A network perspective on nitrogen metabolism from model to crop plants using integrated 'omics' approaches

Journal of Experimental Botany

Volumn 65, Issue 19, 2014, Pages 5619-5630

  Fukushima, Atsushi ^a,b   Kusano, Miyako ^a,b,c  

^a RIKEN Center for Sustainable Resource Science   (Japan)

^b JAPAN SCIENCE AND TECHNOLOGY AGENCY   (Japan)

^c UNIVERSITY OF TSUKUBA   (Japan)

Author keywords

Central metabolism; Deep sequencing; Metabolite profling; Nitrogen metabolism; RNA seq; Transcript profling

Indexed keywords

AMINO ACID; CARBON; NITROGEN;

CROP; GENE EXPRESSION PROFILING; METABOLISM; METABOLOMICS; PLANT;

AMINO ACIDS; CARBON; CROPS, AGRICULTURAL; GENE EXPRESSION PROFILING; METABOLOMICS; NITROGEN; PLANTS;

EID: 84919358648     PISSN: 00220957     EISSN: 14602431     Source Type: Journal    
DOI: 10.1093/jxb/eru322     Document Type: Review

References (126)

1. Afendi FM, Okada T, Yamazaki M et al. 2012. KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research. Plant Cell Physiology 53, e1.
2. Aoki K, Ogata Y, Shibata D. 2007. Approaches for extracting practical information from gene co-expression networks in plant biology. Plant Cell Physiology 48, 381-390.
3. Araujo WL, Tohge T, Osorio S et al. 2012. Antisense inhibition of the 2-oxoglutarate dehydrogenase complex in tomato demonstrates its importance for plant respiration and during leaf senescence and fruit maturation. Plant Cell 24, 2328-2351.
4. Baba K, Karlberg A, Schmidt J, Schrader J, Hvidsten TR, Bako L, Bhalerao RP. 2011. Activity-dormancy transition in the cambial meristem involves stage-specific modulation of auxin response in hybrid aspen. Proceedings of the National Academy of Sciences, USA 108, 3418-3423.
5. Baerenfaller K, Massonnet C, Walsh S et al. 2012. Systems-based analysis of Arabidopsis leaf growth reveals adaptation to water deficit. Molecular Systems Biology 8, 606.
6. Bais P, Moon SM, He K et al. 2010. PlantMetabolomics.org: a web portal for plant metabolomics experiments. Plant Physiology 152, 1807-1816.
7. Barabasi AL, Oltvai ZN. 2004. Network biology: understanding the cell's functional organization. Nature Review Genetics 5, 101-113.
8. Barzel B, Barabasi AL. 2013. Network link prediction by global silencing of indirect correlations. Nature Biotechnology 31, 720-725.
9. Benstein RM, Ludewig K, Wulfert S, Wittek S, Gigolashvili T, Frerigmann H, Gierth M, Flugge UI, Krueger S. 2013. Arabidopsis phosphoglycerate dehydrogenase1 of the phosphoserine pathway is essential for development and required for ammonium assimilation and tryptophan biosynthesis. Plant Cell 25, 5011-5029.
10. Borisjuk L, Rolletschek H, Neuberger T. 2012. Surveying the plant's world by magnetic resonance imaging. Plant Journal 70, 129-146.
11. Broyart C, Fontaine JX, Molinie R, Cailleu D, Terce-Laforgue T, Dubois F, Hirel B, Mesnard F. 2010. Metabolic Profling of Maize Mutants Deficient for Two Glutamine Synthetase Isoenzymes Using H-1-NMR-based Metabolomics. Phytochemical Analysis 21, 102-109.
12. Cabeza R, Koester B, Liese R et al. 2014. An RNA sequencing transcriptome analysis reveals novel insights into molecular aspects of the nitrate impact on the nodule activity of Medicago truncatula. Plant Physiology 164, 400-411.
13. Caldana C, Degenkolbe T, Cuadros-Inostroza A et al. 2011. Highdensity kinetic analysis of the metabolomic and transcriptomic response of Arabidopsis to eight environmental conditions. Plant Journal 67, 869-884.
