Metabolomic correlation-network modules in Arabidopsis based on a graph-clustering approach

BMC Systems Biology

Volumn 5, Issue , 2011, Pages

  Fukushima, Atsushi ^a   Kusano, Miyako ^a,b   Redestig, Henning ^a   Arita, Masanori ^a,c,d   Saito, Kazuki ^a,e  

^a RIKEN Center for Sustainable Resource Science   (Japan)

^b YOKOHAMA CITY UNIVERSITY   (Japan)

^c UNIVERSITY OF TOKYO   (Japan)

^d KEIO UNIVERSITY   (Japan)

^e CHIBA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ARABIDOPSIS;

ALGORITHM; ARABIDOPSIS; ARTICLE; CLUSTER ANALYSIS; FACTUAL DATABASE; GENETICS; GENOTYPE; MASS FRAGMENTOGRAPHY; METABOLISM; METABOLOME; METABOLOMICS; METHODOLOGY; MULTIVARIATE ANALYSIS; PHENOTYPE; PLANT; PLANT ROOT;

ALGORITHMS; ARABIDOPSIS; CLUSTER ANALYSIS; DATABASES, FACTUAL; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; GENOTYPE; METABOLOME; METABOLOMICS; MULTIVARIATE ANALYSIS; PHENOTYPE; PLANT COMPONENTS, AERIAL; PLANT ROOTS;

EID: 78650676139     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-5-1     Document Type: Article

References (46)

