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Advancement in Sustainable Agriculture: Computational and Bioinformatics Tools

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Abstract

Sustainable agricultural production is an urgent issue in response to global climate change and population increase. Furthermore, recent increased demand for biofuel crops has created a new market for agricultural commodities. One potential solution is to increase plant yield by designing plants based on a molecular understanding of gene function and on the regulatory networks involved in stress tolerance, development and growth. Recent progress in plant genomics has allowed us to discover and isolate important genes and to analyze functions that regulate yields and tolerance to environmental stress.

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References

  • Abdallah, C., Dumas-Gaudot, E., Renaut, J., & Sergeant, K. (2012). Gel-based and gel-free quantitative proteomics approaches at a glance. International Journal of Plant Genomics, 2012, 494572. https://doi.org/10.1155/2012/494572.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Achnine, L., Huhman, D. V., Farag, M. A., Sumner, L. W., Blount, J. W., & Dixon, R. A. (2005). Genomics-based selection and functional characterization of triterpene glycosyltransferases from the model legume Medicago truncatula. The Plant Journal, 41, 875–887.

    Article  CAS  PubMed  Google Scholar 

  • Adams, M. D., Soares, M. B., Kerlavage, A. R., Fields, C., & Venter, J. C. (1993). Rapid cDNA sequencing (expressed sequence tags) from a directionally cloned human infant brain cDNA library. Nature Genetics, 4, 373–380.

    Article  CAS  PubMed  Google Scholar 

  • Aharoni, A., & Brandizzi, F. (2012). High-resolution measurements in plant biology. The Plant Journal, 70, 1–4.

    Article  CAS  PubMed  Google Scholar 

  • Alfarano, C., Andrade, C. E., Anthony, K., Bahroos, N., Bajec, M., et al. (2005). The biomolecular interaction network database and related tools 2005 update. Nucleic Acids Research, 33, D418–D424.

    Article  CAS  PubMed  Google Scholar 

  • Allen, J. E., Pertea, M., & Salzberg, S. L. (2004). Computational gene prediction using multiple sources of evidence. Genome Research, 14, 142–148.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Alonso, R., Salavert, F., Garcia-Garcia, F., Carbonell-Caballero, J., Bleda, M., et al. (2015). Babelomics 5.0: Functional interpretation for new generations of genomic data. Nucleic Acids Research, 43, W1): 117–W1): 121.

    Article  CAS  Google Scholar 

  • Alseekh, S., Tohge, T., Wendenberg, R., Scossa, F., Omranian, N., Li, J., Kleessen, S., Giavalisco, P., Pleban, T., Mueller-Roeber, B., et al. (2015). Identification and mode of inheritance of quantitative trait loci for secondary metabolite abundance in tomato. Plant Cell, 27, 485–512.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Al-Shahrour, F., Minguez, P., Tarraga, J., et al. (2006). BABELOMICS: A systems biology perspective in the functional annotation of genome-scale experiments. Nucleic Acids Research, 34, W472–W476.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Altenbach, S. B., Vensel, W. H., & DuPont, F. M. (2010). Integration of transcriptomic and proteomic data from a single wheat cultivar provides new tools for understanding the roles of individual alpha gliadin proteins in flour quality and celiac disease. Journal of Cereal Science, 52, 143–151.

    Article  CAS  Google Scholar 

  • Anderson, D. C., Campbell, E. L., & Meeks, J. C. (2006). A soluble 3D LC/MS/MS proteome of the filamentous cyanobacterium Nostoc punctiforme. Journal of Proteome Research, 5, 3096–3104.

    Article  CAS  PubMed  Google Scholar 

  • Andrade, A. E., Silva, L. P., Pereira, J. L., Noronha, E. F., Reis, F. B., Jr., Bloch, C., Jr., et al. (2008). In vivo proteome analysis of Xanthomonas campestris pv. Campestris in the interaction with the host plant Brassica oleracea. FEMS Microbiology Letters, 281, 167–174.

    Article  CAS  PubMed  Google Scholar 

  • Anisimov, S. V. (2008). Serial analysis of gene expression (SAGE): 13 years of application in research. Current Pharmaceutical Biotechnology, 9, 338–350.

    Article  CAS  PubMed  Google Scholar 

  • Ansorge, W. J. (2009). Next-generation DNA sequencing techniques. Nature Biotechnology, 25, 195–203.

    CAS  Google Scholar 

  • Aoki, K., Yano, K., Suzuki, A., Kawamura, S., Sakurai, N., Sud, K., et al. (2010). Large-scale analysis of full-length cDNAs from the tomato (Solanum lycopersicum) cultivar Micro-Tom, a reference system for the Solanaceae genomics. BMC Genomics, 11, 210.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Arabidopsis Interactome Mapping Consortium. (2011). Evidence for network evolution in an Arabidopsis interactome map. Science, 333, 601–607.

    Article  PubMed Central  CAS  Google Scholar 

  • Aranda, B., Achuthan, P., Alam-Faruque, Y., Armean, I., Bridge, A., Derow, C., et al. (2010). The IntAct molecular interaction database in 2010. Nucleic Acids Research, 38, D525–D531.

    Article  CAS  PubMed  Google Scholar 

  • Araújo, W. L., Ishizaki, K., Nunes-Nesi, A., Larson, T. R., Tohge, T., Krahnert, I., Witt, S., Obata, T., Schauer, N., Graham, I. A., et al. (2010). Identification of the 2-hydroxyglutarate and isovaleryl-CoA dehydrogenases as alternative electron donors linking lysine catabolism to the electron transport chain of Arabidopsis mitochondria. Plant Cell, 22, 1549–1563.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Ashburner, M., Ball, C., Blake, J., Botstein, D., Butler, H., et al. (2000). Gene ontology: Tool for the unification of biology. The gene ontology consortium. Nature Genetics, 25, 25–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Assmann, S. M., & Albert, R. (2009). Discrete dynamic modeling with asynchronous update, or how to model complex systems in the absence of quantitative information. Methods in Molecular Biology, 553, 207–225.

    Article  CAS  PubMed  Google Scholar 

  • Avraham, S., Tung, C. W., Ilic, K., et al. (2008). The plant ontology database: A community resource for plant structure and developmental stages controlled vocabulary and annotations. Nucleic Acids Research, 36(1), D449–D454.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Babu, M. M., Luscombe, N. M., Aravind, L., et al. (2004). Structure and evolution of transcriptional regulatory networks. Current Opinion in Structural Biology, 14(3), 283–291.

    Article  CAS  PubMed  Google Scholar 

  • Bagnarol, E., Popovici, J., Alloisio, N., Marechal, J., Pujic, P., Normand, P., et al. (2007). Differential Frankia protein patterns induced by phenolic extracts from Myricaceae seeds. Physiologia Plantarum, 130, 380–390.

    Article  CAS  Google Scholar 

  • Barabasi, A. L., & Oltvai, Z. N. (2004). Network biology: Understanding the cell’s functional organization. Nature Reviews Genetics, 5, 101–115.

    Article  CAS  PubMed  Google Scholar 

  • Barakat, A., Wall, P. K., Diloreto, S., Depamphilis, C. W., & Carlson, J. E. (2007). Conservation and divergence of microRNAs in Populus. BMC Genomics, 8, 481.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Bard, J. B., & Rhee, S. Y. (2004). Ontologies in biology: Design, applications and future challenges. Nature Reviews. Genetics, 5, 213–222.

    Article  CAS  PubMed  Google Scholar 

  • Bard, J., Rhee, S. Y., & Ashburner, M. (2005). An ontology for cell types. Genome Biology, 6, R21.

    Article  PubMed  PubMed Central  Google Scholar 

  • Barrett, T., Troup, D. B., Wilhite, S. E., Ledoux, P., Rudnev, D., Evangelista, C., et al. (2009). NCBI GEO: Archive for high-throughput functional genomic data. Nucleic Acids Research, 37, D885–D890.

    Article  CAS  PubMed  Google Scholar 

  • Baum, B., & Craig, G. (2004). RNAi in a postmodern, postgenomic era. Oncogene, 23(51), 8336–8339.

    Article  CAS  PubMed  Google Scholar 

  • Bedell, J. A., Budiman, M. A., Nunberg, A., Citek, R. W., Robbins, D., et al. (2005). Sorghum genome sequencing by methylation filtration. PLoS Biology, 3, e13.

    Article  PubMed  PubMed Central  Google Scholar 

  • Benedict, C., Geisler, M., Trygg, J., et al. (2006). Consensus by democracy. Using meta-analyses of microarray and genomic data to model the cold acclimation signaling pathway in Arabidopsis. Plant Physiology, 141(4), 1219–1232.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Benedito, V. A., Torres-Jerez, I., Murray, J. D., Andriankaja, A., Allen, S., Kakar, K., et al. (2008). A gene expression atlas of the model legume Medicago truncatula. The Plant Journal, 55, 504–513.

    Article  CAS  PubMed  Google Scholar 

  • Bernardo, A. N., Bradbury, P. J., Ma, H., Hu, S., Bowden, R. L., Buckler, E. S., et al. (2009). Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays. BMC Genomics, 10, 251.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Berners-Lee, T., Hendler, J., & Lassila, O. (2001). The semantic web. Scientific American, 284, 34–43.

    Article  Google Scholar 

  • Bevan, M. (1997). Objective: The complete sequence of a plant genome. Plant Cell, 9, 476–478.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Bhalla, R., Narasimhan, K., & Swarup, S. (2005). Metabolomics and its role in understanding cellular responses in plants. Plant Cell Reports, 24, 562–571. https://doi.org/10.1007/s00299-005-0054-9.

    Article  CAS  PubMed  Google Scholar 

  • Bino, R. J., Hall, R. D., Fiehn, O., Kopka, J., Saito, K., Draper, J., Nikolau, B. J., Mendes, P., Roessner-Tunali, U., Beale, M. H., Trethewey, R. N., Lange, B. M., Wurtele, E. S., & Sumner, L. W. (2004). Potential of metabolomics as a functional genomics tool. Trends in Plant Science, 9, 418–425.

    Article  CAS  PubMed  Google Scholar 

  • Blais, A., & Dynlacht, B. D. (2005). Constructing transcriptional regulatory networks. Genes & Development, 19(13), 1499–1511.

    Article  CAS  Google Scholar 

  • Blake-Kalff, M. M. A., Harrison, K. R., Hawkesford, M. J., Zhao, F. J., & McGrath, S. P. (1998). Distribution of sulfur within oilseed rape leaves in response to sulfur deficiency during vegetative growth. Plant Physiology, 118, 1337–1344.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Blakes, J., Twycross, J., Romero, F. J., et al. (2011). The Infobiotics Workbench: An integrated in silico modelling platform for systems and synthetic biology. Bioinformatics, 27(23), 3323–3324.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Blaschke, C., Krallinger, M., Leon, E., & Valencia, A. (2005). Evaluation of biocreative assessment of task 2. BMC Bioinformatics, 6, S16.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Blazej, R. G., Paegel, B. M., & Mathies, R. A. (2003). Polymorphism ratio sequencing: A new approach for single nucleotide polymorphism discovery and genotyping. Genome Research, 13, 287–293.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Blazejczyk, M., Miron, M., & Nadon, R. (2007). FlexArray: A statistical data analysis software for gene expression microarrays. Genome Quebec. Montreal, 39, 1208–1216.

    Google Scholar 

  • Boguski, M. S., & Schuler, G. D. (1995). ESTablishing a human transcript map. Nature Genetics, 10, 369–371.

    Article  CAS  PubMed  Google Scholar 

  • Boguski, M. S., Lowe, T. M., & Tolstoshev, C. M. (1993). dbEST—Database for ‘expressed sequence tags’. Nature Genetics, 4, 332–333.

    Article  CAS  PubMed  Google Scholar 

  • Bolger, A., Scossa, F., Bolger, M. E., Lanz, C., Maumus, F., Tohge, T., Quesneville, H., Alseekh, S., Sørensen, I., Lichtenstein, G., et al. (2014). The genome of the stress-tolerant wild tomato species Solanum pennellii. Nature Genetics, 46, 1034–1038.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Boone, C., Bussey, H., & Andrews, B. J. (2007). Exploring genetic interactions and networks with yeast. Nature Reviews Genetics, 8(6), 437–449.

    Article  CAS  PubMed  Google Scholar 

  • Brady, S. M., & Provart, N. J. (2009). Web-queryable large-scale data sets for hypothesis generation in plant biology. Plant Cell, 21, 1034–1051.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brady, S. M., Orlando, D. A., Lee, J. Y., Wang, J. Y., Koch, J., Dinneny, J. R., et al. (2007). A high-resolution root spatiotemporal map reveals dominant expression patterns. Science, 318, 801–806.

    Article  CAS  PubMed  Google Scholar 

  • Breitkreutz, B. J., Stark, C., & Tyers, M. (2003). Osprey: A network visualization system. Genome Biology, 4(3), R22.

    Article  PubMed  PubMed Central  Google Scholar 

  • Brendel, V., & Zhu, W. (2002). Computational modeling of gene structure in Arabidopsis thaliana. Plant Molecular Biology, 48, 49–58.

    Article  CAS  PubMed  Google Scholar 

  • Brenner, S., Johnson, M., Bridgham, J., Golda, G., Lloyd, D. H., Johnson, D., et al. (2000). Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nature Biotechnology, 18, 630–634.

