Plant Gene Regulatory Networks Methods and Protocols 2nd Edition by Kerstin Kaufmann, Klaas Vandepoele ISBN 9781071633533 1071633538

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ISBN 10: 1071633538
ISBN 13: 9781071633533
Author: Kerstin Kaufmann, Klaas Vandepoele

This second edition details protocols that analyze and explore gene regulatory networks (GRNs). Chapters guide readers through experimental techniques used to study genes and their regulatory interactions in plants, and computational approaches used for the integration of experimental data and bioinformatics-based predictions of regulatory interactions. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols.
Authoritative and cutting-edge, Plant Gene Regulatory Networks: Methods and Protocols, Second Edition aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge.

Plant Gene Regulatory Networks Methods and Protocols 2nd Edition Table of contents:

Chapter 1: Characterization of Gene Regulatory Networks in Plants Using New Methods and Data Types
1 Introduction
2 Experimental Methods to Map GRNs in Plants
3 Data Analysis and Inference Methods to Accurately Model Gene Regulation
4 Conclusions
References
Chapter 2: Inducible, Tissue-Specific Gene Expression in Arabidopsis Using GR-LhG4-Mediated Trans-Activation
1 Introduction
2 Materials
3 Methods
3.1 Preparing Plant Expression Vector Using GreenGate Cloning
3.2 PCR Amplification of Insert DNA
3.3 Entry Module Preparation
3.4 Destination Module Preparation
3.5 Intermediate Supermodule Preparation
3.6 Transform the Plant Expression Vector into A. tumefaciens
3.7 Generation of Transgenic Arabidopsis Plants
3.8 Induction of Trans-Activation in Arabidopsis Driver Lines
3.8.1 Root
3.8.2 Shoot Apical Meristem (SAM)
3.8.3 Stem
3.9 Imaging of Reporter Expression in Arabidopsis Driver Lines
3.9.1 Root
3.9.2 Shoot Apical Meristem
3.9.3 Stem
4 Notes
References
Chapter 3: Targeted Activation of Arabidopsis Genes by a Potent CRISPR-Act3.0 System
1 Introduction
2 Materials
2.1 Plant and Bacterial Strains
2.2 Plasmids
2.3 Vector Construction
2.4 Culture Media and Stock Solutions
2.5 Arabidopsis Transformation Using the Floral Dip Method
2.6 qRT-PCR Analysis of Transgenic Plants
3 Methods
3.1 Growth of Arabidopsis Plants
3.2 CRISPR-Act3.0 Construct Assembly
3.2.1 sgRNA Design for Targeted Gene Activation
3.3 Floral Dipping Transformation of Arabidopsis Plants
3.4 Quantitate the Activation Level of Target Genes in Transgenic Plants
4 Notes
References
Chapter 4: Single Cell RNA-Sequencing in Arabidopsis Root Tissues
1 Introduction
2 Materials
2.1 Plant Material
2.2 Generating Protoplasts
2.3 Quality/Quantity Assessment
2.4 Flow Cytometry
2.5 Library Preparation and Sequencing
3 Methods
3.1 Plant Material Preparation
3.2 Protoplast Generation
3.3 Sample Preparation for Direct Loading
3.4 Sample Preparation for Flow Cytometry
3.5 Loading Protoplasts
3.6 10x Genomics Sample Preparation, Library Construction, and Sequencing
3.7 Computational Workflow
3.7.1 Build the Arabidopsis Genome Reference
3.7.2 Read the Filtered Feature-Barcode Matrices in R and Clean the Data
3.7.3 Preprocessing of the Data
3.7.4 Normalizing the Raw Counts
3.7.5 Detecting Highly Variable Genes
3.7.6 Scaling the Data
3.7.7 Performing Linear Dimensional Reduction (PCA)
3.7.8 Clustering and Visualization
3.7.9 Cell Identity Assignment and Validation
4 Notes
References
Chapter 5: Analysis of Chromatin Accessibility, Histone Modifications, and Transcriptional States in Specific Cell Types Using…
1 Introduction
2 Materials
2.1 In Vitro Plant Cultivation
