CAGE Preparation Kit

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CAGE Preparation Kit

CAGE Preparation Kit is a ready-to-use product that includes reagents* and the protocol necessary for the preparation of a CAGE library, which allows the easy introduction of Cap Analysis of Gene Expression, CAGE, into your R&D.
* Note: Reverse Transcriptase is not inclued.

CAGE enables sequencing and mapping of short tags derived from the 5'-end of mRNA, thereby quantifying the frequency of tag sequences. A distinctive feature of CAGE is its capability to accurately identify promoter sites for each transcript and obtain gene expression profiles based on identified promoters.

A sequencing run using one channel on the Illumina Sequencer can yield over 4,000,000 reads per sample. Expression profiles obtained from DeepCAGE (i.e., combination of next-generation sequencing with next-generation expressing profiling) will be powerful tools for various gene expression analyses and genome annotation projects.

Applications

  • Genome-wide gene-expression analysis
  • Prediction of promoter sites
  • Quantitative mRNA expression profiling

Examples of actual usage of CAGE

  • "Functional Annotation of Mouse (FANTOM) project" by RIKEN
  • "Encyclopedia of DNA Elements (ENCODE) project" by the National Institute of Health (NIH)
  • "Gene Networks project" by the Ministry of Education, Culture, Sports, Science and Technology

Product specifications

  • The cap-trapper method involves capturing the 5'-cap of mRNA while removing rRNA.
  • The random priming method allows generation of hybridization products from non-coding mRNAs, in addition to those from mRNAs
  • The use of barcodes allows multiplex sequence analysis.
  • Prepared CAGE libraries can be analyzed with an Illumina next-generation DNA sequencer.
  • Note: the CAGE Kit does not contain reverse transcriptase.

For data analysis, Platform system for next-generation sequencing (NGS) data analysis is available at the National Institutes of Genetics.
National Institutes of Genetics > NGS Analysis Platform

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Technical Information

CAGE is a novel approach for identifying promoters and gene expression profiling.
CAGE is based on full-length cDNA library technology for next-generation sequencing technologies, where an adaptor is ligated to the 5’ end of each full-length cDNA. By mapping genomic sequences on the CAGE tags, transcriptional start sites can be identified. Thus, CAGE can be a powerful tool for discovery of novel genes, genome-wide gene-expression profiling, and promoter analysis.

Sample Data Download

Downlod the raw fastq data, processed fastq data, reference genome, and analysis results
* The file may take some time to download as the total data size is 32.6GB.
Download

Difference from RNA-Seq and other gene analysis techniques

Different from Microarray and RNA-seq, CAGE is able to accurately identify transcriptional start sites (TSSs) and the corresponding promoter regions through sequencing the 3’ end of cDNA (5’ end of RNA). This makes CAGE a powerful tool to analyze the gene regulation in the TSSs level, enabling analysis of the gene regulated by multiple alternative promoters. Therefore, CAGE can serve as a new perspective approach for genome annotation, by elucidating transcriptional signaling cascades, and performing other functions.

Comparison among major gene expression analysis techniques
CAGE RNA-seq SAGE Microarray
de novo Gene Finding ×
Gene Expression Quantification 1
Determining Promoter Site × ×
Motif Finding for Transcription Factor Binding Site × 2 × 2
Identification of Bidirectional Enhancer RNA × × ×
Determining Transcription Start/1st Exon Site × ×
Determining Gene Structure (intron/exon, alternative splicing variants) × 3 × ×
Duration of Work Process
Library Preparation Complicatedness × 4
Data Analysis Tools
  • 1 free of PCR biasunaffected by gene size
  • 2 depending on known 5' end sequence information
  • 3 depending on sequence depth
  • 4 8 days

