DOI QR코드

DOI QR Code

SSR-Primer Generator: A Tool for Finding Simple Sequence Repeats and Designing SSR-Primers

  • Hong, Chang-Pyo (Department of Horticulture, College of Agriculture and Life Science, Chungnam National University) ;
  • Choi, Su-Ryun (Department of Horticulture, College of Agriculture and Life Science, Chungnam National University) ;
  • Lim, Yong-Pyo (Department of Horticulture, College of Agriculture and Life Science, Chungnam National University)
  • Received : 2011.10.11
  • Accepted : 2011.11.15
  • Published : 2011.12.31

Abstract

Simple sequence repeats (SSRs) are ubiquitous short tandem duplications found within eukaryotic genomes. Their length variability and abundance throughout the genome has led them to be widely used as molecular markers for crop-breeding programs, facilitating the use of marker-assisted selection as well as estimation of genetic population structure. Here, we report a software application, "SSR-Primer Generator " for SSR discovery, SSR-primer design, and homology-based search of in silico amplicons from a DNA sequence dataset. On submission of multiple FASTA-format DNA sequences, those analyses are batch processed in a Java runtime environment (JRE) platform, in a pipeline, and the resulting data are visualized in HTML tabular format. This application will be a useful tool for reducing the time and costs associated with the development and application of SSR markers.

Keywords

References

  1. Hong, C.P., Piao, Z.Y., Kang, T.W., Batley, J., Yang, T.J., Hur, Y.K., Bhak, J., Park, B.S., Edwards, D., and Lim, Y.P. (2007). Genomic distribution of simple sequence repeats in Brassica rapa. Mol. Cells. 23, 349-356.
  2. Jewell, E., Robinson, A., Savage, D., Erwin, T., Love, C.G., Lim, G.A., Li, X., Batley, J., Spangenberg, G.C., and Edwards, D. (2006). SSRPrimer and SSR Taxonomy Tree: Biome SSR discovery. Nucleic Acids Res. 34, W656-W659. https://doi.org/10.1093/nar/gkl083
  3. Kruglyak, S., Durrett, R.T., Schug, M.D., and Aquadro, C.F. (1998). Equilibrium distributions of microsatellite repeat length resulting from a balance between slippage events and point mutations. Proc. Natl. Acad. Sci. U.S.A. 95, 10774-10778. https://doi.org/10.1073/pnas.95.18.10774
  4. Li, Y.C., Korol, A.B., Fahima, T., and Nevo, E. (2004). Microsatellites within genes: structure, function, and evolution. Mol. Biol. Evol. 21, 991-1007. https://doi.org/10.1093/molbev/msh073
  5. Pertea, G., Huang, X., Liang, F., Antonescu, V., Sultana, R., Karamycheva, S., Lee, Y., White, J., Cheung, F., Parvizi, B., Tsai, J., and Quackenbush, J. (2003). TIGR Gene Indices clustering tools (TGICL): a software system for fast clustering of large EST datasets. Bioinformatics 19, 651-652. https://doi.org/10.1093/bioinformatics/btg034
  6. Schlotterer, C. (2000). Evolutionary dynamics of microsatellite DNA. Chromosoma 109, 365-371. https://doi.org/10.1007/s004120000089