Bacterial pangenomics : methods and protocols

Preface
	Reference
Contents
Contributors
Part I: Opportunities from Novel Sequencing Technologies
	Chapter 1: PacBio-Based Protocol for Bacterial Genome Assembly
		1 Introduction
		2 Materials
			2.1 General Purpose
			2.2 Biological Material
			2.3 Computer Hardware
			2.4 Computer Software
		3 Methods
			3.1 Obtaining of PacBio Reads
			3.2 Primary Analysis: Quality Control and Adapter Trimming with SMRT Analysis
			3.3 Assembly of PacBio  Data
			3.4 Polishing the Assembled Genomes with PacBio  Data
			3.5 Functional Annotation of the Genomes
		4 Notes
		References
	Chapter 2: The Illumina Sequencing Protocol and the NovaSeq 6000 System
		1 Introduction
		2 Materials
			2.1 General Equipment and Reagents
			2.2 Proprietary Reagents and Materials from Illumina
		3 Methods
			3.1 Preparation of the Sequencing Pool
				3.1.1 Validation, Quality Control, and Quantification of the Sequencing Libraries
				3.1.2 Pooling Libraries for Sequencing
			3.2 NovaSeq 6000 Sequencing Workflow
				3.2.1 Standard Workflow
					Thaw SBS and Cluster Cartridges
					Prepare Flow Cell
					Denature Library Pool and PhiX Control for Sequencing
					Prepare SBS and Cluster Cartridges
				3.2.2 XP Workflow
					Thaw SBS and Cluster Cartridge
			3.3 Set Up Sequencing Run
		4 Notes
		References
Part II: Pangenomics of Cultured Isolates
	Chapter 3: Comparative Analysis of Core and Accessory Genes in Coexpression Network
		1 Introduction
		2 Materials
			2.1 Genome and Gene Expression  Data
			2.2 Bioinformatic Tools
		3 Methods
			3.1 Core Gene Definition
				3.1.1 Ortholog Inference
				3.1.2 Phylogenetic Tree Construction
				3.1.3 Core Gene Identification
			3.2 Construction of Coexpression Network
				3.2.1 Input Data for WGCNA
				3.2.2 Select Soft Thresholding Power β
				3.2.3 Calculating Adjacency Matrix and Topological Overlap Matrix
			3.3 Module Detection
			3.4 Sample Clustering
			3.5 Network Visualization
			3.6 Relate the Network Concepts to External Gene Information
				3.6.1 Comparative Analysis of Different Subset Genes
				3.6.2 Functional Enrichment Analysis
		4 Notes
		References
	Chapter 4: Inferring Core Genome Phylogenies for Bacteria
		1 Introduction
		2 Dependencies and Installation
			2.1 General Computing Environment
			2.2 Assembly and Annotation
			2.3 Core Genome Phylogenetic Analyses
			2.4 Visualization
		3 Data Analysis
			3.1 Test Data
			3.2 Assembly and Annotation
			3.3 Single-Copy Core Gene Extraction and Phylogenomic Analysis
			3.4 Visualization
		4 Notes
		References
	Chapter 5: Inferring Phylogenomic Relationship of Microbes Using Scalable Alignment-Free Methods
		1 Introduction
		2 Materials
			2.1 Data
			2.2 Software
		3 Methods
			3.1 Generation of Pairwise Distance Matrix Using k-mers
			3.2 Inference of Phylogenetic  Tree
			3.3 Calculation of Jackknife Support Values for Each Node (Optional)
			3.4 Inference of Phylogenomic Networks (Optional)
		4 Notes
		References
	Chapter 6: Fast Phylogeny Reconstruction from Genomes of Closely Related Microbes
		1 Introduction
		2 Method
			2.1 Distance Estimation
			2.2 Support Values
		3 Application
			3.1 Simulated Data
			3.2 Genome Data
		4 Discussion
		References
	Chapter 7: Comparative Genomics, from the Annotated Genome to Valuable Biological Information: A Case Study
		1 Introduction
		2 Materials
			2.1 Genomic Sequences
			2.2 Computer Hardware
			2.3 Computer Software
		3 Methods
			3.1 Genome Annotation
				3.1.1 Prokka
				3.1.2 PGAP
			3.2 Whole-Genome Comparison and Synteny Analyses
				3.2.1 JSpecies
				3.2.2 Mauve
				3.2.3 BRIG
			3.3 Functional Assignment
				3.3.1 Egg-NOG-Mapper
				3.3.2 antiSMASH
			3.4 Detection of Defined Sequences of Interest
				3.4.1 IslandViewer
				3.4.2 CRISPRCasFinder
				3.4.3 Phast/Phaster [35]
				3.4.4 PlasmidFinder
			3.5 Pangenome Analysis
				3.5.1 BPGA
				3.5.2 Roary
		4 Notes
		References
Part III: Dark Matter Pangenomics
	Chapter 8: Accurate Annotation of Microbial Metagenomic Genes and Identification of Core Sets
		1 Introduction
		2 Materials
		3 Methods
			3.1 First Section
				3.1.1 Gene Prediction
				3.1.2 Gene Clustering
				3.1.3 Functional Annotation of the Gene Clusters
				3.1.4 Remote-Homology Detection
				3.1.5 Taxonomy Assignment
				3.1.6 First Section Output
			3.2 Second Section
				3.2.1 How to Use Gene Clusters to Explore Pangenomes Using Anvi´o
				3.2.2 Create a Collection of Metagenome-Assembled Genomes (MAGs)