1. Bino RJ, Hall RD, Fiehn O, Kopka J, Saito K, Draper J, Nikolau BJ, Mendes P, Roessner-Tunali U, Beale MH, et al. Potential of metabolomics as a functional genomics tool. Trends Plant Sci 2004, 9(9):418-425. 10.1016/j.tplants.2004.07.004, 15337491.
2. Hall RD. Plant metabolomics: from holistic hope, to hype, to hot topic. New Phytol 2006, 169(3):453-468. 10.1111/j.1469-8137.2005.01632.x, 16411949.
3. Stitt M, Sulpice R, Keurentjes J. Metabolic networks: how to identify key components in the regulation of metabolism and growth. Plant Physiol 2010, 152(2):428-444. 10.1104/pp.109.150821, 20018593.
4. Saito K, Matsuda F. Metabolomics for functional genomics, systems biology, and biotechnology. Annu Rev Plant Biol 2010, 61:463-489. 10.1146/annurev.arplant.043008.092035, 19152489.
5. Saito K, Hirai MY, Yonekura-Sakakibara K. Decoding genes with coexpression networks and metabolomics - 'majority report by precogs'. Trends Plant Sci 2008, 13(1):36-43. 10.1016/j.tplants.2007.10.006, 18160330.
6. Mentzen WI, Wurtele ES. Regulon organization of Arabidopsis. BMC Plant Biol 2008, 8:99. 10.1186/1471-2229-8-99, 2567982, 18826618.
7. Fukushima A, Wada M, Kanaya S, Arita M. SVD-based anatomy of gene expressions for correlation analysis in Arabidopsis thaliana. DNA Res 2008, 15(6):367-374. 10.1093/dnares/dsn025, 2608847, 18931094.
8. Mao L, Van Hemert JL, Dash S, Dickerson JA. Arabidopsis gene co-expression network and its functional modules. BMC Bioinformatics 2009, 10:346. 10.1186/1471-2105-10-346, 2772859, 19845953.
9. Oksman-Caldentey KM, Saito K. Integrating genomics and metabolomics for engineering plant metabolic pathways. Curr Opin Biotechnol 2005, 16(2):174-179. 10.1016/j.copbio.2005.02.007, 15831383.
10. Yuan JS, Galbraith DW, Dai SY, Griffin P, Stewart CN. Plant systems biology comes of age. Trends Plant Sci 2008, 13(4):165-171. 10.1016/j.tplants.2008.02.003, 18329321.
11. Fukushima A, Kusano M, Redestig H, Arita M, Saito K. Integrated omics approaches in plant systems biology. Curr Opin Chem Biol 2009, 13(5-6):532-538. 10.1016/j.cbpa.2009.09.022, 19837627.
12. Steuer R. Review: on the analysis and interpretation of correlations in metabolomic data. Brief Bioinform 2006, 7(2):151-158. 10.1093/bib/bbl009, 16772265.
13. Roessner U, Luedemann A, Brust D, Fiehn O, Linke T, Willmitzer L, Fernie A. Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 2001, 13(1):11-29. 10.1105/tpc.13.1.11, 2652711, 11158526.
14. Kose F, Weckwerth W, Linke T, Fiehn O. Visualizing plant metabolomic correlation networks using clique-metabolite matrices. Bioinformatics 2001, 17(12):1198-1208. 10.1093/bioinformatics/17.12.1198, 11751228.
15. Martins AM, Camacho D, Shuman J, Sha W, Mendes P, Shulaev V. A Systems Biology Study of Two Distinct Growth Phases of Saccharomyces cerevisiae Cultures. Curr Genomics 2004, 5:649-663.
16. Weckwerth W, Loureiro ME, Wenzel K, Fiehn O. Differential metabolic networks unravel the effects of silent plant phenotypes. Proc Natl Acad Sci USA 2004, 101(20):7809-7814. 10.1073/pnas.0303415101, 419688, 15136733.
17. Steuer R, Kurths J, Fiehn O, Weckwerth W. Observing and interpreting correlations in metabolomic networks. Bioinformatics 2003, 19(8):1019-1026. 10.1093/bioinformatics/btg120, 12761066.
18. Camacho D, de la Fuente A, Mendes P. The origin of correlations in metabolomics data. Metabolomics 2005, 1(1):53-63.
19. Muller-Linow M, Weckwerth W, Hutt MT. Consistency analysis of metabolic correlation networks. BMC Syst Biol 2007, 1:44. 10.1186/1752-0509-1-44, 2077335, 17892579.
20. Kanehisa M, Goto S, Furumichi M, Tanabe M, Hirakawa M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res 2010, (38 Database):D355-360. 10.1093/nar/gkp896, 2808910, 19880382.
21. Szymanski J, Jozefczuk S, Nikoloski Z, Selbig J, Nikiforova V, Catchpole G, Willmitzer L. Stability of metabolic correlations under changing environmental conditions in Escherichia coli--a systems approach. PLoS ONE 2009, 4(10):e7441. 10.1371/journal.pone.0007441, 2759078, 19829699.
22. Urano K, Maruyama K, Ogata Y, Morishita Y, Takeda M, Sakurai N, Suzuki H, Saito K, Shibata D, Kobayashi M, et al. Characterization of the ABA-regulated global responses to dehydration in Arabidopsis by metabolomics. Plant J 2009, 57(6):1065-1078. 10.1111/j.1365-313X.2008.03748.x, 19036030.
23. Inaba K, Fujiwara T, Hayashi H, Chino M, Komeda Y, Naito S. Isolation of an Arabidopsis thaliana Mutant, mto1, That Overaccumulates Soluble Methionine (Temporal and Spatial Patterns of Soluble Methionine Accumulation). Plant Physiol 1994, 104(3):881-887. 160685, 12232133.
24. Shikazono N, Yokota Y, Kitamura S, Suzuki C, Watanabe H, Tano S, Tanaka A. Mutation rate and novel tt mutants of Arabidopsis thaliana induced by carbon ions. Genetics 2003, 163(4):1449-1455. 1462525, 12702688.
25. Kusano M, Fukushima A, Arita M, Jonsson P, Moritz T, Kobayashi M, Hayashi N, Tohge T, Saito K. Unbiased characterization of genotype-dependent metabolic regulations by metabolomic approach in Arabidopsis thaliana. BMC Syst Biol 2007, 1:53. 10.1186/1752-0509-1-53, 2233643, 18028551.