References

FANTOM main paper

Others

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  2. Roy S et al, Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics, Nucleic Acids Res, 43(14), 6969-6982 (2015)
  3. Yu NY et al, Complementing tissue characterization by integrating transcriptome profiling from the Human Protein Atlas and from the FANTOM5 consortium, Nucleic Acids Res, 43(14), 6787-6798 (2015)
  4. Mina M et al, Promoter-level expression clustering identifies time development of transcriptional regulatory cascades initiated by ErbB receptors in breast cancer cells, Sci Rep, 5, 11999 (2015)
  5. Ramilowski JA et al, A draft network of ligand-receptor-mediated multicellular signalling in human, Nat Commun, 6, 7866 (2015)
  6. Aitken S et al, Transcriptional dynamics reveal critical roles for non-coding RNAs in the immediate-early response, PLoS Comput Biol, 11(4), e1004217 (2015)
  7. Haberle V et al, CAGEr: precise TSS data retrieval and high-resolution promoterome mining for integrative analyses, Nucleic Acids Res, 43(8), e51 (2015)
  8. Taguchi A et al, Characterization of Novel Transcripts of Human Papillomavirus Type 16 Using Cap Analysis Gene Expression Technology, Journal of Virology, 89(4), 2448-2452 (2015)
  9. Arner E et al, Gene regulation. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells, Science, 347(6225), 1010-1014 (2015)
  10. Joshi A et al, Transcription factor, promoter, and enhancer utilization in human myeloid cells, J Leukoc Biol, 97(5), 985-995 (2015)
  11. Fort A et al, Nuclear transcriptome profiling of induced pluripotent stem cells and embryonic stem cells identify noncoding loci resistant to reprogramming, Cell Cycle, 14(8), 1148-1155 (2015)
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  16. Fort A et al, Deep transcriptome profiling of mammalian stem cells supports a regulatory role for retrotransposons in pluripotency maintenance, Nature Genetics, 46(6), 558-566 (2014)
  17. Hasegawa A et al, MOIRAI: a compact workflow system for CAGE analysis, BMC Bioinformatics, 15, 144 (2014)
  18. Yamaga R et al, Systemic identification of estrogen-regulated genes in breast cancer cells through cap analysis of gene expression mapping, Biochem Biophys Res Commun, 447(3), 531-536 (2014)
  19. Prasad P et al, High-throughput transcription profiling identifies putative epigenetic regulators of hematopoiesis, Blood, 123(17), e46-e57 (2014)
  20. Ohmiya H et al, RECLU: a pipeline to discover reproducible transcriptional start sites and their alternative regulation using capped analysis of gene expression (CAGE), BMC Genomics, 15, 269 (2014)
  21. Kawaji H et al, Comparison of CAGE and RNA-seq transcriptome profiling using a clonally amplified and single molecule next generation sequencing, Genome Res, 24(4), 708-717 (2014)
  22. Rönnerblad M et al, Analysis of the DNA methylome and transcriptome in granulopoiesis reveals timed changes and dynamic enhancer methylation, Blood, 123(17), e79-e89 (2014)
  23. Motakis E et al, Redefinition of the human mast cell transcriptome by deep-CAGE sequencing, Blood, 123(17), e58-e67 (2014)
  24. Schmidl C et al, The enhancer and promoter landscape of human regulatory and conventional T cell subpopulations, Blood, 123(17), e68-e78 (2014)
  25. Schmidl C et al, Transcription and enhancer profiling in human monocyte subsets, Blood, 123(17), e90-e99 (2014)
  26. Morikawa H et al, Differential roles of epigenetic changes and Foxp3 expression in regulatory T cell-specific transcriptional regulation, Proc Natl Acad Sci USA, 111(14), 5289-5294 (2014)
  27. Severin J et al, Interactive visualization and analysis of large-scale NGS data-sets using ZENBU, Nature Biotechnology, 32(3), 217-219 (2014)
  28. 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)
  29. Murata M et al, Detecting expressed genes using CAGE, Methods Mol Biol, 1164, 67-85 (2014)
  30. Pascarella G et al, NanoCAGE analysis of the mouse olfactory epithelium identifies the expression of vomeronasal receptors and of proximal LINE elements, Front Cell Neurosci, 8, 41 (2014)
  31. Nepal C et al, Dynamic regulation of the transcription initiation landscape at single nucleotide resolution during vertebrate embryogenesis, Genome Res, 23(11), 1938-1950 (2013)
  32. 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)
