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Plant Systems Biology pp 373–393Cite as

Democratization and Integration of Genomic Profiling Tools

Part of the Methods in Molecular Biology™ book series (MIMB,volume 553)

Abstract

Systems biology is a comprehensive means of creating a complete understanding of how all components of an organism work together to maintain and procreate life. By quantitatively profiling one at a time, the effect of thousands and millions of genetic and environmental perturbations on the cell, systems biologists are attempting to recreate and measure the effect of the many different states that have been explored during the 3 billion years in which life has evolved. A key aspect of this work is the development of innovative new approaches to quantify changes in the transcriptome, proteome, and metabolome. In this chapter we provide a review and evaluation of several genomic profiling techniques used in plant systems biology as well as make recommendations for future progress in their use and integration.

Key words

  • Transcriptomics
  • proteomics
  • metabolomics

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References

  1. Quakenbush, J. (2001) Computational analysis of microarray data. Nat. Rev. Genet. 2, 418–427.

    CrossRef  Google Scholar 

  2. Stears, R.L., Martinsky, T., and Schena, M. (2003) Trends in microarray analysis. Nat. Med. 9, 140–145.

    PubMed  CrossRef  CAS  Google Scholar 

  3. The Arabidopsis Functional Genomics Network (AFGN). Web site: http://www.uni-tuebingen.de/plantphys/AFGN/atgenex.htm.

  4. Schmid, M., Davison, T.S., Henz, S.R., Pape, U.J., Demar, M., Vingron, M., Schölkopf, B., Weigel, D., and Lohmann, J.U. (2005) A gene expression map of Arabidopsis thalianadevelopment. Nat. Genet. 37, 501–506.

    PubMed  CrossRef  CAS  Google Scholar 

  5. Kilian, J., Whitehead, D., Horak, J., Wanke, D., Weinl, S., Batistic, O., D’Angelo, C., Bornberg-Bauer, E., Kudla, J., and Harter, K. (2007) The AtGenExpress global stress expression data set: protocols, evaluation and model data analysis of UV-B light, drought and cold stress responses. Plant J. 50, 347–363.

    PubMed  CrossRef  CAS  Google Scholar 

  6. Goda, H., Sasaki, E., Akiyama, K., Maruyama-Nakashita, A., Nakabayashi, K., Li, W., Ogawa, M., Yamauchi, Y., Preston, J., Aoki, K., Kiba, T., Takatsuto, S., Fujioka, S., Asami, T., Nakano, T., Kato, H., Mizuno, T., Sakakibara, H., Yamaguchi, S., Nambara, E., Kamiya, Y., Takahashi, H., Hirai, M.Y., Sakurai, T., Shinozaki, K., Saito, K., Yoshida, S., and Shimada, Y. (2008) The AtGenExpress hormone- and chemical-treatment data set: experimental design, data evaluation, model data analysis, and data access. Plant J.E-pub (ahead of print).

    Google Scholar 

  7. Swiss Federal Institute of Technology Zurich. Genevestigator. Web site: https://www.genevestigator.ethz.ch/.

  8. Zimmermann, P., Hirsch-Hoffmann, M., Hennig, L., and Gruissem, W. (2004) GENEVESTIGATOR: Arabidopsismicroarray database and analysis toolbox. Plant Phys. 136, 2621–2632.

    CrossRef  CAS  Google Scholar 

  9. Zimmermann, P., Hennig, L., and Gruissem, W. (2005) Gene expression analysis and network discovery using Genevestigator. Trends Plant Sci. 9, 407–409.

    CrossRef  Google Scholar 

  10. Wohlbach, D.J., Quirino, B.F., and Sussman, M.R. (2008) Analysis of the Arabidopsis histidine kinase ATHK1 reveals a connection between vegetative osmotic stress sensing and seed maturation. Plant Cell.E-pub (ahead of print).

    Google Scholar 

  11. Bolstad, B.M., Irizarry, R.A., Astrand, M., and Speed, T.P. (2003) A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 19, 185–193.

    PubMed  CrossRef  CAS  Google Scholar 

  12. Irizarry, R.A., Bolstad, B.M., Collin, F., Cope, L.M., Hobbs, B., and Speed, T.P. (2003) Summaries of Affymetrix GeneChip probe level data. Nucleic Acids Res. 31, e15.