    Article  CAS  PubMed  Google Scholar 

  • Brkljacic, J., Grotewold, E., Scholl, R., Mockler, T., Garvin, D. F., Vain, P., et al. (2011). Brachypodium as a model for the grasses: Today and the future. Plant Physiology, 157, 3–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Brown, J. R., & Sanseau, P. (2005). A computational view of microRNAs and their targets. Drug Discovery Today, 10, 595–601.

    Article  CAS  PubMed  Google Scholar 

  • Buck, M. J., & Lieb, J. D. (2004). ChIP-chip: Considerations for the design, analysis, and application of genome-wide chromatin immunoprecipitation experiments. Genomics, 83, 349–360.

    Article  CAS  PubMed  Google Scholar 

  • Buttner, D., & Bonas, U. (2002). Getting across bacterial type III effector proteins on their way to the plant cell. The EMBO Journal, 21, 5313–5322.

    Article  PubMed  PubMed Central  Google Scholar 

  • Caicedo, A. L., Williamson, S. H., Hernandez, R. D., Boyko, A., Fledel-Alon, A., York, T. L., et al. (2007). Genome-wide patterns of nucleotide polymorphism in domesticated rice. PLoS Genetics, 3, 1745–1756.

    Article  CAS  PubMed  Google Scholar 

  • Calla, B., Vuong, T., Radwan, O., Hartman, G. L., & Clough, S. J. (2009). Gene expression profiling soybean stem tissue early response to Sclerotinia sclerotiorum and in silico mapping in relation to resistance markers. The Plant Genome Journal, 2(2), 149–166.

    Article  CAS  Google Scholar 

  • Carollo, V., Matthews, D. E., Lazo, G. R., Blake, T. K., Hummel, D. D., Lui, N., et al. (2005). GrainGenes 2.0. An improved resource for the small-grains community. Plant Physiology, 139, 643–651.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Carrari, F., Baxter, C., Usadel, B., Urbanczyk-Wochniak, E., Zanor, M. I., NunesNesi, A., Nikiforova, V., Centero, D., Ratzka, A., Pauly, M., et al. (2006). Integrated analysis of metabolite and transcript levels reveals the metabolic shifts that underlie tomato fruit development and highlight regulatory aspects of metabolic network behavior. Plant Physiology, 142, 1380–1396.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Casati, P., Campi, M., Morrow, D. J., Fernandes, J. F., & Walbot, V. (2011). Transcriptomic, proteomic and metabolomic analysis of UV-B signaling in maize. BMC Genomics, 12, 321.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Caspi, R., Altman, T., Dale, J. M., et al. (2010). The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Research, 38(1), D473–D479.

    Article  CAS  PubMed  Google Scholar 

  • Chatziioannou, A., Moulos, P., & Kolisis, F. N. (2009). Gene ARMADA: An integrated multi-analysis platform for microarray data implemented in MATLAB. BMC Bioinformatics, 10(1), 354.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Chellappan, P., & Jin, H. (2009). Discovery of plant microRNAs and short-interfering RNAs by deep parallel sequencing. Methods in Molecular Biology, 495, 121–132.

    Article  CAS  PubMed  Google Scholar 

  • Chen, T., Kao, M. Y., Tepel, M., Rush, J., & Church, G. M. (2001). A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry. Journal of Computational Biology, 8, 325–337.

    Article  CAS  PubMed  Google Scholar 

  • Chisholm, S. T., Coaker, G., Day, B., & Staskawicz, B. J. (2006). Host microbe interactions: Shaping the evolution of the plant immune response. Cell, 124, 803–814.

    Article  CAS  PubMed  Google Scholar 

  • Chodavarapu, R. K., Feng, S., Bernatavichute, Y. V., Chen, P. Y., Stroud, H., Yu, Y., et al. (2010). Relationship between nucleosome positioning and DNA methylation. Nature, 466, 388–392.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Choi, H., & Pavelka, N. (2011). When one and one gives more than two: Challenges and opportunities of integrative omics. Frontiers in Genetics, 2, 105.

    Article  PubMed  Google Scholar 

  • Close, T. J., Bhat, P. R., Lonardi, S., Wu, Y., Rostoks, N., Ramsay, L., et al. (2009). Development and implementation of high-throughput SNP genotyping in barley. BMC Genomics, 10, 582. https://doi.org/10.1186/1471-2164-10-582.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Coen, E. S., & Meyerowitz, E. M. (1991). The war of the whorls: Genetic interactions controlling flower development. Nature, 353(6339), 31–37.

    Article  CAS  PubMed  Google Scholar 

  • Cohen, A. M., & Hersh, W. R. (2005). A survey of current work in biomedical text mining. Briefings in Bioinformatics, 6, 57–71.

    Article  CAS  PubMed  Google Scholar 

  • Cokus, S. J., Feng, S., Zhang, X., Chen, Z., Merriman, B., Haudenschild, C. D., et al. (2008). Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature, 452, 215–219.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Cope, L. M., Irizarry, R. A., Jaffee, H. A., Wu, Z., & Speed, T. P. (2004). A benchmark for Affymetrix GeneChip expression measures. Bioinformatics, 20, 323–331.

    Article  CAS  PubMed  Google Scholar 

  • Dalby, P. A. (2003). Optimising enzyme function by directed evolution. Current Opinion in Structural Biology, 13, 500–505.

    Article  CAS  PubMed  Google Scholar 

  • Dam, S., Laursen, B. S., Ornfelt, J. H., Jochimsen, B., Staerfeldt, H. H., Friis, C., et al. (2009). The proteome of seed development in the model legume Lotus japonicus. Plant Physiology, 149, 1325–1340.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Dancik, V., Addona, T. A., Clauser, K. R., Vath, J. E., & Pevzner, P. A. (1999). De novo peptide sequencing via tandem mass spectrometry. Journal of Computational Biology, 6, 327–342.

    Article  CAS  PubMed  Google Scholar 

  • Davies, P. J. (Ed.). (2004). Plant hormones: Biosynthesis, signal transduction, action. Dordrecht: Kluwer Academic Publishers.

    Google Scholar 

  • De Bodt, S., Maere, S., & Van de Peer, Y. (2005). Genome duplication and the origin of angiosperms. Trends in Ecology & Evolution, 20, 591–597.

    Article  Google Scholar 

  • de Folter, S., Immink, R. G., Kieffer, M., et al. (2005). Comprehensive interaction map of the Arabidopsis MADS box transcription factors. Plant Cell, 17(5), 1424–1433.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • de Hoon, M., & Hayashizaki, Y. (2008). Deep cap analysis gene expression (CAGE): Genome-wide identifi cation of promoters, quantifi cation of their expression, and network inference. BioTechniques, 44, 627–628, 630, 632.

    Google Scholar 

  • De Keersmaecker, S. C., Thijs, I., Vanderleyden, J., et al. (2006). Integration of omics data: How well does it work for bacteria? Molecular Microbiology, 62(5), 1239–1250.

    Article  PubMed  CAS  Google Scholar 

  • Delker, C., Poschl, Y., Raschke, A., Ullrich, K., Ettingshausen, S., Hauptmann, V., et al. (2010). Natural variation of transcriptional auxin response networks in Arabidopsis thaliana. Plant Cell, 22, 2184–2200.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Delmotte, N., Ahrens, C. H., Knief, C., Qeli, E., Koch, M., Fischer, H.-M., et al. (2010). An integrated proteomics and transcriptomics reference data set provides new insights into the Bradyrhizobium japonicum bacteroid metabolism in soybean root nodules. Proteomics, 10, 1391–1400.

    Article  CAS  PubMed  Google Scholar 

  • Depuydt, S., & Hardtke, C. S. (2011). Hormone signalling crosstalk in plant growth regulation. Current Biology, 21, R365–R373.

    Article  CAS  PubMed  Google Scholar 

  • Dhar, P. K., Zhu, H., & Mishra, S. K. (2004). Computational approach to systems biology: From fraction to integration and beyond. IEEE Transactions on NanoBioscience, 3(3), 144–152.

    Article  PubMed  Google Scholar 

  • Di, X., Matsuzaki, H., Webster, T. A., Hubbell, E., Liu, G., et al. (2005). Dynamic model based algorithms for screening and genotyping over 100 K SNPs on oligonucleotide microarrays. Bioinformatics, 21, 1958–1963.

    Article  CAS  PubMed  Google Scholar 

  • Digman, M. A., Brown, C. M., Sengupta, P., Wiseman, P. W., Horwitz, A. R., & Gratton, E. (2005). Measuring fast dynamics in solutions and cells with a laser scanning microscope. Biophysical Journal, 89, 1317–1327.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ding, J., Viswanathan, K., Berleant, D., Hughes, L., Wurtele, E. S., et al. (2005). Using the biological taxonomy to access biological literature with PathBinderH. Bioinformatics, 21, 2560–2562.

    Article  CAS  PubMed  Google Scholar 

  • Donaldson, I., Martin, J., de Bruijn, B., Wolting, C., Lay, V., et al. (2003). PreBIND and Textomy—Mining the biomedical literature for protein-protein interactions using a support vector machine. BMC Bioinformatics, 4, 11.

    Article  PubMed  PubMed Central  Google Scholar 

  • Doolittle, W. F. (1999). Phylogenetic classification and the universal tree. Science, 284, 2124–2129.

    Article  CAS  PubMed  Google Scholar 

  • Drăghici, S. (2011). Statistics and data analysis for microarrays using R and bioconductor. Boca Raton: CRC Press.

    Google Scholar 

  • Driever, S. M., & Kromdijk, J. (2013). Will C3 crops enhanced with the C4 CO2- concentrating mechanism live up to their full potential (yield)? Journal of Experimental Botany, 64, 3925–3935. https://doi.org/10.1093/jxb/ert103.

    Article  CAS  PubMed  Google Scholar 

  • Duvick, J., Fu, A., Muppirala, U., Sabharwal, M., Wilkerson, M. D., Lawrence, C. J., et al. (2008). PlantGDB: A resource for comparative plant genomics. Nucleic Acids Research, 36, D959–D965.

    Article  CAS  PubMed  Google Scholar 

  • Edwards, J. S., & Palsson, B. O. (2000). The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities. Proceedings of the National Academy of Sciences of the United States of America, 97, 5528–5533.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Eilbeck, K., Lewis, S. E., Mungall, C. J., Yandell, M., Stein, L., et al. (2005). The sequence ontology: A tool for the unification of genome annotations. Genome Biology, 6, R44.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Eisen, M. B., Spellman, P. T., Brown, P. O., & Botstein, D. (1998). Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences of the United States of America, 95, 14863–14868.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Emmert-Buck, M. R., Bonner, R. F., Smith, P. D., Chuaqui, R. F., Zhuang, Z., et al. (1996). Laser capture microdissection. Science, 274, 998–1001.

    Article  CAS  PubMed  Google Scholar 

  • Enfissi, E. M., Barneche, F., Ahmed, I., Lichtle, C., Gerrish, C., McQuinn, R. P., et al. (2010). Integrative transcript and metabolite analysis of nutritionally enhanced DE-ETIOLATED1 downregulated tomato fruit. Plant Cell, 22, 1190–1215.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fazzari, M. J., & Greally, J. M. (2004). Epigenomics: Beyond CpG islands. Nature Reviews Genetics, 5, 446–455.

    Article  CAS  PubMed  Google Scholar 

  • Feltus, F. A., Wan, J., Schulze, S. R., Estill, J. C., Jiang, N., & Paterson, A. H. (2004). An SNP resource for rice genetics and breeding based on subspecies indica and japonica genome alignments. Genome Research, 14, 1812–1819.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fiehn, O. (2001). Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comparative and Functional Genomics, 2, 155–168.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Forrester, J. W. (1958). Industrial dynamics: A major breakthrough for decision makers. Harvard Business Review, 36(4), 37–66.

    Google Scholar 

  • Forrester, J. W. (1961). Industrial dynamics. Portland: Productivity Press.

    Google Scholar 

  • Foster, I. (2002). What is the grid? A three point checklist. In GRIDToday (p. 4). Chicago: Argonne National Lab & University of Chicago.

    Google Scholar 

  • Fouracre, J. P., Ando, S., & Langdale, J. A. (2014). Cracking the Kranz enigma with systems biology. Journal of Experimental Botany, 65(13), 3327–3339. https://doi.org/10.1093/jxb/eru015.

    Article  PubMed  Google Scholar 

  • Fu, J., Keurentjes, J. J., Bouwmeester, H., America, T., Verstappen, F. W., Ward, J. L., et al. (2009). System-wide molecular evidence for phenotypic buffering in Arabidopsis. Nature Genetics, 41, 166–167.

    Article  CAS  PubMed  Google Scholar 

  • Fujimura, Y., Kurihara, K., Ida, M., Kosaka, R., Miura, D., Wariishi, H., et al. (2011). Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars. PLoS One, 6, e23426.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Fujita, M., Horiuchi, Y., Ueda, Y., Mizuta, Y., Kubo, T., Yano, K., et al. (2010). Rice expression atlas in reproductive development. Plant & Cell Physiology, 51, 2060–2081.

    Article  CAS  Google Scholar 

  • Fukuda, H., & Higashiyama, T. (2011). Diverse functions of plant peptides: Entering a new phase. Plant & Cell Physiology, 52, 1–4.

