommendations for genetic conservation of the Kama and Ob sterlet populations have been developed. These data should be used to manage replacement broodstocks in sterlet artificial reproduction for further release of the fry in a population with an identical gene pool.

Keywords: genetic diversity, gene pool, genetic structure, ISSR-PCR markers, molecular-genetic identification, Acipenser ruthenus L., sterlets.

 

Full article (Rus)

Full article (Eng)

 

REFERENCES

  1. Kharchenko P.N., Glazko V.I. DNK-tekhnologii v razvitii agrobiologii [DNA technology in the development of agrobiology]. Moscow, 2006 (in Russ.). 
  2. Chen Y., Peng Z., Wu C., Ma Z., Ding G., Cao G., Ruan S., Lin S. Genetic diversity and variation of Chinese fir from Fujian province and Taiwan, China, based on ISSR markers. PLoS ONE, 2017, 12(4): e0175571 CrossRef
  3. Wazid H., Surendra Nath B. Genetic characterization of microsporidians infection Indian non-mulberry silkworms (Antheraea assamensis and Samia cynthia ricini) by using PCR based ISSR and RAPD marker assay. Int. J. Indust. Entomol., 2015, 30(1): 6-16.
  4. Mel'nikova M.N., Senchukova S.D., Pavlov S.D. Doklady akademii nauk, 2010, 435(1): 138-141 (in Russ.).  
  5. Zietkiewicz E., Rafalski A., Labuda D. Genome fingerprinting by simple sequence repeat (SSR)-anchored polymerase chain reaction amplification. Genomics, 1994, 20: 176-183.
  6. Glazko V.I., Feofilov A.V., Bardukov N.V., Glazko T.T. Izvestiya Timiryazevskoi sel'skokhozyaistvennoi akademii, 2012, 1: 18-125 (in Russ.).  
  7. Stolpovskii Yu.A. Vavilovskii zhurnal genetiki i selektsii, 2013, 17(4/2): 900-915 (in Russ.).  
  8. Stolpovskii Yu.A., Lazebnyi O.E., Stolpovskii K.Yu., Sulimova G.E. Genetika, 2010, 46(6): 1-9 (in Russ.).  
  9. Stolpovskii Yu.A., Kol N.V., Evsyukov A.N., Nesteruk L.V., Dorzha Ch.M., Tsendsuren TS., Sulimova G.E. Genetika, 2014, 50(10): 1163-1176 CrossRef (in Russ.).  
  10. Nesteruk L.V., Makarova N.N., Evsyukov A.N., Svishcheva G.R., Lhasaranov B.B., Stolpovsky Yu.A. Comparative estimate of the sheep breed gene pools using ISSR-analysis. Russian Journal of Genetics, 2016, 52(3): 304-313 CrossRef
  11. Srivastava P.P., Kar P.K., Awasthi A.K., Raje Urs S. Identification and association of ISSR markers for thermal stress in polyvoltine silkworm Bombyx mori. Russian Journal of Genetics, 2007, 43(8): 858-864 CrossRef
  12. Bhuvaneswari G., Surendra Nath B. Molecular characterization and phylogenetic relationships of seven microsporidian isolates from different Lepidopteran pests cross infecting silkworm Bombyx mori based on intergenic spacer sequence analysis. Journal of Entomology and Zoology Studies, 2015, 3(2): 324-330.
  13. Bazelyuk N.N., Kozlova N.V., Mukhamedova R.M. Estestvennye nauki, 2013, 2: 82-86 (in Russ.). 
  14. Kovalchuk O.M., Hilton E.J. Neogene and Pleistocene sturgeon (Acipenseriformes, Acipenseridae) remains from southeastern Europe. J. Vertebr. Paleontol., 2017, 37(5): e1362644 CrossRef
  15. Krasnaya kniga Rossiiskoi Federatsii. Zhivotnye. [The Red Book of the Russian Federation. Animals]. Moscow, 2001 (in Russ.).  
  16. Krasnaya kniga Permskogo kraya /Pod redaktsiei A.I. Shepelya [The Red Book of the Perm Krai. A.I. Shepel (ed.)]. Perm', 2008 (in Russ.). 
  17. Krasnaya kniga Kirovskoi oblasti. Zhivotnye, rasteniya, griby [The Red Book of Kirov Province. Anumals, plants, fungi]. Ekaterinburg, 2001 (in Russ.). 
  18. Timoshkina N.N., Vodolazhskii D.I., Usatov A.V. Ekologicheskaya genetika, 2010, 8: 12-24 (in Russ.).  
  19. Fopp-Bayat D., Kuzniar P., Kolman R., Liszewski T., Kucinski M. Genetic analysis of six sterlet (Acipenser ruthenus) populations — recommendations for the plan of restitution in the Dniester River. Iran. J. Fish. Sci., 2015, 14(3): 634-645.
  20. Adrianov A.V. Biologiya morya, 2004, 30(1): 3-19 (in Russ.). 
  21. Rogers S.O., Bendich A.J. Extraction of DNA from milligram amounts of fresh, herbarium and mummified plant tissues. Plant Mol. Biol., 1985, 5: 69-76.
  22. Komarova L.V., Kostitsyna N.V., Boronnikova S.V. Materialy Mezhdunarodnoi konferentsii «Tendentsii innovatsionnykh protsessov v nauke»[Proc. Int. Conf. «Trends in innovative processes in science. Part 1]. Moscow, 2015, chast’ 1: 6-8 (in Russ.). 
  23. Yeh F.C., Mao J., Young R.C. POPGENE, the Microsoft Windows-based user-friendly software for population genetic analysis of co-dominant and dominant markers and quantitative traits. Alta, Department of Renewable Resources, University of Alberta, Edmonton, 1999.
  24. Peakall R., Smouse P.E. GenAlEx6: Genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes, 2006, 6: 288-295.
  25. Nei M. Molecular population genetics and evolution. Amsterdam, 1975.
  26. Nei M., Li W.-H. Mathematical model for studying genetic variation in terms restriction endonucleases. PNAS USA, 1979, 76: 5269-5273 CrossRef
  27. Earl D.A., Vonholdt B.M. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv. Genet. Resour., 2012, 4(2): 359-361 CrossRef
  28. Evanno G., Regnaut S., Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol. Ecol., 2005, 14(8): 2611-2620 CrossRef
  29. Glazko V.I., Gladyr’ E.A., Feofilov A.V., Bardukov N.V., Glazko T.T. ISSR-PCR and mobile genetic elements in genomes of farm mammalian species. Agricultural Biology, 2013, 2: 71-75 CrossRef
  30. Barmintseva A.E., Myuge N.S. Genetika zhivotnykh, 2013, 49: 1093-1105 CrossRef (in Russ.). 

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