SE146:/S1/M4/D2

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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.

RESULTS:
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.

CONCLUSIONS:
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.
Comment


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Sample Information

ID S1
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
Kernel

Organ specification
Brown rice

Sample Preparation Details ID SS1
Comment

Sample Preparation Details Information

ID SS1
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).

Comment_of_details

Analytical Method Information

ID M4
Title LC-IT-TOF-MS
Method Details ID MS4
Sample Amount 0.5 µl, ca. 33.3 µg of each sample
Comment

Analytical Method Details Information

ID MS4
Title Extraction for IT-MS
Instrument LC, Shimadzu LC-20AD system; MS, Shimadzu LCMS-IT-TOF
Instrument Type
Ionization ESI
Ion Mode positive
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 IT-MS
Each Sample (50 mg) was extracted with 750 µl of chloroform/MeOH (1:1, v/v) containing 1.25 µM 1,2-dioctanoyl-sn-glycero-3-phosphocholine (SIGMA) followed by centrifugation at 10,000g at 4°C for 5 min. The supernatant was transferred to a 2 ml tube, and the extraction procedure was repeated again. The combined supernatant was evaporated to dryness by SPD2010 SpeedVac® concentrator. The residue was dissolved in 750 µl of ethanol, and centrifuged at 10,000g at 4°C for 5 min. Six hundred microlitter of the supernatant was transferred to a glass tube for polar-lipid analysis.

LC-IT-TOF-MS conditions
Extracts (0.5 µl, ca. 33.3 µg of each sample) was analyzed by LCMS with ESI interface (LC, Shimadzu LC-20AD system; MS, Shimadzu LCMS-IT-TOF) operated by Shimadzu LCMSsolution software (version 3.60). Two-solvent system was used for separation of each metabolite. The analytical conditions were as follows. Column, Shim-pack XR-ODS (2.0 mm I.D., 50 mm long); solvent A, water (1% 1M ammonium formate and 0.1% formic acid); solvent B, acetonitrile/isopropyl alcohol (40:60, v/v. 1% 1M ammonium formate and 0.1% formic acid); gradient program, 40% B at 0 min, 75% B at 3 min, 95% B at 10 min, 100% B at 19 min, 100% B at 27 min, 40% B at 27.01 min (total run time, 30 min); flow rate, 0.3 ml/min; column temperature, 55°C; MS interface voltage, 4.50 kV, nebulizer gas, 1.50 L/min; CDL temperature 200.0°C, heat block temperature, 200°C; detection mode, scan (m/z 150˜1600, positive); scan time, 0.25 sec; ion accumulation time, 20 msec.

Comment_of_details

Data Analysis Information

ID D2
Title Data analysis
Data Analysis Details ID DS5
Recommended decimal places of m/z
Comment


Data Analysis Details Information

ID DS5
Title Data analysis
Description All data analyses were performed using R v2.12.1. Network visualization was done using Cytoscape and the GOlorize plug-in. Missing value robust PCA was performed using the pcaMethods package.
Comment_of_details
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