    Article  CAS  Google Scholar 

  • Fukuda, H., Hirakawa, Y., & Sawa, S. (2007). Peptide signaling in vascular development. Current Opinion in Plant Biology, 10, 477–482.

    Article  CAS  PubMed  Google Scholar 

  • Fukushima, A., Kanaya, S., & Nishida, K. (2014). Integrated network analysis and effective tools in plant systems biology. Frontiers in Plant Science, 5, 598.

    Article  PubMed  PubMed Central  Google Scholar 

  • Galindo González, L. M., El Kayal, W., Ju, C. J. T., et al. (2012). Integrated transcriptomic and proteomic profiling of white spruce stems during the transition from active growth to dormancy. Plant, Cell & Environment, 35(4), 682–701.

    Article  CAS  Google Scholar 

  • Garcia-Hernandez, M., Berardini, T. Z., Chen, G., Crist, D., Doyle, A., et al. (2002). TAIR: A resource for integrated Arabidopsis data. Functional & Integrative Genomics, 2, 239–253.

    Article  CAS  Google Scholar 

  • Garcia-Seco, D., Chiapello, M., Bracale, M., Pesce, C., Bagnaresi, P., et al. (2017). Transcriptome and proteome analysis reveal new insight into proximal and distal responses of wheat to foliar infection by Xanthomonas translucens. Scientific Reports, 7, 10157.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gechev, T. S., Benina, M., Obata, T., Tohge, T., Sujeeth, N., Minkov, I., Hille, J., Temanni, M. R., Marriott, A. S., Bergström, E., et al. (2013). Molecular mechanisms of desiccation tolerance in the resurrection glacial relic Haberlea rhodopensis. Cellular and Molecular Life Sciences, 70, 689–709.

    Article  CAS  PubMed  Google Scholar 

  • Gehlenborg, N., O’Donoghue, S. I., Baliga, N. S., et al. (2010). Visualization of omics data for systems biology. Nature Methods, 7, S56–S68.

    Article  CAS  PubMed  Google Scholar 

  • Gibbs, R. A., & Weinstock, G. M. (2003). Evolving methods for the assembly of large genomes. Cold Spring Harbor Symposia on Quantitative Biology, 68, 189–194.

    Article  CAS  PubMed  Google Scholar 

  • Glaubitz, U., Li, X., Schaedel, S., Erban, A., Sulpice, R., Kopka, J., et al. (2017). Integrated analysis of rice transcriptomic and metabolomic responses to elevated night temperatures identifies sensitivity-and tolerance-related profiles. Plant, Cell & Environment, 40(1), 121–137.

    Article  CAS  Google Scholar 

  • Glinski, M., & Weckwerth, W. (2006). The role of mass spectrometry in plant systems biology. Mass Spectrometry Reviews, 25, 173–214. https://doi.org/10.1002/mas.20063.

    Article  CAS  PubMed  Google Scholar 

  • Goda, H., Sasaki, E., Akiyama, K., Maruyama-Nakashita, A., Nakabayashi, K., Li, W., et al. (2008). The AtGenExpress hormone and chemical treatment data set: Experimental design, data evaluation, model. The Plant Journal, 55(3), 526–542.

    Article  CAS  PubMed  Google Scholar 

  • Goff, S. A., Ricke, D., Lan, T. H., Presting, G., Wang, R., Dunn, M., et al. (2002). A draft sequence of the rice genome (Oryza sativa L. ssp. japonica). Science, 296, 92–100.

    Article  CAS  PubMed  Google Scholar 

  • Gomez-Gomez, L., Felix, G., & Boller, T. (1999). A single locus determines sensitivity to bacterial flagellin in Arabidopsis thaliana. The Plant Journal, 18, 277–284. https://doi.org/10.1046/j.1365-313X.1999.00451.x.

    Article  CAS  PubMed  Google Scholar 

  • Gong, C. Y., & Wang, T. (2013). Proteomic evaluation of genetically modified crops: Current status and challenges. Frontiers in Plant Science, 4, 41. https://doi.org/10.3389/fpls.2013.00041.

    Article  PubMed  PubMed Central  Google Scholar 

  • Gonzalez, N., De Bodt, S., Sulpice, R., et al. (2010). Increased leaf size: Different means to an end. Plant Physiology, 153, 1261–1279.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gorg, A., Obermaier, C., Boguth, G., Harder, A., Scheibe, B., et al. (2000). The current state of two-dimensional electrophoresis with immobilized pH gradients. Electrophoresis, 21, 1037–1053.

    Article  CAS  PubMed  Google Scholar 

  • Gourion, B., Rossignol, M., & Vorholt, J. A. (2006). A proteomic study of Methylobacterium extorquens reveals a response regulator essential for epiphytic growth. Proceedings of the National Academy of Sciences of the United States of America, 103, 13186–13191.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Grant, D., Nelson, R. T., Cannon, S. B., & Shoemaker, R. C. (2010). SoyBase, the USDA-ARS soybean genetics and genomics database. Nucleic Acids Research, 38, D843–D846.

    Article  CAS  PubMed  Google Scholar 

  • Gras, R., & Muller, M. (2001). Computational aspects of protein identification by mass spectrometry. Current Opinion in Molecular Therapeutics, 3, 526–532.

    CAS  PubMed  Google Scholar 

  • Grimsrud, P. A., den Os, D., Wenger, C. D., Swaney, D. L., Schwartz, D., Sussman, M. R., et al. (2010). Large-scale phosphoprotein analysis in Medicago truncatula roots provides insight into in vivo kinase activity in legumes. Plant Physiology, 152, 19–28.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Gygi, S. P., Rochon, Y., Franza, B. R., et al. (1999). Correlation between protein and mRNA abundance in yeast. Molecular and Cellular Biology, 19, 1720–1730.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hannah, M. A., Caldana, C., Steinhauser, D., Balbo, I., Fernie, A. R., & Willmitzer, L. (2010). Combined transcript and metabolite profiling of Arabidopsis grown under widely variant growth conditions facilitates the identification of novel metabolite-mediated regulation of gene expression. Plant Physiology, 152, 2120–2129.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Harris, M. A., Clark, J., Ireland, A., Lomax, J., Ashburner, M., et al. (2004). The Gene Ontology (GO) database and informatics resource. Nucleic Acids Research, 32, D258–D261.

    Article  CAS  PubMed  Google Scholar 

  • He, D., & Yang, P. (2013). Proteomics of rice seed germination. Frontiers in Plant Science, 4, 246. https://doi.org/10.3389/fpls.2013.00246.

    Article  PubMed  PubMed Central  Google Scholar 

  • He, G., Zhu, X., Elling, A. A., Chen, L., Wang, X., Guo, L., et al. (2010). Global epigenetic and transcriptional trends among two rice subspecies and their reciprocal hybrids. Plant Cell, 22, 17–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • He, G., Elling, A. A., & Deng, X. W. (2011). The epigenome and plant development. Annual Review of Plant Biology, 62, 411–435.

    Article  CAS  PubMed  Google Scholar 

  • He, G., Chen, B., Wang, X., et al. (2013). Conservation and divergence of transcriptomic and epigenomic variation in maize hybrids. Genome Biology, 14(6), R57.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Heesacker, A., Kishore, V. K., Gao, W., Tang, S., Kolkman, J. M., Gingle, A., et al. (2008). SSRs and INDELs mined from the sunfl ower EST database: Abundance, polymorphisms, and cross-taxa utility. Theoretical and Applied Genetics, 117, 1021–1029.

    Article  CAS  PubMed  Google Scholar 

  • Heinrich, R., & Schuster, S. (1996). The regulation of cellular systems. New York: Chapman & Hall.

    Book  Google Scholar 

  • Heisler, M. G., Ohno, C., Das, P., Sieber, P., Reddy, G. V., et al. (2005). Patterns of auxin transport and gene expression during primordium development revealed by live imaging of the Arabidopsis inflorescence meristem. Current Biology, 15, 1899–1911.

    Article  CAS  PubMed  Google Scholar 

  • Helmy, M., Tomita, M., & Ishihama, Y. (2011). OryzaPG-DB: Rice proteome database based on shotgun proteogenomics. BMC Plant Biology, 11, 63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hirai, M. Y., Yano, M., Goodenowe, D. B., Kanaya, S., Kimura, T., Awazuhara, M., et al. (2004). Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana. Proceedings of the National Academy of Sciences of the United States of America, 101, 10205–10210.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hobo, T., Suwabe, K., Aya, K., Suzuki, G., Yano, K., Ishimizu, T., et al. (2008). Various spatiotemporal expression profiles of anther-expressed genes in rice. Plant & Cell Physiology, 49, 1417–1428.

    Article  CAS  Google Scholar 

  • Hoffmann, R., & Valencia, A. (2004). A gene network for navigating the literature. Nature Genetics, 36, 664.

    Article  CAS  PubMed  Google Scholar 

  • Hoops, S., Sahle, S., Gauges, R., et al. (2006). COPASI—A complex pathway simulator. Bioinformatics, 22(24), 3067–3074.

    Article  CAS  PubMed  Google Scholar 

  • Hori, K., Sato, K., & Takeda, K. (2007). Detection of seed dormancy QTL in multiple mapping populations derived from crosses involving novel barley germplasm. Theoretical and Applied Genetics, 115, 869–876.

    Article  PubMed  Google Scholar 

  • Huang, X., Feng, Q., Qian, Q., Zhao, Q., Wang, L., Wang, A., et al. (2009). High-throughput genotyping by whole-genome resequencing. Genome Research, 19, 1068–1076.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Hucka, M., Finney, A., Sauro, H. M., et al. (2003). The systems biology markup language (SBML): A medium for representation and exchange of biochemical network models. Bioinformatics, 19(4), 524–531.

    Article  CAS  PubMed  Google Scholar 

  • Hucka, M., Finney, A., Bornstein, B. J., Keating, S. M., Shapiro, B. E., et al. (2004). Evolving a lingua franca and associated software infrastructure for computational systems biology: The Systems Biology Markup Language (SBML) Project. Systematic Biology, 1, 41–53.

    Article  CAS  Google Scholar 

  • Hulsen, T., de Vlieg, J., & Groenen, P. M. (2006). PhyloPat: Phylogenetic pattern analysis of eukaryotic genes. BMC Bioinformatics, 7, 398.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Iijima, Y., Nakamura, Y., Ogata, Y., Tanaka, K., Sakurai, N., Suda, K., et al. (2008). Metabolite annotations based on the integration of mass spectral information. The Plant Journal, 54, 949–962.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ikeda, S., Okubo, T., Anda, M., Nakashita, H., Yasuda, M., Sato, S., et al. (2010). Community- and genome-based views of plant-associated bacteria: Plant–bacterial interactions in soybean and rice. Plant & Cell Physiology, 51, 1398–1410.

    Article  CAS  Google Scholar 

  • Inada, D. C., Bashir, A., Lee, C., Thomas, B. C., Ko, C., et al. (2003). Conserved noncoding sequences in the grasses. Genome Research, 13, 2030–2041.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • International Brachypodium Initiative. (2010). Genome sequencing and analysis of the model grass Brachypodium distachyon. Nature, 463, 763–768.

    Article  CAS  Google Scholar 

  • International Rice Genome Sequencing Project. (2005). The map-based sequence of the rice genome. Nature, 436, 793–800.

    Article  CAS  Google Scholar 

  • Itoh, T., Tanaka, T., Barrero, R. A., Yamasaki, C., Fujii, Y., Hilton, P. B., et al. (2007). Curated genome annotation of Oryza sativa ssp. Japonica and comparative genome analysis with Arabidopsis thaliana. Genome Research, 17, 175–183.

    Article  PubMed  PubMed Central  Google Scholar 

  • Izawa, T., Mihara, M., Suzuki, Y., Gupta, M., Itoh, H., Nagano, A. J., et al. (2011). Os-GIGANTEA confers robust diurnal rhythms on the global transcriptome of rice in the field. Plant Cell, 23, 1741–1755.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Jacobs, J. M., Babujee, L., Meng, F., Milling, A., & Allen, C. (2012). The in planta transcriptome of Ralstonia solanacearum: Conserved physiological and virulence strategies during bacterial wilt of tomato. MBio, 3, e00114–e00112.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Janeway, C. A., & Medzhitov, R. (2002). Innate immune recognition. Annual Review of Immunology, 20, 197–216.

    Article  CAS  PubMed  Google Scholar 

  • Jiang, N., Bao, Z., Zhang, X., Eddy, S. R., & Wessler, S. R. (2004). Pack-MULE transposable elements mediate gene evolution in plants. Nature, 431, 569–573.

    Article  CAS  PubMed  Google Scholar 

  • Jiao, Y., Lau, O. S., & Deng, X. W. (2007). Light-regulated transcriptional networks in higher plants. Nature Reviews Genetics, 8(3), 217–230.

    Article  CAS  PubMed  Google Scholar 

  • Jones, J. D., & Dangl, J. L. (2006). The plant immune system. Nature, 444, 323–329.

    Article  CAS  PubMed  Google Scholar 

  • Jorrín-Novo, J. V., Pascual, J., Sánchez-Lucas, R., Romero-Rodríguez, M. C., Rodríguez-Ortega, M. J., Lenz, C., et al. (2015). Fourteen years of plant proteomics reflected in proteomics: Moving from model species and 2DE−based approaches to orphan species and gel-free platforms. Proteomics, 15, 1089–1112. https://doi.org/10.1002/pmic.201400349.