2.2 Protoplasting
2.3 Nuclei Isolation from Protoplasts
2.4 Sorting (FACS/FANS)
2.5 RNA-seq Library
2.6 ATAC-seq Library
2.7 ChIP-seq Library
3 Methods
3.1 Protoplast Generation and Purification
3.2 Nuclei Isolation from Protoplasts
3.3 FACS
3.4 FANS
3.5 RNA-seq Paired-End Library Preparation (Protoplasts)
3.6 ATAC-seq Paired-End Library Preparation (Nuclei)
3.7 ChIP-seq Paired-End Library Generation (Nuclei)
4 Notes
References
Chapter 6: Untargeted Proteomics and Metabolomics Analysis of Plant Organ Development
1 Introduction
2 Materials
2.1 Plant Material (See Notes 1 and 2)
2.2 Protein and Metabolite Extraction (as Described in) (See Notes 3, 5 and 9)
2.3 Metabolomic Reagents (Using MS-Grade Reagents) (as Described in)
2.4 Lipidomic Reagents (Using MS-Grade Reagents) (as Described in)
2.5 Proteomic Reagents (Using MS-Grade Reagents)
3 Methods
3.1 Metabolite and Protein Extraction (See Note 5)
3.2 Lipidomic Analysis
3.3 Metabolomic Analysis
3.4 Proteomic Analysis (See Notes 8 and 9)
3.5 Data Integration
4 Notes
References
Chapter 7: DamID-seq: A Genome-Wide DNA Methylation Method that Captures Both Transient and Stable TF-DNA Interactions in Plan…
1 Introduction
2 Materials
2.1 Cloning
2.2 Plant Growth and Protoplasting
2.3 Solutions
2.4 Protoplast Transfections
2.5 DNA Preparation
2.6 DamID
2.7 DNA Library Preparation
2.8 Equipment
3 Methods
3.1 Vector Cloning and Preparation
3.2 Plant Growth and Protoplast Isolation
3.3 Protoplast Transfection and Treatments (TARGET)
3.4 Isolation and Amplification of Methylated DNA Fragments (DamID)
3.5 Library Preparation and Sequencing
3.6 Data Analysis: TF-Target Gene Identification
4 Notes
References
Chapter 8: CUT&Tag for Mapping In Vivo Protein-DNA Interactions in Plants
1 Introduction
2 Materials
2.1 Formaldehyde Fixation
2.2 Nuclei Isolation
2.3 CUT&Tag
2.4 DNA Purification and Library Amplification
3 Methods
3.1 Formaldehyde Fixation
3.2 Nuclei Isolation
3.3 CUT&Tag
3.4 DNA Purification and Library Amplification
4 Notes
References
Chapter 9: Identification of Plant Transcription Factor DNA-Binding Sites Using seq-DAP-seq
1 Introduction
2 Materials
2.1 Equipment
2.2 Kits
2.3 Reagents and Materials
2.4 Buffers
2.5 Primers
2.6 Bioinformatics Requirements
3 Methods
3.1 DAP-seq and ampDAP-seq Input Library Preparation
3.1.1 ampDAP Libraries Without DNA Modifications (Fig. 5)
3.2 TF Expression, TF Complex Formation, and Sequential Pull Down
3.3 Binding of DNA to Immobilized TF Complex
3.4 DNA Amplification, Pooling, and Sequencing
3.5 Bioinformatic Analysis (Fig. 10)
4 Notes
References
Chapter 10: Estimating DNA-Binding Specificities of Transcription Factors Using SELEX-Seq
1 Introduction
2 Materials
2.1 Double-Stranded DNA Library Preparation
2.2 Protein (Protein Complex) In Vitro Synthesis
2.3 First Round (R1) of SELEX
2.4 PCR Amplification of the Selected DNA Fragments
2.5 Validation of SELEX by Electrophoretic Mobility Shift Assay (EMSA)
2.6 High-Throughput Sequencing of the SELEX Libraries
3 Methods
3.1 Double-Stranded DNA Library Preparation
3.2 Protein (Protein Complex) In Vitro Synthesis
3.3 First Round (R1) of SELEX
3.4 PCR Amplification of the Selected DNA Sequences
3.5 Subsequent Rounds (Rx) of SELEX
3.6 Validation of SELEX by Electrophoretic Mobility Shift Assay (EMSA)
3.7 High-Throughput Sequencing of the SELEX Libraries
4 Bioinformatics Analysis
5 Notes
References
Chapter 11: Immunoprecipitation-Mass Spectrometry (IP-MS) of Protein-Protein Interactions of Nuclear-Localized Plant Proteins
1 Introduction
2 Materials
2.1 Plant Lines
2.2 Common Material
