SE161:/S1/M1/D1

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Sample Set Information

ID TSE1320
Title Dissection of genotype-phenotype associations in rice grains using metabolome quantitative trait loci analysis.
Description 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 x 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.
Authors Matsuda F, Okazaki Y, Oikawa A, Kusano M, Nakabayashi R, Kikuchi J, Yonemaru J, Ebana K, Yano M, Saito K.
Reference Plant J. 2012 May;70(4):624-36. doi: 10.1111/j.1365-313X.2012.04903.x. Epub 2012 Feb 10.
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Sample Information

ID S1
Title Rice
Organism - Scientific Name Oryza sativa
Organism - ID NCBI taxonomy:4530
Compound - ID
Compound - Source
Preparation The plant population consisted of 85 back‐crossed inbred lines derived from the cross Sasanishiki/Habataki//Sasanishiki///Sasanishiki (Sasanishiki x Habataki) (Nagata et al., 2002b). Seeds from the experimental lines were grown in a paddy field at the National Institute of Agrobiological Sciences (Tsukuba, Japan) in 2005 and 2007, employing similar cultivation schedules. The seeds of the 2005 and 2007 harvests were used for metabolome analysis. One hundred dehulled seeds obtained from whole seeds harvested from 10 independent plants were ground to a fine powder using an MM300 mixer mill (Retsch, http://www.retsch.com/) at 20Hz for 2min in a stainless steel grinding vessel. The powder was divided between small sample tubes (50–100mg) under nitrogen, and the samples were stored at −80°C until analysis.
Sample Preparation Details ID
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Analytical Method Information

ID M1
Title LC‐ESI‐Q‐TOF‐MS
Method Details ID MS1
Sample Amount 3 μL
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Analytical Method Details Information

ID MS1
Title LC‐ESI‐Q‐TOF‐MS
Instrument LC, Waters Acquity UPLC system; Q-TOF-MS, Waters Q-Tof Premier
Instrument Type UPLC-QTOF-MS
Ionization ESI
Ion Mode Positive
Description Sample metabolomic data were acquired using four time-of-flight mass spectrometers (TOF-MS), including CE-TOF-MS for analysis of polar metabolites, GC-TOF-MS for analysis of primary metabolites, LC-Q-TOF-MS for analysis of secondary metabolites and LC-IT-TOF-MS for analysis of lipids. Analysis was performed in triplicate, and the samples were extracted from each pipeline using optimized methods.


For the LC-Q-TOF-MS pipeline, 100 mg of rice seed powder was homogenized in 10 volumes of 5% aqueous methanol containing 0.1% acetic acid (Tokyo Kasei, http://www.tciamerica.com/) using an MM300 mixer mill (Retsch, http://www.retsch.com/) with a zirconia bead for 10 min at 20 Hz. Next, the samples were centrifuged at 15000 g for 10 min. The supernatant (500 ll) was diluted to 5.0 ml using water containing 0.1% acetic acid, and was applied to a 3 cc OASIS HLB cartridge (Waters, http://www.waters.com/) that had been equilibrated with 0.5% aqueous methanol containing 0.1% acetic acid. After pre-equilibrium with 5 ml of 0.5% aqueous methanol containing 0.1% acetic acid, metabolites were eluted with 3 ml of 90% aqueous methanol containing 0.1% acetic acid. The eluate was dried under vacuum and then suspended in 100 ll water containing the internal standard (0.5 mg/ml lidocaine). Insoluble residue was removed by filtration using an Ultrafree-MC filter with 0.2 lm pore size (Millipore, http://www.millipore.com/). The samples (3µl) were subsequently subjected to metabolome analysis by liquid chromatography coupled with electrospray quadrupole time-of-flight tandem mass spectrometry (LC-ESI-Q-TOF-MS) using an Acquity BEH ODS column (LC, Waters Acquity UPLC system; Q-TOF-MS, Waters Q-Tof Premier).

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Data Analysis Information

ID D1
Title Data Processing and Analysis (LC-ESI-Q-TOF-MS)
Data Analysis Details ID DS1
Recommended decimal places of m/z
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Data Analysis Details Information

ID DS1
Title Data processing and analisys (LC-ESI-Q-TOF-MS)
Description Metabolome analysis and data processing were performed as described previously (Matsuda et al., 2009, 2010). Briefly, the metabolome data were obtained in the positive ion mode (m/z 100–2000; dwell time 0.45 sec; inter-scan delay 0.05 sec), from which a data matrix was generated using MetAlign (De Vos et al., 2007; Lommen, 2009). The metabolite signals commonly detected from both the 2005 and 2007 harvest datasets were used for subsequent analysis, and a data matrix containing mean values for 362 metabolite intensities from 510 runs (85 experimental lines x two yearly harvests x three analytical replicates) was produced.
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