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

Preface......Page 3
Contents......Page 7
1. Cap Analysis Gene Expression (CAGE)......Page 14
2.1 The Output of the Genome is Complex......Page 20
2.2 Mapping 5’ Ends: From ESTs to Tagging Technologies\n......Page 22
2.3 Linking Core Promoters to Genomic Elements......Page 25
2.4 cDNA Ends or the Whole Sequence?......Page 27
2.5 Identification of Functional Elements in the Genome\n......Page 28
2.6 Technology Evolution, Same Lessons?......Page 30
3.1 Introduction......Page 34
3.2 Stage 1: Synthesis of First-Strand cDNA......Page 35
3.3 Stage 2: Oxidation/Biotinylation......Page 37
3.4 Stage 3: Capture-Release......Page 38
3.5 Stage 4: Single Strand Linker Ligation......Page 40
3.6 Stage 5: the Second Strand cDNA Synthesis......Page 42
3.7 Stage 6: Preparing CAGE Tags......Page 43
3.8 Stage: 7 Amplification of CAGE Tags......Page 45
3.9 Stage 8: Restriction......Page 48
3.10 Stage 9: Concatenation......Page 50
4. Transcriptome and Genome Characterization Using Massively Parallel Paired End Tag (PET) Sequencing Analysis......Page 54
4.1 Introduction......Page 55
4.2 The Development of Pair end diTag (PET) Analysis \n......Page 56
4.3 GIS-PET for Transcriptome Analysis......Page 59
4.4 ChIP-PET for Whole Genome Mapping of Transcription Factor Binding Sites and Epigenetic Modifications......Page 61
4.5 ChIA-PET for Whole Genome Identification of Long Range interactions......Page 65
4.6 Perspective......Page 68
5. New Era of Genome-Wide Gene Expression Analysis......Page 74
5.2 Tagging Technologies for Genome-Wide Analysis \n......Page 75
5.3 Principles of Next Generation Sequencing Technologies......Page 77
5.4 Genome Analyzer (Illumina/Solexa)......Page 79
5.5 SOLiD System (Applied Biosystems)......Page 81
5.6 Advantages of Next Generation Sequencing Technologies \nover Conventional Sequencing Technology on Tagging Technologies......Page 82
5.7 From Static Analysis to Dynamic Analysis......Page 84
5.8 CAGE Method and Next Generation Sequencing Technologies......Page 85
5.9 Conclusions and Outlook......Page 86
6. Computational Tools to Analyze CAGE — Introduction to PART II......Page 92
7.1 Overview......Page 96
7.2 Using Read Qualities and Read Properties, Pre- and Post-Extraction......Page 97
7.3 Procedures Before Tag Extraction......Page 98
7.5 Origin of Sequence Errors......Page 100
7.7 A Simple CAGE Tag Extraction Method......Page 101
8.1 Mapping Pipelines for Sequence Tag Technologies......Page 106
8.2 A Mapping Pipeline for CAGE......Page 109
8.3 Benchmarking with a Sample Dataset......Page 110
9.1 High Throughput Expression Platforms......Page 114
9.3 Platform Normalization......Page 116
9.4 Replication......Page 118
9.5 Gene Models and Complex Loci......Page 120
9.6 Construction of CAGE Promoters and Calculation of Gene \nExpression Levels......Page 121
9.7 Comparison of CAGE Expression between Technical Replicates......Page 122
9.8 Comparison of CAGE Expression from Biological Replicates......Page 123
9.9 Comparison of CAGE Expression Between Different Time \nPoints Within a Single Time-Course......Page 124
9.10 Comparison of CAGE Expression Profiling to qRT-PCR Expression Measurements......Page 126
9.12 Present/Absent Calls......Page 127
9.13 Discussion......Page 129
10.1 Introduction......Page 136
10.2 Transcription Maps and Activity......Page 137
10.3 Public Databases......Page 139
10.4 Genomic View of In-House Data......Page 141
10.5 For Expression Analyses......Page 145
10.6 Discussion......Page 146
11. Computational Methods to Identify Transcription Factor  Binding Sites Using CAGE Information\n......Page 150
11.1 Introduction......Page 151
11.2 Schema of the Methodology Process......Page 152
11.3 Initial Links of TF with the Affected Genes......Page 155
11.4 Correlation of CAGE Tag Counts of Genes and TFs 146......Page 159
11.5 Ranking TF, TFBS, TSS/Promoter, GENE Association: The Effective Use of CAGE Tags......Page 160
11.6 Verification of Results......Page 162
11.7 Reconstruction of TRNs......Page 163
12. Transcription Regulatory Networks Analysis Using CAGE......Page 166
12.1 CAGE Data for Network Reconstruction......Page 167
12.2 Methodology......Page 170
12.3 Gene Expression Data Complementary to CAGE for Network Reconstruction......Page 171
12.4 Using Physical Interactions......Page 173
12.5 TRNs Reconstruction......Page 174
12.7 Validation of the Reconstructed Networks......Page 175
13.1 Introduction......Page 182
13.2 Annotating Gene Expression......Page 186
13.3 Using Ontologies to Integrate Expression Information\n......Page 187
14.1 Introduction......Page 192
14.2 The Classic View on Transcription Start Sites and Core Promoters......Page 193
14.3 CAGE-Based Views of Transcription Start Sites......Page 195
14.4 Probing Biological Mechanisms Using CAGE......Page 203
15.1 What are we Measuring?......Page 210
15.2 How Close to “The Truth” areWe?......Page 212
16. Comparative Genomics and Mammalian Promoter Evolution\n......Page 222
16.1 Introduction......Page 223
16.2 Resources for Comparative Genomic Analysis......Page 225
16.3 Genome Wide Trends in Mammalian Promoter Evolution......Page 230
16.4 Promoters Represent an Unusual Genomic Environment\n......Page 231
16.5 Integration of Population Genetic Data with Comparative Genomics......Page 234
16.6 Concluding Remarks......Page 235
17.1 Introduction......Page 240
17.2 Transcription start site and promoter characteristics \nrevealed by CAGE......Page 242
17.3 Transcriptional Complexity: Sense-Antisense Transcription and Non-Coding RNA......Page 248
17.4 Construction of Macrophage Transcriptional Networks......Page 249
17.5 What does CAGE Data Offer for Traditional Studies of \nPromoter Regulation?......Page 250
17.6 Conclusion......Page 253
Color Index......Page 258
Index......Page 278