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Cereal Research Communications

, Volume 42, Issue 4, pp 558–567 | Cite as

Comparative Efficiency of Functional Gene-based Markers, Start Codon Targeted Polymorphism (SCoT) and Conserved DNA-derived Polymorphism (CDDP) with ISSR Markers for Diagnostic Fingerprinting in Wheat (Triticum aestivum L.)

  • H. Hamidi
  • R. TalebiEmail author
  • F. Keshavarzi
Genetics

Abstract

Three molecular markering techniques: inter-simple sequence repeat (ISSR); start codon targeted (SCoT), conserved DNA-derived polymorphism (CDDP) markers were compared for fingerprinting of 40 varieties of bread wheat. The number of scoreable and polymorphic bands produced using the ISSR, SCoT and CDDP primers for varieties was more than that of genotypes. Average polymorphism information content (PIC) for ISSR, SCoT and CDDP markers was 0.39, 0.41 and 0.34, respectively, and this revealed that three different marker types were equal for the assessment of diversity amongst genotypes. Cluster analysis for three different molecular types revealed that genotypes taken for the analysis can be divided in three and four distinct clusters. There were no significant differences among these markers in terms of the evaluation of genotypes. These results suggest that efficiency of SCoT, CDDP and ISSR markers was relatively the same in fingerprinting of genotypes but SCoT and CDDP analysis are more effective in fingerprinting of wheat genotypes. To our knowledge, this was the first detailed report of a comparison of performance among two targeted DNA region molecular markers (SCoT and CDDP) in comparision with ISSR technique on a set of samples of wheat cultivars. Overall, our results indicate that SCoT, ISSR and CDDP fingerprinting could be used to detect polymorphism for genotypes of wheat.