14. Canales J, Moyano TC, Villarroel E, Gutiérrez RA. 2014. Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments. Frontiers in Plant Science 5, 22.
15. Carrari F, Fernie AR. 2006. Metabolic regulation underlying tomato fruit development. Journal of Experimental Botany 57, 1883-1897.
16. Cubillos FA, Coustham V, Loudet O. 2012. Lessons from eQTL mapping studies: non-coding regions and their role behind natural phenotypic variation in plants. Current Opinion in Plant Biology 15, 192-198.
17. De Jong F, Thodey K, Lejay LV, Bevan MW. 2014. Glucose elevates NITRATE TRANSPORTER2.1 protein levels and nitrate transport activity independently of its HEXOKINASE1-mediated stimulation of NITRATE TRANSPORTER2.1 expression. Plant Physiology 164, 308-320.
18. De La Fuente A, Bing N, Hoeschele I, Mendes P. 2004. Discovery of meaningful associations in genomic data using partial correlation coefficients. Bioinformatics 20, 3565-3574.
19. De Luis A, Markmann K, Cognat V, Holt DB, Charpentier M, Parniske M, Stougaard J, Voinnet O. 2012. Two microRNAs linked to nodule infection and nitrogen-fixing ability in the legume Lotus japonicus. Plant Physiology 160, 2137-2154.
20. Diaz C, Lemaitre T, Christ A, Azzopardi M, Kato Y, Sato F, Morot-Gaudry JF, Le Dily F, Masclaux-Daubresse C. 2008. Nitrogen recycling and remobilization are differentially controlled by leaf senescence and development stage in Arabidopsis under low nitrogen nutrition. Plant Physiology 147, 1437-1449.
21. Eriksson ME, Moritz T. 2002. Daylength and spatial expression of a gibberellin 20-oxidase isolated from hybrid aspen (Populus tremula L. x P-tremuloides Michx.). Planta 214, 920-930.
22. Faith JJ, Hayete B, Thaden JT, Mogno I, Wierzbowski J, Cottarel G, Kasif S, Collins JJ, Gardner TS. 2007. Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profles. PLoS Biology 5, e8.
23. Feizi S, Marbach D, Medard M, Kellis M. 2013. Network deconvolution as a general method to distinguish direct dependencies in networks. Nature Biotechnology 31, 726-733.
24. Fernie AR, Morgan JA. 2013. Analysis of metabolic flux using dynamic labelling and metabolic modelling. Plant, Cell and Environment 36, 1738-1750.
25. Fernie AR, Stitt M. 2012. On the discordance of metabolomics with proteomics and transcriptomics: coping with increasing complexity in logic, chemistry, and network interactions scientific correspondence. Plant Physiology 158, 1139-1145.
26. Fiehn O. 2002. Metabolomics-the link between genotypes and phenotypes. Plant Molecular Biology 48, 155-171.
27. Fiehn O, Barupal DK, Kind T. 2011. Extending biochemical databases by metabolomic surveys. Journal of Biological Chemistry 286, 23637-23643.
28. Filichkin SA, Priest HD, Givan SA, Shen R, Bryant DW, Fox SE, Wong WK, Mockler TC. 2010. Genome-wide mapping of alternative splicing in Arabidopsis thaliana. Genome Research 20, 45-58.
29. Fontaine JX, Terce-Laforgue T, Armengaud P et al. 2012. Characterization of a NADH-dependent glutamate dehydrogenase mutant of Arabidopsis demonstrates the key role of this enzyme in root carbon and nitrogen metabolism. Plant Cell 24, 4044-4065.
30. Friedman N, Linial M, Nachman I, Pe'er D. 2000. Using Bayesian networks to analyze expression data. Journal of Computational Biology 7, 601-620.
31. Fukushima A, Kusano M. 2013. Recent progress in the development of metabolome databases for plant systems biology. Frontiers in Plant Science 4, 73.
32. Fukushima A, Kusano M, Mejia RF et al. 2014. Metabolomic characterization of knock-out mutants in Arabidopsis-development of a metabolite profling database for knock-out mutants in Arabidopsis (MeKO). Plant Physiology, in press.