				3.2.3 Building a Pangenome with Anvi´o
		4 Notes
		References
	Chapter 9: Metagenomic Assembly: Reconstructing Genomes from Metagenomes
		1 Introduction
		2 Materials
			2.1 Raw Read Files
			2.2 Hardware
			2.3 Software
		3 Methods
			3.1 Quality Assessment of Raw Sequencing Reads
			3.2 Quality Trimming of Raw Sequencing Reads
			3.3 Metagenomic Assembly to Generate Contigs or Scaffolds
			3.4 Assignment of Assembled Contigs/Scaffolds to Genomic ``Bins´´
			3.5 Postassembly Quality Evaluation
			3.6 Potential Applications of Recovered Genomes for Downstream Analyses
		4 Case Study
		References
	Chapter 10: Genome Recovery, Functional Profiling, and Taxonomic Classification from Metagenomes
		1 Introduction
		2 Materials
			2.1 Input Files
			2.2 Software and Hardware Requirements
		3 Methods
			3.1 Quality Control and Filtering
			3.2 Assembly
			3.3 Binning
				3.3.1 Mapping Reads to the Assembly
				3.3.2 Computing Coverage Depth
				3.3.3 Run MetaBat 2
			3.4 Quality Assessment and Dereplication
			3.5 Taxonomic Classification
			3.6 Functional Annotation
				3.6.1 Annotating Using Prokka
				3.6.2 Annotating Using EggNOG-Mapper
		4 Notes
		References
	Chapter 11: Functional Metagenomics for Identification of Antibiotic Resistance Genes (ARGs)
		1 Introduction
			1.1 Notes for Readers
		2 Materials
			2.1 Metagenomic Sequences, Contigs Files, and Taxonomic Profiles
			2.2 Software
		3 Methods
			3.1 Coverage from Metagenomic Data and Its Analysis
			3.2 ARGs Identification
		4 Conclusions
		References
	Chapter 12: Host Trait Prediction from High-Resolution Microbial Features
		1 Introduction
		2 Materials
			2.1 Data Files
			2.2 Software Requirements
		3 Methods
			3.1 Importing  Data
			3.2 Data Transformation
			3.3 Training Models
			3.4 Model Evaluation
			3.5 Selecting Bacterial Features
		References
Part IV: Progresses in Genome-to-Phenome Inference
	Chapter 13: Phylogenetic Methods for Genome-Wide Association Studies in Bacteria
		1 Introduction
		2 Materials
			2.1 Genomic Data
			2.2 Phenotypic Data
			2.3 Software
		3 Methods
			3.1 Genome Alignment
			3.2 Phylogenetic Inference
			3.3 Analysis of Phenotypic Distribution
			3.4 Selection of Genetic Variants to Be Tested
			3.5 Measuring the Strength of Association
			3.6 Assessing Statistical Significance
			3.7 Correction for Multiple Testing
			3.8 Interpretation of Results
			3.9 Graphical Representation of Results
		4 Notes
		References
	Chapter 14: Simple, Reliable, and Time-Efficient Manual Annotation of Bacterial Genomes with MAISEN
		1 Introduction
			1.1 MAISEN Data Processing
			1.2 Other Reference Databases
			1.3 MAISEN Annotation Pipeline
		2 Materials
			2.1 Input Prokaryotic DNA Sequences
			2.2 Hardware and Software
		3 Methods
			3.1 Sequence Submission
			3.2 Computation Results and Interface
				3.2.1 Sequence Statistics Panel
				3.2.2 Sequence Browser
				3.2.3 Alignment  Hits
				3.2.4 Feature Details
			3.3 Manual Annotation Procedure
				3.3.1 tRNA Coding Sequences
				3.3.2 CDS Annotation
					Functional Annotation
					Using External Databases for Functional Annotation
					CDS Trimming and Extension
			3.4 Download the Annotation
		4 Notes
		References
Part V: Cookbook for Pangenomics
	Chapter 15: A Compendium of Bioinformatic Tools for Bacterial Pangenomics to Be Used by Wet-Lab Scientists
		1 Introduction
		2 Databases
			2.1 National Center for Biotechnology Information (NCBI)
			2.2 Integrated Microbial Genomes and Microbiomes (IMG/M)
		3 Genome Analysis Pipelines
			3.1 Prokka
			3.2 CD-HIT
			3.3 Roary
			3.4 GET_ HOMOLOGUES
			3.5 PGAP
			3.6 PanSeq
			3.7 BPGA
			3.8 panX
			3.9 MetaRef
		4 Phylogenetic Analysis
			4.1 RAxML (Randomized Axelerated Maximum Likelihood)
			4.2 SNVPhyl (Single Nucleotide Variant Phylogenomics)
		5 General Tool for Multiple Use
			5.1 Galaxy
			5.2 Kbase
			5.3 Epiviz
			5.4 Genome Modeling System (GMS)
		6 RNAseq
			6.1 Rockhopper
			6.2 ZENBU
		7 Simulation for RNAseq Data Analysis in Kbase
			7.1 Pros and Cons for Kbase Pipeline Utilization
		8 Conclusions
		References
	Chapter 16: A Protocol for Teaching Basic Next Generation Sequencing (NGS) Analysis Skills to Undergraduate Students Using Bas...
		1 Introduction
		2 Materials
			2.1 Data Files
			2.2 Software Requirements
		3 Methods
			3.1 Quality Check of Reads
			3.2 Coverage Estimation, Calculation, and Visualization
			3.3 Per Gene Coverage Computation
			3.4 RPKM and FPKM Computation and Data Visualization
		4 Notes
		References
Index