    PubMed  CrossRef  Google Scholar 

  13. Irizarry, R.A., Hobbs, B., Collin, F., Beazer-Barclay, Y.D., Antonellis, K.J., Scherf, U., and Speed, T.P. (2003) Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 4, 249–264.

    PubMed  CrossRef  Google Scholar 

  14. Bioconductor. Web site: http://bioconductor.org/.

  15. Domon, B. and Aebersold, R. (2006) Mass spectrometry and protein analysis. Science. 312(5771), 212–217.

    PubMed  CrossRef  CAS  Google Scholar 

  16. Sadygov, R.G., Cociorva, D., and Yates, J.R. III (2004) Large-scale database searching using tandem mass spectra: looking up the answer in the back of the book. Nat. Methods. 1(3), 195–202.

    PubMed  CrossRef  CAS  Google Scholar 

  17. Steen, H. and Mann, M. (2004) The ABC’s (and XYZ’s) of peptide sequencing. Nat. Rev. Mol. Cell Biol. 5(9), 699–711.

    PubMed  CrossRef  CAS  Google Scholar 

  18. Gygi, S.P., Rist, B., Gerber, S.A., Turecek, F., Gelb, M.H., and Aebersold, R. (1999) Quantitative analysis of complex protein mixtures using isotope-coded affinity tags. Nat. Biotechnol. 17(10), 994–999.

    PubMed  CrossRef  CAS  Google Scholar 

  19. Ross, P.L., Huang, Y.N., Marchese, J.N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., Purkayastha, S., Juhasz, P., Martin, S., Bartlet-Jones, M., He, F., Jacobson, A., and Pappin, D.J. (2004) Multiplexed protein quantitation in Saccharomyces cerevisiaeusing amine-reactive isobaric tagging reagents. Mol. Cell Proteomics. 3, 1154–1169.

    PubMed  CrossRef  CAS  Google Scholar 

  20. Yao, X., Freas, A., Ramirez, J., Demirev, P.A., and Fenslau, C. (2001) Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus. Anal. Chem. 73, 2836–2842.

    PubMed  CrossRef  CAS  Google Scholar 

  21. Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D.B., Steen, H., Pandey, A., and Mann, M. (2002) Stable isotope labeling by amino acids in cell culture, SILAC, as a simple and accurate approach to expression proteomics. Mol. Cell Proteomics. 1, 376–386.

    PubMed  CrossRef  CAS  Google Scholar 

  22. Krijgsveld, J., Ketting, R.F., Mahmoudi, T., Johansen, J., Artal-Sanz, M., Verrijzer, C.P., Plasterk, R.H.A., and Heck, A.J.R. (2003) Metabolic labeling of C. elegansand D. melanogasterfor quantitative proteomics. Nat. Biotechnol. 21, 927–931.

    PubMed  CrossRef  CAS  Google Scholar 

  23. Thelen, J.J. and Peck, S.C. (2007) Quantitative proteomics in plants: choices in abundance. Plant Cell. 19(11), 3339–3346.

    PubMed  CrossRef  CAS  Google Scholar 

  24. Graumann, J., Hubner, N.C., Kim, J.B., Ko, K., Moser, M., Kumar, C., Cox, J., Scholer, H., and Mann, M. (2008) Stable isotope labeling by amino acids in cell culture (SILAC) and proteome quantitation of mouse embryonic stem cells to a depth of 5,111 proteins. Mol. Cell Proteomics. 7(4), 672–683.

    PubMed  CAS  Google Scholar 

  25. Baerenfaller, K., Grossmann, J., Grobei, M.A., Hull, R., Hirsch-Hoffmann, M., Yalovsky, S., Zimmermann, P., Grossniklaus, U., Gruissem, W., and Baginsky, S. (2008) Genome scale proteomics reveals Arabidopsis thalianagene models and proteome dynamics. Science. 320, 938–941.

    PubMed  CrossRef  CAS  Google Scholar 

  26. Gygi, S.P., Rochon, Y., Franza, B.R., and Aebersold, R. (1999) Correlation between protein and mRNA abundance in yeast. Mol. Cell Biol. 19(3), 1720–1730.

