SE60:/S01/M01/D01

Sample Set Information

ID	SE60
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
Comment

The original paper is available at The Plant Journal.

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

Sample Information

ID	S01
Title	Japanese rice
Organism - Scientific Name	Oryza sativa
Organism - ID	NCBI taxonomy:4530
Compound - ID
Compound - Source
Preparation	A Japanese rice collection of 175 accessions were used in this study (Table S1) (Yonemaru et al., 2012). The Sasanishiki/Habataki chromosome segment substitution lines (CSSLs, 39 accessions) were also used (Ando et al., 2008).
Sample Preparation Details ID	SS01
Comment

Sample Preparation Details Information

ID	SS01
Title	Sample Preparation
Description	Seeds were sterilized in 10% sodium hypochloric acid solution by vacuum infiltration for 1 h, and then immersed in aqueous 2% PPMTM solution (Nacalai Tesque, Kyoto, Japan, http://www.nacalai.co.jp/) at 28°C for 1 day in darkness. Seeds were sown in wet commercial fertilized soil (Bonsol II; Sumitomo Chemical, Tokyo, Japan, http://www.sumitomochem.co.jp/), and maintained under a 12-h light (28°C)/12-h dark (20°C) cycle for germination. Plants were kept under constant subirrigation conditions with tap water. After 2 weeks of growth, the entire aboveground (or aerial) part of one seedling was collected, weighed, and frozen in liquid nitrogen for analysis. Samples were stored at -80℃ until analysis.
Comment_of_details

Analytical Method Information

ID	M01
Title	Metabolic profiling analysis using LC-ESI-Q-Tof/MS
Method Details ID	MS01
Sample Amount	3 μL
Comment

Analytical Method Details Information

ID	MS01
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, http://www.tcichemicals.com/), using a mixer mill (MM 300, Retsch, Haan, Germany, http://www.retsch.com/) 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, http://www.waters.com/). 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).
Comment_of_details

Data Analysis Information

ID	D01
Title	Metabolite annotation
Data Analysis Details ID	DS01
Recommended decimal places of m/z	Default
Comment

Data Analysis Details Information

ID	DS01
Title	Metabolite annotation
Description	For structural elucidation of metabolite signals, MS/MS spectral tag (MS2T) libraries were constructed (Matsuda et al., 2011). The extracts of 14–15 cultivars were mixed and utilized for MS/MS spectra data acquisition. Analyses were repeated for 12 mixtures using automated data acquisition methods as previously described (Matsuda et al., 2009). Each MS2T entry was assigned a unique code, OSAXXpXXXXX, indicating the library name (OSAXXp) and entry number. MS2T libraries containing 164 051 entries were constructed. MS2Ts were added to metabolite signals, from which the structure of each metabolite signal was elucidated by searching the ReSpect (RIKEN MS/MS spectra database for phytochemicals) (Sawada et al., 2012), MassBank (Horai et al., 2010), KNApSAcK (Afendi et al., 2012), and PRIMe standard compound database (Sakurai et al., 2013). The two spectra were considered to be similar when the similarity score of the ReSpect search was greater than 0.6. Thresholds were set at m/z Δ0.05 and 0.15 min, respectively, for the molecular formula search on the KNApSAcK database and comparison of retention times. Based on the criteria proposed by the metabolome standard initiative (MSI) (Sumner et al., 2007), metabolite signals were ‘characterized’ when parts of a structure were deduced from mass data. Metabolite signals were‘annotated’ when a common metabolite was observed in the outputs from both the ReSpect and KNApSAcK searches. Metabolite signals were considered to be ‘identified’ when three distinct pieces of information, including the MS/MS spectra, exact mass number, and chromatographic behavior, were matched to identical metabolites (Table S4). Data obtained in this study are available on the PRIMe website (http://prime.psc.riken.jp/) (Sakurai et al., 2013). Isolation and structural determination of rice flavones has been reported previously (Yang et al., 2014).
Comment_of_details

The peak data files of this analysis are available at MS2T.

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