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Cytology and Genetics

, Volume 52, Issue 1, pp 1–10 | Cite as

Comparative analysis of the efficiency of intron-length polymorphism of β-tubulin genes and microsatellite loci for flax varieties genotyping

  • A. N. RabokonEmail author
  • Ya. V. Pirko
  • A. Ye. Demkovych
  • Ya. B. Blume
Article

Abstract

Efficacy of the β-tubulin introns lenght polymorphism method (TBP) was used for Ukrainian bredeed flax cultivars genotyping. For this purpose, TBP data were compared with data produced using the two most effective species-specific SSR markers. Both methods were used to evaluate intra- and intercultivar flax polymorphism. For each cultivar, PIC data (Polymorphism Information Content) and the range of allele lenghts, as well as the number of allele phenotypes, were calculated using TBP and SSR markers. The dendrograms, built using Nei and Li’s similarity coefficient, differ for SSR and TBP markers. Most flax cultivars of Ukrainian selection were genetically heterogeneous. The TBP method was highly efficient for differentiation of flax genotypes versus SSR analysis.

Keywords

molecular-genetic markers TBP (tubulin base polymorphism) SSR (simple sequence repeats) flax (Linum L.) DNA fingerprinting 

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References

  1. 1.
    Pali, V., Verma, S.K., Xalxo, M.S., Saxena, R.R., Mehta, N., and Verulkar, S.B., Identification of microsatellite markers for fingerprinting popular Indian flax (Linum usitatissimum L.) cultivars and their utilization in seed genetic purity assessments, Austral. J. Crop Sci., 2014, vol. 8, no. 1, pp. 119–126.Google Scholar
  2. 2.
    Khlestkina, E.K., Molecular markers in genetic studies and breeding, Russ. J. Genet. Appl. Res., 2014, vol. 4, no. 3, pp. 236–244.CrossRefGoogle Scholar
  3. 3.
    Genetic Aspects of Plant Breeding: Biotechnology in Plant Breeding, vol. 4: Genomics and Genetic Engineering, Kilchevsky, A.V. and Khotyleva, L.V., Eds., Minsk: Belaruskaya Navuka, 2014.Google Scholar
  4. 4.
    Kvavadze, E., Bar-Yosef, O., Belfer-Cohen, A., Boaretto, E., Jakeli, N., Matskevich, Z., and Meshveliani, T., 30000-Year-old wild flax fibers, Science, 2009, vol. 325, no. 5946, p. 1359.CrossRefPubMedGoogle Scholar
  5. 5.
    Jhala, A.J. and Hall, L.M., Flax (Linum usitatissimum L.): current uses and future applications, Austral. J. Basic Appl. Sci., 2010, vol. 4, no. 9, pp. 4304–4312.Google Scholar
  6. 6.
    Allaby, R.G., Peterson, G.W., Merriwether, D.A., and Fu, Y.B., Evidence of the domestication history of flax (Linum usitatissimum L.) from genetic diversity of the sad2 locus, Theor. Appl. Genet., 2005, vol. 112, no. 1, pp. 58–65.CrossRefPubMedGoogle Scholar
  7. 7.
    Blakeney, M., Intellectual property, biological diversity and agricultural research in Australia, Austral. J. Agric. Res., 2002, vol. 53, no. 2, pp. 127–147.CrossRefGoogle Scholar
  8. 8.
    Singh, P., Mehta, N., and Sao, A., Genetic purity assessment in linseed (Linum usitatissimum L.) varieties using microsatellite markers, Bioscan, 2015, vol. 10, no. 4, pp. 2031–2036.Google Scholar
  9. 9.
    Oh, T.J., Gorman, M., and Cullis, C.A., RFLP and RAPD mapping in flax (Linum usitatissimum), Theor. Appl. Genet., 2000, vol. 101, no. 4, pp. 590–593.CrossRefGoogle Scholar
  10. 10.
    Cloutier, S., Ragupathy, R., Miranda, E., Radovanovic, N., Reimer, E., Walichnowski, A., Ward, K., Rowland, G., Duguid, S., and Banik, M., Integrated consensus genetic and physical maps of flax (Linum usitatissimum L.), Theor. Appl. Genet., 2012, vol. 125, no. 8, pp. 1783–1795.CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Fu, Y.B., Redundancy and distinctiveness in flax germplasm as revealed by RAPD dissimilarity, Plant Genet. Res., 2006, vol. 4, pp. 117–124.CrossRefGoogle Scholar
  12. 12.
    Everaert, I., De Riek, J., De Loose, M., Van Waes, J., and Van Bockstaele, E., Most similar variety grouping for distinctness evaluation of flax and linseed (Linum usitatissimum L.) varieties by means of AFLP and morphological data, Plant Variet. Seeds, 2001, vol. 14, no. 2, pp. 69–87.Google Scholar
  13. 13.
    Pali, V., Mehta, N., Verulkar, S.B., Xalxo, M.S., and Saxena, R.R., Molecular diversity in flax (Linum usitatissimum L.) as revealed by DNA based markers, Int. J. Plant Res., 2015, vol. 28, pp. 157–165.Google Scholar
  14. 14.
    Rabokon, N., Pirko, Ya., Demkovych, A., and Blume, Ya., Intron length polymorphism of betatubulin genes as an effective instrument for plant genotyping, Mol. Appl. Genet. (Minsk), 2015, vol. 19, pp. 35–44.Google Scholar
  15. 15.
