Cap-Analysis Gene Expression (CAGE) : The Science of Decoding Genes Transcription book cover
1st Edition

Cap-Analysis Gene Expression (CAGE)
The Science of Decoding Genes Transcription

Edited By

Piero Carninci

ISBN 9789814241342
Published October 31, 2009 by Jenny Stanford Publishing
266 Pages 19 Color & 31 B/W Illustrations

USD $170.00

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Book Description

This book is a guide for users of new technologies, as it includes accurately proven protocols, allowing readers to prepare their samples for experiments. Additionally, it is a guide for the bioinformatics tools that are available for the analysis of the obtained tags, including the design of the software, the sources and the Web. Finally, the book provides examples of the application of these technologies to identify promoters, annotate genomes, identify new RNAs and reconstruct models of transcriptional control. Although examples mainly concern mammalians, the discussion expands to other groups of eukaryotes, where these approaches are complementing genome sequencing.

Table of Contents

Preface v
Cap Analysis Gene Expression (CAGE)
Tagging Transcription Starting Sites with CAGE
The Output of the Genome is Complex
Mapping 5’ Ends: From ESTs to Tagging Technologies
Linking Core Promoters to Genomic Elements
cDNA Ends or the Whole Sequence?
Identification of Functional Elements in the Genome
Technology Evolution, Same Lessons?
Construction of CAGE Libraries
Stage 1: Synthesis of First-Strand cDNA
Stage 2: Oxidation/Biotinylation
Stage 3: Capture-Release
Stage 4: Single Strand Linker Ligation
Stage 5: the Second Strand cDNA Synthesis
Stage 6: Preparing CAGE Tags
Stage: 7 Amplification of CAGE Tags
Stage 8: Restriction
Stage 9: Concatenation
Transcriptome and Genome Characterization Using Massively Parallel Paired End Tag (PET) Sequencing Analysis
The Development of Pair end diTag (PET) Analysis
GIS-PET for Transcriptome Analysis
ChIP-PET for Whole Genome Mapping of Transcription Factor Binding Sites and Epigenetic Modifications
ChIA-PET for Whole Genome Identification of Long Range interactions
New Era of Genome-Wide Gene Expression Analysis
Tagging Technologies for Genome-Wide Analysis
Principles of Next Generation Sequencing Technologies
Genome Analyzer (Illumina/Solexa)
SOLiD System (Applied Biosystems)
Advantages of Next Generation Sequencing Technologies over Conventional Sequencing Technology on Tagging Technologies
From Static Analysis to Dynamic Analysis
CAGE Method and Next Generation Sequencing Technologies
Conclusions and Outlook
Computational Tools to Analyze CAGE
Introduction to PART II
Extraction and Quality Control of CAGE Tags
Using Read Qualities and Read Properties, Pre- and Post-Extraction
Procedures Before Tag Extraction
Using QC Values After Tag Extraction
Origin of Sequence Errors
Using Sequence Errors to Estimate CAGE Quality
A Simple CAGE Tag Extraction Method
Setting CAGE Tags in a Genomic Context
Mapping Pipelines for Sequence Tag Technologies
A Mapping Pipeline for CAGE
Benchmarking with a Sample Dataset
Using CAGE Data for Quantitative Expression
High Throughput Expression Platforms
Comparing CAGE to Other Measures of Gene Expression
Platform Normalization
Gene Models and Complex Loci
Construction of CAGE Promoters and Calculation of Gene Expression Levels
Comparison of CAGE Expression between Technical Replicates
Comparison of CAGE Expression from Biological Replicates
Comparison of CAGE Expression Between Different Time Points Within a Single Time-Course
Comparison of CAGE Expression Profiling to qRT-PCR Expression Measurements
Comparison of CAGE Expression Profiling to MicroarrayMeasurements
Present/Absent Calls
Databases for CAGE Visualization and Analysis
Transcription Maps and Activity
Public Databases
Genomic View of In-House Data
For Expression Analyses
Computational Methods to Identify Transcription Factor Binding Sites Using CAGE Information
Schema of the Methodology Process
Initial Links of TF with the Affected Genes
Correlation of CAGE Tag Counts of Genes and TFs
Ranking TF!TFBS!TSS/Promoter!GENE Association: The Effective Use of CAGE Tags
Verification of Results
Reconstruction of TRNs
Transcription Regulatory Networks Analysis Using CAGE
CAGE Data for Network Reconstruction
Gene Expression Data Complementary to CAGE for Network Reconstruction
Using Physical Interactions
TRNs Reconstruction
Using Pathway Information
Validation of the Reconstructed Networks
Gene-Expression Ontologies and Tag-Based Expression Profiling
Annotating Gene Expression
Using Ontologies to Integrate Expression Information
Lessons Learned from Genomic CAGE
The Classic View on Transcription Start Sites and Core Promoters
CAGE-Based Views of Transcription Start Sites
Probing Biological Mechanisms Using CAGE
Future Challenges in CAGE Analysis
What are we Measuring?
How Close to "The Truth" areWe?
Comparative Genomics and Mammalian Promoter Evolution
Resources for Comparative Genomic Analysis
Genome Wide Trends in Mammalian Promoter Evolution
Promoters Represent an Unusual Genomic Environment
Integration of Population Genetic Data with Comparative Genomics
Concluding Remarks
The Impact of CAGE Data on Understanding Macrophage Transcriptional Biology
Transcription start site and promoter characteristics revealed by CAGE
Transcriptional Complexity: Sense-Antisense Transcription and Non-Coding RNA
Construction of Macrophage Transcriptional Networks
What does CAGE Data Offer for Traditional Studies of Promoter Regulation?
Color Index

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Piero Carninci was born in Italy in 1965 and earned his doctorate in biological science at the University of Trieste in 1989. For six months from April 1989, he worked as a research associate at the International Center for Genetic Engineering and Biotechnology and then served as a health assistant in the Italian army. In 1990, he became a researcher at a biotech company called TALENT, after which he moved to RIKEN as a researcher in 1995. Since 2003, he has been working as a senior scientist at the Genome Science Laboratory at the RIKEN Frontier Research Institute and at the RIKEN Genomic Sciences Center.


"This is a comprehensive introduction to a powerful and important new technique that is transforming our understanding of gene regulation. This volume contains everything you need to know to become an expert in CAGE, from library construction to bioinformatic analysis of the voluminous data sets."
—Gene E. Robinson, University of Illinois