    Article  CAS  PubMed  Google Scholar 

  • Joshi-Tope, G., Gillespie, M., Vastrik, I., et al. (2005). Reactome: A knowledgebase of biological pathways. Nucleic Acids Research, 33(1), D428–D432.

    CAS  PubMed  Google Scholar 

  • Joyce, A. R., & Palsson, B. O. (2006). The model organism as a system: Integrating ‘omics’ data sets. Nature Reviews. Molecular Cell Biology, 7, 198–210.

    Article  CAS  PubMed  Google Scholar 

  • Kanehisa, M., & Goto, S. (2000). KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28, 27–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kanehisa, M., Goto, S., Hattori, M., Aoki-Kinoshita, K. F., Itoh, M., Kawashima, S., Katayama, T., Araki, M., & Hirakawa, M. (2006). From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Research, 34, D354–D357.

    Article  CAS  PubMed  Google Scholar 

  • Kanehisa, M., Goto, S., Sato, Y., et al. (2012). KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Research, 40(D1), D109–D114.

    Article  CAS  PubMed  Google Scholar 

  • Kang, J. H., Gonzales-Vigil, E., Matsuba, Y., Pichersky, E., & Barry, C. S. (2014). Determination of residues responsible for substrate and product specificity of Solanum habrochaites short-chain cis-prenyltransferases. Plant Physiology, 164, 80–91.

    Article  CAS  PubMed  Google Scholar 

  • Kanno, Y., Jikumaru, Y., Hanada, A., Nambara, E., Abrams, S. R., Kamiya, Y., et al. (2010). Comprehensive hormone profiling in developing Arabidopsis seeds: Examination of the site of ABA biosynthesis, ABA transport and hormone interactions. Plant & Cell Physiology, 51, 1988–2001.

    Article  CAS  Google Scholar 

  • Karlin, S., & Altschul, S. F. (1990). Methods for assessing the statistical significance of molecular sequence features by using general scoring schemes. Proceedings of the National Academy of Sciences of the United States of America, 87, 2264–2268.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Katari, M. S., Nowicki, S. D., Aceituno, F. F., et al. (2010). VirtualPlant: A software platform to support systems biology research. Plant Physiology, 152(2), 500–515.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kawaguchi, M., & Minamisawa, K. (2010). Plant–microbe communications for symbiosis. Plant & Cell Physiology, 51(9), 1377–1380.

    Article  CAS  Google Scholar 

  • Kell, D. B., Brown, M., Davey, H. M., Dunn, W. B., Spasic, I., & Oliver, S. G. (2005). Metabolic footprinting and systems biology: The medium is the message. Nature Reviews. Microbiology, 3, 557–565.

    Article  CAS  PubMed  Google Scholar 

  • Keseler, I. M., Collado-vides, J., Gama-Castro, S., Ingraham, J., Paley, S., Paulsen, I. T., Peralta-Gil, M., & Karp, P. D. (2005). EcoCyc: A comprehensive database resource for Escherichia coli. Nucleic Acids Research, 33, D334–D337.

    Article  CAS  PubMed  Google Scholar 

  • Khatri, P., & Draghici, S. (2005). Ontological analysis of gene expression data: Current tools, limitations, and open problems. Bioinformatics, 21, 3587–3595.

    Article  CAS  PubMed  Google Scholar 

  • Khojasteh, M., Khahani, B., Taghavi, M., & Tvakol, E. (2017). Identification and characterization of responsive genes in rice during compatible interactions with pathogenic pathovars of Xanthomonas oryzae. European Journal of Plant Pathology, 151(1), 141–153.

    Google Scholar 

  • Kim, H. J., Baek, K. H., Lee, S. W., Kim, J., Lee, B. W., Cho, H. S., et al. (2008). Pepper EST database: Comprehensive in silico tool for analyzing the chili pepper (Capsicum annuum) transcriptome. BMC Plant Biology, 8, 101.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Kitano, H. (2002). Systems biology: A brief overview. Science, 295(5560), 1662–1664.

    Article  CAS  PubMed  Google Scholar 

  • Klamt, S., Stelling, J., Ginkel, M., & Gilles, E. D. (2003). FluxAnalyzer: Exploring structure, pathways, and flux distributions in metabolic networks on interactive flux maps. Bioinformatics, 19, 261–269.

    Article  CAS  PubMed  Google Scholar 

  • Koenig, D., Jiménez-Gómez, J. M., Kimura, S., Fulop, D., Chitwood, D. H., Headland, L. R., Kumar, R., Covington, M. F., Devisetty, U. K., Tat, A. V., et al. (2013). Comparative transcriptomics reveals patterns of selection in domesticated and wild tomato. Proceedings of the National Academy of Sciences of the United States of America, 110, E2655–E2662.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kogel, K. H., Voll, L. M., Schäfer, P., et al. (2010). Transcriptome and metabolome profiling of field-grown transgenic barley lack induced differences but show cultivar-specific variances. Proceedings of the National Academy of Sciences of the United States of America, 107(14), 6198–6203.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kojima, M., Kamada-Nobusada, T., Komatsu, H., Takei, K., Kuroha, T., Mizutani, M., et al. (2009). Highly sensitive and high-throughput analysis of plant hormones using MS-probe modification and liquid chromatography-tandem mass spectrometry: An application for hormone profiling in Oryza sativa. Plant & Cell Physiology, 50(7), 1201–1214.

    Article  CAS  Google Scholar 

  • Komatsu, S., Mock, H. P., Yang, P., & Svensson, B. (2013). Application of proteomics for improving crop protection/artificial regulation. Frontiers in Plant Science, 4, 522. https://doi.org/10.3389/fpls.2013.00522. Published 2013 Dec 19.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kondou, Y., Higuchi, M., Takahashi, S., Sakurai, T., Ichikawa, T., Kuroda, H., et al. (2009). Systematic approaches to using the FOX hunting system to identify useful rice genes. The Plant Journal, 57, 883–894.

    Article  CAS  PubMed  Google Scholar 

  • Kosová, K., Vítámvás, P., Prášil, I. T., & Renaut, J. (2011). Plant proteome changes under abiotic stress–contribution of proteomics studies to understanding plant stress response. Journal of Proteomics, 74, 1301–1322. https://doi.org/10.1016/j.jprot.2011.02.006.

    Article  CAS  PubMed  Google Scholar 

  • Kouchi, H., Imaizumi-Anraku, H., Hayashi, M., Hakoyama, T., Nakagawa, T., Umehara, Y., et al. (2010). How many peas in a pod? Legume genes responsible for mutualistic symbioses underground. Plant & Cell Physiology, 51, 1381–1397.

    Article  CAS  Google Scholar 

  • Krallinger, M., Rodriguez-Penagos, C., Tendulkar, A., et al. (2009). PLAN2L: A web tool for integrated text mining and literature-based bioentity relation extraction. Nucleic Acids Research, 37(2), W160–W165.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Krieger, C. J., Zhang, P., Mu¨ller, L. A., Wang, A., Paley, S., Arnaud, M., Pick, J., Rhee, S. Y., & Karp, P. D. (2004). MetaCyc: A multiorganism database of metabolic pathways and enzymes. Nucleic Acids Research, 32, D438–D442.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Kusano, M., Tohge, T., Fukushima, A., Kobayashi, M., Hayashi, N., Otsuki, H., et al. (2011). Metabolomics reveals comprehensive reprogramming involving two independent metabolic responses of Arabidopsis to UV-B light. The Plant Journal, 67, 354–369.

    Article  CAS  PubMed  Google Scholar 

  • Laakso, M., & Hautaniemi, S. (2010). Integrative platform to translate gene sets to networks. Bioinformatics, 26(14), 1802–1803.

    Article  CAS  PubMed  Google Scholar 

  • Langridge, P., & Fleury, D. (2011). Making the most of ‘omics’ for crop breeding. Trends in Biotechnology, 29, 33–40. https://doi.org/10.1016/j.tibtech.2010.09.006.

    Article  CAS  PubMed  Google Scholar 

  • Le Novere, N., Bornstein, B., Broicher, A., et al. (2006). BioModels database: A free, centralized database of curated, published, quantitative kinetic models of biochemical and cellular systems. Nucleic Acids Research, 34(1), D689–D691.

    Article  PubMed  CAS  Google Scholar 

  • Lee, S. W., Jeong, K. S., Han, S. W., Lee, S. E., Phee, B. K., Hahn, T. R., et al. (2008). The Xanthomonas oryzae pv. oryzae PhoPQ twocomponent system is required for AvrXA21 activity, hrpG expression, and virulence. Journal of Bacteriology, 190, 2183–2197.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lelandais-Briere, C., Naya, L., Sallet, E., Calenge, F., Frugier, F., Hartmann, C., et al. (2009). Genome-wide Medicago truncatula small RNA analysis revealed novel microRNAs and isoformsdifferentially regulated in roots and nodules. Plant Cell, 21, 780–2796.

    Article  Google Scholar 

  • Lewin, B. (2003). Genes VIII. Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Li, F., Kitashiba, H., Inaba, K., & Nishio, T. (2009). A Brassica rapa linkage map of EST-based SNP markers for identifi cation of candidategenes controlling fl owering time and leaf morphological traits. DNA Research, 16, 311–323.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Li, P., Zang, W., Li, Y., Xu, F., Wang, J., & Shi, T. (2011). AtPID: The overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis. Nucleic Acids Research, 39, D1130–D1133.

    Article  CAS  PubMed  Google Scholar 

  • Liang, C., Jaiswal, P., Hebbard, C., Avraham, S., Buckler, E. S., Casstevens, T., et al. (2008). Gramene: A growing plant comparative genomics resource. Nucleic Acids Research, 36, D947–D953.

    Article  CAS  PubMed  Google Scholar 

  • Libault, M., Farmer, A., Joshi, T., Takahashi, K., Langley, R. J., Franklin, L. D., et al. (2010). An integrated transcriptome atlas of the crop model Glycine max, and its use in comparative analyses in plants. The Plant Journal, 63, 86–99.

    CAS  PubMed  Google Scholar 

  • Lin, Q., Wang, C., Dong, W., Jiang, Q., Wang, D., Li, S., Chen, M., Liu, C., Sun, C., & Chen, K. (2015). Transcriptome and metabolome analyses of sugar and organic acid metabolism in ponkan (Citrus reticulata) fruit during fruit maturation. Gene, 554, 64–74.

    Article  CAS  PubMed  Google Scholar 

  • Lister, R., O’Malley, R. C., Tonti-Filippini, J., Gregory, B. D., Berry, C. C., Millar, A. H., et al. (2008). Highly integrated single-base resolution maps of the epigenome in Arabidopsis. Cell, 133, 523–536.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Liu, X., Noll, D. M., Lieb, J. D., & Clarke, N. D. (2005). DIP-chip: Rapid and accurate determination of DNA-binding specificity. Genome Research, 15, 421–427.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Lobell, D. B., Schlenker, W., & Costa-Roberts, J. (2011). Climate trends and global crop production since 1980. Science, 333, 616–620.

    Article  CAS  PubMed  Google Scholar 

  • Loew, L. M., & Schaff, J. C. (2001). The virtual cell: A software environment for computational cell biology. Trends in Biotechnology, 19(10), 401–406.

    Article  CAS  PubMed  Google Scholar 

  • Long, T. A., Brady, S. M., & Benfey, P. N. (2008). Systems approaches to identifying gene regulatory networks in plants. Annual Review of Cell and Developmental Biology, 24, 81–103.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Looger, L. L., Dwyer, M. A., Smith, J. J., & Hellinga, H. W. (2003). Computational design of receptor and sensor proteins with novel functions. Nature, 423, 185–190.

    Article  CAS  PubMed  Google Scholar 

  • Lord, P. W., Stevens, R. D., Brass, A., & Goble, C. A. (2003). Investigating semantic similarity measures across the Gene Ontology: The relationship between sequence and annotation. Bioinformatics, 19, 1275–1283.

    Article  CAS  PubMed  Google Scholar 

  • Luo, J. (2015). Metabolite-based genome-wide association studies in plants. Current Opinion in Plant Biology, 24, 31–38.

    Article  CAS  PubMed  Google Scholar 

  • Ma, J. F., Yamaji, N., Mitani, N., Tamai, K., Konishi, S., Fujiwara, T., et al. (2007). An effl ux transporter of silicon in rice. Nature, 448, 209–212.

    Article  CAS  PubMed  Google Scholar 

  • Ma, F., Jazmin, L. J., Young, J. D., & Allen, D. K. (2014). Isotopically nonstationary 13C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation. Proceedings of the National Academy of Sciences of the United States of America, 111, 16967–16972.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mace, E. S., Rami, J. F., Bouchet, S., Klein, P. E., Klein, R. R., Kilian, A., et al. (2009). A consensus genetic map of sorghum that integrates multiple component maps and high-throughput Diversity Array Technology (DArT) markers. BMC Plant Biology, 9, 13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Macho, A. P., Boutrot, F., Rathjen, J. P., & Zipfel, C. (2012). Asparate oxidase plays an important role in Arabidopsis stomatal immunity. Plant Physiology, 159, 1845–1856.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Makita, Y., Kobayashi, N., Mochizuki, Y., et al. (2009). PosMed-plus: An intelligent search engine that inferentially integrates crossspecies information resources for molecular breeding of plants. Plant & Cell Physiology, 50(7), 1249–1259.

