□Comparison with other gene expression analysis techniques

There are numerous techniques for analyzing gene expression, and each method has its advantages. CAGE differs from other major gene expression analysis techniques in its capability to accurately identify transcriptional start sites in a genome-wide fashion.

Since CAGE enables detailed analyses of the promoter regions of a gene, it is possible to further analyze the expression of a specific gene regulated by each promoter. Therefore, CAGE can serve as a “new-perspective” approach for genome annotation, by elucidating transcriptional signaling cascades, and performing other functions.

("N/A" means not applicable)

□FANTOM Main Paper

• FANTOM Consortium et al, A promoter level mammalian expression atlas, Nature, 507(7493), 462-470 (2014)
• Andersson R et al, An atlas of active enhancers across human cell types and tissues, Nature, 507(7493), 455-461 (2014)

□Others

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• Severin J et al, Interactive visualization and analysis of large-scale NGS data-sets using ZENBU, Nature Biotechnology, 32(3), 217-219 (2014)
• Rye M et al, Chromatin states reveal functional associations for globally defined transcription start sites in four human cell lines, BMC Genomics, 15, 120 (2014)
• Murata M et al, Detecting expressed genes using CAGE, Methods Mol Biol, 1164, 67-85 (2014)
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• Sompallae R et al, Sompallae RA comprehensive promoter landscape identifies a novel promoter for CD133 in restricted tissues, cancers, and stem cells, Front Genet, 4, 209 (2013)
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• Harbers M et al, Comparison of RNA- or LNA-hybrid oligonucleotides in template-switching reactions for high-speed sequencing library preparation, BMC Genomics, 14, 665 (2013)
• Tang DT et al, Suppression of artifacts and barcode bias in high-throughput transcriptome analyses utilizing template switching, Nucleic Acids Res, 41(3), e44 (2013)
• ENCODE Project Consortium, An integrated encyclopedia of DNA elements in the human genome, Nature, 489(7414), 57-74 (2012)
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• Djebali S et al, Landscape of transcription in human cells, Nature, 489(7414), 101-108 (2012)
• Itoh M et al, Automated workflow for preparation of cDNA for cap analysis of gene expression on a single molecule sequencer, PLoS One, 7(1), e30809 (2012)
• Takahashi H et al, CAGE (cap analysis of gene expression): a protocol for the detection of promoter and transcriptional networks, Methods Mol Biol, 786, 181-200 (2014)
• Schroder K et al, Conservation and divergence in Toll-like receptor 4-regulated gene expression in primary human versus mouse macrophages, Proc Natl Acad Sci USA, 109(16), E944-E953 (2012)
• Plessy C et al, Promoter architecture of mouse olfactory receptor genes, Genome Res, 22(3), 486-497 (2012)
• Takahashi H et al, 5' end-centered expression profiling using cap-analysis gene expression and next-generation sequencing, Nat Protoc, 7, 542-561 (2012)
• Chien CH et al, Identifying transcriptional start sites of human microRNAs based on high-throughput sequencing data, Nucleic Acids Res, 39(21), 9345-9356 (2011)
• Kanamori-Katayama M et al, Unamplified cap analysis of gene expression on a single-molecule sequencer, Genome Res, 21(7), 1150-1159 (2011)
• Hoskins RA et al, Genome-wide analysis of promoter architecture in Drosophila melanogaster, Genome Res, 21(2), 182-192 (2011)
• Salimullah M et al, NanoCAGE: a high-resolution technique to discover and interrogate cell transcriptomes, Cold Spring Harb Protoc, 2011(1), pdb.prot5559 (2011)
• Schaefer U et al, High sensitivity TSS prediction: estimates of locations where TSS cannot occur, PLoS One, 5(11), e13934 (2010)
• Vitezic M et al, Building promoter aware transcriptional regulatory networks using siRNA perturbation and deepCAGE, Nucleic Acids Res, 38(22), 8141-8148 (2010)
• Hestand MS et al, Tissue-specific transcript annotation and expression profiling with complementary next-generation sequencing technologies, Nucleic Acids Res, 38(16), e165 (2010)
• Plessy C et al, Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan, Nat Methods, 7(7), 528-534 (2010)
• Atanur SS et al, The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance, Genome Res, 20(6), 791-803 (2010)
• FANTOM Consortium et al, The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line, Nat Genet, 41(5), 553-62 (2009)
• Faulkner GJ et al, The regulated retrotransposon transcriptome of mammalian cells, Nat Genet, 41(5), 563-571 (2009)
• Balwierz PJ et al, Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE data, Genome Biol, 10(7), R79 (2009)
• Valen E et al, Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE, Genome Res, 19(2), 255-265 (2009)
• Hofmann O et al, Genome-wide analysis of cancer/testis gene expression, Proc Natl Acad Sci USA, 105(51), 20422-20427 (2008)
• ENCODE Project Consortium et al, Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project, Nature, 447(7146), 799-816 (2007)
• Shimokawa K et al, Large-scale clustering of CAGE tag expression data, BMC Bioinformatics, 8, 161 (2007)
• Kawaji H et al, Dynamic usage of transcription start sites within core promoters, Genome Biol, 7(12), R118 (2006)
• Carninci P et al, Genome-wide analysis of mammalian promoter architecture and evolution, Nat Genet, 38(6), 626-635 (2006)
• Kodzius R et al, CAGE: cap analysis of gene expression, Nat Methods, 3(3), 211-222 (2006)
• Shiraki T et al, Cap analysis gene expression for high-throughput analysis of transcriptional starting point and identification of promoter usage, Proc Natl Acad Sci USA, 100(26), 15776-15781 (2003)
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