33. Garber M, Grabherr MG, Guttman M, Trapnell C. 2011. Computational methods for transcriptome annotation and quantification using RNA-seq. Nature Methods 8, 469-477.
34. Gierlinger N, Keplinger T, Harrington M. 2012. Imaging of plant cell walls by confocal Raman microscopy. Nature Protocols 7, 1694-1708.
35. Gifford ML, Banta JA, Katari MS et al. 2013. Plasticity regulators modulate specific root traits in discrete nitrogen environments. PLoS Genetics 9, e1003760.
36. Gifford ML, Dean A, Gutierrez RA, Coruzzi GM, Birnbaum KD. 2008. Cell-specific nitrogen responses mediate developmental plasticity. Proceedings of the National Academy of Sciences, USA 105, 803-808.
37. Giorgi FM, Del Fabbro C, Licausi F. 2013. Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana. Bioinformatics 29, 717-724.
38. Gutierrez RA, Lejay LV, Dean A, Chiaromonte F, Shasha DE, Coruzzi GM. 2007. Qualitative network models and genome-wide expression data define carbon/nitrogen-responsive molecular machines in Arabidopsis. Genome Biology 8, R7.
39. Gutierrez RA, Stokes TL, Thum K et al. 2008. Systems approach identifes an organic nitrogen-responsive gene network that is regulated by the master clock control gene CCA1. Proceedings of the National Academy of Sciences, USA 105, 4939-4944.
40. Higashi Y, Saito K. 2013. Network analysis for gene discovery in plantspecialized metabolism. Plant, Cell and Environment 36, 1597-1606.
41. Hirel B, Bertin P, Quillere I et al. 2001. Towards a better understanding of the genetic and physiological basis for nitrogen use efficiency in maize. Plant Physiology 125, 1258-1270.
42. Hochberg U, Degu A, Toubiana D, Gendler T, Nikoloski Z, Rachmilevitch S, Fait A. 2013. Metabolite profling and network analysis reveal coordinated changes in grapevine water stress response. BMC Plant Biology 13, 184.
43. Huang CY, Roessner U, Eickmeier I, Genc Y, Callahan DL, Shirley N, Langridge P, Bacic A. 2008. Metabolite profling reveals distinct changes in carbon and nitrogen metabolism in phosphate-deficient barley plants (Hordeum vulgare L.). Plant Cell Physiology 49, 691-703.
44. Hur M, Campbell AA, Almeida-De-Macedo M, Li L, Ransom N, Jose A, Crispin M, Nikolau BJ, Wurtele ES. 2013. A global approach to analysis and interpretation of metabolic data for plant natural product discovery. Nature Product Reports 30, 565-583.
45. Hwang S, Rhee SY, Marcotte EM, Lee I. 2011. Systematic prediction of gene function in Arabidopsis thaliana using a probabilistic functional gene network. Nature Protocols 6, 1429-1442.
46. Jimenez-Gomez JM. 2011. Next generation quantitative genetics in plants. Frontiers in Plant Science 2, 77.
47. Kamada-Nobusada T, Makita N, Kojima M, Sakakibara H. 2013. Nitrogen-dependent regulation of de novo cytokinin biosynthesis in rice: the role of glutamine metabolism as an additional signal. Plant Cell Physiology 54, 1881-1893.
48. Kanehisa M, Goto S, Sato Y, Kawashima M, Furumichi M, Tanabe M. 2014. Data, information, knowledge and principle: back to metabolism in KEGG. Nucleic Acids Research 42, D199-205.
49. Kaspar S, Peukert M, Svatos A, Matros A, Mock HP. 2011. MALDI-imaging mass spectrometry-An emerging technique in plant biology. Proteomics 11, 1840-1850.
50. Kiba T, Kudo T, Kojima M, Sakakibara H. 2011. Hormonal control of nitrogen acquisition: roles of auxin, abscisic acid, and cytokinin. Journal of Experimental Botany 62, 1399-1409.
