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Functional mapping of quantitative trait loci associated with rice tillering

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Abstract

Several biologically significant parameters that are related to rice tillering are closely associated with rice grain yield. Although identification of the genes that control rice tillering and therefore influence crop yield would be valuable for rice production management and genetic improvement, these genes remain largely unidentified. In this study, we carried out functional mapping of quantitative trait loci (QTLs) for rice tillering in 129 doubled haploid lines, which were derived from a cross between IR64 and Azucena. We measured the average number of tillers in each plot at seven developmental stages and fit the growth trajectory of rice tillering with the Wang–Lan–Ding mathematical model. Four biologically meaningful parameters in this model––the potential maximum for tiller number (K), the optimum tiller time (t 0), and the increased rate (r), or the reduced rate (c) at the time of deviation from t 0––were our defined variables for multi-marker joint analysis under the framework of penalized maximum likelihood, as well as composite interval mapping. We detected a total of 27 QTLs that accounted for 2.49–8.54% of the total phenotypic variance. Nine common QTLs across multi-marker joint analysis and composite interval mapping showed high stability, while one QTL was environment-specific and three were epistatic. We also identified several genomic segments that are associated with multiple traits. Our results describe the genetic basis of rice tiller development, enable further marker-assisted selection in rice cultivar development, and provide useful information for rice production management.

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Acknowledgments

We are grateful to the Chief Editor, Dr. Stefan Hohmann; the Communicating Editor, Dr. Stig W. Omholt; the two anonymous reviewers; and Dr. Sara J. Miller of Cornell University for their constructive comments and suggestions, which significantly improved this manuscript. This work was supported by the National Basic Research Program of China (2006CB101708), the National Natural Science Foundation of China (30971848), the Jiangsu Natural Science Foundation (BK2008335), the 111 Project (B08025) and the State Key Laboratory of Crop Genetics and Germplasm Enhancement (ZW2007001).

Conflict of interest

The authors declare that they have no conflicts of interest.

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Authors and Affiliations

  1. Guangdong Key Lab of Plant Molecular Breeding, South China Agricultural University, Guangzhou, 510642, People’s Republic of China

    G. F. Liu

  2. Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, China

    M. Li, J. Wen, Y. Du & Y.-M. Zhang

Authors
  1. G. F. Liu
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  2. M. Li
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  3. J. Wen
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  4. Y. Du
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  5. Y.-M. Zhang
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Corresponding author

Correspondence to Y.-M. Zhang.

Additional information

Communicated by S. Omholt.

G. F. Liu and M. Li contributed equally to this work.

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Liu, G.F., Li, M., Wen, J. et al. Functional mapping of quantitative trait loci associated with rice tillering. Mol Genet Genomics 284, 263–271 (2010). https://doi.org/10.1007/s00438-010-0566-z

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  • DOI: https://doi.org/10.1007/s00438-010-0566-z

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