Theoretical and Applied Genetics

, Volume 125, Issue 4, pp 647–657 | Cite as

OsGA20ox1, a candidate gene for a major QTL controlling seedling vigor in rice

  • Akira AbeEmail author
  • Hiroki Takagi
  • Takahiro Fujibe
  • Koichiro Aya
  • Mikiko Kojima
  • Hitoshi Sakakibara
  • Aiko Uemura
  • Makoto Matsuoka
  • Ryohei Terauchi
Original Paper


Seedling vigor is among the major determinants of stable stand establishment in direct-seeded rice (Oryza sativa L.) in temperate regions. Quantitative trait loci (QTL) for seedling vigor were identified using 250 recombinant inbred lines (RILs) derived from a cross between two japonica rice cultivars Kakehashi and Dunghan Shali. Seedling heights measured at 14 days after sowing were 20.3 and 29.4 cm for Kakehashi and Dunghan Shali, respectively. For the RILs, the height ranged from 14.1 to 31.7 cm. Four putative QTLs associated with seedling height were detected. qPHS3-2, the major QTL that was located on the long arm of chromosome 3, accounted for 26.2 % of the phenotypic variance. Using progeny of the near isogenic lines (NILs) produced by the backcross introduction of a chromosome segment carrying this major QTL into an elite cultivar Iwatekko, we fine-mapped qPHS3-2 to a 81-kb interval between two markers, ID_CAPS_01 and RM16227. Within this mapped region, we identified the gene OsGA20ox1, which is related to gibberellin (GA) biosynthesis. The relative expression levels of GA20ox1 in seedlings of Dunghan Shali and NILs were higher than that of Iwatekko. Concomitantly, the amount of endogenous active GA was higher in Dunghan Shali and the NILs compared to the level detected in Iwatekko. These results indicate that OsGA20ox1 is a strong candidate gene for major QTL controlling seedling vigor in rice.


Quantitative Trait Locus Simple Sequence Repeat Marker Quantitative Trait Locus Analysis Segregation Distortion Major Quantitative Trait Locus 
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 Yutaka Kiuchi, Tsutomu Sasaki and Hitoshi Hatakeyama for general support of the work. We are also grateful to the following staffs for technical support: N. Kikuchi, E. Kanzaki, J. Tokuta, A. Yamaguchi, Y. Ogasawara, K. Itoh and Y. Ochiai. Our gratitude extends to Muluneh Tamiru for improvement of the manuscript. We thank the NIAS Genebank, Japan for providing the seeds of Dunghan Shali. This work was supported by the Program for Promotion of Basic and Applied Researches for Innovations in Bio-oriented Industry (PRO-BRAIN) and by Japan Advanced Plant Science Network.

Supplementary material

122_2012_1857_MOESM1_ESM.doc (84 kb)
Supplementary material 1 (DOC 83 kb)


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Akira Abe
    • 1
    • 2
    Email author
  • Hiroki Takagi
    • 2
    • 3
  • Takahiro Fujibe
    • 3
  • Koichiro Aya
    • 4
  • Mikiko Kojima
    • 5
  • Hitoshi Sakakibara
    • 5
  • Aiko Uemura
    • 3
  • Makoto Matsuoka
    • 4
  • Ryohei Terauchi
    • 3
  1. 1.Iwate Agricultural Research CenterKitakamiJapan
  2. 2.United Graduate School of Agricultural Sciences, Iwate UniversityMoriokaJapan
  3. 3.Iwate Biotechnology Research CenterKitakamiJapan
  4. 4.Bioscience and Biotechnology Center, Nagoya UniversityNagoyaJapan
  5. 5.RIKEN Plant Science CenterYokohamaJapan

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