51. Kochevenko A, Araujo WL, Maloney GS, Tieman DM, Do PT, Taylor MG, Klee HJ, Fernie AR. 2012. Catabolism of branched chain amino acids supports respiration but not volatile synthesis in tomato fruits. Molecular Plant 5, 366-375.
52. Kopka J, Fernie A, Weckwerth W, Gibon Y, Stitt M. 2004. Metabolite profling in plant biology: platforms and destinations. Genome Biology 5, 109.
53. Krapp A, Berthome R, Orsel M et al. 2011. Arabidopsis roots and shoots show distinct temporal adaptation patterns toward nitrogen starvation. Plant Physiology 157, 1255-1282.
54. Krouk G, Crawford NM, Coruzzi GM, Tsay YF. 2010a. Nitrate signaling: adaptation to fluctuating environments. Current Opinion in Plant Biology 13, 266-273.
55. Krouk G, Mirowski P, Le Cun Y, Shasha DE, Coruzzi GM. 2010b. Predictive network modeling of the high-resolution dynamic plant transcriptome in response to nitrate. Genome Biology 11, R123.
56. Kusano M, Fukushima A. 2013. Current challenges and future potential of tomato breeding using omics approaches. Breeding Science 63, 31-41.
57. Kusano M, Fukushima A, Redestig H, Saito K. 2011a. Metabolomic approaches toward understanding nitrogen metabolism in plants. Journal of Experimental Botany 62, 1439-1453.
58. Kusano M, Jonsson P, Fukushima A, Gullberg J, Sjostrom M, Trygg J, Moritz T. 2011b. Metabolite signature during short-day induced growth cessation in Populus. Frontiers in Plant Science 2, 29.
59. Kusano M, Tabuchi M, Fukushima A et al. 2011c. Metabolomics data reveal a crucial role of cytosolic glutamine synthetase 1;1 in coordinating metabolic balance in rice. Plant Journal 66, 456-466.
60. Lee I, Ambaru B, Thakkar P, Marcotte EM, Rhee SY. 2010. Rational association of genes with traits using a genome-scale gene network for Arabidopsis thaliana. Nature Biotechnology 28, 149-156.
61. Lee I, Seo YS, Coltrane D, Hwang S, Oh T, Marcotte EM, Ronald PC. 2011. Genetic dissection of the biotic stress response using a genomescale gene network for rice. Proceedings of the National Academy of Sciences, USA 108, 18548-18553.
62. Lei Z, Huhman DV, Sumner LW. 2011. Mass spectrometry strategies in metabolomics. Journal of Biological Chemistry 286, 25435-25442.
63. Levin JZ, Yassour M, Adiconis X, Nusbaum C, Thompson DA, Friedman N, Gnirke A, Regev A. 2010. Comprehensive comparative analysis of strand-specific RNA sequencing methods. Nature Methods 7, 709-715.
64. Li J, Li X, Su H, Chen H, Galbraith DW. 2006. A framework of integrating gene relations from heterogeneous data sources: an experiment on Arabidopsis thaliana. Bioinformatics 22, 2037-2043.
65. Lohse M, Bolger AM, Nagel A, Fernie AR, Lunn JE, Stitt M, Usadel B. 2012. RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics. Nucleic Acids Research 40, W622-627.
66. Lv H. 2013. Mass spectrometry-based metabolomics towards understanding of gene functions with a diversity of biological contexts. Mass Spectrometry Reviews 32, 118-128.
67. Ma S, Gong Q, Bohnert HJ. 2007. An Arabidopsis gene network based on the graphical Gaussian model. Genome Research 17, 1614-1625.
68. Maere S, Heymans K, Kuiper M. 2005. BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks. Bioinformatics 21, 3448-3449.
69. Majewski J, Pastinen T. 2011. The study of eQTL variations by RNA-seq: from SNPs to phenotypes. Trends Genetics 27, 72-79.
70. Mao L, Van Hemert JL, Dash S, Dickerson JA. 2009. Arabidopsis gene co-expression network and its functional modules. BMC Bioinformatics 10, 346.
71. Marbach D, Costello JC, Kuffner R et al. 2012. Wisdom of crowds for robust gene network inference. Nature Methods 9, 796-804.
