Advances in Plant Omics and Systems Biology Approaches

Preface
Acknowledgments
Contents
Editors and Contributors
About the Editor
Contributors
Abbreviations
1: Introduction: Advances in Plant Omics and Systems Biology
	1.1	 Overview of Systems Theory Applied to Plant Sciences
	1.2	 Advances in Omics and Systems Biology Applications in Plant Sciences
	1.3	 Challenges in Plant Systems Biology and Paths to Expand the Research Field
	References
2: Modern Approaches for Transcriptome Analyses in Plants
	2.1	 Introduction
	2.2	 Transcriptomics Approaches
		2.2.1	 Array-Based Approaches
		2.2.2	 Sequencing-Based Approaches
			2.2.2.1	 RNA-Seq
			2.2.2.2	 Strand-Specific RNA-Seq
			2.2.2.3	 Long Read RNA Sequencing
		2.2.3	 Transcriptome Assembly
			2.2.3.1	 Genome-Guided Transcriptome Assembly
			2.2.3.2	 De Novo Transcriptome Assembly
			2.2.3.3	 Assessment of Transcript Assemblies
				Evaluation of Sequencing Depth
				Percent Reads Mapped
				Identification of Sets of Conserved Genes
				Contamination Screening and Filtration
		2.2.4	 Transcript Quantification
			2.2.4.1	 Alignment/Mapping-Based Approaches
			2.2.4.2	 Alignment-Free Approaches
	2.3	 Applications
		2.3.1	 Differential Gene Expression
		2.3.2	 Co-expression Networks
		2.3.3	 Polymorphisms
		2.3.4	 Machine Learning Technologies for Transcriptomics
	2.4	 Case/Examples of Transcriptomics in Non-model Plants
		2.4.1	 Construction of Improved Transcripts Catalogs
		2.4.2	 Populations Mapping
		2.4.3	 Stress-Related Studies
		2.4.4	 Phylogenomics
	2.5	 Future Directions in the Field
	References
3: Plant Proteomics and Systems Biology
	3.1	 Introduction
	3.2	 Research and Technical Approaches
		3.2.1	 The Gel-Electrophoresis-Based Plant Proteome Analysis
		3.2.2	 Mass Spectrometry-Based Proteomics
		3.2.3	 Proteomics Analyses of Posttranslational Modifications (PTMs)
	3.3	 Proteomics of Non-model Species
	3.4	 Future Directions
	References
4: Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants
	4.1	 Introduction
		4.1.1	 The Historical Context of Subcellular Location in Proteomics
		4.1.2	 Collation of Arabidopsis Subcellular Data Established Subcellular Proteomics
		4.1.3	 The Collation of Plant Subcellular Data Progressed into Crop Plants by Establishing cropPAL
	4.2	 Research and Technical Approach
		4.2.1	 Visualization and Separation of Proteins for Subcellular Localization Are Improving
		4.2.2	 Subcellular Proteomics Can Be Supplemented with Homology Gap-Filling and Subcellular Protein Location Predictions
		4.2.3	 An Objective Collation and Unification Strategy Can Resolve Varied and Conflicting Subcellular Location Information
		4.2.4	 Subcellular Proteomics Data Resources in SUBA Have Contributed to Over 900 Downstream Scientific Reports
		4.2.5	 The Collation and Integration of Arabidopsis Subcellular Proteomics Data Presents Opportunities for New Approaches for In Silico Analysis
	4.3	 Future Directions in the Field
	References
5: The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science
	5.1	 Introduction and Overview of Plant Metabolomics
	5.2	 Applications of Metabolomics in Plant Sciences
		5.2.1	 Pattern Recognition and Discrimination
		5.2.2	 Functional Genomics
		5.2.3	 Metabolomics as a Prediction Tool
		5.2.4	 Flux Analysis
		5.2.5	 Integration with Other Omics
	5.3	 Final Considerations and Future Perspectives
	References
6: Interactomes: Experimental and In Silico Approaches
	6.1	 Introduction
	6.2	 Molecular Technologies for Protein–Protein Interactions (PPI) Identification
		6.2.1	 Yeast Two Hybrid (Y2H)
		6.2.2	 Pull-Down
		6.2.3	 Co-immunoprecipitation (Co-IP)
		6.2.4	 Tandem Affinity Purification: Mass Spectrometry (TAP-MS)
		6.2.5	 Förster Resonance Energy Transfer
		6.2.6	 Bimolecular Fluorescence Complementation (BiFC)
	6.3	 In Silico Approaches for Protein–Protein Interactions (PPI) Identification
		6.3.1	 Databases
		6.3.2	 In Silico PPI Reliability Based on Interaction Topology
		6.3.3	 PPI Reliability Evaluation Based on Subcellular Localization
		6.3.4	 Publicly Available Databases
		6.3.5	 In Silico Predictions
			6.3.5.1	 Reciprocal BLAST
			6.3.5.2	 OrthoMCL
			6.3.5.3	 InParanoid
	References
7: Probabilistic Graphical Models Applied to Biological Networks
	7.1	 Biological Regulatory Networks
	7.2	 Probabilistic Graphical Models
	7.3	 Data Preparation and Normalization
	7.4	 Graph Theory and Biological Networks
		7.4.1	 Concepts and Properties
		7.4.2	 Types of Topology
		7.4.3	 Bayesian Networks (BNs)
		7.4.4	 Graphical Gaussian Models (GGMs)
	7.5	 Network Representation and Visualization Tools
	References
8: Cataloging Posttranslational Modifications in Plant Histones
	8.1	 Introduction
	8.2	 Profiling of Histone Modifications in Plants
		8.2.1	 Novel Lysine Acylations Discovered in Plants
		8.2.2	 Beyond Identification of Histone Modifications
	8.3	 Strategies for the Analysis of Plant Histone Modifications
		8.3.1	 The Whole-Proteome Approach
		8.3.2	 Approaches Based on Histone Purification
	8.4	 Perspective
	References
9: Current Challenges in Plant Systems Biology
	9.1	 Introduction
	9.2	 From the Genomic to the Plant Systems Biology Era
	9.3	 Data Production for Plant Systems Biology: Technical Limitations of Omic Approaches
	9.4	 Methodological Limitations of Omic Approaches: From Alive vs. Dead Comparisons to More Dose and Dynamic Analyses
	9.5	 Toward a Systemic Plant Biology
	9.6	 Reconstructing Plant Metabolic Networks: The Challenge to Reach an Integrative Nonsteady State Large-Scale Modeling Platform
	9.7	 From Arabidopsis to Crops, from the Phytotron to the Field: The Challenge for Crop Yield Improvement
	9.8	 Concluding Remarks and Future Perspectives
	References
10: Contribution of Omics and Systems Biology to Plant Biotechnology
	10.1	 Introduction
		10.1.1	 Plants Have Shaped Human Life History on Earth
	10.2	 Development
		10.2.1	 Plant–Microbe Interaction: Effectors, Omics and Strategies for Plant Breeding
		10.2.2	 Effectors from Beneficial Microorganisms
		10.2.3	 Effectors of Plant-Pathogens
		10.2.4	 Omics as Tools to Identify Microbe Effectors and Plant Targets
		10.2.5	 Biotechnology Approaches for Genetic Engineering Plants to Improve Productivity and Disease Resistance
		10.2.6	 Gene Expression Regulation by Small Noncoding RNAs
			10.2.6.1	 Biological Roles of Plant miRNAs
		10.2.7	 Recent Applications of Omics and Small RNA Research in Plant Biotechnology
	10.3	 Concluding remarks
	References
Index