SE55:/DS01
Sample Set Information
| ID | SE55 |
|---|---|
| Title | AtMetExpress development: a phytochemical atlas of arabidopsis development |
| Description | We analyzed phytochemical accumulation during development of the model plant Arabidopsis (Arabidopsis thaliana) using liquid chromatography-mass spectrometry in samples covering many growth stages and organs. We also obtained tandem mass spectrometry spectral tags of many metabolites as a resource for elucidation of metabolite structure. These are part of the AtMetExpress metabolite accumulation atlas. Based on the dataset, we detected 1,589 metabolite signals from which the structures of 167 metabolites were elucidated. The integrated analyses with transcriptome data demonstrated that Arabidopsis produces various phytochemicals in a highly tissue-specific manner, which often accompanies the expression of key biosynthesis-related genes. We also found that a set of biosynthesis-related genes is coordinately expressed among the tissues. These data suggested that the simple mode of regulation, transcript to metabolite, is an origin of the dynamics and diversity of plant secondary metabolism. |
| Authors | Fumio Matsuda, Masami Yokota Hirai, Eriko Sasaki, Kenji Akiyama, Keiko Yonekura-Sakakibara, Nicholas J. Provart, Tetsuya Sakurai, Yukihisa Shimada, Kazuki Saito |
| Reference | Matsuda F et al. (2010) Plant Physiology 152: 566-578 |
| Comment |
The raw data files are available at DROP Met web site in PRIMe database of RIKEN.
Data Analysis Details Information
| ID | DS01 |
|---|---|
| Title | Profiling by MetAlign and MS2T-based peak annotation |
| Description | The scans were repeated for 19.5 min in a single run. The raw data were recorded with the aid of MassLynx version 4.1 software (Waters).The raw chromatogram data were processed to produce a data matrix consisting of 1,589 metabolite signals (773 from positive and 816 from negative ion mode; Supplemental Data S1) using MetAlign (Lommen, 2009). The parameters used for data processing were as follows: maximum amplitude, 10,000; peak slope factor, 1; peak threshold factor, 6; average peakwidth at half weight, 8; scaling options, none; maximum shift per scan, 35; select min nr per peak set, 4. The data matrix generated by MetAlign was processed with inhouse software written in Perl/Tk (Matsuda et al., 2009). By this procedure, the metabolite signals eluted before 0.85 min and after 12.0 min were discarded, original peak intensity values were divided with those of the internal standards (lidocaine: m/z = 235 [M + H]+, eluted at 4.19 min; camphor-10-sulfonic acid: m/z = 231 [M 2 H]2, eluted at 3.84 min, for the positive and negative ion modes, respectively) to normalize the peak intensity values, discarding low-intensity data (under signal-to-noise ratio , 5), and isotope peaks were removed by employing specific parameters (rthres . 0.8, DRt = 0.5 s, and Dm/z = 2 D). Metabolite signals were assigned unique accession codes, such as adn031026 (representing AtMetExpress Development negative ion mode data, peak number 31026).
MS2T data were acquired from nine tissues of Arabidopsis and processed to create 36 MS2T libraries using previously described methods (Matsuda et al., 2009). Each MS2T entry was assigned a unique accession code, such as ATH10n03690, in which ATH10n is the name of the library and 03690 is the entry number. A total of 36 MS2T libraries with 476,120 accession codes were created in this study (Supplemental Table S2). The MS2T libraries contain a high volume of redundant and low-quality data (Matsuda et al., 2009). Since the metabolic profile data and the MS2T libraries were acquired using compatible analytical conditions, a metabolite signal obtained in the profile can be tagged with MS2Ts obtained from a corresponding metabolite with identical unit mass eluting at a similar retention time. By this method, approximately 95% of the metabolite signals were tagged with at least one MS2T. The mean number of MS2Ts tagged to each metabolite peak was 13.5. |
| Comment_of_details |
