RNA-Seq in Drug Discovery and Development

Description

The research and development process in modern drug discovery and development is a complex and challenging task. Using traditional biological test methods such as PCR to measure the expression levels or function of these genes is costly and time-consuming. RNA-seq can measure the expression patterns of thousands of genes simultaneously and provide insights into functional pathways or regulations in biological processes, which has revolutionized the way biological scientists examine gene functions. This book addresses the various aspects of the RNA-seq technique, especially its application in drug discovery and development. Features • One of the few books that focuses on the applications of the RNA-seq technique in drug discovery and development • Comprehensive and timely publication which relates RNA sequencing to drug targets, mechanisms of action, and resistance • The editor has extensive experience in the field of computational medicinal chemistry, computational biophysics, and bioinformatics • Chapter authors are at the frontline of the academic and industrial science in this particular area of RNA sequencing Cover Half Title Series Page Title Page Copyright Page Table of Contents Preface Editors Contributors Chapter 1 Introduction to RNA Sequencing and Quality Control 1.1 What is RNA Sequencing? 1.1.1 What is RNA? 1.1.2 What is RNA-seq? 1.2 cDNA Library Preparation in RNA-seq 1.2.1 Isolation of the RNA and RNA Quality Check 1.2.2 Selection and Depletion of Particular RNA 1.2.3 Fragmentation 1.2.4 Reverse Transcription to Generate cDNA and Adaptor Sequences 1.2.5 Single-End and Paired-End Sequencing Technique 1.3 RNA-seq Techniques and Platforms 1.3.1 Roche 454 1.3.2 Illumina Platform 1.3.3 Small-Scale RNA-seq Platform 1.3.4 Third-Generation Sequencing 1.4 RNA-seq File Format 1.4.1 Output File: FASTQ File 1.4.2 Mapped File: SAM/BAM/BIGWIG Formats 1.4.3 GTF File 1.4.4 BED File 1.5 Quality Control of RNA-seq Data 1.5.1 Basic Usage of the Public Server Galaxy 1.5.2 FastQC Program 1.5.3 Trimmomatic Tool for Adapter Trimming 1.6 Advantages of RNA-seq Over Expression Microarrays 1.7 Summary Keywords and Phrases Bibliography Chapter 2 Read Alignment and Transcriptome Assembly 2.1 Transcriptome Assembly Methodology 2.2 Genome-Guided Assembly 2.2.1 Unspliced Aligners: Burrows–Wheeler Transform (BWT) 2.2.1.1 BWT Method 2.2.1.2 EXACTMATCH Method 2.2.2 Unspliced Aligners: Seed Methods 2.2.3 Spliced Aligners: TopHat 2.2.4 Spliced Aligners: HISAT2 2.2.5 Spliced Aligners: STAR 2.3 De Novo Assembly 2.3.1 Trinity Package 2.4 Summary Keywords and Phrases Bibliography Chapter 3 Normalization and Downstream Analyses 3.1 Quantification of Transcript Abundance 3.2 Raw Counts Extraction 3.2.1 Rsubread and Featurecounts 3.3 Normalization Methods 3.4 Differential Gene Expression Analysis 3.4.1 DESeq2 3.4.2 EdgeR 3.4.3 Ballgown 3.5 Visualization of Differential Expression 3.5.1 Integrative Genomics Viewer 3.5.2 UCSC Genome Browser 3.5.3 Heatmaps 3.5.4 Volcano Plots 3.6 Pathway Analysis Using the NIH DAVID Web Server 3.7 Summary Keywords and Phrases Bibliography Chapter 4 Constitutive and Alternative Splicing Events 4.1 What is Splicing? 