26. Altaf-Ul-Amin M, Shinbo Y, Mihara K, Kurokawa K, Kanaya S. Development and implementation of an algorithm for detection of protein complexes in large interaction networks. BMC Bioinformatics 2006, 7:207. 10.1186/1471-2105-7-207, 1473204, 16613608.
27. Schauer N, Steinhauser D, Strelkov S, Schomburg D, Allison G, Moritz T, Lundgren K, Roessner-Tunali U, Forbes MG, Willmitzer L, et al. GC-MS libraries for the rapid identification of metabolites in complex biological samples. FEBS Lett 2005, 579(6):1332-1337. 10.1016/j.febslet.2005.01.029, 15733837.
28. Redestig H, Kusano M, Fukushima A, Matsuda F, Saito K, Arita M. Consolidating metabolite identifiers to enable contextual and multi-platform metabolomics data analysis. BMC Bioinformatics 2010, 11(1):214. 10.1186/1471-2105-11-214, 2879285, 20426876.
29. Strimmer K. fdrtool: a versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics 2008, 24(12):1461-1462. 10.1093/bioinformatics/btn209, 18441000.
30. Barabasi AL, Oltvai ZN. Network biology: understanding the cell's functional organization. Nat Rev Genet 2004, 5(2):101-113. 10.1038/nrg1272, 14735121.
31. Kusano M, Fukushima A, Redestig H, Kobayashi M, Otsuki H, Onouchi H, Naito S, Hirai MY, Saito K. Comparative metabolomics charts the impact of genotype-dependent methionine accumulation in Arabidopsis thaliana. Amino Acids 2010, 39(4):1013-1021. 10.1007/s00726-010-0562-y, 20354740.
32. Facchini PJ, Bird DA, St-Pierre B. Can Arabidopsis make complex alkaloids?. Trends Plant Sci 2004, 9(3):116-122. 10.1016/j.tplants.2004.01.004, 15003234.
33. Freeman TC, Goldovsky L, Brosch M, van Dongen S, Maziere P, Grocock RJ, Freilich S, Thornton J, Enright AJ. Construction, visualisation, and clustering of transcription networks from microarray expression data. PLoS Comput Biol 2007, 3(10):2032-2042. 10.1371/journal.pcbi.0030206, 2041979, 17967053.
34. Ma S, Gong Q, Bohnert HJ. An Arabidopsis gene network based on the graphical Gaussian model. Genome Res 2007, 17(11):1614-1625. 10.1101/gr.6911207, 2045144, 17921353.
35. Fukushima A, Kanaya S, Arita M. Characterizing gene coexpression modules in Oryza sativa based on a graph-clustering approach. Plant Biotechnol 2009, 26:485-493.
36. Steuer R, Kurths J, Daub CO, Weise J, Selbig J. The mutual information: detecting and evaluating dependencies between variables. Bioinformatics 2002, 18(Suppl 2):S231-240.
37. de la Fuente A, Bing N, Hoeschele I, Mendes P. Discovery of meaningful associations in genomic data using partial correlation coefficients. Bioinformatics 2004, 20(18):3565-3574. 10.1093/bioinformatics/bth445, 15284096.
38. Tarpley L, Duran AL, Kebrom TH, Sumner LW. Biomarker metabolites capturing the metabolite variance present in a rice plant developmental period. BMC Plant Biol 2005, 5:8. 10.1186/1471-2229-5-8, 1175851, 15927065.
39. Yonekura-Sakakibara K, Tohge T, Matsuda F, Nakabayashi R, Takayama H, Niida R, Watanabe-Takahashi A, Inoue E, Saito K. Comprehensive flavonol profiling and transcriptome coexpression analysis leading to decoding gene-metabolite correlations in Arabidopsis. Plant Cell 2008, 20(8):2160-2176. 10.1105/tpc.108.058040, 2553606, 18757557.
40. Albinsky D, Kusano M, Higuchi M, Hayashi N, Kobayashi M, Fukushima A, Mori M, Ichikawa T, Matsui K, Kuroda H, et al. Metabolomic Screening Applied to Rice FOX Arabidopsis Lines Leads to the Identification of a Gene-Changing Nitrogen Metabolism. Mol Plant 2010, 3(1):125-142. 10.1093/mp/ssp069, 20085895.
41. de la Fuente A. From 'differential expression' to 'differential networking' - identification of dysfunctional regulatory networks in diseases. Trends Genet 2010, 26(7):326-333. 10.1016/j.tig.2010.05.001, 20570387.
42. Jonsson P, Johansson ES, Wuolikainen A, Lindberg J, Schuppe-Koistinen I, Kusano M, Sjostrom M, Trygg J, Moritz T, Antti H. Predictive metabolite profiling applying hierarchical multivariate curve resolution to GC-MS data--a potential tool for multi-parametric diagnosis. J Proteome Res 2006, 5(6):1407-1414. 10.1021/pr0600071, 16739992.
43. Kopka J, Schauer N, Krueger S, Birkemeyer C, Usadel B, Bergmuller E, Dormann P, Weckwerth W, Gibon Y, Stitt M, et al. GMD@CSB.DB: the Golm Metabolome Database. Bioinformatics 2005, 21(8):1635-1638. 10.1093/bioinformatics/bti236, 15613389.
44. Breitling R, Armengaud P, Amtmann A, Herzyk P. Rank products: a simple, yet powerful, new method to detect differentially regulated genes in replicated microarray experiments. FEBS Lett 2004, 573(1-3):83-92. 10.1016/j.febslet.2004.07.055, 15327980.
45. Stacklies W, Redestig H, Scholz M, Walther D, Selbig J. pcaMethods--a bioconductor package providing PCA methods for incomplete data. Bioinformatics 2007, 23(9):1164-1167. 10.1093/bioinformatics/btm069, 17344241.
46. Csardi G, Nepusz T. The igraph software package for complex network research. Int J Complex Syst 2006, , http://necsi.org/events/iccs6/viewabstract.php?id=88