72. Marchive C, Roudier F, Castaings L, Brehaut V, Blondet E, Colot V, Meyer C, Krapp A. 2013. Nuclear retention of the transcription factor NLP7 orchestrates the early response to nitrate in plants. Nature Communications 4, 1713.
73. Margolin AA, Nemenman I, Basso K, Wiggins C, Stolovitzky G, Dalla Favera R, Califano A. 2006. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 7 Suppl 1, S7.
74. Marguerat S, Bahler J. 2010. RNA-seq: from technology to biology. Cell Molecular Life Science 67, 569-579.
75. Martin A, Lee J, Kichey T et al. 2006. Two cytosolic glutamine synthetase isoforms of maize are specifically involved in the control of grain production. Plant Cell 18, 3252-3274.
76. Masumoto C, Miyazawa S, Ohkawa H et al. 2010. Phosphoenolpyruvate carboxylase intrinsically located in the chloroplast of rice plays a crucial role in ammonium assimilation. Proceedings of the National Academy of Sciences, USA 107, 5226-5231.
77. Meyer PE, Kontos K, Laftte F, Bontempi G. 2007. Informationtheoretic inference of large transcriptional regulatory networks. EURASIP Journal on Bioinformatics and Systems Biology, 79879.
78. Miller AJ, Fan X, Orsel M, Smith SJ, Wells DM. 2007. Nitrate transport and signalling. Journal of Experimental Botany 58, 2297-2306.
79. Miller AJ, Fan X, Shen Q, Smith SJ. 2008. Amino acids and nitrate as signals for the regulation of nitrogen acquisition. Journal of Experimental Botany 59, 111-119.
80. Nakano K, Suzuki T, Hayakawa T, Yamaya T. 2000. Organ and cellular localization of asparagine synthetase in rice plants. Plant Cell Physiology 41, 874-880.
81. Nariai N, Tamada Y, Imoto S, Miyano S. 2005. Estimating gene regulatory networks and protein-protein interactions of Saccharomyces cerevisiae from multiple genome-wide data. Bioinformatics 21 Suppl 2, ii206-212.
82. Olsen JE, Junttila O, Nilsen J, Eriksson ME, Martinussen I, Olsson O, Sandberg G, Moritz T. 1997. Ectopic expression of oat phytochrome A in hybrid aspen changes critical daylength for growth and prevents cold acclimatization. Plant Journal 12, 1339-1350.
83. Opgen-Rhein R, Strimmer K. 2007. Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregressive process. BMC Bioinformatics 8 Suppl 2, S3.
84. Osorio S, Vallarino JG, Szecowka M, Ufaz S, Tzin V, Angelovici R, Galili G, Fernie AR. 2013. Alteration of the interconversion of pyruvate and malate in the plastid or cytosol of ripening tomato fruit invokes diverse consequences on sugar but similar effects on cellular organic acid, metabolism, and transitory starch accumulation. Plant Physiology 161, 628-643.
85. Perez-Delgado CM, Garcia-Calderon M, Sanchez DH, Udvardi MK, Kopka J, Marquez AJ, Betti M. 2013. Transcriptomic and metabolic changes associated with photorespiratory ammonium accumulation in the model legume Lotus japonicus. Plant Physiology 162, 1834-1848.
86. Phinney KW, Ballihaut G, Bedner M et al. 2013. Development of a Standard Reference Material for metabolomics research. Analytical Chemistry 85, 11732-11738.
87. Provart N. 2012. Correlation networks visualization. Frontiers in Plant Science 3, 240.
88. Rao SR, Ford KL, Cassin AM, Roessner U, Patterson JH, Bacic A. 2010. Proteomic and metabolic profling of rice suspension culture cells as a model to study abscisic acid signaling response pathways in plants. Journal of Proteome Research 9, 6623-6634.
89. Reich M, Liefield T, Gould J, Lerner J, Tamayo P, Mesirov JP. 2006. GenePattern 2.0. Nature Genetics 38, 500-501.