    Article  CAS  Google Scholar 

  • Manandhar-Shrestha, K., Tamot, B., Pratt, E. P. S., Saitie, S., Bräutigam, A., Weber, A. P. M., et al. (2013). Comparative proteomics of chloroplasts envelopes from bundle sheath and mesophyll chloroplasts reveals novel membrane proteins with a possible role in C4-related metabolite fluxes and development. Frontiers in Plant Science, 4, 65. https://doi.org/10.3389/fpls.2013.00065.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Manavalan, L. P., Guttikonda, S. K., Tran, L. S., & Nguyen, H. T. (2009). Physiological and molecular approaches to improve drought resistance in soybean. Plant & Cell Physiology, 50, 1260–1276.

    Article  CAS  Google Scholar 

  • Mao, X., Cai, T., Olyarchuk, J. G., & Wei, L. (2005). Automated genome annotation and pathway identification using the KEGG Orthology (KO) as a controlled vocabulary. Bioinformatics, 21, 3787–3793.

    Article  CAS  PubMed  Google Scholar 

  • Margulies, M., Egholm, M., Altman, W. E., Attiya, S., Bader, J. S., et al. (2005). Genome sequencing in microfabricated high-density picolitre reactors. Nature, 437, 376–380.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Maruyama, K., Takeda, M., Kidokoro, S., Yamada, K., Sakuma, Y., Urano, K., et al. (2009). Metabolic pathways involved in cold acclimation identified by integrated analysis of metabolites and transcripts regulated by DREB1A and DREB2A. Plant Physiology, 150, 1972–1980.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Masoudi-Nejad, A., Tonomura, K., Kawashima, S., Moriya, Y., Suzuki, M., Itoh, M., et al. (2006). EGassembler: Online bioinformatics service for large-scale processing, clustering and assembling ESTs and genomic DNA fragments. Nucleic Acids Research, 34, W459–W462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Matros, A., & Mock, H.-P. (2013). Mass spectrometry based imaging techniques for spatially resolved analysis of molecules. Frontiers in Plant Science, 4, 89. https://doi.org/10.3389/fpls.2013.00089.

    Article  PubMed  PubMed Central  Google Scholar 

  • Matsumura, H., Reich, S., Ito, A., Saitoh, H., Kamoun, S., Winter, P., et al. (2003). Gene expression analysis of plant host–pathogen interactions by SuperSAGE. Proceedings of the National Academy of Sciences of the United States of America, 100, 15718–15723.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Matsumura, H., Kruger, D. H., Kahl, G., & Terauchi, R. (2008). SuperSAGE: A modern platform for genome-wide quantitative transcript profi ling. Current Pharmaceutical Biotechnology, 9, 368–374.

    Article  CAS  PubMed  Google Scholar 

  • Matzke, M., Kanno, T., Daxinger, L., Huettel, B., & Matzke, A. J. (2009). RNA-mediated chromatin-based silencing in plants. Current Opinion in Cell Biology, 21, 367–376.

    Article  CAS  PubMed  Google Scholar 

  • Mayer, K. F., Martis, M., Hedley, P. E., Simkova, H., Liu, H., Morris, J. A., et al. (2011). Unlocking the barley genome by chromosomal and comparative genomics. Plant Cell, 23, 1249–1263.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • McCann, H. C., & Guttman, D. S. (2008). Evolution of the type III secretion system and its effectors in plant–microbe interactions. The New Phytologist, 177, 33–47. https://doi.org/10.1111/j.1469-8137.2007.02293.x.

    Article  CAS  PubMed  Google Scholar 

  • Mehta, R. A., Cassol, T., Li, N., Ali, N., Handa, A. K., & Mattoo, A. K. (2002). Engineered polyamine accumulation in tomato enhances phytonutrient content, juice quality, and vine life. Nature Biotechnology, 20, 613–618.

    Article  CAS  PubMed  Google Scholar 

  • Meihls, L. N., Handrick, V., Glauser, G., Barbier, H., Kaur, H., Haribal, M. M., Lipka, A. E., Gershenzon, J., Buckler, E. S., Erb, M., et al. (2013). Natural variation in maize aphid resistance is associated with 2,4-dihydroxy-7- methoxy-1,4-benzoxazin-3-one glucoside methyltransferase activity. Plant Cell, 25, 2341–2355.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mendes, P. (1997). Biochemistry by numbers: Simulation of biochemical pathways with Gepasi 3. Trends in Biochemical Sciences, 22, 361–363.

    Article  CAS  PubMed  Google Scholar 

  • Meng, Y., Shao, C., Wang, H., et al. (2011). The regulatory activities of plant microRNAs: A more dynamic perspective. Plant Physiology, 157(4), 1583–1595.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Meyers, B. C., Galbraith, D. W., Nelson, T., & Agrawal, V. (2004). Methods for transcriptional profiling in plants. Be fruitful and replicate. Plant Physiology, 135, 637–652.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Miyagi, A., Takahara, K., Takahashi, H., Kawai-Yamada, M., & Uchimiya, H. (2010). Metabolomics, 6, 497–510. https://doi.org/10.1007/s11306-010-0220-0.

    Article  CAS  Google Scholar 

  • Mochida, K., Saisho, D., Yoshida, T., Sakurai, T., & Shinozaki, K. (2008). TriMEDB: A database to integrate transcribed markers and facilitate genetic studies of the tribe Triticeae. BMC Plant Biology, 8, 72.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Mochida, K., Furuta, T., Ebana, K., Shinozaki, K., & Kikuchi, J. (2009). Correlation exploration of metabolic and genomic diversities in rice. BMC Genomics, 10, 568.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Mochida, K., Yoshida, T., Sakurai, T., Yamaguchi-Shinozaki, K., Shinozaki, K., & Tran, L. S. (2010). LegumeTFDB: An integrative database of Glycine max, Lotus japonicus and Medicago truncatula transcription factors. Bioinformatics, 26, 290–291.

    Article  CAS  PubMed  Google Scholar 

  • Mochida, K., Uehara-Yamaguchi, Y., Yoshida, T., Sakurai, T., & Shinozaki, K. (2011). Global landscape of a co-expressed gene network in barley and its application to gene discovery in Triticeae crops. Plant & Cell Physiology, 52, 785–803.

    Article  CAS  Google Scholar 

  • Mockler, T. C., & Ecker, J. R. (2005). Applications of DNA tiling arrays for whole-genome analysis. Genomics, 85, 1–15.

    Article  CAS  PubMed  Google Scholar 

  • Moco, S., Bino, R. J., Vorst, O., Verhoeven, H. A., de Groot, J., van Beek, T. A., et al. (2006). A liquid chromatography–mass spectrometry-based metabolome database for tomato. Plant Physiology, 141, 1205–1218.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Moran, N. A., McLaughlin, H. J., & Sorek, R. (2009). The dynamics and time scale of ongoing genomic erosion in symbiotic bacteria. Science, 323, 379–382.

    Article  CAS  PubMed  Google Scholar 

  • Morsy, M., Gouthu, S., Orchard, S., Thorneycroft, D., Harper, J. F., Mittler, R., et al. (2008). Charting plant interactomes: Possibilities and challenges. Trends in Plant Science, 13, 183–191.

    Article  CAS  PubMed  Google Scholar 

  • Mostafavi, S., Ray, D., Warde-Farley, D., et al. (2008). GeneMANIA: A real-time multiple association network integration algorithm for predicting gene function. Genome Biology, 9(1), S4.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Mueller, L. A., Zhang, P., & Rhee, S. Y. (2003). AraCyc: A biochemical pathway database for Arabidopsis. Plant Physiology, 132, 453–460.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Mukhtar, M. S., Carvunis, A. R., Dreze, M., Epple, P., Steinbrenner, J., Moore, J., et al. (2011). Independently evolved virulence effectors converge onto hubs in a plant immune system network. Science, 333, 596–601.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nagasaki, M., Saito, A., Jeong, E., et al. (2010). Cell illustrator 4.0: A computational platform for systems biology. In Silico Biology, 10(1), 5–26.

    CAS  PubMed  Google Scholar 

  • Nakabayashi, R., & Saito, K. (2015). Integrated metabolomics for abiotic stress responses in plants. Current Opinion in Plant Biology, 24, 10–16.

    Article  CAS  PubMed  Google Scholar 

  • Nakamura, Y., Teo, N. Z., Shui, G., Chua, C. H., Cheong, W. F., Parameswaran, S., Koizumi, R., Ohta, H., Wenk, M. R., & Ito, T. (2014). Transcriptomic and lipidomic profiles of glycerolipids during Arabidopsis flower development. The New Phytologist, 203, 310–322.

    Article  CAS  PubMed  Google Scholar 

  • Nakashima, K., Ito, Y., & Yamaguchi-Shinozaki, K. (2009). Transcriptional regulatory networks in response to abiotic stresses in Arabidopsis and grasses. Plant Physiology, 149(1), 88–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nashilevitz, S., Melamed-Bessudo, C., Izkovich, Y., Rogachev, I., Osorio, S., Itkin, M., et al. (2010). An orange ripening mutant links plastid NAD(P)H dehydrogenase complex activity to central and specialized metabolism during tomato fruit maturation. Plant Cell, 22, 1977–1997.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Neumann, E. (2005). A life science semantic web: Are we there yet? Science STKE, 283, pe22.

    Google Scholar 

  • Newton, A. C., Fitt, B. D. L., Atkins, S. D., Walters, D. R., & Daniell, T. J. (2010). Pathogenesis, parasitism and mutualism in the trophic space of microbe–plant interactions. Trends in Microbiology, 18, 365–373.

    Article  CAS  PubMed  Google Scholar 

  • Nishimura, D. (2001). BioCarta. Biotech Software & Internet Report, 2, 117–120.

    Article  Google Scholar 

  • Nobuta, K., Venu, R. C., Lu, C., Belo, A., Vemaraju, K., Kulkarni, K., et al. (2007). An expression atlas of rice mRNAs and small RNAs. Nature Biotechnology, 25, 473–477.

    Article  CAS  PubMed  Google Scholar 

  • Nobuta, K., Lu, C., Shrivastava, R., Pillay, M., De Paoli, E., Accerbi, M., et al. (2008). Distinct size distribution of endogeneous siRNAs in maize: Evidence from deep sequencing in the mop1-1 mutant. Proceedings of the National Academy of Sciences of the United States of America, 105, 14958–14963.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Noel, J. P., Austin, M. B., & Bomati, E. K. (2005). Structure-function relationships in plant phenylpropanoid biosynthesis. Current Opinion in Plant Biology, 8, 249–253.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Nomura, M., Arunothayanan, H., Dao, T. V., Le, H. T. P., Takakazu Kaneko, T., Sato, S., et al. (2010). Differential protein profiles of Bradyrhizobium japonicum USDA110 bacteroid during soybean nodule development. Soil Science & Plant Nutrition, 56, 579–590.

    Article  CAS  Google Scholar 

  • Obayashi, T., Hayashi, S., Saeki, M., Ohta, H., & Kinoshita, K. (2009). ATTED-II provides coexpressed gene networks for Arabidopsis. Nucleic Acids Research, 37, D987–D991.

    Article  CAS  PubMed  Google Scholar 

  • Ogasawara, O., Otsuji, M., Watanabe, K., Iizuka, T., Tamura, T., Hishiki, T., et al. (2006). BodyMap-Xs: Anatomical breakdown of 17 million animal ESTs for cross-species comparison of gene expression. Nucleic Acids Research, 34, D628–D631.

    Article  CAS  PubMed  Google Scholar 

  • Okazaki, Y., Shimojima, M., Sawada, Y., Toyooka, K., Narisawa, T., Mochida, K., et al. (2009). A chloroplastic UDP-glucose pyrophosphorylase from Arabidopsis is the committed enzyme for the first step of sulfolipid biosynthesis. Plant Cell, 21, 892–909.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Olivier, B. G., & Snoep, J. L. (2004). Web-based kinetic modelling using JWS online. Bioinformatics, 20, 2143–2144.

    Article  CAS  PubMed  Google Scholar 

  • Ozaki, S., Ogata, Y., Suda, K., Kurabayashi, A., Suzuki, T., Yamamoto, N., et al. (2010). Coexpression analysis of tomato genes and experimental verification of coordinated expression of genes found in a functionally enriched coexpression module. DNA Research, 17, 105–116.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ozinsky, A., Underhill, D. M., Fontenot, J. D., Hajjar, A. M., Smith, K. D., Wilson, C. B., Schroeder, L., & Aderem, A. (2000). The repertoire for pattern recognition of pathogens by the innate immune system is defined by cooperation between toll-like receptors. Proceedings of the National Academy of Sciences of the United States of America, 97, 13766–13771.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pabinger, S., Rader, R., Agren, R., et al. (2011). MEMOSys: Bioinformatics platform for genome-scale metabolic models. BMC Systems Biology, 5(1), 20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Paine, J. A., Shipton, C. A., Chaggar, S., Howells, R. M., Kennedy, M. J., Vernon, G., Wright, S. Y., Hinchliffe, E., Adams, J. L., Silverstone, A. L., & Drake, R. (2005). Improving the nutritional value of Golden Rice through increased pro-vitamin a content. Nature Biotechnology, 23, 482–487.

