Omics and System Biology Approaches in Plant Stress Research

The continuous development of analytical and experimental technologies as well as instruments resulted in the development of very specialized experimental approaches that can identify, measure and quantify particular types of cellular molecules. These technologies are known as “Omics Technologies”. Most of the omics technologies are high throughput with very fast data generation rates and humongous outputs. Thus, they are highly dependent on bioinformatics and computational tools. These technologies have made noticeable contributions to the current advancements in our understanding of plant biology in general and plant stress tolerance and response in particular. In this chapter, we will introduce the main omics technologies employed in plant biology and the bioinformatics platforms associated with them.

[1]  K. Mysore,et al.  Virus-induced gene silencing is a versatile tool for unraveling the functional relevance of multiple abiotic-stress-responsive genes in crop plants , 2014, Front. Plant Sci..

[2]  Yu Xue,et al.  dbPPT: a comprehensive database of protein phosphorylation in plants , 2014, Database J. Biol. Databases Curation.

[3]  Burkhard Morgenstern,et al.  AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints , 2005, Nucleic Acids Res..

[4]  R. Sommer,et al.  Proteogenomics of Pristionchus pacificus reveals distinct proteome structure of nematode models. , 2010, Genome research.

[5]  S. Abbà,et al.  Novel aspects of grapevine response to phytoplasma infection investigated by a proteomic and phospho-proteomic approach with data integration into functional networks , 2013, BMC Genomics.

[6]  M. Bellgard,et al.  High‐throughput parallel proteogenomics: A bacterial case study , 2014, Proteomics.

[7]  Bailin Liu,et al.  Proteomic changes during tuber dormancy release process revealed by iTRAQ quantitative proteomics in potato. , 2015, Plant physiology and biochemistry : PPB.

[8]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[9]  Richard D. Smith,et al.  Proteogenomics: needs and roles to be filled by proteomics in genome annotation. , 2008, Briefings in functional genomics & proteomics.

[10]  J. Vanderleyden,et al.  Beans (Phaseolus spp.) – model food legumes , 2004, Plant and Soil.

[11]  Stephen E. Stein,et al.  The Drosophila melanogaster PeptideAtlas facilitates the use of peptide data for improved fly proteomics and genome annotation , 2009, BMC Bioinformatics.

[12]  Ruedi Aebersold,et al.  Mass spectrometry-based proteomic quest for diabetes biomarkers. , 2015, Biochimica et biophysica acta.

[13]  Paolo Fontana,et al.  Argot2: a large scale function prediction tool relying on semantic similarity of weighted Gene Ontology terms , 2012, BMC Bioinformatics.

[14]  Sabine Lüthje,et al.  The plasma membrane proteome of maize roots grown under low and high iron conditions. , 2013, Journal of proteomics.

[15]  P. Zimmermann,et al.  Genome-Scale Proteomics Reveals Arabidopsis thaliana Gene Models and Proteome Dynamics , 2008, Science.

[16]  Avner Schlessinger,et al.  PredictProtein—an open resource for online prediction of protein structural and functional features , 2014, Nucleic Acids Res..

[17]  Janick Mathys,et al.  RNAseq-based transcriptome analysis of Lactuca sativa infected by the fungal necrotroph Botrytis cinerea. , 2013, Plant, cell & environment.

[18]  Hwan-Gue Cho,et al.  A Scaffold Analysis Tool Using Mate-Pair Information in Genome Sequencing , 2008, Journal of biomedicine & biotechnology.

[19]  M. Tomita,et al.  The Rice Proteogenomics Database OryzaPG-DB: Development, Expansion, and New Features , 2012, Front. Plant Sci..

[20]  Allan Orozco,et al.  A review of Bioinformatics training applied to research in Molecular Medicine, Agriculture and Biodiversity in Costa Rica and Central America , 2013, Briefings Bioinform..

[21]  J. Batley,et al.  Genome sequence data: management, storage, and visualization. , 2009, BioTechniques.

[22]  P. Hoffmann,et al.  State of the art of 2D DIGE , 2015, Proteomics. Clinical applications.

[23]  Sara El-Metwally,et al.  Next Generation Sequencing Technologies and Challenges in Sequence Assembly , 2014, SpringerBriefs in Systems Biology.

[24]  David E Matthews,et al.  Plant and crop databases. , 2009, Methods in molecular biology.

[25]  D. Jacob,et al.  MeRy-B, a metabolomic database and knowledge base for exploring plant primary metabolism. , 2014, Methods in molecular biology.

[26]  Sara El-Metwally,et al.  Next-Generation Sequence Assembly Overview , 2014 .

