Dissection of genotype–phenotype associations in rice grains using metabolome quantitative trait loci analysis
Article first published online: 10 FEB 2012
© 2012 The Authors. The Plant Journal © 2012 Blackwell Publishing Ltd
The Plant Journal
Volume 70, Issue 4, pages 624–636, May 2012
How to Cite
Matsuda, F., Okazaki, Y., Oikawa, A., Kusano, M., Nakabayashi, R., Kikuchi, J., Yonemaru, J.-I., Ebana, K., Yano, M. and Saito, K. (2012), Dissection of genotype–phenotype associations in rice grains using metabolome quantitative trait loci analysis. The Plant Journal, 70: 624–636. doi: 10.1111/j.1365-313X.2012.04903.x
- Issue published online: 7 MAY 2012
- Article first published online: 10 FEB 2012
- Accepted manuscript online: 9 JAN 2012 04:50PM EST
- Received 15 February 2011; revised 4 January 2012; accepted 6 January 2012; published online 10 February 2012.
- rice grain metabolites;
- QTL analysis;
- metabolome analysis;
- Oryza sativa;
A comprehensive and large-scale metabolome quantitative trait loci (mQTL) analysis was performed to investigate the genetic backgrounds associated with metabolic phenotypes in rice grains. The metabolome dataset consisted of 759 metabolite signals obtained from the grains of 85 lines of rice (Oryza sativa, Sasanishiki × Habataki back-crossed inbred lines). Metabolome analysis was performed using four mass spectrometry pipelines to enhance detection of different classes of metabolites. This mQTL analysis of a wide range of metabolites highlighted an uneven distribution of 802 mQTLs on the rice genome, as well as different modes of metabolic trait (m-trait) control among various types of metabolites. The levels of most metabolites within rice grains were highly sensitive to environmental factors, but only weakly associated with mQTLs. Coordinated control was observed for several groups of metabolites, such as amino acids linked to the mQTL hotspot on chromosome 3. For flavonoids, m-trait variation among the experimental lines was tightly governed by genetic factors that alter the glycosylation of flavones. Many loci affecting levels of metabolites were detected by QTL analysis, and plausible gene candidates were evaluated by in silico analysis. Several mQTLs profoundly influenced metabolite levels, providing insight into the control of rice metabolism. The genomic region and genes potentially responsible for the biosynthesis of apigenin-6,8-di-C-α-l-arabinoside are presented as an example of a critical mQTL identified by the analysis.