  33. Sompallae R, A comprehensive promoter landscape identifies a novel promoter for CD133 in restricted tissues, cancers, and stem cells, Front Genet, 4, 209 (2013)
  34. 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)
  35. 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)
  36. ENCODE Project Consortium, An integrated encyclopedia of DNA elements in the human genome, Nature, 489(7414), 57-74 (2012)
  37. Derrien T et al, The GENCODE v7 catalog of human long noncoding RNAs: analysis of their gene structure, evolution, and expression, Genome Res, 22(9), 1775-1789 (2012)
  38. Djebali S et al, Landscape of transcription in human cells, Nature, 489(7414), 101-108 (2012)
  39. 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)
  40. 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)
  41. 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)
  42. Plessy C et al, Promoter architecture of mouse olfactory receptor genes, Genome Res, 22(3), 486-497 (2012)
  43. Takahashi H et al, 5' end-centered expression profiling using cap-analysis gene expression and next-generation sequencing, Nat Protoc7, 542-561 (2012)
  44. 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)
  45. Kanamori-Katayama M et al, Unamplified cap analysis of gene expression on a single-molecule sequencer, Genome Res, 21(7), 1150-1159 (2011)
  46. Hoskins RA et al, Genome-wide analysis of promoter architecture in Drosophila melanogaster, Genome Res, 21(2), 182-192 (2011)
  47. Salimullah M et al, NanoCAGE: a high-resolution technique to discover and interrogate cell transcriptomes, Cold Spring Harb Protoc, 2011(1), pdb.prot5559 (2011)
  48. Schaefer U et al, High sensitivity TSS prediction: estimates of locations where TSS cannot occur, PLoS One, 5(11), e13934 (2010)
  49. Vitezic M et al, Building promoter aware transcriptional regulatory networks using siRNA perturbation and deepCAGE, Nucleic Acids Res, 38(22), 8141-8148 (2010)
  50. Hestand MS et al, Tissue-specific transcript annotation and expression profiling with complementary next-generation sequencing technologies, Nucleic Acids Res, 38(16), e165 (2010)
  51. Plessy C et al, Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan, Nat Methods, 7(7), 528-534 (2010)
  52. Atanur SS et al, The genome sequence of the spontaneously hypertensive rat: Analysis and functional significance, Genome Res, 20(6), 791-803 (2010)
  53. 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)
  54. Faulkner GJ et al, The regulated retrotransposon transcriptome of mammalian cells, Nat Genet, 41(5), 563-571 (2009)
  55. 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)
  56. Valen E et al, Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE, Genome Res, 19(2), 255-265 (2009)
  57. Hofmann O et al, Genome-wide analysis of cancer/testis gene expression, Proc Natl Acad Sci USA, 105(51), 20422-20427 (2008)
  58. 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)
  59. Shimokawa K et al, Large-scale clustering of CAGE tag expression data, BMC Bioinformatics, 8, 161 (2007)
  60. Kawaji H et al, Dynamic usage of transcription start sites within core promoters, Genome Biol, 7(12), R118 (2006)
  61. Carninci P et al, Genome-wide analysis of mammalian promoter architecture and evolution, Nat Genet, 38(6), 626-635 (2006)
  62. Kodzius R et al, CAGE: cap analysis of gene expression, Nat Methods, 3(3), 211-222 (2006)
  63. 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)
  64. Carninci P et al, High-efficiency full-length cDNA cloning by biotinylated CAP trapper, Genomics, 37(3), 327-336 (1996)

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Price

Reagent quantities support 8 library preparations.

  • Item:CAGE Library preparation kit 8 sample version
  • 200,000 JPY (Tax excluded)

Reagent quantities support 48 library preparations.

  • Item:CAGE Library preparation kit 48 sample version
  • 1,200,000 JPY(Tax excluded)

Reagent quantities support 96 library preparations.

  • Item:CAGE Library preparation kit 96 sample version
  • 2,400,000 JPY(Tax excluded)

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Import duties, taxes, and charges are not included in the item prices or shipping cost. These charges are the customer's responsibility. Please check with your country's customs office to determine what these additional costs will be prior to placing your order. All transactions will be conducted in JPY.

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