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Crop Science Abstract - GENOMICS, MOLECULAR GENETICS & BIOTECHNOLOGY

Identification of Quantitative Trait Loci in Rice for Yield, Yield Components, and Agronomic Traits across Years and Locations

 

This article in CS

  1. Vol. 47 No. 6, p. 2403-2417
     
    Received: Aug 2, 2006


    * Corresponding author(s): SRM4@cornell.edu
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doi:10.2135/cropsci2006.08.0509
  1. Yong-Gu Choab,
  2. Hyeon-Jung Kangc,
  3. Jeom-Sig Leed,
  4. Young-Tae Leec,
  5. Sang-Jong Limd,
  6. Hugh Gauchabcde,
  7. Moo-Young Euna and
  8. Susan R. McCouch *e
  1. a National Institute of Agricultural Biotechnology, Suwon 441-707, Korea
    b current address: Dep. of Crop Science, Chungbuk National Univ., Chongju 361-763, Korea
    c Honam Agricultural Research Institute, Iksan 570-080, Korea
    d Youngnam Agricultural Research Institute, Milyang 627-130, Korea;. H. Gauch, Crop and Soil Sciences, Cornell Univ., Ithaca, NY 14853-1901
    e Dep. of Plant Breeding, Cornell Univ., Ithaca, NY 14853-1901. This research was supported by grants from the Rural Development Administration and the Rockefeller Foundation's Biotechnology Career Fellowship (RF95001, No. 342) for Y.G. Cho's work at Cornell

Abstract

A population of 164 recombinant inbred lines (RILs) of rice (Oryza sativa L.) derived from a cross between Milyang23 and Gihobyeo was evaluated for nine phenotypic characters over three years and two regions in Korea. The population had been previously mapped using 414 molecular markers. Genotype × environment (G × E) interaction was analyzed for six grain yield-related traits and three agronomic traits across years and locations using the AMMI model. The quantitative trait loci (QTLs) were detected by interval mapping and composite interval mapping. A total of 75 QTLs were identified for the nine traits across five environments and they were categorized as (i) 29 QTLs with main effect, (ii) 18 QTLs with minor effect, (iii) 13 QTLs with G × E interaction effect, (iv) six QTLs with both main effect and G × E interaction effect, and (v) nine potential QTLs with low log of the odds (LOD) scores. The AMMI model explained from 68.6% to 84.7% of the interaction effect and 19 QTLs were significantly associated with G × E interaction. Culm length had the least G × E, while the maximum G × E interaction was exhibited for spikelets per panicle (39.7%) and percent ripened grain (35.3%). Markers closely linked to main effect QTLs will be most useful for marker-assisted breeding.

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