    PubMed  CAS  Google Scholar 

  27. Gingras, A.C., Gstaiger, M., Raught, B., and Aebersold, R. (2007) Analysis of protein complexes using mass spectrometry. Nat. Rev. Mol. Cell Biol. 8(8), 645–654.

    PubMed  CrossRef  CAS  Google Scholar 

  28. Cravatt, B.F., Simon, G.M., and Yates, J.R. III (2007) The biological impact of mass-spectrometry-based proteomics. Nature. 450(7172), 991–1000.

    PubMed  CrossRef  CAS  Google Scholar 

  29. Blagoev, B., Kratchmarova, I., Ong, S.E., Nielsen, M., Foster, L.J., and Mann, M. (2003) A proteomics strategy to elucidate functional protein–protein interactions applied to EGF signalling. Nat. Biotechnol. 21(3), 315–318.

    PubMed  CrossRef  CAS  Google Scholar 

  30. Pflieger, D., Junger, M.A., Muller, M., Rinner, O., Lee, H., Gehrig, P.M., Gstaiger, M., and Aebersold, R. (2008) Quantitative proteomic analysis of protein complexes: concurrent identification of interactors and their state of phosphorylation. Mol. Cell Proteomics. 7(2), 326–346.

    PubMed  CAS  Google Scholar 

  31. Dharmasiri, N., Dharmasiri, S., and Estelle, M. (2005) The F-box protein TIR1 is an auxin receptor. Nature. 435(7041), 441–445.

    PubMed  CrossRef  CAS  Google Scholar 

  32. Kepinski, S. and Leyser, O. (2005) The Arabidopsis F-box protein TIR1 is an auxin receptor. Nature. 435(7041), 446–451.

    PubMed  CrossRef  CAS  Google Scholar 

  33. Doherty, M.K. and Beynon, R.J. (2006) Protein turnover on the scale of the proteome. Expert Rev. Proteomics. 3(1), 97–110.

    PubMed  CrossRef  CAS  Google Scholar 

  34. Pratt, J.M., Petty, J., Riba-Garcia, I., Robertson, D.H., Gaskell, S.J., Oliver, S.G., and Beynon, R.J. (2002) Dynamics of protein turnover, a missing dimension in proteomics. Mol. Cell Proteomics. 1(8), 579–591.

    PubMed  CrossRef  CAS  Google Scholar 

  35. Rao, P.K., Roxas, B.A.P., and Li, Q. (2008) Determination of global protein turnover in stressed mycobacterium cells using hybrid-linear ion trap-fourier transform mass spectrometry. Anal. Chem. 80, 396–406.

    PubMed  CrossRef  CAS  Google Scholar 

  36. Doherty, M.K., Whitehead, C., McCormack, H., Gaskell, S.J., and Beynon, R.J. (2005) Proteome dynamics in complex organisms: using stable isotopes to monitor individual protein turnover rates. Proteomics. 5(2), 522–533.

    PubMed  CrossRef  CAS  Google Scholar 

  37. Gruhler, A., Schulze, W.X., Matthiesen, R., Mann, M., and Jensen, O.N. (2005) Stable isotope labeling of Arabidopsis thaliana cells and quantitative proteomics by mass spectrometry. Mol. Cell Proteomics. 4(11), 952–964.

    Google Scholar 

  38. Kim, J.K., Harada, K., Bamba, T., Fukusaki, E.-I., and Bobayashi, A. (2005) Stable isotope dilution-based accurate comparative quantification of nitrogen-containing metabolites in Arabidopsis thalianaT87 cells using in vivo 15N-isotope enrichment. Biosci. Biotechnol. Biochem. 69(7), 1331–1340.

    PubMed  CrossRef  CAS  Google Scholar 

  39. Harada, K., Fukusaki, E., Bamba, T., Sato, F., and Kobayashi, A. (2006) In vivo 15N-enrichment of metabolites in suspension cultured cells and its application to metabolomics. Biotechnol. Prog. 22(4), 1003–1011.

    PubMed  CrossRef  CAS  Google Scholar 

  40. Engelsberger, W.R., Erban, A., Kopka, J., and Schulze, W.X. (2006) Metabolic labeling of plant cell cultures with K15NO3as a tool for quantitative analysis of proteins and metabolites. Plant Methods. 2, 14–25.

