Plant Systems Biology: Methods and Protocols (Methods in Molecular Biology, 2395)

Description

This second edition volume expands on the previous edition with an update on the latest techniques used to study plant systems biology on three specific scales: the molecular level, the tissue level, and the whole plant. Chapters cover topics such as gene regulatory network inference and dynamic modeling using ordinary differential equations or Boolean formalisms; protocols for at-will induction of plant aerial or root organs, or quantification of tissue mechanical properties; mathematical modeling of plant tissue using SimuPlant or VirtualLeaf; and simulating crop root systems using OpenSimRoot or R-SWMS. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step, readily reproducible laboratory protocols or software tutorials, and tips on troubleshooting and avoiding known pitfalls.  Comprehensive and cutting-edge, Plants Systems Biology: Methods and Protocols, Second Edition is a valuable resource for plant biologists looking for different approaches to finding solutions to their questions and generating new ideas, as well as for students who desire to discover the field of plant systems biology.  Dedication Preface Contents Contributors Chapter 1: Plant Systems Biology: Lessons from Teaching 1 Introduction: Lessons from Teaching Plant Systems Biology 1.1 What Is a System? 1.1.1 Systems Are First and Foremost Dependent on a Point of View 1.1.2 Every Object that Biology Studies Is a System of Systems 1.2 Modeling Biological Systems 1.2.1 Biological Systems Study Is Never Done in a Vacuum 1.2.2 Biological Systems Complexity Is Nonlinear and More Than Exponential 1.3 The Seven Steps of Systems Study 1.3.1 Studying a System Is Trying to Predict Its Behavior 1.3.2 Being Able to Predict Its Behavior Means Attaining Perfect Control Over a System 2 Plant Systems Biology at the Molecular Scale 3 Plant Systems Biology at the Tissue Scale 4 Plant Systems Biology at the Whole Plant Scale 5 Going Forward References Chapter 2: How to Use the TDCor Algorithm to Infer Gene Regulatory Networks from Time Series Transcriptomic Data 1 Introduction 2 Materials 2.1 What Kind of Data Can Be Used for Inferring a GRN Topology Using TDCor? 2.2 How to Install TDCor and Get Help? 3 Methods 3.1 How to Set Up the Working Directory? 3.2 How to Import the Transcriptomic Data into the R Workspace? 3.3 How to Define the Main Input Vectors? 3.4 How to Generate the TPI and DPI Databases? 3.5 How to Find the Right Parameters for Time Shift Estimation? 3.6 How to Reconstruct the Network? 3.7 How to Visualize the Network in Cytoscape? 4 Notes References Chapter 3: Gene Regulatory Network Investigation Using Ordinary Differential Equations 1 Introduction 2 Materials 2.1 Elementary Reactions 2.2 Michaelis-Menten and Hill Approximations 2.3 Example (Continued): Mutual Gene Inhibition 3 Methods 3.1 How to Analyze a Model 3.2 Case Study 1: Auxin Signaling 3.3 Case Study 2: Auxin Transporters 3.4 Nondimensionalization 3.5 Steady State Analysis 4 Notes References Chapter 4: Gene Regulatory Network Dynamical Logical Models for Plant Development 1 Introduction 2 Methods 2.1 Definitions 2.2 Modeling Protocols 2.2.1 Deterministic Discrete GRN Modeling 2.2.2 Assembling a Network (Genes and Boolean Rules) Define the List of State Variables (Genes) Define Boolean Rules Define the ``Expected Attractors´´ GRN Model Dynamical Analysis Testing the Consistency of the Model Validation of the Model Testing Robustness Simulation of Gain and Loss of Function Mutations 2.3 Stochastic Discrete GRN Modeling 2.3.1 Introducing Stochasticity 2.3.2 Extending a Discrete Dynamical Boolean Model to a Stochastic Model Define Discrete Stochastic Functions Generate a Transition Matrix Derive a Probabilistic Dynamic Model 2.3.3 Example of a Discrete Stochastic Model for Flower Organ Morphogenesis 3 Notes References Chapter 5: Postembryonic Organogenesis in Plants: Experimental Induction of New Shoot and Root Organs 1 Introduction 2 Postembryonic Organogenesis in Shoots 2.1 New Shoot Organs Originate from the Shoot Apical Meristem 2.2 Functional Patterning of the Shoot Apical Meristem Through Hormonal Cues and Other Non-cell-Autonomous Signals 2.3 Rhythmic Accumulation of Auxin Triggers