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Sample Set Information

ID TSE1303
Title Exploring molecular backgrounds of quality traits in rice by predictive models based on high-coverage metabolomics
Description BACKGROUND:

Increasing awareness of limitations to natural resources has set high expectations for plant science to deliver efficient crops with increased yields, improved stress tolerance, and tailored composition. Collections of representative varieties are a valuable resource for compiling broad breeding germplasms that can satisfy these diverse needs.

Here we show that the untargeted high-coverage metabolomic characterization of such core collections is a powerful approach for studying the molecular backgrounds of quality traits and for constructing predictive metabolome-trait models. We profiled the metabolic composition of kernels from field-grown plants of the rice diversity research set using 4 complementary analytical platforms. We found that the metabolite profiles were correlated with both the overall population structure and fine-grained genetic diversity. Multivariate regression analysis showed that 10 of the 17 studied quality traits could be predicted from the metabolic composition independently of the population structure. Furthermore, the model of amylose ratio could be validated using external varieties grown in an independent experiment.

Our results demonstrate the utility of metabolomics for linking traits with quantitative molecular data. This opens up new opportunities for trait prediction and construction of tailored germplasms to support modern plant breeding.

Authors Redestig H, Kusano M, Ebana K, Kobayashi M, Oikawa A, Okazaki Y, Matsuda F, Arita M, Fujita N, Saito K
Reference BMC Syst Biol. 2011 Oct 28;5:176.

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Sample Information

Title Oryza sativa L.
Organism - Scientific Name Oryza sativa L.
Organism - ID NCBI taxonomy:4530
Compound - ID
Compound - Source
Preparation Genotype

The rice diversity research set (RDRS) consists of 68 accessions and Nipponbare and Kasalath as reference cultivars. We furthermore chose to include the salinity resistant cultivar Pokkari. Four additional varieties outside the RDRS (Yumetoiro, Hoshiyutaka, Kinmaze and Soft158) and two amylose hyper accumulating Starch synthase IIIa (SSIIIa) knock-out lines (Tos17 retrotransposon insert): e1, a single knock-out (Nipponbare background) [9] and 4019, double knockout, with Nipponbare/Kinmaze backgroundwere used for the validation experiment.


Organ specification
Brown rice

Sample Preparation Details ID SS1

Sample Preparation Details Information

Title Sample Preparation
Description Growth condition

Twenty-five rice seeds for each of RDRS were sown at a rice field in NIAS, Tsukuba (Lat., 36.030753; Long. 140.099858), Japan in Spring. For the external set of samples, seeds were grown at a rice field in Akita (Lat. 39.803897; Long. 140.046451), Japan.

Sampling and sampling date
For RDRS, seeds were harvested independently for each variety after 40 days, starting from the day on which the first panicle of rice was observed in 2005 and 2006. For others, seeds were also harvested independently for each variety in 2005 (for Yumetoiro, Hoshiyutaka, Kinmaze, Soft158, el and Nipponbare) and 2008 (for 4019 and Nipponbare).


Analytical Method Information

Method Details ID MS2
Sample Amount 5 µl

Analytical Method Details Information

Title Extraction for LC-MS
Instrument HPLC, Waters Acquity UPLC system; MS, Waters Q-Tof Premier
Instrument Type UPLC-QTOF-MS
Ionization ESI
Ion Mode positive and negative
Description BioSource amount

For RDRS and Hoshiyutaka, 100 seeds of each variety were selected according to the average weight and length of seeds. After separating the husks from the seeds, the brown rice seeds obtained were bulked and crushed by using a Retsch mixer mill MM301 at a frequency of 20 Hz for 2 min at 4 °C. Successively, the obtained powder was divided into three to four pools. For external set of samples harvested in Akita, 100 seeds of each biological replicate were selected and crushed in the same way as RDRS.

Extraction for LC-MS
100 mg of each sample was extracted with extraction buffer [methanol/water (5:95, v/v)] at a concentration of of 100 mg/ml using a Retsch mixer mill MM310 at a frequency of 20 Hz for 10 min at 4°C. After centrifugation for 10 min at 15,000 x g, 500 µl of the supernatant was transferred into a tube and diluted in 0.1% acetic acid solution. and then it was filtered using an Oasis® HLB µ-elusion plate (30 µm, Waters Co., Massachusetts, USA). The extracts ca. 0.1 mg of each sample) were evaporated to dryness in an SPD2010 SpeedVac® concentrator.The extracts were dissolved by 200 µl of water containing five reference compounds as follows:
0.5 mg/l of lidocaine,
1.0 mg/l of ampiciline,
1.0 mg/l of torperizone,
0.5 mg/l of 10-camphor sulfonic acid and
1.0 mg/l of 2-naphthalene-4-sodium sulfate.

LC-q-TOF-MS conditions
After filtration of the extracts (Ultrafree-MC, 0.2 µm pore size;Millipore), 5 µl of extracts (ca. 0.1 mg each sample) was analyzed using an LC-MS system equipped with an electrospray ionization (ESI) interface (HPLC, Waters Acquity UPLC system; MS, Waters Q-Tof Premier). The analytical conditions were as follows. HPLC: column, Acquity bridged ethyl hybrid (BEH) C18 (pore size 1.7 µ m, length 2.0 x 100 mm, Waters); solvent system, acetonitrile (0.1% formic acid):water (0.1% formic acid); gradient program, 1:99 v/v at 0 min, 1:99 v/v at 0.1 min, 64.0 : 0.5 at 10.0 min, 99.5 : 0.5 at 11.5 min, 1:99 v/v at 11.6 min and 1:99 at 14.0 min; flow rate, 0.3 ml min−1; temperature, 38°C; MS detection: capillary voltage, +3.0 keV; cone voltage, 23 V for positive mode and 35 V for negative mode; source temperature, 120°C; desolvation temperature, 450°C; cone gas flow, 50 l h−1; desolvation gas flow, 800 l/ h; collision energy, 2 V for positive mode and 5 V for negative mode ; detection mode, scan (m/z 100–2000; dwell time 0.45 sec; interscan delay 0.05 sec, centroid). The scans were repeated for 14.0 min in a single run. The data were recorded using MassLynx version 4.1 software (Waters).


Data Analysis Information

Title Data processing (LC-MS)
Data Analysis Details ID DS2
Recommended decimal places of m/z

Data Analysis Details Information

Title Data processing (LC-MS)
Description The profiling data files recorded in the MassLynx format (raw) were converted to the NetCDF format using the DataBridge function of MassLynx 4.1. From the set of NetCDF data files, the data matrix was generated using the MetAlign software (De Vos et al., 2007). By using this procedure, the data matrixes with unit mass data were generated. The data matrices were processed using in-house software written in Perl/Tk. The original peak intensity values were divided with that of the internal standards (lidocaine at m/z 235 [M + H]+ and (–)-camphor-10-sulfonic acid at m/z 231 [M–H]– for the positive and negative ion modes, respectively) determined in the same samples to normalize the peak intensity values among the metabolic profile data.
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