Literature DB >> 20369372

Toward genome-wide metabolotyping and elucidation of metabolic system: metabolic profiling of large-scale bioresources.

Masami Yokota Hirai1, Yuji Sawada, Shigehiko Kanaya, Takashi Kuromori, Masatomo Kobayashi, Romy Klausnitzer, Kosuke Hanada, Kenji Akiyama, Tetsuya Sakurai, Kazuki Saito, Kazuo Shinozaki.   

Abstract

An improvement in plant production is increasingly important for a sustainable human society. For this purpose, understanding the mechanism of plant production, that is, the plant metabolic system, is an immediate necessity. After the sequencing of the Arabidopsis genome, it has become possible to obtain a bird's eye view of its metabolism by means of omics such as transcriptomics and proteomics. Availability of thousands of transcriptome data points in the public domain has resulted in great advances in the methodology of functional genomics. Metabolome data can be a "gold mine" of biological findings. However, as the total throughput of metabolomics is far lower than that of transcriptomics due to technical difficulties, there is currently no publicly available large-scale metabolome dataset that is comparable in size to the transcriptome dataset. Recently, we established a novel methodology, termed widely targeted metabolomics, which can generate thousands of metabolome data points in a high-throughput manner. We previously conducted a targeted metabolite analysis of large-scale Arabidopsis bioresources, namely transposon-tagged mutants and accessions, to make a smaller dataset of metabolite accumulation. In this paper, we release approximately 3,000 metabolic profiles obtained by targeted analysis for 36 metabolites and discuss the possible regulation of amino acid accumulation.

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Year:  2010        PMID: 20369372     DOI: 10.1007/s10265-010-0337-2

Source DB:  PubMed          Journal:  J Plant Res        ISSN: 0918-9440            Impact factor:   2.629


  44 in total

1.  Multiple reaction monitoring to identify sites of protein phosphorylation with high sensitivity.

Authors:  Richard D Unwin; John R Griffiths; Michael K Leverentz; Agnes Grallert; Iain M Hagan; Anthony D Whetton
Journal:  Mol Cell Proteomics       Date:  2005-05-27       Impact factor: 5.911

2.  A trial of phenome analysis using 4000 Ds-insertional mutants in gene-coding regions of Arabidopsis.

Authors:  Takashi Kuromori; Takuji Wada; Asako Kamiya; Masahiro Yuguchi; Takuro Yokouchi; Yuko Imura; Hiroko Takabe; Tetsuya Sakurai; Kenji Akiyama; Takashi Hirayama; Kiyotaka Okada; Kazuo Shinozaki
Journal:  Plant J       Date:  2006-06-30       Impact factor: 6.417

Review 3.  Glucosinolate metabolism and its control.

Authors:  C Douglas Grubb; Steffen Abel
Journal:  Trends Plant Sci       Date:  2006-01-09       Impact factor: 18.313

4.  PRIMe: a Web site that assembles tools for metabolomics and transcriptomics.

Authors:  Kenji Akiyama; Eisuke Chikayama; Hiroaki Yuasa; Yukihisa Shimada; Takayuki Tohge; Kazuo Shinozaki; Masami Yokota Hirai; Tetsuya Sakurai; Jun Kikuchi; Kazuki Saito
Journal:  In Silico Biol       Date:  2008

5.  Floral dip: a simplified method for Agrobacterium-mediated transformation of Arabidopsis thaliana.

Authors:  S J Clough; A F Bent
Journal:  Plant J       Date:  1998-12       Impact factor: 6.417

6.  The transcript and metabolite networks affected by the two clades of Arabidopsis glucosinolate biosynthesis regulators.

Authors:  Sergey Malitsky; Eyal Blum; Hadar Less; Ilya Venger; Moshe Elbaz; Shai Morin; Yuval Eshed; Asaph Aharoni
Journal:  Plant Physiol       Date:  2008-10-01       Impact factor: 8.340

7.  Omics-based identification of Arabidopsis Myb transcription factors regulating aliphatic glucosinolate biosynthesis.

Authors:  Masami Yokota Hirai; Kenjiro Sugiyama; Yuji Sawada; Takayuki Tohge; Takeshi Obayashi; Akane Suzuki; Ryoichi Araki; Nozomu Sakurai; Hideyuki Suzuki; Koh Aoki; Hideki Goda; Osamu Ishizaki Nishizawa; Daisuke Shibata; Kazuki Saito
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-09       Impact factor: 11.205

8.  Widely targeted metabolomics based on large-scale MS/MS data for elucidating metabolite accumulation patterns in plants.

Authors:  Yuji Sawada; Kenji Akiyama; Akane Sakata; Ayuko Kuwahara; Hitomi Otsuki; Tetsuya Sakurai; Kazuki Saito; Masami Yokota Hirai
Journal:  Plant Cell Physiol       Date:  2008-12-02       Impact factor: 4.927

9.  ATTED-II provides coexpressed gene networks for Arabidopsis.

Authors:  Takeshi Obayashi; Shinpei Hayashi; Motoshi Saeki; Hiroyuki Ohta; Kengo Kinoshita
Journal:  Nucleic Acids Res       Date:  2008-10-25       Impact factor: 16.971

10.  Unbiased characterization of genotype-dependent metabolic regulations by metabolomic approach in Arabidopsis thaliana.

Authors:  Miyako Kusano; Atsushi Fukushima; Masanori Arita; Pär Jonsson; Thomas Moritz; Makoto Kobayashi; Naomi Hayashi; Takayuki Tohge; Kazuki Saito
Journal:  BMC Syst Biol       Date:  2007-11-21
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  4 in total

1.  Integrated metabolomics identifies CYP72A67 and CYP72A68 oxidases in the biosynthesis of Medicago truncatula oleanate sapogenins.

Authors:  Vered Tzin; John H Snyder; Dong Sik Yang; David V Huhman; Bonnie S Watson; Stacy N Allen; Yuhong Tang; Karel Miettinen; Philipp Arendt; Jacob Pollier; Alain Goossens; Lloyd W Sumner
Journal:  Metabolomics       Date:  2019-05-29       Impact factor: 4.290

Review 2.  Integrated LC-MS/MS system for plant metabolomics.

Authors:  Yuji Sawada; Masami Yokota Hirai
Journal:  Comput Struct Biotechnol J       Date:  2013-05-23       Impact factor: 7.271

3.  Evolutionary interplay between sister cytochrome P450 genes shapes plasticity in plant metabolism.

Authors:  Zhenhua Liu; Raquel Tavares; Evan S Forsythe; François André; Raphaël Lugan; Gabriella Jonasson; Stéphanie Boutet-Mercey; Takayuki Tohge; Mark A Beilstein; Danièle Werck-Reichhart; Hugues Renault
Journal:  Nat Commun       Date:  2016-10-07       Impact factor: 14.919

4.  Metabolomic Variation Aligns with Two Geographically Distinct Subpopulations of Brachypodium Distachyon before and after Drought Stress.

Authors:  Aleksandra Skalska; Manfred Beckmann; Fiona Corke; Gulsemin Savas Tuna; Metin Tuna; John H Doonan; Robert Hasterok; Luis A J Mur
Journal:  Cells       Date:  2021-03-19       Impact factor: 6.600

  4 in total

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