K.K. DNAFORM

New approach for genome-wide promoter
identification and gene expression profiling
 
         Quantify all RNA Polymerase II transcripts:
 Analyze transcripts not only as genes but also as Transcription Start Sites
 Discover alternative promoters for all endogenous genes
 Predict transcription factor binding motifs more reliably
 Provide a powerful tool to reveal gene network dynamics
Extensively used in research projects:
  • The ENCODE project at NIH
  • The FANTOM project at RIKEN
  • The national project “Transcription Network Analysis” in Japan

 
CAGE: A unique transcriptome analysis method for 5’-ends of nc/mRNA
Cap Analysis of Gene Expression (CAGE) is a new method for expression profiling and promoter identification, which allows transcriptional network analysis and transcriptome characterization.

CAGE utilizes “cap-trapping” technology to capture the 5’ cap of mRNA/ncRNA. Through high volume parallel sequencing of cDNA corresponding to 5’-end of RNA and analysis of the sequenced tags, Transcription Start Sites (TSS) and transcript amount are inferred on a genome-wide scale (Fig. 1).

The process of library preparation of CAGE use neither PCR nor fragmentation of RNA which cause biased results of the gene expression in RNA-seq.


 
A powerful tool in gene regulation research
CAGE accurately identifies the position and expression level of TSS on a genome-wide scale with high repro-ducibility (Fig. 2).

The cap-trapping technology which captures one transcript with a 5’ cap as one read, and the PCR-free library preparation process without fragmentation allow for digital quantification of RNA transcript abundances including low expressed transcripts.

CAGE detects precise position of TSS, which is extremely difficult for most transcriptomic technologies to identify (Fig. 3, and Table 1).

Using information obtained by CAGE, such as precise positions, variants and transcript abundances of TSS, you can detect the corresponding promoters and accurately estimate signaling cascades.

 

  Table 1. Features of CAGE and other transcriptome analyses (“N/A” means not applicable)
Purpose of the study CAGE RNA-seq ChIP-seq Micro
array		 SAGE
de novo Gene/ncRNA finding good good average N/A good
Gene expression quantification superior good N/A average good
Determining a promoter site superior average good N/A N/A
Motif finding for the transcription factor binding site superior average superior average average
Identification of bidirectional enhancer RNA average N/A N/A N/A N/A
Determining transcription start /1st exon site superior average N/A N/A N/A
Determining gene structure
(intron/exon, fusion gene, alternative splicing variants)		 N/A average N/A N/A N/A

 
CAGE identifies complex gene expression networks

CAGE accurately provides information such as alternative TSS usage on a genome-wide scale (Fig. 4). CAGE is a powerful tool in gene expression network research.

Comparative analysis of promoter activity
Reliable estimation of promoter regions and their activities based on precise TSS information enable you to find alternative promoters and to compare promoter utilization patterns among different organs, developmental stages and diseased/normal organs which are essential in identifying expression networks underlying differentiation, development and diseases. CAGE also allows you to characterize type and genome-wide distribution of promoters (Carninci et al. 2006, Ohmiya et al. 2014).

Valuable tool in the development of new biomarkers of cancers and other diseases
CAGE detects TSS variants of mRNAs/ncRNAs, which vary in expression level and pattern depending on the type of cancer cells, diseased/normal organs (Fig. 5). TSS variants are valuable candidate of biomarkers even in the case that there are no difference at the transcript level.

Explore transcription factor binding motifs
CAGE enables you to explore transcription factor binding motifs. With CAGE, you can perform a genome-wide motif search around precise TSS positions which have different expression profiles depending on case and control (i.e. “up-regulated” or “down-regulated”) to obtain a list of candidates for transcription factor binding motifs which correspond to different expressions (Table 2).

The precise distance between each motif and TSS obtained by CAGE can verify estimations of associated transcription factors and enable you to find candidate genes that are regulated by specific transcription factors (Fig. 6).

Non-coding RNA analysis
CAGE can be applied to detect and quantify long non-coding RNAs (lncRNAs), even those which are not polyadenylated. CAGE provides accurate information of the promoters and 5’-end sequence of the lncRNAs, which are difficult to determine by RNA-seq.

CAGE also enables you to identify active enhancers by detection of TSS of enhancer associated bidirectional RNAs (eRNAs). Enhancer identification by eRNAs is more precise than mapping analysis by ChIP-seq. 		    
Motif No. Consensus Motif Foreground:
/100		 Background:
/1000		 P value Known Motifs
(P value)
AMD_001 CAACTNGCG 27 51 1.42E-04 NA
AMD_002 GTARCNNWNSCCG 31 54 1.32E-05 NA
AMD_003 CTTCARNNNNCGA 36 108 4.77E-03 NA
AMD_004 ACGTNNNNGNNACC 28 44 1.24E-05 PPARγ
(9.21e-05)
Table 2. Motif search near TSS with an expression level higher in preadipocytes than in mesenchymal stem cells
The known adipose differentiation marker, PPARγ, is detected.