[27]  M. Larsen,et al.  Battle through Signaling between Wheat and the Fungal Pathogen Septoria tritici Revealed by Proteomics and Phosphoproteomics* , 2013, Molecular & Cellular Proteomics.

[28]  Chao-jun Zhang,et al.  Transcriptome analysis reveals salt-stress-regulated biological processes and key pathways in roots of cotton (Gossypium hirsutum L.). , 2011, Genomics.

[29]  P. T. V. Lakshmi,et al.  The Arabidopsis Stress Responsive Gene Database , 2013, International journal of plant genomics.

[30]  Kazuki Saito,et al.  Metabolomics for functional genomics, systems biology, and biotechnology. , 2010, Annual review of plant biology.

[31]  S. Lewis,et al.  The generic genome browser: a building block for a model organism system database. , 2002, Genome research.

[32]  K. Shinozaki,et al.  Differential Gene Expression in Soybean Leaf Tissues at Late Developmental Stages under Drought Stress Revealed by Genome-Wide Transcriptome Analysis , 2012, PloS one.

[33]  Geetha Govind,et al.  Identification and functional validation of a unique set of drought induced genes preferentially expressed in response to gradual water stress in peanut , 2009, Molecular Genetics and Genomics.

[34]  B. Cargile,et al.  Gel based isoelectric focusing of peptides and the utility of isoelectric point in protein identification. , 2004, Journal of proteome research.

[35]  P. Spanu,et al.  In Planta Proteomics and Proteogenomics of the Biotrophic Barley Fungal Pathogen Blumeria graminis f. sp. hordei* , 2009, Molecular & Cellular Proteomics.

[36]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[37]  L. Tran,et al.  Systems biology-based approaches toward understanding drought tolerance in food crops , 2013, Critical reviews in biotechnology.

[38]  K. Shinozaki,et al.  Genomics and Bioinformatics Resources for Crop Improvement , 2010, Plant & cell physiology.

[39]  Vincent J. Denef,et al.  Proteogenomic basis for ecological divergence of closely related bacteria in natural acidophilic microbial communities , 2010, Proceedings of the National Academy of Sciences.

[40]  Aurélien Naldi,et al.  Logical modelling of gene regulatory networks with GINsim. , 2012, Methods in molecular biology.

[41]  C. Liu,et al.  Comparative Transcriptome Analysis to Reveal Genes Involved in Wheat Hybrid Necrosis , 2014, International journal of molecular sciences.

[42]  L. Hoffmann,et al.  Towards a synthetic view of potato cold and salt stress response by transcriptomic and proteomic analyses , 2012, Plant Molecular Biology.

[43]  Morgan C. Giddings,et al.  Peppy: proteogenomic search software. , 2013, Journal of proteome research.

[44]  Sara El-Metwally,et al.  Assessment of Next-Generation Sequence Assembly , 2014 .

[45]  K. Mysore,et al.  A high-throughput virus-induced gene silencing protocol identifies genes involved in multi-stress tolerance , 2013, BMC Plant Biology.

[46]  K. Shinozaki,et al.  Advances in Omics and Bioinformatics Tools for Systems Analyses of Plant Functions , 2011, Plant & cell physiology.

[47]  K. Shinozaki,et al.  'Omics' analyses of regulatory networks in plant abiotic stress responses. , 2010, Current opinion in plant biology.

[48]  Mukesh Jain,et al.  RiceSRTFDB: A database of rice transcription factors containing comprehensive expression, cis-regulatory element and mutant information to facilitate gene function analysis , 2013, Database J. Biol. Databases Curation.

[49]  S. Mathivanan,et al.  Proteogenomic analysis of the Venturia pirina (Pear Scab Fungus) secretome reveals potential effectors. , 2014, Journal of proteome research.

[50]  D. Main,et al.  Genomics and bioinformatics resources for translational science in Rosaceae , 2013, Plant Biotechnology Reports.

[51]  Feng Wu,et al.  Proteomics insights into the basis of interspecific facilitation for maize (Zea mays) in faba bean (Vicia faba)/maize intercropping. , 2014, Journal of proteomics.

[52]  M. Helmy,et al.  First- and Next-Generations Sequencing Methods , 2014 .

[53]  Navdeep Jaitly,et al.  DAnTE: a statistical tool for quantitative analysis of -omics data , 2008, Bioinform..

[54]  M. Wilkins,et al.  Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing. , 2014, Journal of proteome research.

[55]  P. Siguier,et al.  Alliance of Proteomics and Genomics to Unravel the Specificities of Sahara Bacterium Deinococcus deserti , 2009, PLoS genetics.