90. Reshef DN, Reshef YA, Finucane HK, Grossman SR, McVean G, Turnbaugh PJ, Lander ES, Mitzenmacher M, Sabeti PC. 2011. Detecting novel associations in large data sets. Science 334, 1518-1524.
91. Rhee SY, Mutwil M. 2014. Towards revealing the functions of all genes in plants. Trends in Plant Science 19, 212-221.
92. Saito K, Hirai MY, Yonekura-Sakakibara K. 2008. Decoding genes with coexpression networks and metabolomics-'majority report by precogs'. Trends in Plant Science 13, 36-43.
93. Saito K, Matsuda F. 2010. Metabolomics for functional genomics, systems biology, and biotechnology. Annual Review of Plant Biology 61, 463-489.
94. Sato S, Yanagisawa S. 2014. Characterization of metabolic states of Arabidopsis thaliana under diverse carbon and nitrogen nutrient conditions via targeted metabolomic analysis. Plant Cell Physiology 55, 306-319.
95. Scalbert A, Andres-Lacueva C, Arita M, Kroon P, Manach C, Urpi-Sarda M, Wishart D. 2011. Databases on food phytochemicals and their health-promoting effects. Journal of Agricultural and Food Chemistry 59, 4331-4348.
96. Scheible WR, Lauerer M, Schulze ED, Caboche M, Stitt M. 1997. Accumulation of nitrate in the shoot acts as a signal to regulate shoot-root allocation in tobacco. Plant Journal 11, 671-691.
97. Schluter U, Colmsee C, Scholz U, Brautigam A, Weber AP, Zellerhoff N, Bucher M, Fahnenstich H, Sonnewald U. 2013. Adaptation of maize source leaf metabolism to stress related disturbances in carbon, nitrogen and phosphorus balance. BMC Genomics 14, 442.
98. Schluter U, Mascher M, Colmsee C, Scholz U, Brautigam A, Fahnenstich H, Sonnewald U. 2012. Maize source leaf adaptation to nitrogen deficiency affects not only nitrogen and carbon metabolism but also control of phosphate homeostasis. Plant Physiology 160, 1384-1406.
99. Simon-Manso Y, Lowenthal MS, Kilpatrick LE et al. 2013. Metabolite profling of a NIST Standard Reference Material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources. Analytical Chemistry 85, 11725-11731.
100. Steuer R, Kurths J, Daub CO, Weise J, Selbig J. 2002. The mutual information: detecting and evaluating dependencies between variables. Bioinformatics 18 Suppl 2, S231-240.
101. Stitt M. 2013. Systems-integration of plant metabolism: means, motive and opportunity. Current Opinion in Plant Biology 16, 381-388.
102. Stitt M, Muller C, Matt P, Gibon Y, Carillo P, Morcuende R, Scheible WR, Krapp A. 2002. Steps towards an integrated view of nitrogen metabolism. Journal of Experimental Botany 53, 959-970.
103. Sugimoto M, Kawakami M, Robert M, Soga T, Tomita M. 2012. Bioinformatics tools for mass spectroscopy-based metabolomic data processing and analysis. Current Bioinformatics 7, 96-108.
104. Sulpice R, Flis A, Ivakov AA et al. 2014. Arabidopsis coordinates the diurnal regulation of carbon allocation and growth across a wide range of photoperiods. Molecular Plant 7, 137-155.
105. Sulpice R, Nikoloski Z, Tschoep H et al. 2013. Impact of the carbon and nitrogen supply on relationships and connectivity between metabolism and biomass in a broad panel of Arabidopsis accessions. Plant Physiology 162, 347-363.
106. Suzuki M, Kusano M, Takahashi H et al. 2010. Rice-Arabidopsis FOX line screening with FT-NIR-based fingerprinting for GC-TOF/MS-based metabolite profling. Metabolomics 6, 137-145.
107. Sweetlove LJ, Obata T, Fernie AR. 2014. Systems analysis of metabolic phenotypes: what have we learnt? Trends in Plant Science 19, 222-230.
108. Tabuchi M, Abiko T, Yamaya T. 2007. Assimilation of ammonium ions and reutilization of nitrogen in rice (Oryza sativa L.). Journal of Experimental Botany 58, 2319-2327.