    PubMed  CrossRef  Google Scholar 

  41. Lanquar, V., Kuhn, L., Lelievre, F., Khafif, M., Espagne, C., Bruley, C., Barbier-Brygoo, H., Garin, J., and Thomine, S. (2007) 15N-metabolic labeling for comparative plasma membrane proteomics in Arabidopsis cells. Proteomics. 7(5), 750–754.

    PubMed  CrossRef  CAS  Google Scholar 

  42. Ippel, J.H., Pouvreau, L., Kroef, T., Gruppen, H., Versteeg, G., van den Putten, P., Struik, P.C., and van Mierlo, C.P. (2004) In vivo uniform 15N-isotope labelling of plants: using the greenhouse for structural proteomics. Proteomics. 4(1), 226–234.

    PubMed  CrossRef  CAS  Google Scholar 

  43. Nelson, C.J., Huttlin, E.L., Hegeman, A.D., Harms, A.C., and Sussman, M.R. (2007) Implications of 15N-metabolic labeling for automated peptide identification in Arabidopsis thaliana. Proteomics. 7(8), 1279–1292.

    PubMed  CrossRef  CAS  Google Scholar 

  44. Huttlin, E.L., Hegeman, A.D., Harms, A.C., and Sussman, M.R. (2007) Comparison of full versus partial metabolic labeling for quantitative proteomics analysis in Arabidopsis thaliana. Mol. Cell Proteomics. 6(5), 860–881.

    PubMed  CrossRef  CAS  Google Scholar 

  45. Hebeler, R., Oekjeklaus, S., Reidegeld, K.A., Eisenacher, M., Staphan, C., Sitek, B., Stuhler, K., Meyer, H.E., Sturre, M.J., Dijkwel, P.P., and Warscheid, B. (2008) Study of early leaf senescence in Arabidopsis thalianaby quantitative proteomics using reciprocal 14N/15N labeling and difference gel electrophoresis. Mol. Cell Proteomics. 7(1), 108–120.

    PubMed  CAS  Google Scholar 

  46. Maor, R., Jones, A., Nuhse, T.S., Studholme, D.H., Peck, S.C., and Shirasu, K. (2007) Multidimensional protein identification technology (MudPIT) analysis of ubiquitinated proteins in plants. Mol. Cell Proteomics. 6(4), 601–610.

    PubMed  CrossRef  CAS  Google Scholar 

  47. Fitchette, A.C., Dinh, O.T., Faye, L., and Bardor, M. (2007) Plant proteomics and glycosylation. Methods Mol. Biol. 355, 317–342.

    PubMed  CAS  Google Scholar 

  48. Peck, S.C. (2006) Phosphoproteomics in Arabidopsis: moving from empirical to predictive science. J. Exp. Bot. 57(7), 1523–1527.

    PubMed  CrossRef  CAS  Google Scholar 

  49. Ding, S.J., Qian, W.J., and Smith, R.D. (2007) Quantitative proteomics approaches for studying phosphotyrosine signaling. Expert Rev. Proteomics. 4(1), 13–23.

    PubMed  CrossRef  CAS  Google Scholar 

  50. Vener, A.V., Harms, A., Sussman, M.R., and Vierstra, R.D. (2001) Mass spectrometric resolution of reversible protein phosphorylation in photosynthetic membranes of Arabidopsis thaliana. J. Biol. Chem. 276(10), 6959–6966.

    PubMed  CrossRef  CAS  Google Scholar 

  51. Ficarro, S.B., McCleland, M.L., Stukenberg, P.T., Burke, D.J., Ross, M.M., Shabanowitz, J., Hunt, D.F., and White, F.M. (2002) Phosphoproteome analysis by mass spectrometry and its application to Saccharomyces cerevisiae. Nat. Biotechnol. 20, 301–305.

    PubMed  CrossRef  CAS  Google Scholar 

  52. Nuhse, T.S., Stensballe, A., Jensen, O.N., and Peck, S.C. (2003) Large-scale analysis of in vivo phosphorylated membrane proteins by immobilized metal ion affinity chromatography and mass spectrometry. Mol. Cell Proteomics. 2(12), 1261–1270.