    Article  CAS  PubMed  Google Scholar 

  • Papin, J. A., Reed, J. L., & Palsson, B. O. (2004). Hierarchical thinking in network biology: The unbiased modularization of biochemical networks. Trends in Biochemical Sciences, 29, 641–647.

    Article  CAS  PubMed  Google Scholar 

  • Pappin, D. J., Hojrup, P., & Bleasby, A. J. (1993). Rapid identification of proteins by peptide-mass fingerprinting. Current Biology, 3, 327–332.

    Article  CAS  PubMed  Google Scholar 

  • Park, P. J. (2009). ChIP-seq: Advantages and challenges of a maturing technology. Nature Reviews Genetics, 10, 669–680.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Paterson, A. H., Bowers, J. E., Bruggmann, R., Dubchak, I., Grimwood, J., Gundlach, H., et al. (2009). The Sorghum bicolor genome and the diversifi cation of grasses. Nature, 457, 551–556.

    Article  CAS  PubMed  Google Scholar 

  • Patil, N., Berno, A. J., Hinds, D. A., Barrett, W. A., Doshi, J. M., et al. (2001). Blocks of limited haplotype diversity revealed by high-resolution scanning of human chromosome 21. Science, 294, 1719–1723. 102.

    Article  CAS  PubMed  Google Scholar 

  • Peña, P. A., Quach, T., Sato, S., Ge, Z., Nersesian, N., et al. (2017). Expression of the maize Dof 1 transcription factor in wheat and sorghum. Frontiers in Plant Science, 8, 434.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pérez-Delgado, C. M., Moyano, T. C., García-Calderón, M., Canales, J., Gutiérrez, R. A., et al. (2016). Use of transcriptomics and co-expression networks to analyze the interconnections between nitrogen assimilation and photorespiratory metabolism. Journal of Experimental Botany, 67(10), 3095–3108.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Pichersky, E., & Gang, D. R. (2000). Genetics and biochemistry of secondary metabolites: An evolutionary perspective. Trends in Plant Science, 5, 439–445.

    Article  CAS  PubMed  Google Scholar 

  • Pires, N. D., Yi, K., Breuninger, H., et al. (2013). Recruitment and remodeling of an ancient gene regulatory network during land plant evolution. Proceedings of the National Academy of Sciences of the United States of America, 110(23), 9571–9576.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Pop, M., Phillippy, A., Delcher, A. L., & Salzberg, S. L. (2004). Comparative genome assembly. Briefings in Bioinformatics, 5, 237–248.

    Article  CAS  PubMed  Google Scholar 

  • Poultney, C. S., Gutiérrez, R. A., Katari, M. S., et al. (2007). Sungear: Interactive visualization and functional analysis of genomic datasets. Bioinformatics, 23(2), 259–261.

    Article  CAS  PubMed  Google Scholar 

  • Proietti, S., Bertini, L., Timperio, A. M., et al. (2013). Crosstalk between salicylic acid and jasmonate in Arabidopsis investigated by an integrated proteomic and transcriptomic approach. Molecular BioSystems, 9(6), 1169–1187.

    Article  CAS  PubMed  Google Scholar 

  • Proost, S., Van Bel, M., Sterck, L., Billiau, K., Van Parys, T., Van de Peer, Y., & Vandepoele, K. (2009). PLAZA: A comparative genomics resource to study gene and genome evolution in plants. Plant Cell, 21, 3718–3731.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Rhodes, D., Yu, J., Shanker, K., Deshpande, N., Varambally, R., et al. (2004). Large-scale metaanalysis of cancer microarray data identifies common transcriptional profiles of neoplastic transformation and progression. Proceedings of the National Academy of Sciences of the United States of America, 101, 9309–9314.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Riechmann, J. L., Heard, J., Martin, G., Reuber, L., Jiang, C., Keddie, J., et al. (2000). Arabidopsis transcription factors: Genome-wide comparative analysis among eukaryotes. Science, 290, 2105–2110.

    Article  CAS  PubMed  Google Scholar 

  • Rischer, H., Orešič, M., Seppänen-Laakso, T., et al. (2006). Gene-tometabolite networks for terpenoid indole alkaloid biosynthesis in Catharanthus roseus cells. Proceedings of the National Academy of Sciences, 103(14), 5614–5619.

    Article  CAS  Google Scholar 

  • Roberts, C., Nelson, B., Marton, M., Stoughton, R., Meyer, M., et al. (2000). Signaling and circuitry of multiple MAPK pathways revealed by a matrix of global gene expression profiles. Science, 287, 873–880.

    Article  CAS  PubMed  Google Scholar 

  • Roth, F. P., Hughes, J. D., Estep, P. W., & Church, G. M. (1998). Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation. Nature Biotechnology, 16, 939–945.

    Article  CAS  PubMed  Google Scholar 

  • Roux, M., Schwessinger, B., Albrecht, C., Chinchilla, D., Jones, A., Holton, N., et al. (2011). The Arabidopsis leucine-rich repeat receptor-like kinases BAK1/SERK3 and BKK1/SERK4 are required for innate immunity to hemibiotrophic and biotrophic pathogens. Plant Cell, 23, 2440–2455.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Ruiz-Ferrer, V., & Voinnet, O. (2009). Roles of plant small RNAs in biotic stress responses. Annual Review of Plant Biology, 60, 485–510.

    Article  CAS  PubMed  Google Scholar 

  • Saal, L. H., Troein, C., Vallon-Christersson, J., Gruvberger, S., Borg, A., & Peterson, C. (2002). BioArray Software Environment: A platform for comprehensive management and analysis of microarray data. Genome Biology, 3, software000.

    Article  Google Scholar 

  • Saisho, D., & Takeda, K. (2011). Barley: Emergence as a new research material of crop science. Plant & Cell Physiology, 52, 724–727.

    Article  CAS  Google Scholar 

  • Saito, K., & Matsuda, F. (2010). Metabolomics for functional genomics, systems biology, and biotechnology. Annual Review of Plant Biology, 61, 463–489.

    Article  CAS  PubMed  Google Scholar 

  • Saito, T., Ariizumi, T., Okabe, Y., Asamizu, E., Hiwasa-Tanase, K., Fukuda, N., et al. (2011). TOMATOMA: A novel tomato mutant database distributing micro-tom mutant collections. Plant & Cell Physiology, 52, 283–296.

    Article  CAS  Google Scholar 

  • Sakurai, N., Ara, T., Ogata, Y., Sano, R., Ohno, T., Sugiyama, K., et al. (2011). KaPPA-View4: A metabolic pathway database for representation and analysis of correlation networks of gene co-expression and metabolite co-accumulation and omics data. Nucleic Acids Research, 39, D677–D684.

    Article  CAS  PubMed  Google Scholar 

  • Sanchez, L., Courteaux, B., Hubert, J., Kauffmann, S., Renault, J.-H., Clement, C., et al. (2012). Rhamnolipids elicit defense responses and induce disease resistance against biotrophic, hemibiotrophic, and necrotrophic pathogens that require different signaling pathways in Arabidopsis and highlight a central role for salicylic acid. Plant Physiology, 160, 1630–1641.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Santner, A., & Estelle, M. (2009). Recent advances and emerging trends in plant hormone signalling. Nature, 459, 1071.

    Article  CAS  PubMed  Google Scholar 

  • Sauro, H. M., Hucka, M., Finney, A., et al. (2003). Next generation simulation tools: The systems biology workbench and BioSPICE integration. OMICS, 7(4), 355–372.

    Article  CAS  PubMed  Google Scholar 

  • Sauvage, C., Segura, V., Bauchet, G., Stevens, R., Do, P. T., Nikoloski, Z., Fernie, A. R., & Causse, M. (2014). Genome-wide association in tomato reveals 44 candidate loci for fruit metabolic traits. Plant Physiology, 165, 1120–1132.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sawada, Y., Akiyama, K., Sakata, A., Kuwahara, A., Otsuki, H., Sakurai, T., et al. (2009a). Widely targeted metabolomics based on large-scale MS/MS data for elucidating metabolite accumulation patterns in plants. Plant & Cell Physiology, 50, 37–47.

    Article  CAS  Google Scholar 

  • Sawada, Y., Kuwahara, A., Nagano, M., Narisawa, T., Sakata, A., Saito, K., et al. (2009b). Omics-based approaches to methionine side chain elongation in Arabidopsis: Characterization of the genes encoding methylthioalkylmalate isomerase and methylthioalkylmalate dehydrogenase. Plant & Cell Physiology, 50, 1181–1190.

    Article  CAS  Google Scholar 

  • Schaefer, C. F., Anthony, K., Krupa, S., et al. (2009). PID: The pathway interaction database. Nucleic Acids Research, 37(1), D674–D679.

    Article  CAS  PubMed  Google Scholar 

  • Schauer, N., Semel, Y., Balbo, I., Steinfath, M., Repsilber, D., Selbig, J., et al. (2008). Mode of inheritance of primary metabolic traits in tomato. The Plant Cell, 20, 509–523.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Scheible, W. R., Morcuende, R., Czechowski, T., et al. (2004). Genomewide reprogramming of primary and secondary metabolism, protein synthesis, cellular growth processes, and the regulatory infrastructure of Arabidopsis in response to nitrogen. Plant Physiology, 136(1), 2483–2499.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schena, M., Shalon, D., Davis, R. W., & Brown, P. O. (1995). Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science, 270, 467–470.

    Article  CAS  PubMed  Google Scholar 

  • Schilmiller, A. L., Moghe, G. D., Fan, P., Ghosh, B., Ning, J., Jones, A. D., & Last, R. L. (2015). Functionally divergent alleles and duplicated loci encoding an acyltransferase contribute to acylsugar metabolite diversity in Solanum trichomes. Plant Cell, 27, 1002–1017.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schlueter, S. D., Dong, Q., & Brendel, V. (2003). GeneSeqer@PlantGDB: Gene structure prediction in plant genomes. Nucleic Acids Research, 31, 3597–3600.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schmitz, R. J., & Zhang, X. (2011). High-throughput approaches for plant epigenomic studies. Current Opinion in Plant Biology, 14, 130–136.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Schmutz, J., Cannon, S. B., Schlueter, J., Ma, J., Mitros, T., Nelson, W., et al. (2010). Genome sequence of the palaeopolyploid soybean. Nature, 463, 178–183.

    Article  CAS  PubMed  Google Scholar 

  • Schwender, J., Hebbelmann, I., Heinzel, N., Hildebrandt, T., Rogers, A., Naik, D., Klapperstück, M., Braun, H. P., Schreiber, F., Denolf, P., et al. (2015). Quantitative multilevel analysis of central metabolism in developing oilseeds of oilseed rape during in vitro culture. Plant Physiology, 168, 828–848.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Scossa, F., Brotman, Y., de Abreu e Lima, F., Willmitzer, L., Nikoloski, Z., Tohge, T., & Fernie, A. R. (2015). Genomics-based strategies for the use of natural variation in the improvement of crop metabolism. Plant Science. https://doi.org/10.1016/j.plantsci.2015.05.0213.

  • Seki, M., Narusaka, M., Ishida, J., Nanjo, T., Fujita, M., Oono, Y., et al. (2002). Monitoring the expression profi les of 7000 Arabidopsis genes under drought, cold and high-salinity stresses using a fulllength cDNA microarray. The Plant Journal, 31, 279–292.

    Article  CAS  PubMed  Google Scholar 

  • Seo, Y. S., Chern, M., Bartley, L. E., Han, M., Jung, K. H., Lee, I., et al. (2011). Towards establishment of a rice stress response interactome. PLoS Genetics, 7, e1002020.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shanks, J. V. (2005). Phytochemical engineering: Combining chemical reaction engineering with plant science. AICHE Journal, 51, 2–7.

    Article  CAS  Google Scholar 

  • Shannon, P., Markiel, A., Ozier, O., et al. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13(11), 2498–2504.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sheard, L. B., Tan, X., Mao, H., Withers, J., Ben-Nissan, G., Hinds, T. R., et al. (2010). Jasmonate perception by inositol-phosphatepotentiated COI1–JAZ co-receptor. Nature, 468, 400–405.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shen, Y. J., Jiang, H., Jin, J. P., Zhang, Z. B., Xi, B., He, Y. Y., et al. (2004). Development of genome-wide DNA polymorphism database for map-based cloning of rice genes. Plant Physiology, 135, 1198–1205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shen, L., Gong, J., Caldo, R. A., Nettleton, D., Cook, D., et al. (2005). Barley base—An expression profiling database for plant genomics. Nucleic Acids Research, 33, D614–D618.

    Article  CAS  PubMed  Google Scholar 

  • Shingaki-Wells, R. N., Huang, S., Taylor, N. L., Carroll, A. J., Zhou, W., & Millar, A. H. (2011). Differential molecular responses of rice and wheat coleoptiles to anoxia reveal novel metabolic adaptations in amino acid metabolism for tissue tolerance. Plant Physiology, 156, 1706–1724.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Shoemaker, R., Deng, J., Wang, W., & Zhang, K. (2010). Allele-specific methylation is prevalent and is contributed by CpG-SNPs in the human genome. Genome Research, 20, 883–889.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Simons, M., Misra, A., & Sriram, G. (2014). Genome-scale models of plant metabolism. Methods in Molecular Biology, 1083, 213–230.

