Theoretical and Applied Genetics

, Volume 110, Issue 7, pp 1334–1346 | Cite as

Stability of QTLs for rice grain dimension and endosperm chalkiness characteristics across eight environments

  • X. Y. Wan
  • J. M. WanEmail author
  • J. F. Weng
  • L. Jiang
  • J. C. Bi
  • C. M. Wang
  • H. Q. Zhai
Original Paper


Rice appearance quality, including traits specifying grain dimension and endosperm chalkiness, represents a major problem in many rice-producing areas of the world. In this study, the genetic basis of six appearance quality traits of milled rice was dissected into quantitative trait loci (QTL) main effects, and the stability of these QTLs was assessed in a population of 66 chromosome segment substitution lines (CSSLs) across eight environments. The CSSLs showed transgressive segregation for many of the traits, and significant correlations were detected among most of the traits. Twenty-two QTLs were identified on eight chromosomes, and numerous QTLs affecting related traits were mapped in the same regions, probably reflecting pleiotropic effects. Nine QTLs, namely qGL-1,qGL-3, qGW-5,qLWR-3, qLWR-5,qPGWC-8, qPGWC-9, qACE-8, and qDEC-8, were consistently detected across the eight environments. The additive main effect and multiplicative interaction (AMMI) analysis showed that genotype (G) × environment (E) interaction was significant for all six traits, with the first three iPCA terms accounting for over 80% of the G × E variance. Both D I values and the iPCA1-iPCA2 biplots showed that the CSSLs harboring the nine QTL alleles were more stable than those carrying any of the additional 13 QTL alleles, thereby confirming their environmental stability and pointing to their appropriateness as targets for marker-assisted selection for high-quality rice varieties.


Quantitative Trait Locus Quantitative Trait Locus Allele Phenotypic Variation Explain Quantitative Trait Locus Cluster Grain Length 
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 are extremely grateful to Prof. A. Yoshimura, Kyushu University, Japan, for kindly providing the CSSL population and genotype data. We thank for linguistic correction. This research is supported by the grants from the National High Technology Research and Development Program of China (No. 2003AA222131; 2003AA207020), the National Natural Science Foundation of China (No.30270811).


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Copyright information

© Springer-Verlag 2005

Authors and Affiliations

  • X. Y. Wan
    • 1
  • J. M. Wan
    • 1
    • 2
    Email author
  • J. F. Weng
    • 1
  • L. Jiang
    • 1
  • J. C. Bi
    • 1
  • C. M. Wang
    • 1
  • H. Q. Zhai
    • 2
  1. 1.National Key Laboratory for Crop Genetics and Germplasm Enhancement, Jiangsu Plant Gene Engineering Research CenterNanjing Agricultural UniversityNanjingChina
  2. 2.Institute of Crop ScienceChinese Academy of Agriculture SciencesBeijingChina

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