Theoretical and Applied Genetics

, Volume 114, Issue 3, pp 559–568 | Cite as

Genetic diversity analysis of traditional and improved Indonesian rice (Oryza sativa L.) germplasm using microsatellite markers

  • Michael J. Thomson
  • Endang M. Septiningsih
  • Fatimah Suwardjo
  • Tri J. Santoso
  • Tiur S. Silitonga
  • Susan R. McCouchEmail author
Original Paper


The archipelago of Indonesia has a long history of rice production across a broad range of rice-growing environments resulting in a diverse array of local Indonesian rice varieties. Although some have been incorporated into modern breeding programs, the vast majority of these landraces remain untapped. To better understand this rich source of genetic diversity we have characterized 330 rice accessions, including 246 Indonesian landraces and 63 Indonesian improved cultivars, using 30 fluorescently-labeled microsatellite markers. The landraces were selected across 21 provinces and include representatives of the classical subpopulations of cere, bulu, and gundil rices. A total of 394 alleles were detected at the 30 simple sequence repeat loci, with an average number of 13 alleles per locus across all accessions, and an average polymorphism information content value of 0.66. Genetic diversity analysis characterized the Indonesian landraces as 68% indica and 32% tropical japonica, with an indica gene diversity of 0.53 and a tropical japonica gene diversity of 0.56, and a F st of 0.38 between the two groups. All of the improved varieties sampled were indica, and had an average gene diversity of 0.46. A set of high quality Indonesian varieties, including Rojolele, formed a separate cluster within the tropical japonicas. This germplasm presents a valuable source of diversity for future breeding and association mapping efforts.


Simple Sequence Repeat Marker Rice Accession Tropical Japonica Temperate Japonica Japonica Group 
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.



This material is based upon work supported by the US National Science Foundation under grant no. 0301919 as an International Research Fellowship Program award to M.J.T. We also acknowledge the Indonesian Agency for Agricultural Research and Development for an RPTP 2004 grant to E.M.S. We would also like to thank Dr. Sugiono Moeljopawiro, Dr. M. Herman, and Dr. Sutrisno for hosting M.J.T. in Indonesia, Dr. Ida Hanarida Soemantri for providing access to the Indonesian rice germplasm collection, Matsuma for technical support and Lois Swales for help in formatting this manuscript.

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Michael J. Thomson
    • 1
    • 3
  • Endang M. Septiningsih
    • 1
    • 3
  • Fatimah Suwardjo
    • 1
  • Tri J. Santoso
    • 1
  • Tiur S. Silitonga
    • 1
  • Susan R. McCouch
    • 2
    Email author
  1. 1.Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and DevelopmentBogorIndonesia
  2. 2.Department of Plant Breeding and GeneticsCornell UniversityIthacaUSA
  3. 3.International Rice Research InstituteLagunaPhilippines

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