[56]  B. Roschitzki,et al.  Community proteogenomics reveals insights into the physiology of phyllosphere bacteria , 2009, Proceedings of the National Academy of Sciences.

[57]  Gary D. Bader,et al.  Ten Simple Rules for Developing Public Biological Databases , 2016, PLoS Comput. Biol..

[58]  Trey Ideker,et al.  Cytoscape tools for the web age: D3.js and Cytoscape.js exporters , 2014, F1000Research.

[59]  M. Helmy,et al.  Novel Next-Generation Sequencing Applications , 2014 .

[60]  A I Saeed,et al.  TM4: a free, open-source system for microarray data management and analysis. , 2003, BioTechniques.

[61]  Terrence S. Furey,et al.  The UCSC Genome Browser Database , 2003, Nucleic Acids Res..

[62]  Khader Shameer,et al.  STIFDB2: An Updated Version of Plant Stress-Responsive TranscrIption Factor DataBase with Additional Stress Signals, Stress-Responsive Transcription Factor Binding Sites and Stress-Responsive Genes in Arabidopsis and Rice , 2013, Plant & cell physiology.

[63]  Rakesh Yadav,et al.  Perspectives for genetic engineering of poplars for enhanced phytoremediation abilities , 2010, Ecotoxicology.

[64]  Samuel H. Payne,et al.  Discovery and revision of Arabidopsis genes by proteogenomics , 2008, Proceedings of the National Academy of Sciences.

[65]  H. Kanamori,et al.  Simultaneous RNA-Seq Analysis of a Mixed Transcriptome of Rice and Blast Fungus Interaction , 2012, PloS one.

[66]  California Jack Cassidy,et al.  An Automated Proteogenomic Method Uses Mass Spectrometry to Reveal Novel Genes in Zea mays* , 2013, Molecular & Cellular Proteomics.

[67]  Xiaowu Wang,et al.  Bolbase: a comprehensive genomics database for Brassica oleracea , 2013, BMC Genomics.

[68]  Huiyu Li,et al.  The salt-responsive transcriptome of Populus simonii × Populus nigra via DGE. , 2012, Gene.

[69]  D. Scheel,et al.  Sustained mitogen-activated protein kinase activation reprograms defense metabolism and phosphoprotein profile in Arabidopsis thaliana , 2014, Front. Plant Sci..

[70]  Sara El-Metwally,et al.  Next-Generation Sequence Assembly: Four Stages of Data Processing and Computational Challenges , 2013, PLoS Comput. Biol..

[71]  S. Komatsu,et al.  Rice proteome analysis: A step toward functional analysis of the rice genome , 2005, Proteomics.

[72]  J. Yates,et al.  An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database , 1994, Journal of the American Society for Mass Spectrometry.

[73]  S. Komatsu,et al.  Wheat proteomics: proteome modulation and abiotic stress acclimation , 2014, Front. Plant Sci..

[74]  M. Tomita,et al.  Mass spectrum sequential subtraction speeds up searching large peptide MS/MS spectra datasets against large nucleotide databases for proteogenomics , 2012, Genes to cells : devoted to molecular & cellular mechanisms.

[75]  Thomas L. Madden,et al.  BLAST 2 Sequences, a new tool for comparing protein and nucleotide sequences. , 1999, FEMS microbiology letters.

[76]  D. N. Perkins,et al.  Probability‐based protein identification by searching sequence databases using mass spectrometry data , 1999, Electrophoresis.

[77]  Gary D. Bader,et al.  Cytoscape Web: an interactive web-based network browser , 2010, Bioinform..

[78]  F. Loreto,et al.  RNAi-mediated suppression of isoprene emission in poplar transiently impacts phenolic metabolism under high temperature and high light intensities: a transcriptomic and metabolomic analysis , 2010, Plant Molecular Biology.

[79]  Sara El-Metwally,et al.  New Horizons in Next-Generation Sequencing , 2014 .

[80]  Vincent J. Henry,et al.  OMICtools: an informative directory for multi-omic data analysis , 2014, Database J. Biol. Databases Curation.

[81]  Damian Szklarczyk,et al.  STRING v9.1: protein-protein interaction networks, with increased coverage and integration , 2012, Nucleic Acids Res..

[82]  James K. Hane,et al.  Deep proteogenomics; high throughput gene validation by multidimensional liquid chromatography and mass spectrometry of proteins from the fungal wheat pathogen Stagonospora nodorum , 2009, BMC Bioinformatics.

[83]  James C. Wright,et al.  Exploiting proteomic data for genome annotation and gene model validation in Aspergillus niger , 2009, BMC Genomics.