4.2 Molecular Mechanism of Splicing 4.3 Alternative Splicing 4.4 Differential Splicing Analysis 4.4.1 Cuffdiff 2 4.4.2 DiffSplice 4.4.3 DEXSeq 4.4.4 edgeR 4.4.5 LIMMA 4.5 Summary Keywords and Phrases Bibliography Chapter 5 The Role of Transcriptomics in Identifying Fusion Genes and Chimeric RNAs in Cancer 5.1 Fusion Gene 5.1.1 What is a Fusion Gene 5.1.2 Mechanisms that Generate New Fusion Genes 5.1.3 Fusion RNA Transcripts 5.1.4 The Connection between Fusion Genes and Non-Coding RNAs 5.2 Detection Methods for Identification of Fusion Genes and Chimeric Proteins 5.2.1 Guided Detection Approaches 5.2.2 High-Throughput Sequencing-Based Detection Methods 5.2.3 ChimPipe 5.2.3.1 Exhaustive Paired-End and SPLIT Read Mapping with Genome Multitool GEM 5.2.3.2 ChimSplice 5.2.3.3 ChimPE 5.2.3.4 ChimFilter 5.2.4 GFusion 5.2.4.1 The Beginning Alignment 5.2.4.2 Anchors 5.2.4.3 Alignment and Localization 5.2.4.4 Fusion Boundaries 5.2.4.5 Confirming Fusion Models 5.2.4.6 Grouping Candidate Fusions 5.2.4.7 Fusion Index and Realignment 5.2.5 InFusion 5.2.5.1 Short Reads Alignment 5.2.5.2 Local Short Reads Alignment 5.2.5.3 Local Alignment Analysis 5.2.5.4 Analysis of End-to-End Alignments 5.2.5.5 Clustering and Establishing Putative Fusions 5.2.5.6 Purifying and Filtering Fusions 5.2.5.7 Reporting Fusions 5.2.6 STAR-Fusion 5.3 Summary Keywords and Phrases Bibliography Chapter 6 MiRNA and RNA-seq 6.1 MiRNAs 6.1.1 What are miRNAs? 6.1.2 Generation of miRNAs 6.2 lncRNAs 6.2.1 What are lncRNAs? 6.2.2 Generation and Structure of lncRNAs 6.3 miRDeep2 6.3.1 Methodology of miRDeep2 6.3.2 MirDeep2 Galaxy Example 6.4 Applications 6.4.1 Non-Coding RNAs in Hypertrophic Cardiomyopathy 6.4.2 miRNA-Regulated Drug-Pathway (MRDP) Network 6.5 Summary Keywords and Phrases Bibliography Chapter 7 Toxicogenomics and RNA-seq 7.1 Introduction of Toxicology 7.1.1 What is Toxicology? 7.1.2 Mechanisms of Toxicity 7.1.3 In Vivo Animal Model in Toxicology 7.2 Toxicogenomics 7.2.1 What is Toxicogenomics? 7.2.2 The Advantage of Toxicogenomics 7.2.3 Limitations of Toxicogenomics: 7.3 Methods for Toxicogenomics Data Analysis 7.3.1 Identification of Differentially Expressed Genes 7.3.2 Gene Networks 7.3.3 Co-Expression Networks 7.3.3.1 Context Likelihood of Relatedness 7.3.3.2 Weighted Gene Co-expression Network Analysis 7.3.4 Signature Matching 7.4 Toxicogenomics Databases 7.4.1 Comparative Toxicogenomics Database 7.4.2 Japanese Toxicogenomics Project 7.4.3 DrugMatrix 7.5 Comparing Microarray vs. RNA-seq 7.6 Summary Keywords and Phrases Bibliography Chapter 8 Herbal Medicine and RNA-seq 8.1 What is Herbal Medicine? 8.1.1 Traditional Medicine 8.1.2 Herbal Medicine 8.1.3 Use of Database for Bioactive Compound Example 8.1.4 Properties of Candidate Herbal Compounds 8.1.5 RNA-seq and Herbal Medicine 8.2 Mining Functional Genes of Medicinal Plants 8.3 Discovery of Secondary Metabolites and their Metabolic Pathways 8.4 Discovery of Developmental Mechanisms 8.5 Development of Molecular Markers to Improve Plant Breeding 8.6 Identification of Target Genes and Molecular Mechanisms of Herbal Drugs 8.7 Synergism of Herbal Compounds in Pathway Regulation 8.8 Herbal Medicine Toxicity 8.9 Natural Drug Repurposing 8.10 Summary Keywords and Phrases Bibliography Chapter 9 Single-Cell RNA Sequencing 9.1 Introduction to Single-Cell RNA Sequencing 9.2 Microdroplet Approaches to Cell Capture 9.2.1 Drop-Seq Platform 9.2.2 Chromium System 9.3 Non-Microfluidic Approaches to Cell Capture 9.3.1 Fluorescence-Activated Single-Cell Sorting (FACS) 9.3.2 CytoSeq 9.3.3 SPLiT-seq 9.4 scRNA-seq Output Data 9.4.1 Amplification Step in scRNA-seq 9.4.2 Output Data of scRNA-seq 9.5 scRNA-seq Data Analysis 9.5.1 ScRNA-seq Analysis Program 1: Cell Ranger 9.5.2 ScRNA-seq Analysis Program 2: STARsolo 9.5.3 ScRNA-seq Analysis Program 3: DropletUtils 9.5.4 ScRNA-seq Analysis Program 4: Seurat 9.6 Limitations of scRNA-seq 9.7 Applications of scRNA-seq in Drug Discovery 9.8 Summary Keywords and Phrases Bibliography Index