2.3 Nuclear Protein Extraction and Protein Immunoprecipitation
2.4 IP and Input Sample Processing
2.5 Peptide Desalting
2.6 Liquid Chromatography-Mass Spectrometry (LC-MS)
2.7 Data Analysis
3 Methods
3.1 Plant Tissue Preparation
3.2 Nuclear Protein Extraction
3.3 Protein Immunoprecipitation
3.4 Input Sample Processing
3.5 IP Sample Processing
3.6 Peptide Desalting
3.7 LC-MS Measurements (See Note 9)
3.8 Protein Identification, Label-Free Quantification, and Data Analysis
4 Notes
References
Chapter 12: Mapping Active Gene-Associated Chromatin Loops by ChIA-PET in Rice
1 Introduction
2 Materials
2.1 Dual Crosslinking
2.2 Nuclei Lysis
2.3 Chromatin Immunoprecipitation
2.4 Proximity Ligation
2.5 Reverse Crosslinking and DNA Purification
2.6 Library Preparation and Sequencing
3 Methods
3.1 Dual Crosslinking
3.2 Nuclei Lysis and Chromatin Fragmentation
3.3 Chromatin Immunoprecipitation
3.4 Proximity Ligation
3.5 Reverse Crosslinking and DNA Purification
3.6 Library Preparation and Sequencing
4 Notes
References
Chapter 13: Building High-Confidence Gene Regulatory Networks by Integrating Validated TF-Target Gene Interactions Using Conne…
1 Introduction
2 Materials
3 Methods
3.1 Intersecting Validated TF-Target Interaction Datasets
3.2 Network Walking: Unified Networks Linking Direct Targets to In Planta Responses
3.3 Pruning Predicted TF-Target Interactions with Precision-Recall Analysis
3.4 Setting Up a Private Instance of ConnecTF
4 Notes
References
Chapter 14: The ChIP-Hub Resource: Toward plantEncode
1 Introduction
2 A User Guide for the ChIP-Hub Website
2.1 Resources of the ChIP-Hub Website
2.2 Search with ChIP-Hub
2.3 Online Analysis by ChIP-Hub
2.4 Download Data
3 Integrative Analyses with ChIP-Hub
3.1 Comparative Genomic Analysis by “lastz to ́ ́
3.2 Chromatin State Analysis
4 Perspectives
5 Notes
References
Chapter 15: A Practical Guide to Inferring Multi-Omics Networks in Plant Systems
1 Introduction
2 Materials
2.1 Software
2.2 Data
3 Methods
3.1 Setup
3.2 Transcriptomics Data Preprocessing
3.2.1 Downloading RNA Sequencing Data from SRA
3.2.2 Preprocessing RNA-seq Data
3.3 Proteomics Data preprocessing
3.3.1 Downloading Raw Proteomics Files from ProteomeExchange
3.3.2 Preprocessing Proteomics Data
3.4 Network Inference Using SC-ION
3.4.1 Preprocessing Data Tables for SC-ION
3.4.2 Running the SC-ION RShiny Application
3.5 Network Visualization and Analysis Using Cytoscape
3.5.1 Importing SC-ION Networks into Cytoscape
3.5.2 Merging Networks in Cytoscape
3.5.3 Importing Additional Information from Tables into Cytoscape Networks
3.5.4 Changing Network Visualization Parameters in Cytoscape
3.5.5 Network Motif (Importance) Score Calculation Using NetMatch* and R
4 Notes
References
Chapter 16: Gene Regulatory Network Modeling Using Single-Cell Multi-Omics in Plants
1 Introduction
2 Materials
2.1 Multi-Omics Integration with Seurat
2.1.1 Download Data for scATAC-seq + scRNA-seq
2.1.2 Install R Packages
2.2 Install Anaconda and Create an Environment for Machine Learning Project
2.3 Download and Install FIMO
2.4 Download Input Data for FIMO Analysis
3 Methods
3.1 Multi-Omics Integration with Seurat
3.1.1 Preprocessing scRNA-seq and scATAC-seq Data
3.1.2 Integrate RNA-seq and ATAC-seq
3.1.3 Marker Gene Identification
3.2 Running FIMO Analysis and Machine Learning
3.2.1 Summarizing the FIMO Outputs
3.2.2 Creating a Data Matrix
3.2.3 Selecting the Genes for Training the Machine Learning Algorithms
3.2.4 Applying the Machine Learning Models on the Dataset
4 Notes
References
Chapter 17: Methodology for Constructing a Knowledgebase for Plant Gene Regulation Information