Organogenesis at the Peripheral Zone Through a Robust and Complex Genetic Network 3 Methods to Induce Postembryonic Organogenesis in Shoot Meristems 3.1 Local Induction of Shoot Organogenesis by Exogenous Auxin Application 3.1.1 Material 3.1.2 Method 3.1.3 Notes 3.2 Shoot Organogenesis Induced by Genetic Manipulation 3.3 Induction of Shoot Organogenesis by Local Cell Wall Modifications 4 Postembryonic Formation in Roots 4.1 New Roots Originate from Selected Pericycle Cells of the Parental Root 4.2 Auxin Signaling Recruits Pericycle Cells to Form New Roots 4.3 Lateral Root Founder Cell Recruitment Translates into a Robust and Plastic Developmental Program 5 Methods to Induce Post-embryonic Formation in Roots 5.1 Auxin Treatment Induces Lateral Root Formation (Himanen et al.) 5.2 Induction of Gene Expression Alone Has Not Succeeded in Triggering Synchronous Lateral Root Organogenesis 5.3 Mechanical Bending of the Parental Root Locally Induces Synchronized Lateral Root Formation 5.3.1 Material 5.3.2 Method 5.3.3 Notes 6 Conclusion References Chapter 6: NanoIndentation, an ImageJ Plugin for the Quantification of Cell Mechanics 1 Introduction 2 Materials 2.1 Software and Plugins 2.2 Images 3 Methods 3.1 Generate a Segmentation 3.2 Alternative Manual Segmentation 3.3 Define the Relative Position of Images 3.4 NanoIndentation Plugin (Fig. 1) 3.4.1 Configuration 3.4.2 Stitching 3.4.3 Segmenting Cells 3.4.4 Labeling Cells 3.4.5 Exporting Results (Fig. 2) 4 Notes References Chapter 7: Introduction to Computational Modeling of Multicellular Tissues 1 Introduction 2 Materials 2.1 Software Tools 3 Methods 3.1 Defining a Tissue Structure 3.2 Example: Tissue Structure Definition 3.3 Modeling Tissue and Cell Properties 3.3.1 Cell Chemical State Synthesis and Degradation of Chemical Species Motion of Mobile Chemical Species Diffusion Example Diffusion and Turnover Example Active Transport Example Turing Pattern Example 3.3.2 Cellular Reorganizations Cell Growth Cell Division Cell Growth and Division Example 3.4 Transversal Example: Turing Pattern with Growth and Division 3.5 Conclusions 4 Notes References Chapter 8: The Virtual Root: Mathematical Modeling of Auxin Transport in the Arabidopsis Root Tip Using the Open-Source Softwa... 1 Introduction 2 Resources 2.1 Requirements 2.2 Installation 3 Methods 3.1 The Program Interface 3.2 Using SimuPlant: The Virtual Root 3.2.1 Specifying the Model 3.2.2 Specifying the Simulation Parameters and Running the Simulation 3.3 Viewing Details of the Simulation Output 3.3.1 Visualizing the Simulation 3.3.2 Viewing Multiple Panels 3.3.3 Viewing the Simulation Output Data 3.4 Saving the Simulation 3.4.1 Saving Images of the Simulation Predictions 3.4.2 Saving the Simulation Data 3.5 Creating a New Simulation 4 Example Simulation with Change of Parameters 5 Conclusion 6 Notes References Chapter 9: Modeling Plant Tissue Development Using VirtualLeaf 1 Introduction 2 Materials 2.1 Required Software: QtCreator, C++ Compiler and Libraries 2.2 Source Code 2.3 Compile the VirtualLeaf Framework 2.4 Test VirtualLeaf 3 Methods Box 1 Mode Definition Outline. New Models are Constructed by Defining the Functions in this Model Definition File 3.1 Basic Usage of the VirtualLeaf 3.2 Prepare an Empty Model Plugin 3.3 Tissue Growth 3.4 Simulating Reaction-Diffusion Systems 3.4.1 Setting up the Model 3.4.2 Initializing the Simulation 3.4.3 Running the Model 3.4.4 Further Remarks 3.5 Reaction-Diffusion and Cell Differentiation 3.6 Polar auxin Transport 3.7 Performing Parameter Studies 3.8 Final Remarks 4 Notes References Chapter 10: Identifying Developmental Patterns in Structured Plant Phenotyping Data 1 Introduction 1.1 Patterns Are Hidden Part of Plant Phenotyping 1.2 Why Focus on Structured Data? 1.3 Phenotyping Devices and Data 1.4 Uses of Plant Phenotyping Data 1.5 Integrative Hierarchical Statistical Models for Analyzing Plant Phenotyping Data 2 Identification of Developmental or Growth Patterns Illustrated by Contrasting Examples 2.1 Developmental Zones of Maize Lateral Root Apices (Fig. 1;) 2.2 Arabidopsis Rosette Developmental Phases (Fig. 2;) 2.3 Growth and Branching Pattern of Maize and Pearl Millet Roots (Fig. 3;) 2.4 Influence of the Growth Pattern on the Branching Pattern (Fig. 4;) 2.5 Mango Growth