    PubMed  CrossRef  Google Scholar 

  53. Nuhse, T., Yu, K., and Salomon, A. (2007) Isolation of phosphopeptides by immobilized metal ion affinity chromatography. Curr. Protoc. Mol. Biol. 18, 18.13.

    Google Scholar 

  54. Pinkse, M.W., Uitto, P.M., Hilhorst, M.J., Ooms, B., and Heck, A.J. (2004) Selective isolation at the femtomole level of phosphopeptides from proteolytic digests using 2D-nano-LC-ESI_MS/MS and titanium oxide precolumns. Anal. Chem. 96(14), 3935–3943.

    CrossRef  Google Scholar 

  55. Beausoleil, S.A., Hedrychowski, M., Schwartz, D., Elias, J.E., Villen, J., Li, J., Cohn, M.A., Cantley, L.C., and Gygi, S.P. (2004) Large-scale characterization of HeLa cell nuclear phosphoproteins. Proc. Nat. Acad. Sci. USA. 101(33), 12130–12135.

    Google Scholar 

  56. Gruhler, A., Olsen, J.V., Mohammed, S., Mortensen, P., Faergeman, N.J., Mann, M., and Jensen, O.N. (2005) Quantitative phosphoproteomics applied to the yeast pheromone signaling pathway. Mol. Cell Proteomics. 4(3), 310–327.

    PubMed  CrossRef  CAS  Google Scholar 

  57. Kelleher, N.L., Zubarev, R.A., Bush, K., Furie, B., Furie, B.C., McLafferty, F.W., and Walsh, C.T. (1999) Localization of labile posttranslational modifications by electron capture dissociation: the case of gamma-carboxyglutamic acid. Anal. Chem. 71(19), 4250–4253.

    PubMed  CrossRef  CAS  Google Scholar 

  58. Zubarev, R.A., Horn, D.M., Fridriksson, E.K., Kelleher, N.L., Kruger, N.A., Lewis, M.A., Carpenter, B.K., and McLafferty, F.W. (2000) Electron capture dissociation for structural characterization of multiply charged protein cations. Anal. Chem. 72(3), 563–573.

    PubMed  CrossRef  CAS  Google Scholar 

  59. Syka, J.E., Coon, J.J., Schroeder, M.J., Shabanowitz, J., and Hunt, D.F. (2004) Peptide and protein sequence analysis by electron transfer dissociation mass spectrometry. Proc. Natl. Acad. Sci. USA. 101(26), 9528–9533.

    Google Scholar 

  60. Gerber, S.A., Rush, J., Stemman, O., Kirschner, M.W., and Gygi, S.P. (2003) Absolute quantification of proteins and phosphoproteins from cell lysates by tandem MS. Proc. Nat. Acad. Sci. USA. 100(12), 6940–6945.

    PubMed  CrossRef  CAS  Google Scholar 

  61. Hegeman, A.D., Harms, A.C., Sussman, M.R., Bunner, A.E., and Harper, J.F. (2004) An isotope labeling strategy for quantifying the degree of phosphorylation at multiple sites in proteins. J. Am. Soc. Mass Spectrom. 15(5), 647–653.

    PubMed  CrossRef  CAS  Google Scholar 

  62. Dunn, W.B., Bailey, N.J.C., and Johnson, H.E. (2005) Measuring the metabolome: current analytical technologies. Analyst. 130, 606–625.

    PubMed  CrossRef  CAS  Google Scholar 

  63. Marshall, E. (2007) Metabolic Research: Canadian group claims “unique” database. Science. 315, 583–584.

    PubMed  CrossRef  CAS  Google Scholar 

  64. Fiehn, O., Kloska, S., and Altmann, T. (2001) Integrated studies on plant biology using multiparallel techniques. Curr. Opin. Biotechnol. 12(1), 82–86.

    PubMed  CrossRef  CAS  Google Scholar 

  65. Kimball, E. and Rabinowitz, J.D. (2006) Identifying decomposition products in extracts of cellular metabolites. Anal. Biochem. 358(2), 273–280.

    PubMed  CrossRef  CAS  Google Scholar 

  66. Want, E.J., O’Maille, G., Smith, C.A., Brandon, T.R., Uritboonthai, W., Qin, C., Trauger, S.A., and Siuzdak, G. (2006) Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Anal. Chem. 78(3), 743–752.