1 Introduction
1.1 Need for Plant GRN Knowledgebases and Their Maintenance
1.2 The GRASSIUS Plant GRN Knowledgebase
1.3 Stages and Goals of Implementing a Plant GRN Knowledgebase
2 Materials
2.1 Hardware Needs-Minimal and Preferred
2.2 Expertise Required
3 Methods
3.1 Data Scope Definition
3.1.1 Identification and Classification of TF Repertoire for a Plant Species
3.1.2 Identification of TF-Target Gene Interactions [Protein-DNA Interactions (PDIs)]3.1.3 Mapping of Transcription Start Sites (TSSs)-CAGE and Other Techniques
3.1.4 Prediction of TF DNA-Binding Sites
3.2 Schema Design
3.3 Implementation of the Database
3.3.1 Implementing Grassius in the Chado Schema
3.3.2 Population of the Database
3.4 User Interface Development
3.4.1 Web Server Setup
3.4.2 Creation of the Web Application
3.4.3 Development of User Views
3.4.4 Development of Queries (Example)
3.4.5 Implementation of Search Features
3.4.6 Addition of Graphic Displays
3.4.7 Addition of Interactive Tools
3.4.8 Development of the User Interface
4 Notes
References
Chapter 18: Predicting Gene Regulatory Interactions Using Natural Genetic Variation
1 Introduction
2 Materials
2.1 Data Needed for the Analyses
2.2 Computational Infrastructure
2.3 Software
3 Methods
3.1 Data Needed to Perform GWAS
3.2 Statistical Model for GWAS
3.3 Workflow to Perform Univariate GWAS
3.4 More Complex GWAS Models
3.4.1 The Multi-Locus Mixed Model
3.4.2 2D-GWAS
3.4.3 Integrating Knowledge About Protein-Protein Interactions
3.4.4 Integrating Gene Expression Data
3.5 Future Perspectives
4 Notes
References
Chapter 19: Prediction of Transcription Factor Regulators and Gene Regulatory Networks in Tomato Using Binding Site Information
1 Introduction
2 Materials
2.1 Bioinformatics Resources
2.2 Data and Code Availability
2.3 Gene ID Conversion Protocol
2.4 Set of Functionally Related or Coregulated Genes
2.5 Tomato Motif Mapping and Enrichment Protocol
2.6 Gene Ontology (GO) Enrichment with PLAZA Dicots 5.0 Workbench
2.7 Functional Network Visualization Using Cytoscape
2.7.1 Genes Within the Gene Set Annotated to a Specific GO Term
2.7.2 All Genes Annotated to a Specific GO Term
2.7.3 Cytoscape Network Visualization
3 Methods
3.1 Conversion of Gene Identifiers (IDs) Between ITAG 2.5 and ITAG 4.0 Genome Annotations
3.2 Running a Motif Enrichment Analysis
3.3 Analysis of Motif Enrichment Results
3.4 Functional GO Analysis of the Motif Enrichment Results
3.5 Visualization of Functional Networks Obtained Through Motif Enrichment
4 Notes
References
Chapter 20: AGENT for Exploring and Analyzing Gene Regulatory Networks from Arabidopsis
1 Introduction
2 Materials
3 Methods
3.1 Exploring Curated GRNs in AGENT
3.2 Network Motif Discovery and Network Attributes
3.3 Expression Overlay
4 Notes
References
Chapter 21: A Transferable Machine Learning Framework for Predicting Transcriptional Responses of Genes Across Species
1 Introduction
2 Materials
2.1 Transcriptomic Data
2.2 Working Environment
2.3 Software Installation
3 Methods
3.1 Label Responsive and Nonresponsive Genes
3.1.1 RNA-seq Data Processing
3.1.2 Differential Expression Gene Analysis
3.2 Binning of Responsive and Nonresponsive Genes
3.3 Quantifying Gene Features
3.3.1 Sorghum Example Data Set
3.3.2 Feature Extraction
3.3.3 Merge Genomic Features and Gene Classification Label
3.4 Gene-Family Clustering
3.5 Model Training/Hyperparameter Tuning
3.6 Model Evaluation
3.7 Cross-Species Predictions
4 Notes
References
Index

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Tags: Kerstin Kaufmann, Klaas Vandepoele, Plant Gene, Regulatory Networks