Cap-Analysis Gene Expression (CAGE)

Abstract

Preface v Cap Analysis Gene Expression (CAGE) Tagging Transcription Starting Sites with CAGE 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 Introduction 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 Introduction 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 Perspective New Era of Genome-Wide Gene Expression Analysis Introduction 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 Overview 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 Replication 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 Discussion Databases for CAGE Visualization and Analysis Introduction Transcription Maps and Activity Public Databases Genomic View of In-House Data For Expression Analyses Discussion Computational Methods to Identify Transcription Factor Binding Sites Using CAGE Information Introduction 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: Effective Use of CAGE Tags Verification of Results Reconstruction of TRNs Transcription Regulatory Networks Analysis Using CAGE CAGE Data for Network Reconstruction Methodology 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 Introduction Annotating Gene Expression Using Ontologies to Integrate Expression Information Lessons Learned from Genomic CAGE Introduction 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 Introduction 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 Impact of CAGE Data on Understanding Macrophage Transcriptional Biology Introduction 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? Conclusion Color Index Index