Russian Journal of Genetics

, Volume 49, Issue 8, pp 827–838 | Cite as

Large-scale development of PIP and SSR markers and their complementary applied in Nicotiana

  • L. HuangEmail author
  • H. Cao
  • L. Yang
  • Y. Yu
  • Y. Wang
Plant Genetics


PIP (Potential Intron Polymorphism) and SSR (Simple Sequence Repeats) were used in many species, but large-scale development and combined use of these two markers have not been reported in tobacco. In this study, a total of 12,388 PIP and 76,848 SSR markers were designed and uploaded to a webaccessible database ( E-PCR analysis showed that PIP and SSR rarely over-lapped and were strongly complementary in the tobacco genome. The density of markers was 3.07 PIP and 1.72 SSR per 10 kb of the known sequences. A total of 153 and 166 alleles were detected by 22 PIP and 22 SSR markers in 64 Nicotiana accessions. SSR produced higher PIC (polymorphism information content) values and identified more alleles than PIP, whereas PIP could identify larger numbers of rare alleles. Mantel testing demonstrated a high correlation coefficient (r = 0.949, P < 0.001) between PIP and SSR. The UPGMA dendrogram created from the combined PIP and SSR markers was clearer and more reliable than the individual PIP or SSR dendrograms. It suggested that PIP and SSR can make up the deficiency of molecular markers not only in tobacco but other plant.


