Theoretical and Applied Genetics

, Volume 109, Issue 4, pp 783–791 | Cite as

Tall fescue EST-SSR markers with transferability across several grass species

  • Malay C. Saha
  • M. A. Rouf Mian
  • Imad Eujayl
  • John C. Zwonitzer
  • Liangjiang Wang
  • Gregory D. May
Original Paper


Tall fescue (Festuca arundinacea Schreb.) is a major cool season forage and turf grass in the temperate regions of the world. It is also a close relative of other important forage and turf grasses, including meadow fescue and the cultivated ryegrass species. Until now, no SSR markers have been developed from the tall fescue genome. We designed 157 EST-SSR primer pairs from tall fescue ESTs and tested them on 11 genotypes representing seven grass species. Nearly 92% of the primer pairs produced characteristic simple sequence repeat (SSR) bands in at least one species. A large proportion of the primer pairs produced clear reproducible bands in other grass species, with most success in the close taxonomic relatives of tall fescue. A high level of marker polymorphism was observed in the outcrossing species tall fescue and ryegrass (66%). The marker polymorphism in the self-pollinated species rice and wheat was low (43% and 38%, respectively). These SSR markers were useful in the evaluation of genetic relationships among the Festuca and Lolium species. Sequencing of selected PCR bands revealed that the nucleotide sequences of the forage grass genotypes were highly conserved. The two cereal species, particularly rice, had significantly different nucleotide sequences compared to the forage grasses. Our results indicate that the tall fescue EST-SSR markers are valuable genetic markers for the Festuca and Lolium genera. These are also potentially useful markers for comparative genomics among several grass species.


Simple Sequence Repeat Marker Grass Species Tall Fescue Simple Sequence Repeat Locus Turf Grass 
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.



We thank Dr. Mark E. Sorrells for critically reviewing this manuscript. We also thank Konstantin Chekhovskiy, Jennifer Black, Ann Harris, and Jarrod Steele for their technical support. This research work was funded by The Samuel Roberts Noble Foundation.

Supplementary material

122_2004_1681_esm.xls (57 kb)
(Excel 50 KB)


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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • Malay C. Saha
    • 1
  • M. A. Rouf Mian
    • 1
  • Imad Eujayl
    • 1
    • 2
  • John C. Zwonitzer
    • 1
  • Liangjiang Wang
    • 1
  • Gregory D. May
    • 1
  1. 1.The Samuel Roberts Noble FoundationArdmoreUSA
  2. 2.Department of Food Science and Human NutritionWashington State UniversityPullmanUSA

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