    PubMed  CrossRef  CAS  Google Scholar 

  67. Rabinowitz, J.D. and Kimball, E. (2007) Acidic acetonitrile for cellular metabolome extraction from Escherichia coli. Anal. Chem. 79(16), 6167–6173.

    PubMed  CrossRef  CAS  Google Scholar 

  68. Lewis, I.A., Schommer, S.C., Hodis, B., Robb, K.A., Tonelli, M., Westler, W.M., Sussman, M.R., and Markley, J.L. (2007) Method for determining molar concentrations of metabolites in complex solutions from two-dimensional 1H-13C NMR spectra. Anal. Chem. 79(24), 9385–9390.

    PubMed  CrossRef  CAS  Google Scholar 

  69. Want, E.J., Nordstrom, A., Morita, H., and Suizdak, G. (2007) From exogenous to endogenous: the inevitable imprint of mass spectrometry in metabolomics. J. Proteome Res. 6(2), 459–468.

    PubMed  CrossRef  CAS  Google Scholar 

  70. Bajad, S.U., Lu, W., Kimball, E.H., Yuan, J., Peterson, C., and Rabinowitz, J.D. (2006) Separation and quantitation of water soluble cellular metabolites by hydrophilic interaction chromatography-tandem mass spectrometry. J. Chromatogr. 1125(1), 76–88.

    CrossRef  CAS  Google Scholar 

  71. Nordstrom, A., Want, E., Northen, T., Lehtio, J., and Siuzdak, G. (2008) Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics. Anal. Chem. 80(2), 421–429.

    PubMed  CrossRef  Google Scholar 

  72. Smith, C.A., Want, E.J., O’Maille, G., Abagyan, R., and Suizdak, G.(2006) XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78(3), 779–787.

    PubMed  CrossRef  CAS  Google Scholar 

  73. NIST Website: http://www.nist.gov/srd/nist1.htm.

  74. Kopka, J., Schauer, N., Krueger, S., Birkemeyer, C., Usadel, B., Bergmuller, E., Dormann, P., Weckwerth, W., Gibon, Y., Stitt, M., Willmitzer, L., Fernie, A.R., and Steinhauser, D. (2005) GMD@CSB.DB: the Golm metabolome database. Bioinformatics. 21(8), 1635–1638.

    PubMed  CrossRef  CAS  Google Scholar 

  75. Smith, C.A., O’Maille, G., Want, E.J., Qin, C., Trauger, S.A., Brandon, T.R., Custodio, D.E., Abagyan, R., and Siuzdak, G. (2005) METLIN: a metabolite mass spectra database. Ther. Drug Monit. 27(6), 747–751.

    PubMed  CrossRef  CAS  Google Scholar 

  76. Wishart, D.S., Tzur, D., Knox, C., Eisner, R., Guo, A.C., Young, N., Cheng, D., Jewell, K., Arndt, D., Sawhney, S., Fung, C., Nikolai, L., Lewis, M., Coutouly, M.-A., Forsythe, I., Tang, P., Shrivastava, S., Jeroncic, K., Stothard, P., Amegbey, G., Block, D., Hau, D.D., Wagner, J., Miniaci, J., Clements, M., Gebremedhin, M., Guo, N., Zhang, Y., Duggan, G.E., MacInnis, G.D., Weljie, A.M., Dowlatabadi, R., Bamforth, F., Clive, D., Greiner, R., Li, L., Marrie, T., Sykes, B.D., Vogel, H.J., and Querengesser, L. (2007) HMDB: the human metabolome database. Nucleic Acids Res. 35, D521–D526.

    PubMed  CrossRef  CAS  Google Scholar 

  77. Cui, Q., Lewis, I.A., Hegeman, A.D., Anderson, M.E., Li, J., Schulte, C.F., Westler, W.M., Eghbalnia, H.R., Sussman, M.R., and Markley, J.R. (2008) Metabolite identification via the Madison metabolomics consortium database. Nat. Biotechnol. 26(2), 162–164.