[84]  Y. Ishihama,et al.  Shotguns in the front line: phosphoproteomics in plants. , 2012, Plant & cell physiology.

[85]  Zsolt Karányi,et al.  FSRD: fungal stress response database , 2013, Database J. Biol. Databases Curation.

[86]  Zhimin Gao,et al.  BambooGDB: a bamboo genome database with functional annotation and an analysis platform , 2014, Database J. Biol. Databases Curation.

[87]  A. Tyagi,et al.  Expanding frontiers in plant transcriptomics in aid of functional genomics and molecular breeding , 2014, Biotechnology journal.

[88]  Justin Preece,et al.  QlicRice: a web interface for abiotic stress responsive QTL and loci interaction channels in rice , 2011, Database J. Biol. Databases Curation.

[89]  Sara El-Metwally,et al.  Next-Generation Sequence Assemblers , 2014 .

[90]  R. Sicher,et al.  Impact of carbon dioxide enrichment on the responses of maize leaf transcripts and metabolites to water stress. , 2012, Physiologia plantarum.

[91]  K. Shinozaki,et al.  Omics and bioinformatics: an essential toolbox for systems analyses of plant functions beyond 2010. , 2009, Plant & cell physiology.

[92]  M. Tomita,et al.  Large-scale phosphorylation mapping reveals the extent of tyrosine phosphorylation in Arabidopsis , 2008, Molecular systems biology.

[93]  Patrik Rydén,et al.  OnPLS integration of transcriptomic, proteomic and metabolomic data shows multi-level oxidative stress responses in the cambium of transgenic hipI- superoxide dismutase Populus plants , 2013, BMC Genomics.

[94]  Lennart Martens,et al.  PRIDE Inspector: a tool to visualize and validate MS proteomics data , 2011, Nature Biotechnology.

[95]  M. Tomita,et al.  OryzaPG-DB: Rice Proteome Database based on Shotgun Proteogenomics , 2011, BMC Plant Biology.

[96]  M. Tress,et al.  Proteomics studies confirm the presence of alternative protein isoforms on a large scale , 2008, Genome Biology.

[97]  N. Benkeblia Microbial Functionality and Diversity in Agroecosystems: A Soil Quality Perspective , 2016 .

[98]  Amarjeet Singh,et al.  Gene Expression Analysis of Rice Seedling under Potassium Deprivation Reveals Major Changes in Metabolism and Signaling Components , 2013, PloS one.

[99]  Keith J. Edwards,et al.  CerealsDB 2.0: an integrated resource for plant breeders and scientists , 2012, BMC Bioinformatics.

[100]  Oliver Fiehn,et al.  A prominent role for the CBF cold response pathway in configuring the low-temperature metabolome of Arabidopsis. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[101]  C. Leslie,et al.  Abiotic Stress - Plant Responses and Applications in Agriculture , 2013 .

[102]  Geoffrey J. Barton,et al.  PIPs: human protein–protein interaction prediction database , 2008, Nucleic Acids Res..

[103]  Mahesh Visvanathan,et al.  An overview of computational life science databases & exchange formats of relevance to chemical biology research. , 2013, Combinatorial chemistry & high throughput screening.

[104]  Xuehua Zhong,et al.  Identification of an RNA Silencing Suppressor from a Plant Double-Stranded RNA Virus , 2005, Journal of Virology.

[105]  Baohong Zhang,et al.  Evaluation and selection of reliable reference genes for gene expression under abiotic stress in cotton (Gossypium hirsutum L.). , 2013, Gene.

[106]  G. Zhu,et al.  Phosphoproteome analysis reveals new drought response and defense mechanisms of seedling leaves in bread wheat (Triticum aestivum L.). , 2014, Journal of proteomics.

[107]  Neil Hall,et al.  Analysis of the Plasmodium falciparum proteome by high-accuracy mass spectrometry , 2002, Nature.

[108]  Jean Armengaud,et al.  Proteogenomics and systems biology: quest for the ultimate missing parts , 2010, Expert review of proteomics.

[109]  Hank C Wu,et al.  Phosphorus Stress in Common Bean: Root Transcript and Metabolic Responses1[W][OA] , 2007, Plant Physiology.

[110]  Masaru Tomita,et al.  Simultaneous determination of anionic intermediates for Bacillus subtilis metabolic pathways by capillary electrophoresis electrospray ionization mass spectrometry. , 2002, Analytical chemistry.

[111]  Yufeng J. Tseng,et al.  3Omics: a web-based systems biology tool for analysis, integration and visualization of human transcriptomic, proteomic and metabolomic data , 2013, BMC Systems Biology.

[112]  M. Tyers,et al.  From genomics to proteomics , 2003, Nature.