Keywords

wheat genetic diversity ISSR SCoT CDDP 

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References

  1. Andersen J.R., Lubberstedt T. 2003. Functional markers in plants. Trends Plant. Sci. 8:554–560.CrossRefGoogle Scholar
  2. Botstein D., White K.L., Skolnick M., Davis R.W. 1980. Construction of a genetic linkage map in man using restriction fragment length polymorphisms. Am. J. Hum. Genet. 32:314–33l.PubMedPubMedCentralGoogle Scholar
  3. Collard B.C.Y., Mackill D.J. 2009a. Conserved DNA-derived polymorphism (CDDP): A simple and novel method for generating DNA markers in plants. Plant. Mol. Biol. Rep. 27:558–562.CrossRefGoogle Scholar
  4. Collard B.C.Y., Mackill D.J. 2009b. Start codon targeted (SCoT) polymorphism: a simple, novel DNA marker technique for generating gene-targeted markers in plants. Plant. Mol. Biol. Rep. 27:86–93.CrossRefGoogle Scholar
  5. Donini P., Law J.R., Koebner R.M.D., Reeves J.C., Cooke R.J. 2000. Temporal trends in the diversity of UK wheats. Theor. Appl. Genet. 100:912–917.CrossRefGoogle Scholar
  6. Eivazi A.R., Naghavi M.R., Hajhaydari M., Piseyedi S.M., Ghaffari M.R., Mohammadi S.A., Majidi I., Salekdeh G.H., Mardi M. 2008. Assessing wheat (Triticum aestivum L.) genetic diversity using quality traits, amplified fragment length polymorphisms, simple sequence repeats and proteome analysis. Ann. Appl. Biol. 152:81–91.CrossRefGoogle Scholar
  7. Fufa H., Baenziger P.S., Beecher B.S., Dweikat I., Graybosch R.A., Eskridge K.M. 2005. Comparison of phenotypic and molecular marker-based classifications of hard red winter wheat cultivars. Euphytica 145:133–146.CrossRefGoogle Scholar
  8. Gorji A.M., Poczai P., Polgar Z., Taller J. 2011. Efficiency of arbitrarily amplified dominant markers (SCoT, ISSR and RAPD) for diagnostic fingerprinting in tetraploid potato. Am. J. Pot. Res. 88:226–237.CrossRefGoogle Scholar
  9. Gupta P.K., Varshney R.K., Sharma P.C., Ramesh B. 1999. Molecular markers and their applications in wheat breeding. Plant. Breed. 118:369–390.CrossRefGoogle Scholar
  10. Lassner M.W., Peterson P., Yoder J.I. 1989. Simultaneous amplification of multiple DNA fragments by polymerase chain reaction in the analysis of transgenic plants and their progeny. Plant. Mol. Biol. Rep. 7:116–128.CrossRefGoogle Scholar
  11. Maccaferri M., Sanguineti M.C., Donini P., Tuberosa R. 2003. Microsatellite analysis reveals a progressive widening of the genetic basis in the elite durum wheat germplasm. Theor. Appl. Genet. 107:783–797.CrossRefGoogle Scholar
  12. Martos V., Royo C., Rharrabti Y., Garcia del Moral L.F. 2005. Using AFLPs to determine phylogenetic relationships and genetic erosion in durum wheat cultivars released in Italy and Spain throughout the 20th century. Field Crop. Res. 91:107–116.CrossRefGoogle Scholar
  13. Nei M. 1973. Analysis of gene diversity in subdivided populations. Proc. Natl Acad. Sci. USA. 70:3321–3323.CrossRefGoogle Scholar
  14. Perrier X., Flori A., Bonnot F. 2003. Data analysis methods. In: Hamon P., Seguin M., Perrier X., Glaszmann J.C. (eds), Genetic Diversity of Cultivated Tropical Plants. Science Publishers Enfield, Montpellier, pp. 43–76.Google Scholar
  15. Perrier X., Jacquemoud-Collet J.P. 2006. DARwin software, https://doi.org/darwin.cirad.fr/darwin
  16. Röder M.S., Korzun V., Gil B.S., Ganal M.W. 1998a. The physical mapping of microsatellite markers in wheat. Genome 41:278–283.CrossRefGoogle Scholar
  17. Röder M.S., Korzum V., Wendehake K., Plashke J., Tixier M.H., Leroy P., Ganal M.W. 1998b. Amicrosatellite map of wheat. Genetics 149:2007–2023.PubMedPubMedCentralGoogle Scholar
  18. Rohlf F.J. 1998. NTSYS-pc Numerical Taxonomy and Multivariate Analysis System. Version 2.02. Exeter Publications Setauket, New York, USA.Google Scholar
  19. Roldan-Ruiz I., van Eeuwijk F.A., Gilliland T.J., Dubreuil P., Dillmann C., Lallemand J., De Loose M., Baril C.P. 2001. A comparative study of molecular and morphological methods of describing relationships between perennial ryegrass (Lolium perenne L.) varieties. Theor. Appl. Genet. 103:1138–1150.CrossRefGoogle Scholar
  20. Schuster I., Vieira E.S.N., da Silva G.C., de Assis Franco F., Marchioro V.S. 2009. Genetic variability in Brazilian wheat cultivars assessed by microsatellite markers. Genet. Mol. Biol. 32:557–563.CrossRefGoogle Scholar
  21. Song Q.J., Shi J.R., Singh S., Fickus E.W., Costa J.M., Lewis J., Gill B.S., Ward R., Creagan P.B. 2005. Development and mapping of microsatellite (SSR) markers in wheat. Theor. Appl. Genet. 110:550–560.CrossRefGoogle Scholar
  22. Talebi R., Fayyaz F., Karami M. 2012. Morphometric and amplified fragment length polymorphism marker analysis in some landrace wheat (Triticum aestivum L.) genotypes collected from north-west of Iran. Environ. Exp. Biol. 10:49–56.Google Scholar
  23. Torres A.M., Weeden N.F., Martin A. 1993. Linkage among isozyme, RFLP and RAPD markers in Vicia faba. Theor. Appl. Genet. 85:935–945.CrossRefGoogle Scholar
  24. Ullah I. 2009. Molecular genetic studies for drought tolerance in cotton. PhD thesis, Quaid-i-Azam University Islamabad, Pakistan.Google Scholar
  25. Wang Q., Zhang B., Lu G. 2009. Conserved region amplification polymorphism (CoRAP), a novel marker technique for plant genotyping in Salvia miltiorrhiza. Plant. Mol. Biol. Rep. 27:139–143.CrossRefGoogle Scholar

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© Akadémiai Kiadó, Budapest 2014

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Cellular and Molecular Biology, Kurdistan Science and Research BranchIslamic Azad UniversitySanandajIran
  2. 2.Department of Agronomy & Plant Breeding, College of Agriculture, Sanandaj BranchIslamic Azad UniversitySanandajIran
  3. 3.Department of Biology, Sanandaj BranchIslamic Azad UniversitySanandajIran

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