    PubMed  CrossRef  CAS  Google Scholar 

  78. Kind, T. and Fiehn, O. (2007) Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC Bioinformatics. 27(8), 105.

    CrossRef  Google Scholar 

  79. Hegeman, A.D., Schulte, C.F., Cui, Q., Lewis, I.A., Huttlin, E.L., Eghbalnia, H., Harms, A.C., Ulrich, E.L., Markley, J.L., and Sussman, M.R. (2007) Stable isotope assisted assignment of elemental compositions for metabolomics. Anal. Chem. 79(18), 6912–6921.

    PubMed  CrossRef  CAS  Google Scholar 

  80. Weckwerth, W., Wenzel, K., and Fiehn, O. (2004) Process for the integrated extraction, identification, and quantification of metabolites, proteins, and RNA to reveal their co-regulation in biochemical networks. Proteomics. 4, 78–83.

    PubMed  CrossRef  CAS  Google Scholar 

  81. Frey, I.M., Rubio-Aliaga, I., Siewert, A., Sailer, D., Drobyshev, A., Beckers, J., de Angelis, M.H., Aubert, J., Hen, A.B., Fiehn, O., Eichinger, H.M., and Daniel, H. (2007) Profiling at mRNA, protein, and metabolite levels reveals alterations in renal amino acid handling and glutathione metabolism in kidney tiddue of Pept2-/- mice. Physiol. Genomics. 28, 301–310.

    PubMed  CAS  Google Scholar 

  82. Trauger, S.A., Kalizak, E., Kalisiak, J., Morita, H., Weinberg, M.V., Menon, A.L., Poole, F.L. II, Adams, M.W.W., and Siuzdak, G. (2008) Correlating the transcriptome, proteome, and metabolome in the environmental adaptation of a hyperthermophile. J. Proteome Res. 7, 1027–1035.

    PubMed  CrossRef  CAS  Google Scholar 

  83. Schauer, N., Semel, Y., Roessner, U., Gur, A., Balbo, I., Carrari, F., Pleban, T., Perez-Melis, A., Bruedigam, C., Kopka, J., Willmitzer, L., Zamir, D., and Fernie, A.R. (2006) Comprehensive metabolic profiling and phenotyping of interspecific introgression lines for tomato improvement. Nat. Biotech. 24, 447–454.

    CrossRef  CAS  Google Scholar 

  84. Lu, Y., Savage, L.J., Ajjawi, I., Imre, K.M., Yoder, D.W., Benning, C., DellaPenna, D., Ohlrogge, J.B., Osteryoung, K.W., Weber, A.P., Wilkerson, C.G., and Last, R.L. (2008) New connections across pathways and cellular processes: industrialized mutant screening reveals novel associations between diverse phenotypes in Arabidopsis. Plant Physiol. 146, 1482–1500.

    PubMed  CrossRef  CAS  Google Scholar 

  85. Wienkoop, S., Morgenthal, K., Wolschin, F., Scholz, M., Selbig, J., and Weckwerth, W. (2008) Integration of metabolomic and proteomic phenotypes – analysis of data-covariance dissects starch and RFO metabolism from low and high temperature response in Arabidopsis thaliana. Mol. Cell Proteomics. 7, 1725–1736.

    PubMed  CrossRef  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Biochemistry, UW Biotechnology Center, University of Wisconsin-Madison, Madison, WI, USA

    Michael R. Sussman

  2. Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, USA

    Edward L. Huttlin

  3. Department of Genetics, University of Wisconsin-Madison, Madison, WI, USA

    Dana J. Wohlbach

Authors
  1. Michael R. Sussman
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  2. Edward L. Huttlin
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  3. Dana J. Wohlbach
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    © 2009 Humana Press, a part of Springer Science+Business Media, LLC

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    Sussman, M.R., Huttlin, E.L., Wohlbach, D.J. (2009). Democratization and Integration of Genomic Profiling Tools. In: Belostotsky, D. (eds) Plant Systems Biology. Methods in Molecular Biology™, vol 553. Humana Press. https://doi.org/10.1007/978-1-60327-563-7_20

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    • DOI: https://doi.org/10.1007/978-1-60327-563-7_20

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    • Publisher Name: Humana Press

    • Print ISBN: 978-1-60327-562-0

    • Online ISBN: 978-1-60327-563-7

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