Theoretical and Applied Genetics

, Volume 113, Issue 1, pp 33–38 | Cite as

Conditional QTL mapping of oil content in rapeseed with respect to protein content and traits related to plant development and grain yield

  • Jianyi Zhao
  • Heiko C. Becker
  • Dongqing Zhang
  • Yaofeng Zhang
  • Wolfgang Ecke
Original Paper

Abstract

Oil content in rapeseed (Brassica napus L.) is generally regarded as a character with high heritability that is negatively correlated with protein content and influenced by plant developmental and yield related traits. To evaluate possible genetic interrelationships between these traits and oil content, QTL for oil content were mapped using data on oil content and on oil content conditioned on the putatively interrelated traits. Phenotypic data were evaluated in a segregating doubled haploid population of 282 lines derived from the F1 of a cross between the old German cultivar Sollux and the Chinese cultivar Gaoyou. The material was tested at four locations, two each in Germany and in China. QTLMapper version 1.0 was used for mapping unconditional and conditional QTL with additive (a) and locus pairs with additive × additive epistatic (aa) effects. Clear evidence was found for a strong genetic relationship between oil and protein content. Six QTL and nine epistatic locus pairs were found, which had pleiotropic effects on both traits. Nevertheless, two QTL were also identified, which control oil content independent from protein content and which could be used in practical breeding programs to increase oil content without affecting seed protein content. In addition, six additional QTL with small effects were only identified in the conditional mapping. Some evidence was apparent for a genetic interrelationship between oil content and the number of seeds per silique but no evidence was found for a genetic relationship between oil content and flowering time, grain filling period or single seed weight. The results indicate that for closely correlated traits conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the level of individual QTL. Furthermore, conditional QTL mapping can reveal additional QTL with small effects that are undetectable in unconditional mapping.

Notes

Acknowledgements

We are grateful to Prof. Dr. Jun Zhu, Institute of Biomathematics, Zhejiang University, China for his valuable suggestions on conditional QTL mapping and for providing the software and facilities during data analysis. We thank Joerg Schondelmaier at Saaten-Union Resistenzlabor GmbH, Hovedissen, Germany, for his contribution to the marker analysis. This research was financially supported by the European Commission within the cooperative project IC18-CT 97-0172, the Natural Science Foundation of Zhejiang Province, China (No. Z303407) and the National Natural Science Foundation of China (No. 30470985).

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Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  • Jianyi Zhao
    • 1
  • Heiko C. Becker
    • 2
  • Dongqing Zhang
    • 1
  • Yaofeng Zhang
    • 1
  • Wolfgang Ecke
    • 2
  1. 1.Crop Research InstituteZhejiang Academy of Agricultural SciencesHangzhouPeople's Republic of China
  2. 2.Institute of Agronomy and Plant BreedingUniversity of GöttingenGöttingenGermany

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