    Bardini, M., Lee, D., Donini, P., Mariani, A., Giani, S., Toschi, M., Lowe, C., and Breviario, D., Tubulin-based polymorphism (TBP): a new tool, based on functionally relevant sequences, to assess genetic diversity in plant species, Genome, 2004, vol. 47, no. 2, pp. 281–291.CrossRefPubMedGoogle Scholar
  16. 16.
    Wang, X., Zhao, X., Zhu, J., and Wu, W., Genomewide investigation of intron length polymorphisms and their potential as molecular markers in rice (Oryza sativa L.), DNA Res., 2005, vol. 12, no. 6, pp. 417–427.CrossRefPubMedGoogle Scholar
  17. 17.
    Braglia, L., Manca, A., Mastromauro, F., and Breviario, D., cTBP: a successful intron length polymorphism (ILP)-based genotyping method targeted to well defined experimental needs, Diversity, 2010, vol. 2, pp. 572–585.CrossRefGoogle Scholar
  18. 18.
    Gavazzi, F., Braglia, L., Mastromauro, F., Giani, S., Morello, L., and Breviario, D., The Tubulin-Based- Polymorphism method provides a simple and effective alternative to the genomic profiling of grape, PLoS One, 2016, vol. 11, no. 9, p. e0163335.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Pirko, Ya.V., Studying of genetic diversity different species of plants by analyzing polymorphism of introns of- tubulin genes, Industr. Bot., 2011, vol. 11, pp. 152–156.Google Scholar
  20. 20.
    Breviario, D., Giani, S., Ponzoni, T., Mastromauro, F., and Morello, L., Plant tubulin intronics, Cell Biol. Int., 2008, vol. 32, no. 5, pp. 571–573.CrossRefPubMedGoogle Scholar
  21. 21.
    Breviario, D., Plant tubulin genes: regulatory and evolutionary aspects, in Plant Microtubules, Nick, P., Ed., Berlin: Springer, 2008, pp. 207–232.CrossRefGoogle Scholar
  22. 22.
    Cleveland, D.W. and Sullivan, K.F., Molecular biology and genetics of tubulin, Annu. Rev. Biochem., 1985, vol. 54, pp. 331–365.CrossRefPubMedGoogle Scholar
  23. 23.
    Sambrook, J. and David, W.R., Molecular Cloning: A Laboratory Manual, New York: Cold Spring Harbor, 2001, vol. 2.Google Scholar
  24. 24.
    Benbouza, H., Jacquemin, J.-M., and Baudin, J.-P., Optimization of a reliable, fast, cheap and sensitive silver staining method to detect SSR markers in polyacrylamide gels, Biotechnol. Agron. Soc. Environ., 2006, vol. 10, no. 2, pp. 77–81.Google Scholar
  25. 25.
    Lazar, I., GelAnalyzer.com [homepage on the Internet], 2010. http://www.gelanalyzer.com/.Google Scholar
  26. 26.
    Nei, M. and Li, W.H., Mathematical model for studying genetic variation in terms of restriction endonucleases, Proc. Natl. Acad. Sci. U.S.A., 1979, vol. 76, no. 10, pp. 5269–5273.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Pavlicek, A., Hrda, S., and Flegr, J., FreeTree—freeware program for construction of phylogenetic trees on the basis of distance data and bootstrap/jackknife analysis of the tree robustness. Application in the RAPD analysis of the genus Frenkelia, Folia Biol. (Praha), 1999, vol. 45, no. 3, pp. 97–99.Google Scholar
  28. 28.
    Hillis, D.M. and Bull, J.J., An empirical test of bootstrapping as a method for assessing confidence in phylogenetic analysis, Syst. Biol., 1993, vol. 42, no. 2, pp. 182–192.CrossRefGoogle Scholar
  29. 29.
    Rambaut, A., FigTree, a graphical viewer of phylogenetic trees, Online, accessed July 27, 2015. http://tree.bio.ed. ac.uk/software/figtree/.Google Scholar
  30. 30.
    Anderson, J.A., Churchill, G.A., Autrique, J.E., Tanksley, S.D., and Sorrells, M.E., Optimizing parental selection for genetic linkage maps, Genome, 1993, vol. 36, no. 1, pp. 181–186.CrossRefPubMedGoogle Scholar
  31. 31.
    Kondratyuk, A.V., Kilchevsky, A.V., and Kuzminova, E.I., Microsatellite loci polymorphism analysis of Belarusian and foreign breeding potato varieties, Mol. Appl. Genet. (Minsk), 2005, vol. 13, pp. 24–29.Google Scholar
  32. 32.
    Kulibaba, R.A. and Liashenko, Y.V., Influence of the pcr artifacts on the genotyping efficiency by the microsatellite loci using native polyacrylamide gel electrophoresis, Cytol. Genet., 2016, vol. 50, no. 3, pp. 162–167.CrossRefGoogle Scholar
  33. 33.
    Chandrawati, SinghN., Kumar, R., Kumar, S., Singh, P.K., Yadav, V.K., Ranade, S.A., and Yadav, H.K., Genetic diversity, population structure and association analysis in linseed (Linum usitatissimum L.), Physiol. Mol. Biol. Plants, 2017, vol. 23, no. 1, pp. 207–219.CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Allerton Press, Inc. 2018

Authors and Affiliations

  • A. N. Rabokon
    • 1
    Email author
  • Ya. V. Pirko
    • 1
  • A. Ye. Demkovych
    • 1
  • Ya. B. Blume
    • 1
  1. 1.Institute of Food Biotechnology and GenomicsNational Academy of Sciences of UkraineKyivUkraine

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