Polymorphism Information Content Nicotiana Tabacum Large Scale Development Tobacco Genome Tobacco Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Arslan, B. and Okumus, A., Genetic and geographic polymorphism of cultivated tobaccos (Nicotiana tabacum) in Turkey, Russ. J. Genet., 2006, vol. 42, no. 6, pp. 667–671.CrossRefGoogle Scholar
  2. 2.
    Lim, K.Y., Matyasek, R., Kovarik, A., and Leitch, A.R., Genome evolution in allotetraploid Nicotiana, Biol. J. Linn. Soc., 2004, vol. 82, no. 4, pp. 599–606.CrossRefGoogle Scholar
  3. 3.
    Knapp, S., Chase, M.W., and Clarkson, J.J., Nomenclatural changes and a new sectional classification in Nicotiana (Solanaceae), Taxon, 2004, vol. 53, no. 1, pp. 73–82.CrossRefGoogle Scholar
  4. 4.
    Goodspeed, T.H., The Genus Nicotiana, Waltham: Mass. Chronica Botanica, 1954.Google Scholar
  5. 5.
    Arumuganathan, K. and Earle, E., Nuclear DNA content of some important plant species, Plant Mol. Biol. Rep., 1991, vol. 9, no. 3, pp. 208–218.CrossRefGoogle Scholar
  6. 6.
    Lewis, R.S., Nicotiana Wild Crop Relatives: Genomic and Breeding Resources, Berlin: Springer-Verlag, 2011.Google Scholar
  7. 7.
    Bindler, G., van der Hoeven, R., Gunduz, I., et al., A microsatellite marker based linkage map of tobacco, Theor. Appl. Genet., 2007, vol. 114, no. 2, pp. 341–349.PubMedCrossRefGoogle Scholar
  8. 8.
    Ren, N. and Timko, M.P., AFLP analysis of genetic polymorphism and evolutionary relationships among cultivated and wild Nicotiana species, Genome, 2001, vol. 44, no. 4, pp. 559–571.PubMedGoogle Scholar
  9. 9.
    Zhang, H.Y., Liu, X.Z., He, C.S., and Yang, Y.M., Genetic diversity among flue-cured tobacco cultivars based on RAPD and AFLP markers, Braz. Arch. Biol. Technol., 2008, vol. 51, pp. 1097–1101.CrossRefGoogle Scholar
  10. 10.
    Yang, B.C., Xiao, B.G., Chen, X.J., and Shi, C.H., Genetic diversity of flue-cured tobacco varieties based on ISSR markers, Yi Chuan, 2005, vol. 27, no. 5, pp. 753–758.PubMedGoogle Scholar
  11. 11.
    Tóth, G., Gáspári, Z., and Jurka, J., Microsatellites in different eukaryotic genomes: Survey and analysis, Genome Res., 2000, vol. 10, no. 7, pp. 967–981.PubMedCrossRefGoogle Scholar
  12. 12.
    Powell, W., Morgante, M., Andre, C., et al., The comparison of RFLP, RAPD, AFLP and SSR (microsatellite) markers for germplasm analysis, Mol. Breed., 1996, vol. 2, no. 3, pp. 225–238.CrossRefGoogle Scholar
  13. 13.
    Davalieva, K., Maleva, I., Filiposki, K., et al., Genetic variability of Macedonian tobacco varieties determined by microsatellite marker analysis, Diversity, 2010, vol. 2, no. 4, pp. 439–449.CrossRefGoogle Scholar
  14. 14.
    Moon, H.S., Nifong, J.M., Nicholson, J.S., et al., Microsatellite-based analysis of tobacco (Nicotiana tabacum L.) genetic resources, Crop Sci., 2009, vol. 49, no. 6, pp. 2149–2159.CrossRefGoogle Scholar
  15. 15.
    Moon, H.S., Nifong, J.M., Heineman, A., et al., Changes in genetic diversity of U.S. flue-cured tobacco germplasm over seven decades of cultivar development, Crop Sci., 2009, vol. 49, no. 2, pp. 498–508.CrossRefGoogle Scholar
  16. 16.
    Moon, H.S., Nicholson, J.S., and Lewis, R.S., Use of transferable Nicotiana tabacum L. microsatellite markers for investigating genetic diversity in the genus Nicotiana, Genome, 2008, vol. 51, no. 8, pp. 547–559.PubMedCrossRefGoogle Scholar
  17. 17.
    Bindler, G., Plieske, J., Bakaher, N., et al., A high density genetic map of tobacco (Nicotiana tabacum L.) obtained from large scale microsatellite marker development, Theor. Appl. Genet., 2011, vol. 123, no. 2, pp. 219–230.PubMedCrossRefGoogle Scholar
  18. 18.
    Wang, X.S., Zhao, X.Q., Zhu, J., and Wu, W.R., Genome-wide investigation of intron length polymorphisms and their potential as molecular markers in rice (Oryza sativa L.), DNA Res., 2006, vol. 12, no. 6, pp. 417–427.CrossRefGoogle Scholar
  19. 19.
    Zhao, X.Q., Yang, L., Zheng, Y., et al., Subspecies-specific intron length polymorphism markers reveal clear genetic differentiation in common wild rice (Oryza rufipogon L.) in relation to the domestication of cultivated rice (O. sativa L.). J. Genet. Genomics, 2009, vol. 36, no. 7, pp. 435–442.PubMedCrossRefGoogle Scholar