109. Thum KE, Shin MJ, Gutierrez RA, Mukherjee I, Katari MS, Nero D, Shasha D, Coruzzi GM. 2008. An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis. BMC Systems Biology 2, 31.
110. Tohge T, Fernie AR. 2012. Co-expression and co-responses: within and beyond transcription. Frontiers in Plant Science 3, 248.
111. Toubiana D, Fernie AR, Nikoloski Z, Fait A. 2013. Network analysis: tackling complex data to study plant metabolism. Trends in Biotechnology 31, 29-36.
112. Trapnell C, Roberts A, Goff L et al. 2012. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cuffinks. Nature Protocols 7, 562-578.
113. Tschoep H, Gibon Y, Carillo P, Armengaud P, Szecowka M, Nunes-Nesi A, Fernie AR, Koehl K, Stitt M. 2009. Adjustment of growth and central metabolism to a mild but sustained nitrogen-limitation in Arabidopsis. Plant, Cell and Environment 32, 300-318.
114. Usadel B, Blasing OE, Gibon Y et al. 2008. Multilevel genomic analysis of the response of transcripts, enzyme activities and metabolites in Arabidopsis rosettes to a progressive decrease of temperature in the nonfreezing range. Plant, Cell and Environment 31, 518-547.
115. Usadel B, Obayashi T, Mutwil M et al. 2009. Co-expression tools for plant biology: opportunities for hypothesis generation and caveats. Plant, Cell and Environment 32, 1633-1651.
116. Vidal EA, Moyano TC, Krouk G, Katari MS, Tanurdzic M, McCombie WR, Coruzzi GM, Gutierrez RA. 2013. Integrated RNA-seq and sRNA-seq analysis identifies novel nitrate-responsive genes in Arabidopsis thaliana roots. BMC Genomics 14, 701.
117. Vu HS, Tamura P, Galeva NA, Chaturvedi R, Roth MR, Williams TD, Wang XM, Shah J, Welti R. 2012. Direct infusion mass spectrometry of oxylipin-containing Arabidopsis membrane lipids reveals varied patterns in different stress responses. Plant Physiology 158, 324-339.
118. Wan Y, Shewry PR, Hawkesford MJ. 2013. A novel family of gamma-gliadin genes are highly regulated by nitrogen supply in developing wheat grain. Journal of Experimental Botany 64, 161-168.
119. 4 plants based on metabolic network analysis. BMC Systems Biology 6 Suppl 2, S9.
120. Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Bryant SH. 2009a. PubChem: a public information system for analyzing bioactivities of small molecules. Nucleic Acids Research 37, W623-633.
121. Wang Z, Gerstein M, Snyder M. 2009b. RNA-Seq: a revolutionary tool for transcriptomics. Nature Review Genetics 10, 57-63.
122. Wei H, Yordanov YS, Georgieva T, Li X, Busov V. 2013. Nitrogen deprivation promotes Populus root growth through global transcriptome reprogramming and activation of hierarchical genetic networks. New Phytologist 200, 483-497.
123. Werhli AV, Grzegorczyk M, Husmeier D. 2006. Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical gaussian models and bayesian networks. Bioinformatics 22, 2523-2531.
124. Wille A, Zimmermann P, Vranova E et al. 2004. Sparse graphical Gaussian modeling of the isoprenoid gene network in Arabidopsis thaliana. Genome Biology 5, R92.
125. Ye H, Gemperline E, Venkateshwaran M, Chen R, Delaux PM, Howes-Podoll M, Ane JM, Li L. 2013. MALDI mass spectrometryassisted molecular imaging of metabolites during nitrogen fixation in the Medicago truncatula-Sinorhizobium meliloti symbiosis. Plant Journal 75, 130-145.
126. Yonekura-Sakakibara K, Fukushima A, Saito K. 2013. Transcriptome data modeling for targeted plant metabolic engineering. Current Opinion in Biotechnology 24, 285-290.