   
How many TSS are present for each gene?

Riken and the FANTOM consortium have identified more than 201,802 human TSS (Science 347, 2015), which is almost four times the number of known protein-coding genes and ncRNAs, using CAGE. More than half of all known genes are regulated by multiple alternative promoters. It is strongly indicated that many of these multiple promoters affect a tissue in a specific way and may be linked to specific diseases.     
CAGE peaks within
500bp of annotated 5’-end		 Human Mouse
Peaks Peaks
/gene		 Peaks Peaks
/gene
Robust
Promoter		 Coding + ncRNA 184,827 116,277
Coding RNA 82,150 4.3 61,1347 3.2
Permissive
Promoter		 Coding + ncRNA 1,048,124 652,860
Coding RNA 245,514 11.8 146,185 7.1
Andersson R, et al. Nature 2014 Mar 27;507(7493):455-61.

   
Representative papers using CAGE

  1. Promoter-level transcriptome in primary lesions of endometrial cancer identified biomarkers associated with lymph node metastasis.
    Yoshida E, et al. Sci. Rep. 2017 Oct 26;7:14160. doi: 10.1038/s41598-017-14418-5.
  2. An atlas of human long non-coding RNAs with accurate 5’ ends.
    Hon CC, et al. Nature. 2017 Mar 9;543(7644):199-204. doi: 10.1038/nature21374.
  3. Single-Nucleotide Resolution Mapping of Hepatitis B Virus Promoters in Infected Human Livers and Hepatocellular Carcinoma.
    Altinel K, et al. J Virol. 2016 Nov 14;90(23):10811-10822.
  4. Reduced expression of APC-1B but not APC-1A by the deletion of promoter 1B is responsible for familial adenomatous polyposis.
    Yamaguchi K, et al. Sci. Rep. 2016 May 24;6:26011. doi: 10.1038/srep26011.
  5. Enhanced Identification of Transcriptional Enhancers Provides Mechanistic Insights into Diseases.
    Murakawa Y, et al. Trends Genet. 2016 Feb;32(2):76-88. doi: 10.1016/j.tig.2015.11.004.
  6. DeepCAGE Transcriptomics Reveal an Important Role of the Transcription Factor MAFB in the Lymphatic Endothelium.
    Dieterich LC, et al. Cell Rep. 2015 Nov 17;13(7):1493-504
  7. Nuclear transcriptome profiling of induced pluripotent stem cells and embryonic stem cells identify non-coding loci resistant to reprogramming.
    Fort A, et al. Cell Cycle. 2015;14(8):1148-55. doi: 10.4161/15384101.2014.988031.
  8. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells.
    Arner E, et al. Science 2015 Feb 27;347(6225):1010-4. doi126/science.1259418.
  9. Deep transcriptome profiling of mammalian stem cells supports a regulatory role for retrotransposons in pluripotency maintenance Fort A, et al. Nat. Genet. 2014 Jun 28;46:558-566. doi:10.1038/ng.2965.
  10. Two independent transcription initiation codes overlap on vertebrate core promoters.
    Haberle V, et al. Nature 2014 Mar 20; 507(7492):381-385. doi: 10.1038/nature12974.
  11. Tiny RNAs associated with transcription start sites in animals.
    Taft RJ, et al. Nat. Gen. 2009 Apr 19;41(5): 572-578. doi:10.1038/ng.312.
*For other papers, please check our website: https://cage-seq.com/index.html

 

   
Project workflow

 

1. Total RNA
submission		 2. Library preparation/
Sequences		 3. Bioinformatics
analysis
Amount > 3 μg
Preferable
Concentration		 > 0.1
μg/μl
Purity A260/A280 > 1.8
A260/A230 > 1.8
RIN > 7.0
Sequencing instrument HiSeq 2500/ NextSeq500
Amount of data 10-15 million
reads/sample
Sequencing 50bp/75bp Single-end
 
Total 4-6 weeks
Raw sequencing data (FASTQ format)
Genome mapping data (BAM format)
TSS cluster with annotation
Differential expression analysis of TSS clusters
(ScatterPlot, Heat map, Clustering)
Motif search analysis

 

   
Ordering information

 

CAGE library preparation & analysis services
Services Price 1
Library preparation 2 500 USD/sample
Sequencing 250 USD/sample
Bioinformatics analysis 250 USD/sample
  1. 1. Shipping : 200 USD/shipment
  2. 2. Library is prepared for Illumina-platform
    
CAGE library preparation Kit 3, 4
Package size Price Cat. No.
8 samples 2,000 USD 52003-8
48 samples 10,000 USD 52003-48
  1. 3. Shipping : 800 USD/shipment
  2. 4. Library is prepared for Illumina-platform

 

K.K. DNAFORM
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TEL: +81-45-508-1539 FAX: +81-45-510-0608 E-mail: contact@dnaform.jp