    Article  CAS  PubMed  Google Scholar 

  • Sinha, U., Bui, A., Taira, R., Dionisio, J., Morioka, C., et al. (2002). A review of medical imaging informatics. Annals of the New York Academy of Sciences, 980, 168–197.

    Article  PubMed  Google Scholar 

  • SMRS Working Group. (2005). Summary recommendations for standardization and reporting of metabolic analyses. Nature Biotechnology, 23, 833–838.

    Article  CAS  Google Scholar 

  • Song, Q. X., Liu, Y. F., Hu, X. Y., Zhang, W. K., Ma, B., Chen, S. Y., & Zhang, J. S. (2011). Identification of miRNAs and their target genes in developing soybean seeds by deep sequencing. BMC Plant Biology, 11, 5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sriram, G., Fulton, D. B., Iyer, V. V., Peterson, J. M., Zhou, R., et al. (2004). Quantification of compartmented metabolic fluxes in developing soybean embryos by employing biosynthetically directed fractional 13C labeling, two-dimensional (13C, 1H) nuclear magnetic resonance, and comprehensive isotopomer balancing. Plant Physiology, 136, 3043–3057.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Staab, P. R., Walossek, J., Nellessen, D., et al. (2010). SynBioWave—A realtime communication platform for molecular and synthetic biology. Bioinformatics, 26(21), 2782–2783.

    Article  CAS  PubMed  Google Scholar 

  • Stacey, G., Libault, M., Brechenmacher, L., Wan, J., & May, G. D. (2006). Genetics and functional genomics of legume nodulation. Current Opinion in Plant Biology, 9, 110–121.

    Article  CAS  PubMed  Google Scholar 

  • Steinfath, M., Repsilber, D., Scholz, M., et al. (2007). Integrated data analysis for genome-wide research. EXS, 97, 309–329.

    CAS  PubMed  Google Scholar 

  • sterck, L., Rombauts, S., Vandepoele, K., Rouze, P., & Van de Peer, Y. (2007). How many genes are there in plants (… and why are they there)? Current Opinion in Plant Biology, 10, 199–203.

    Article  CAS  PubMed  Google Scholar 

  • Steuer, R., Kurths, J., Fiehn, O., & Weckwerth, W. (2003). Interpreting correlations in metabolomic networks. Biochemical Society Transactions, 31, 1476–1478.

    Article  CAS  PubMed  Google Scholar 

  • Stoeckert, C. J., Jr., Causton, H. C., & Ball, C. A. (2002). Microarray databases: Standards and ontologies. Nature Genetics, 32(Suppl), 469–473.

    Article  CAS  PubMed  Google Scholar 

  • Stolc, V., Samanta, M. P., Tongprasit, W., Sethi, H., Liang, S., et al. (2005). Identification of transcribed sequences in Arabidopsis thaliana by using high-resolution genome tiling arrays. Proceedings of the National Academy of Sciences of the United States of America, 102, 4453–4458.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sucaet, Y., Wang, Y., Li, J., et al. (2012). MetNet online: A novel integrated resource for plant systems biology. BMC Bioinformatics, 13(1), 267.

    Article  PubMed  PubMed Central  Google Scholar 

  • Sulpice, R., Trenkamp, S., Steinfath, M., Usadel, B., Gibon, Y., Witucka-Wall, H., Pyl, E. T., Tschoep, H., Steinhauser, M. C., Guenther, M., et al. (2010). Network analysis of enzyme activities and metabolite levels and their relationship to biomass in a large panel of Arabidopsis accessions. Plant Cell, 22, 2872–2893.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Sumner, L. W. (2010). Recent advances in plant metabolomics and greener pastures. F1000 Biology Reports, 2, 7.

    PubMed  PubMed Central  Google Scholar 

  • Sun, W., Xu, X., Zhu, H., Liu, A., Liu, L., Li, J., et al. (2010). Comparative transcriptomic profiling of a salt-tolerant wild tomato species and a salt-sensitive tomato cultivar. Plant & Cell Physiology, 51, 997–1006.

    Article  CAS  Google Scholar 

  • Tadege, M., Wen, J., He, J., Tu, H., Kwak, Y., Eschstruth, A., et al. (2008). Large-scale insertional mutagenesis using the Tnt1 retrotransposonin the model legume Medicago truncatula. The Plant Journal, 54, 335–347.

    Article  CAS  PubMed  Google Scholar 

  • Taji, T., Sakurai, T., Mochida, K., Ishiwata, A., Kurotani, A., Totoki, Y., et al. (2008). Large-scale collection and annotation of full-length enriched cDNAs from a model halophyte, Thellungiella halophila. BMC Plant Biology, 8, 115.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Tanabe, L., Scherf, U., Smith, L. H., Lee, J. K., Hunter, L., & Weinstein, J. N. (1999). MedMiner: An internet text-mining tool for biomedical information, with application to gene expression profiling. BioTechniques, 27, 1210–1217.

    Article  CAS  PubMed  Google Scholar 

  • Tanaka, T., Antonio, B. A., Kikuchi, S., Matsumoto, T., Nagamura, Y., Numa, Y., et al. (2008). The Rice Annotation Project Database (RAP-DB): 2008 update. Nucleic Acids Research, 36, D1028–D1033.

    CAS  PubMed  Google Scholar 

  • Tang, H., Bowers, J. E., Wang, X., Ming, R., Alam, M., & Paterson, A. H. (2008a). Synteny and collinearity in plant genomes. Science, 320, 486–488.

    Article  CAS  PubMed  Google Scholar 

  • Tang, H., Wang, X., Bowers, J. E., Ming, R., Alam, M., & Paterson, A. H. (2008b). Unraveling ancient hexaploidy through multiply-aligned angiosperm gene maps. Genome Research, 18, 1944–1195.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • The Arabidopsis Genome Initiative. (2000). Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature, 408, 796–815.

    Article  Google Scholar 

  • Thijs, G., Lescot, M., Marchal, K., Rombauts, S., De Moor, B., Rouze, P., & Moreau, Y. (2001). A higher-order background model improves the detection of promoter regulatory elements by Gibbs sampling. Bioinformatics, 17, 1113–1122.

    Article  CAS  PubMed  Google Scholar 

  • Thimm, O., Bläsing, O., Gibon, Y., Nagel, A., Meyer, S., Krüger, P., Selbig, J., Müller, L. A., Rhee, S. Y., & Stitt, M. (2004). MAPMAN: A user-driven tool to display genomics data sets onto diagrams of metabolic pathways and other biological processes. The Plant Journal, 37, 914–939.

    Article  CAS  PubMed  Google Scholar 

  • Timm, S., Florian, A., Wittmiß, M., Jahnke, K., Hagemann, M., Fernie, A. R., & Bauwe, H. (2013). Serine acts as a metabolic signal for the transcriptional control of photorespiration-related genes in Arabidopsis. Plant Physiology, 162, 379–389.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Todaka, D., Nakashima, K., Shinozaki, K., et al. (2012). Towards understanding transcriptional regulatory networks in abiotic stress responses and tolerance in rice. Rice, 5(1), 1–9.

    Article  Google Scholar 

  • Tohge, T., & Fernie, A. R. (2010). Combining genetic diversity, informatics and metabolomics to facilitate annotation of plant gene function. Nature Protocols, 5, 1210–1227.

    Article  CAS  PubMed  Google Scholar 

  • Tohge, T., Nishiyama, Y., Hirai, M. Y., Yano, M., Nakajima, J., Awazuhara, M., et al. (2005). Functional genomics by integrated analysis of metabolome and transcriptome of Arabidopsis plants over-expressing an MYB transcription factor. The Plant Journal, 42, 218–235.

    Article  CAS  PubMed  Google Scholar 

  • Tohge, T., de Souza, L. P., & Fernie, A. R. (2014). Genome-enabled plant metabolomics. Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences, 966, 7–20.

    Article  CAS  PubMed  Google Scholar 

  • Tomita, M., Hashimoto, K., Takahashi, K., et al. (1999). E-CELL: Software environment for whole-cell simulation. Bioinformatics, 15(1), 72–84.

    Article  CAS  PubMed  Google Scholar 

  • Töpfer, N., Caldana, C., Grimbs, S., Willmitzer, L., Fernie, A. R., & Nikoloski, Z. (2013). Integration of genome-scale modeling and transcript profiling reveals metabolic pathways underlying light and temperature acclimation in Arabidopsis. Plant Cell, 25, 1197–1211.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Töpfer, N., Scossa, F., Fernie, A., & Nikoloski, Z. (2014). Variability of metabolite levels is linked to differential metabolic pathways in Arabidopsis’s responses to abiotic stresses. PLoS Computational Biology, 10, e1003656.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Torres, D., Barrier, M., Bihl, F., Quesniaux, V. J. F., Maillet, I., Akira, S., Ryffel, B., & Erard, F. (2004). Toll-like receptor 2 is required for optimal control of Listeria monocytogenes infection. Infection and Immunity, 72, 2131–2139.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Toyoda, T., & Shinozaki, K. (2005). Tiling array-driven elucidation of transcriptional structures based on maximum-likelihood and Markov models. The Plant Journal, 43, 611–621.

    Article  CAS  PubMed  Google Scholar 

  • Turenne, N. (2011). Role of a web-based software platform for systems biology. Journal of Computer Science & Systems Biology, 4, 035–041.

    Article  Google Scholar 

  • Ulitsky, I., Maron-Katz, A., Shavit, S., Sagir, D., Linhart, C., et al. (2010). Expander: From expression microarrays to networks and functions. Nature Protocols, 5(2), 303–322.

    Article  CAS  PubMed  Google Scholar 

  • Umehara, M., Hanada, A., Yoshida, S., Akiyama, K., Arite, T., Takeda- Kamiya, N., et al. (2008). Inhibition of shoot branching by new terpenoid plant hormones. Nature, 455, 195–200.

    Article  CAS  PubMed  Google Scholar 

  • Umezawa, T., Sakurai, T., Totoki, Y., Toyoda, A., Seki, M., Ishiwata, A., et al. (2008). Sequencing and analysis of approximately 40 000 soybean cDNA clones from a full-length-enriched cDNA library. DNA Research, 15, 333–346.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Umezawa, T., Nakashima, K., Miyakawa, T., Kuromori, T., Tanokura, M., Shinozaki, K., et al. (2010). Molecular basis of the core regulatory network in ABA responses: Sensing, signaling and transport. Plant & Cell Physiology, 51, 1821–1839.

    Article  CAS  Google Scholar 

  • Urano, K., Maruyama, K., Ogata, Y., Morishita, Y., Takeda, M., Sakurai, N., et al. (2009). Characterization of the ABA-regulated global responses to dehydration in Arabidopsis by metabolomics. The Plant Journal, 57, 1065–1078.

    Article  CAS  PubMed  Google Scholar 

  • Urbanczyk-Wochniak, E., Luedemann, A., Kopka, J., Selbig, J., RoessnerTunali, U., Willmitzer, L., & Fernie, A. R. (2003). Parallel analysis of transcript and metabolic profiles: A new approach in systems biology. EMBO Reports, 4, 989–993.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • van der Werf, M. J., Overkamp, K. M., Muilwijk, B., Coulier, L., & Hankemeier, T. (2007). Microbial metabolomics: Toward a platform with full metabolome coverage. Analytical Biochemistry, 370, 17–25.

    Article  PubMed  CAS  Google Scholar 

  • van Helden, J. (2003). Regulatory sequence analysis tools. Nucleic Acids Research, 31, 3593–3596.

    Article  PubMed  PubMed Central  Google Scholar 

  • Van Helden, J., Rios, A. F., & Collado-Vides, J. (2000). Discovering regulatory elements in non-coding sequences by analysis of spaced dyads. Nucleic Acids Research, 28, 1808–1818.

    Article  PubMed  PubMed Central  Google Scholar 

  • Vandepoele, K., Van Bel, M., Richard, G., Van Landeghem, S., Verhelst, B., Moreau, H., Van de Peer, Y., Grimsley, N., & Piganeau, G. (2013). picoPLAZA, a genome database of microbial photosynthetic eukaryotes. Environmental Microbiology, 15, 2147–2153.

    Article  CAS  PubMed  Google Scholar 

  • Varshney, R. K., Nayak, S. N., May, G. D., & Jackson, S. A. (2009). Next-generation sequencing technologies and their implications for crop genetics and breeding. Trends in Biotechnology, 27, 522–530.

    Article  CAS  PubMed  Google Scholar 

  • Velculescu, V. E., Zhang, L., Vogelstein, B., & Kinzler, K. W. (1995). Serial analysis of gene expression. Science, 270, 484–487.

    Article  CAS  PubMed  Google Scholar 

  • Vernoux, T., Brunoud, G., Farcot, E., Morin, V., Van den Daele, H., Legrand, J., et al. (2011). The auxin signalling network translates dynamic input into robust patterning at the shoot apex. Molecular Systems Biology, 7, 508.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Voit, E. O. (2000). Computational analysis of biochemical systems: A practical guide for biochemists and molecular biologists. Cambridge: Cambridge University Press.

    Google Scholar 

  • von Bertalanffy, L. (1933). Modern theories of development. London: Oxford University Press.

    Google Scholar 

  • von Bertalanffy, L. (1968). General systems theory. In G. Braziller (Ed.), Foundations, development, applications. New York: George Braziller.