Unit Developmental Growth Stages (Fig. 5;) 3 Handling Highly Structured Phenotyping Data 3.1 How to Deal with the Diversity of Data Types? (Fig. 6) 3.2 Prospective Versus Retrospective Measurements 3.3 Multiscale Plant Phenotyping 3.4 Time, Space, and Scale Integration in Spatiotemporal Modeling 4 A Tour Through the Different Features of Plant Architecture that Can Be Investigated Using Hierarchical Statistical Models 4.1 Phyllotaxis 4.2 Shoot Structure 4.3 Phenology 4.4 Shoot Branching Patterns 4.5 Tree Development over Several Years 4.6 Root System 4.7 Shoot-Root Interactions 5 A Wide Palette of Hierarchical Statistical Modeling Tools to Deal with the Variety of Plant Developmental Patterns 5.1 Frequent Occurrence of Two-Scale Structuring in Plant Growth and Development 5.2 Plant Phenotyping Pipelines Combining Advanced Image Analysis Methods with Hierarchical Statistical Models 6 Further Insights References Chapter 11: Putting Plant Roots at Light: Temporal Imaging of Plant Roots and Soil Water with a Light Transmission Technique f... 1 Introduction 2 The Light Transmission Imaging Technique for Plant Water Uptake Studies 2.1 Usefulness and Limits of Light Transmission Imaging 2.2 Theoretical Principles of Measurement 2.3 Materials 2.3.1 Sandy Soil, Rhizotron and Plant Culture 2.3.2 Light Source and Colorimetric Scale 2.3.3 Water Content Calibration Cells 2.3.4 Image Capture and Processing 3 Procedure 3.1 Rhizotron Filling and Plant Culture 3.2 Calibration of Water Content 3.3 Fitting of the Light Source to Rhizotrons 3.4 Imaging Rhizotrons and Processing Images 4 Use of imaging Experiment in Modeling 5 Notes References Chapter 12: RACINE2.2: A Software Application for Processing and Mapping Spatial Distribution of Root Length Density and Poten... 1 Introduction 2 Materials 3 Methods 3.1 Getting Started with RACINE2.2 3.2 Creating a New File 3.3 Working on an Existing File 3.4 Entry or Import of the Number of Roots Intersecting a Soil Profile 3.5 Calculating Root Length Densities, Root Distances, and Potential Root Extraction Ratio in Soil 3.5.1 Calculating Root Length Densities (RLD) 3.5.2 Calculating the Average Root Distances (ARD) 3.5.3 Calculating the Potential Root Extraction Ratio (PRER) 3.6 Exporting Results 3.7 Developing Maps of Root Traits (RLD, ARD, and PRER) Distribution in Soil 3.8 Models Used for RLD, RD, and PRER Computations 3.9 Delete Files. Get out RACINE2.2 4 Notes References Chapter 13: Investigating Soil-Root Interactions with the Numerical Model R-SWMS 1 Introduction 2 Model Description 2.1 Theoretical Principles 2.2 Numerical Solution 2.2.1 Numerical Solution for Soil Water Flow 2.2.2 Numerical Solution for Root Water Flow 3 Application: Use of R-SWMS for Hypothesis Testing 3.1 Material and Methods 3.2 Representing Experimental Results 3.3 Hypothesis Testing 4 Conclusions 5 Notes: How to Install R-SWMS References Chapter 14: How to Define the Appropriate Spatial Resolution of Root Segments When Solving Water Flow in Root System Hydraulic... 1 Introduction 2 Theory 3 Discrete Model Performance 4 Example for Maize Plants 5 Conclusion 6 Note: Demonstration References Chapter 15: Simulating Crop Root Systems Using OpenSimRoot 1 Introduction 2 Materials 2.1 Required Software: C++ Compiler 2.2 Source Code 2.3 Compile OpenSimRoot 2.4 Test OpenSimRoot 3 Methods 3.1 Running OpenSimRoot 3.2 Creating Input Files 3.3 Activating or Deactivating Modules 3.4 Editing Parameters 3.5 Advanced Editing of Parameters 3.6 Creating New Models for Different Genotypes, Species and Environments 3.7 Adding or Removing root Classes 3.8 Graphical User Interface 4 Notes References Chapter 16: Future Challenges in Plant Systems Biology 1 Introduction 2 Current Scientific Challenges in Plant Systems Biology 3 The Next Step: Future Opportunities for Plant Systems Biology References Chapter 17: Plant Systems Biology: Further Reading and Resources 1 Systems Biology Books 2 Additional References for Plant Systems Biology at Various Scales 2.1 Generating GRN and Other Networks 2.2 Validating and Analyzing GRN 2.3 Modeling Plant Tissue 2.4 Modeling Whole Plants and Plant Communities 2.5 Practicing Synthetic Biology 2.6 Further Applications of Systems Biology 3 Online Resources 4 Plant Systems Biology Communities Index