  20. 20.
    Huang, M., Xie, F.M., Chen, L.Y., et al., Comparative analysis of genetic diversity and structure in rice using 1LP and SSR markers, Rice Sci., 2010, vol. 17, no. 4, pp. 257–268.CrossRefGoogle Scholar
  21. 21.
    Dong, Q., Schlueter, S.D., and Brendel, V., Plant- GDB, plant genome database and analysis tools, Nucleic Acids Res., 2004, vol. 32, pp. D354–D359.PubMedCrossRefGoogle Scholar
  22. 22.
    Yang, L., Jin, G., Zhao, X.Q., et al., PIP: A database of potential intron polymorphism markers, Bioinformatics, 2007, vol. 23, no. 16, pp. 2174–2177.PubMedCrossRefGoogle Scholar
  23. 23.
    Wang, Y.Y., Chen, J., Francis, D., et al., Discovery of intron polymorphisms in cultivated tomato using both tomato and Arabidopsis genomic information, Theor. Appl. Genet., 2010, vol. 121, no. 7, pp. 1199–1207.PubMedCrossRefGoogle Scholar
  24. 24.
    Chen, X., Zhang, G., and Wu, W., Investigation and utilization of intron length polymorphisms in conifers, New For., 2011, vol. 41, no. 3, pp. 379–388.CrossRefGoogle Scholar
  25. 25.
    Liu, H.L., Lin, Y.A., Chen, Y., et al., Genome-scale identification of resistance gene analogs and the development of their intron length polymorphism markers in maize, Mol. Breed., 2011, pp. 1–11.Google Scholar
  26. 26.
    Murray, M.G. and Thompson, W.F., Rapid isolation of high molecular weight plant DNA, Nucleic Acids Res., 1980, vol. 8, no. 19, pp. 4321–4326.PubMedCrossRefGoogle Scholar
  27. 27.
    Rozen, S. and Skaletsky, H., Primer3 on the www for general users and for biologist programmers, Methods Mol. Biol., 2000, vol. 132, pp. 365–86.PubMedGoogle Scholar
  28. 28.
    Schuler, G.D., Sequence mapping by electronic PCR, Genome Res., 1997, vol. 7, no. 5, pp. 541–550.PubMedGoogle Scholar
  29. 29.
    Saal, B. and Wricke, G., Development of simple sequence repeat markers in rye (Secale cereale L.), Genome, 1999, vol. 42, no. 5, pp. 964–972.PubMedGoogle Scholar
  30. 30.
    Nei, M., Analysis of gene diversity in subdivided populations, Proc. Natl. Acad. Sci. U.S.A., 1973, vol. 70, no. 12, pp. 3321–3323.PubMedCrossRefGoogle Scholar
  31. 31.
    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.PubMedCrossRefGoogle Scholar
  32. 32.
    Mantel, N., The detection of disease clustering and a generalized regression approach, Cancer Res., 1967, vol. 27, no. 2, pp. 209–220.PubMedGoogle Scholar
  33. 33.
    Rohlf, J.F., NTSYSpc: Numerical Taxonomy and Multi-variate Analysis System, Setauket: Exeter Software, 2000.Google Scholar
  34. 34.
    Hampl, V., Pavlicek, A., and Flegr, J., Construction and bootstrap analysis of DNA fingerprinting-based phylogenetic trees with the freeware program FreeTree: Application to trichomonad parasites, Int. J. Syst. Evol. Microbiol., 2001, vol. 51, no. 3, pp. 731–735.PubMedCrossRefGoogle Scholar
  35. 35.
    Ali, M., Rajewski, J., Baenziger, P., et al., Assessment of genetic diversity and relationship among a collection of U.S. sweet sorghum germplasm by SSR markers, Mol. Breed., 2008, vol. 21, no. 4, pp. 497–509.CrossRefGoogle Scholar
  36. 36.
    Bowcock, A.M., Ruizlinares, A., Tomfohrde, J., et al., High-resolution of human evolutionary trees with polymorphic microsatellites, Nature, 1994, vol. 368, no. 6470, pp. 455–457.PubMedCrossRefGoogle Scholar
  37. 37.
    Lewis, R. and Nicholson, J., Aspects of the evolution of Nicotiana tabacum L. and the status of the United States Nicotiana germplasm collection, Genet. Resour. Crop. Evol., 2007, vol. 54, no. 4, pp. 727–740.CrossRefGoogle Scholar
  38. 38.
    Julio, E., Verrier, J.L., and de Borne, F., Development of SCAR markers linked to three disease resistances based on AFLP within Nicotiana tabacum L., Theor. Appl. Genet., 2006, vol. 112, no. 2, pp. 335–346.PubMedCrossRefGoogle Scholar

Copyright information

© Pleiades Publishing, Ltd. 2013

Authors and Affiliations

  1. 1.Tobacco Laboratory, College of Plant ProtectionShandong Agricultural UniversityTai’an, ShandongChina
  2. 2.College of AgronomyShandong Agricultural UniversityTai’an, ShandongChina

Personalised recommendations