    Google Scholar 

  • Walbot, V. (2009). 10 reasons to be tantalized by the B73 maize genome. PLoS Genetics, 5, e1000723.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Wall, P. K., Leebens-Mack, J., Muller, K. F., Field, D., Altman, N. S., & dePamphilis, C. W. (2008). PlantTribes: A gene and gene family resource for comparative genomics in plants. Nucleic Acids Research, 36, D970–D976.

    Article  CAS  PubMed  Google Scholar 

  • Wan, X., & Xu, D. (2005). Computational methods for remote homolog identification. Current Protein & Peptide Science, 6, 527–546.

    Article  CAS  Google Scholar 

  • Wang, H., Schauer, N., Usadel, B., Frasse, P., Zouine, M., Hernould, M., et al. (2009). Regulatory features underlying pollination-dependent and -independent tomato fruit set revealed by transcript and primary metabolite profiling. Plant Cell, 21, 1428–1452.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wang, K., Peng, X., Ji, Y., Yang, P., Zhu, Y., & Li, S. (2013). Gene, protein, and network of male sterility in rice. Frontiers in Plant Science, 4, 92. https://doi.org/10.3389/fpls.2013.00092.

    Article  PubMed  PubMed Central  Google Scholar 

  • Ware, D. H., Jaiswal, P., Ni, J., Yap, I. V., Pan, X., et al. (2002). Gramene, a tool for grass genomics. Plant Physiology, 130, 1606–1613.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Weckwerth, W. (2003). Metabolomics in systems biology. Annual Review of Plant Biology, 54, 669–689. https://doi.org/10.1146/annurev.arplant.54.031902.135014.

    Article  CAS  PubMed  Google Scholar 

  • Wei, C.-F., Hsu, S.-T., Deng, W.-L., Wen, Y.-D., & Huang, H.-C. (2012). Plant innate immunity induced by flagellin suppresses the hypersensitive response in non-host plants elicited by Pseudomonas syringae pv. Averrhoi. PLoS One, 7, e41056. https://doi.org/10.1371/journal.pone.0041056.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Weigel, D., & Mott, R. (2009). The 1001 genomes project for Arabidopsis thaliana. Genome Biology, 10, 107.

    Article  PubMed  PubMed Central  Google Scholar 

  • Wenzl, P., Raman, H., Wang, J., Zhou, M., Huttner, E., & Kilian, A. (2007). A DArT platform for quantitative bulked segregant analysis. BMC Genomics, 8, 196.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Weston, D. J., Karve, A. A., Gunter, L. E., Jawdy, S. S., Yang, X., Allen, S. M., et al. (2011). Comparative physiology and transcriptional networks underlying the heat shock response in Populus trichocarpa, Arabidopsis thaliana and Glycine max. Plant, Cell & Environment, 34, 1488–1506.

    Article  CAS  Google Scholar 

  • Weston, D. J., Hanson, P. J., Norby, R. J., Tuskan, G. A., & Wullschleger, S. D. (2012). From systems biology to photosynthesis and wholeplant physiology. Plant Signaling & Behavior, 7(2), 260–262.

    Article  Google Scholar 

  • Wheeler, G., Ishikawa, T., Pornsaksit, V., & Smirnoff, N. (2015). Evolution of alternative biosynthetic pathways for vitamin C following plastid acquisition in photosynthetic eukaryotes. eLife, 4, e06369.

    Article  PubMed Central  CAS  Google Scholar 

  • Wiechert, W., Mollney, M., Petersen, S., & de Graaf, A. A. (2001). A universal framework for 13C metabolic flux analysis. Metabolic Engineering, 3, 265–283.

    Article  CAS  PubMed  Google Scholar 

  • Wiener, N. (1948). Cybernetics (p. 112). New York: Wiley.

    Google Scholar 

  • Wienkoop, S., Morgenthal, K., Wolschin, F., Scholz, M., Selbig, J., & Weckwerth, W. (2008). Integration of metabolomic and proteomic phenotypes analysis of data covariance dissects starch and RFO metabolism from low and high temperature compensation response in Arabidopsis thaliana. Molecular & Cellular Proteomics, 7, 1725–1736. https://doi.org/10.1074/mcp.M700273-MCP200.

    Article  CAS  Google Scholar 

  • Windram, O., Madhou, P., McHattie, S., Hill, C., Hickman, R., et al. (2012). Arabidopsis defense against Botrytis cinerea: Chronology and regulation deciphered by high-resolution temporal transcriptomic analysis. The Plant Cell, 24(9), 3530–3557.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Winnenburg, R., Wächter, T., Plake, C., et al. (2008). Facts from text: Can text mining help to scale-up high-quality manual curation of gene products with ontologies? Briefings in Bioinformatics, 9(6), 466–478.

    Article  CAS  PubMed  Google Scholar 

  • Winter, D., Vinegar, B., Nahal, H., Ammar, R., Wilson, G. V., & Provart, N. J. (2007). An ‘electronic fluorescent pictograph’ browser for exploring and analyzing large-scale biological data sets. PLoS One, 2, e718.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Witte, C. E., Archer, K. A., Rae, C. S., Sauer, J. D., Woodward, J. J., & Portnoy, D. A. (2012). Innate immune pathways triggered by Listeria monocytogenes and their role in the induction of cell-mediated immunity. Advances in Immunology, 113, 135–156.

    Article  CAS  PubMed  Google Scholar 

  • Woo, Y., Affourtit, J., Daigle, S., Viale, A., Johnson, K., et al. (2004). A comparison of cDNA, oligonucleotide, and affymetrix GeneChip gene expression microarray platforms. Journal of Biomolecular Techniques, 15, 276–284.

    PubMed  PubMed Central  Google Scholar 

  • Woodward, J. J., Iavarone, A. T., & Portnoy, D. A. (2010). C-di-AMP secreted by intracellular Listeria monocytogenes activates a host type I interferon response. Science, 328, 1703–1705.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Wu H, Yang H, Churchill GA (2011) R/MAANOVA: An extensive R environment for the analysis of microarray experiments.

    Google Scholar 

  • Xu, X., Pan, S., Cheng, S., Zhang, B., Mu, D., Ni, P., et al. (2011). Genome sequence and analysis of the tuber crop potato. Nature, 475, 189–195.

    Article  CAS  PubMed  Google Scholar 

  • Yamada, K., Lim, J., Dale, J. M., Chen, H., Shinn, P., et al. (2003). Empirical analysis of transcriptional activity in the Arabidopsis genome. Science, 302, 842–846.

    Article  CAS  PubMed  Google Scholar 

  • Yamaguchi, S., & Kyozuka, J. (2010). Branching hormone is busy both underground and overground. Plant & Cell Physiology, 51, 1091–1094.

    Article  CAS  Google Scholar 

  • Yamakawa, H., & Hakata, M. (2010). Atlas of rice grain filling-related metabolism under high temperature: Joint analysis of metabolome and transcriptome demonstrated inhibition of starch accumulation and induction of amino acid accumulation. Plant & Cell Physiology, 51(5), 795–809.

    Article  CAS  Google Scholar 

  • Yamamoto, Y. Y., & Obokata, J. (2008). ppdb: A plant promoter database. Nucleic Acids Research, 36, D977–D981.

    Article  CAS  PubMed  Google Scholar 

  • Yamamoto, Y. Y., Yoshitsugu, T., Sakurai, T., Seki, M., Shinozaki, K., & Obokata, J. (2009). Heterogeneity of Arabidopsis core promoters revealed by high-density TSS analysis. The Plant Journal, 60, 350–362.

    Article  CAS  PubMed  Google Scholar 

  • Yang, F., Jacobsen, S., Jørgensen, H. J. L., Collinge, D. B., Svensson, B., & Finnie, C. (2013). Fusarium graminearum and its interactions with cereal heads: Studies in the proteomics era. Frontiers in Plant Science, 4, 37. https://doi.org/10.3389/fpls.2013.00037.

    Article  PubMed  PubMed Central  Google Scholar 

  • Yates, J. R., 3rd, Eng, J. K., McCormack, A. L., & Schieltz, D. (1995). Method to correlate tandem mass spectra of modified peptides to amino acid sequences in the protein database. Analytical Chemistry, 67, 1426–1436.

    Article  CAS  PubMed  Google Scholar 

  • Ye, X., Al-Babili, S., Klöti, A., Zhang, J., Lucca, P., Beyer, P., & Potrykus, I. (2000). Engineering the provitamin A (-carotene) biosynthetic pathway into (carotenoid-free) rice endosperm. Science, 287, 303–305.

    Article  CAS  PubMed  Google Scholar 

  • Yeager, A. F. (1927). Determinate growth in the tomato. The Journal of Heredity, 18, 263–265.

    Article  Google Scholar 

  • Yona, G., & Levitt, M. (2002). Within the twilight zone: A sensitive profile-profile comparison tool based on information theory. Journal of Molecular Biology, 315, 1257–1275.

    Article  CAS  PubMed  Google Scholar 

  • Yonekura-Sakakibara, K., Tohge, T., Matsuda, F., Nakabayashi, R., Takayama, H., Niida, R., et al. (2008). Comprehensive flavonol profiling and transcriptome coexpression analysis leading to decoding gene–metabolite correlations in Arabidopsis. The Plant Cell, 20, 2160–2176.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Young, N. D., & Udvardi, M. (2009). Translating Medicagotruncatula genomics to crop legumes. Current Opinion in Plant Biology, 12, 193–201.

    Article  CAS  PubMed  Google Scholar 

  • Yuan, J. S., Galbraith, D. W., Dai, S. Y., et al. (2008). Plant systems biology comes of age. Trends in Plant Science, 13(4), 165–171.

    Article  CAS  PubMed  Google Scholar 

  • Yun, K. Y., Park, M. R., Mohanty, B., et al. (2010). Transcriptional regulatory network triggered by oxidative signals configures the early response mechanisms of japonica rice to chilling stress. BMC Plant Biology, 10(1), 16.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  • Zeller, G., Henz, S. R., Widmer, C. K., Sachsenberg, T., Ratsch, G., Weigel, D., et al. (2009). Stress-induced changes in the Arabidopsis thaliana transcriptome analyzed using whole-genome tiling arrays. The Plant Journal, 58, 1068–1082.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, M. Q. (2002). Computational prediction of eukaryotic protein-coding genes. Nature Reviews. Genetics, 3, 698–709.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, H., Sreenivasulu, N., Weschke, W., Stein, N., Rudd, S., Radchuk, V., et al. (2004). Large-scale analysis of the barley transcriptome based on expressed sequence tags. The Plant Journal, 40, 276–290.

    Article  PubMed  Google Scholar 

  • Zhang, J., Leiderman, K., Pfeiffer, J. R., Wilson, B. S., Oliver, J. M., & Steinberg, S. L. (2006a). Characterizing the topography of membrane receptors and signaling molecules from spatial patterns obtained using nanometer-scale electron-dense probes and electron microscopy. Micron, 37, 14–34.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, X., Yazaki, J., Sundaresan, A., Cokus, S., Chan, S. W., Chen, H., et al. (2006b). Genome-wide high-resolution mapping and functional analysis of DNA methylation in arabidopsis. Cell, 126, 1189–1201.

    Article  CAS  PubMed  Google Scholar 

  • Zhang, B., Tolstikov, V., Turnbull, C., Hicks, L. M., & Fiehn, O. (2010). Divergent metabolome and proteome suggest functional independence of dual phloem transport systems in cucurbits. Proceedings of the National Academy of Sciences of the United States of America, 107, 13532–13537.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhang, Z., Wu, Y., Gao, M., Zhang, J., Kong, Q., Liu, Y., et al. (2012). Disruption of PAMP-induced MAP kinase cascade by a Pseudomonas syringae effector activates plant immunity mediated by the NB-LRR protein SUMM2. Cell Host & Microbe, 11, 253–263.

    Article  CAS  Google Scholar 

  • Zheng, Y., Ren, N., Wang, H., Stromberg, A. J., & Perry, S. E. (2009). Global identifi cation of targets of the Arabidopsis MADS domain protein AGAMOUS-Like15. Plant Cell, 21, 2563–2577.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhu, T., & Wang, X. (2000). Large-scale profiling of the Arabidopsis transcriptome. Plant Physiology, 124, 1472–1476.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Zhu, H., Bilgin, M., & Snyder, M. (2003). Proteomics. Annual Review of Biochemistry, 72, 783–812.

    Article  CAS  PubMed  Google Scholar 

  • Zimmermann, I. M., Heim, M. A., Weisshaar, B., et al. (2004a). Comprehensive identification of Arabidopsis thaliana MYB transcription factors interacting with R/B-like BHLH proteins. The Plant Journal, 40(1), 22–34.

    Article  CAS  PubMed  Google Scholar 

  • Zimmermann, P., Hirsch-Hoffmann, M., Hennig, L., & Gruissem, W. (2004b). Genevestigator: Arabidopsis microarray database and analysis toolbox. Plant Physiology, 136, 2621–2632.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Parray, J.A., Yaseen Mir, M., Shameem, N. (2019). Advancement in Sustainable Agriculture: Computational and Bioinformatics Tools. In: Sustainable Agriculture: Biotechniques in Plant Biology . Springer, Singapore. https://doi.org/10.1007/978-981-13-8840-8_10

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