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Sample Set Information

Title Metabolome-genome-wide association study dissects genetic architecture for generating natural variation in rice secondary metabolism
Description genome-wide association studies (GWAS) were conducted to investigate the genetic architecture behind the natural variation of rice secondary metabolites. GWAS using the metabolome data of 175 rice accessions successfully identified 323 associations among 143 single nucleotide polymorphisms (SNPs) and 89 metabolites. The data analysis highlighted that levels of many metabolites are tightly associated with a small number of strong quantitative trait loci (QTLs). The tight association may be a mechanism generating strains with distinct metabolic composition through the crossing of two different strains. The results indicate that one plant species produces more diverse phytochemicals than previously expected, and plants still contain many useful compounds for human applications.
Authors Fumio Matsuda, Ryo Nakabayashi, Zhigang Yang, Yozo Okazaki, Jun-ichi Yonemaru, Kaworu Ebana, Masahiro Yano, Kazuki Saito
Reference Matsuda F et al. (2014) The Plant Journal Jan;81(1):13-23

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The raw data files are available at DROP Met web site in PRIMe database of RIKEN.

Analytical Method Details Information

Title Metabolic profiling analysis using LC-ESI-Q-Tof/MS
Instrument Waters Acquity UPLC system and Waters Q-Tof Premier
Instrument Type UPLC-QTOF-MS
Ionization ESI
Ion Mode Positive
Description Analysis was performed using samples with three or four biological replicates per cultivar. Frozen rice tissue was homogenized in five volumes of cold 80% aqueous methanol containing an internal standard (0.5 mgL-1 lidocaine, Tokyo Kasei, Tokyo, Japan,, using a mixer mill (MM 300, Retsch, Haan, Germany, and a zirconia bead for 6 min at 20 Hz. Samples were centrifuged at 15 000 g for 10 min.

The supernatant (3 μl) were subsequently subjected to metabolome analysis using liquid chromatography coupled with electrospray quadrupole time-of-flight tandem mass spectrometry with an Acquity BEH ODS column (LC-ESI-QToF/MS, HPLC: Waters Acquity UPLC system; MS: Waters QToF Premier, Metabolome analysis and data processing were conducted according to a previously described method (Matsuda et al., 2009, 2010). Briefly, metabolome data were obtained in positive ion mode (m/z 100–2000; dwell time: 0.5 sec), from which a data matrix was generated by MetAlign2 (Lommen and Kools, 2012). Signal intensities were normalized by dividing them by the intensities of the internal standard (lidocaine). A data matrix containing the 342 metabolite intensities from 668 runs was produced for the Japanese rice population (Tables S2 and S3).


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