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Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan

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Large-scale sequencing projects have revealed an unexpected complexity in the origins, structures and functions of mammalian transcripts. Many loci are known to produce overlapping coding and noncoding RNAs with capped 5′ ends that vary in size. Methods to identify the 5′ ends of transcripts will facilitate the discovery of new promoters and 5′ ends derived from secondary capping events. Such methods often require high input amounts of RNA not obtainable from highly refined samples such as tissue microdissections and subcellular fractions. Therefore, we developed nano–cap analysis of gene expression (nanoCAGE), a method that captures the 5′ ends of transcripts from as little as 10 ng of total RNA, and CAGEscan, a mate-pair adaptation of nanoCAGE that captures the transcript 5′ ends linked to a downstream region. Both of these methods allow further annotation-agnostic studies of the complex human transcriptome.

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Figure 1: Experimental outline of the nanoCAGE and CAGEscan protocols.
Figure 2: nanoCAGE specifically captures capped 5′ ends.
Figure 3: Promotome-transcriptome analysis with CAGEscan.
Figure 4: CAGEscan connects promoters and downstream sequences.
Figure 5: Expressed repeat elements surveyed by CAGEscan.

Change history

  • 06 October 2010

    In the version of this article initially published, the concentration of the PCR primers for CAGEscan cDNA amplification and CAGEscan cDNA sequencing were erroneously given as millimolar instead of nanomolar. The error has been corrected in the HTML and PDF versions of the article.


  1. 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, 15776–15781 (2003).

    Article  CAS  Google Scholar 

  2. Kodzius, R. et al. CAGE: cap analysis of gene expression. Nat. Methods 3, 211–222 (2006).

    Article  CAS  Google Scholar 

  3. Carninci, P. Cap-Analysis Gene Expression (CAGE): Genome-Scale Promoter Identification and Association with Expression Profile and Regulatory Networks (Pan Stanford Publishing, Singapore, 2009).

  4. Carninci, P. et al. Genome-wide analysis of mammalian promoter architecture and evolution. Nat. Genet. 38, 626–635 (2006).

    Article  CAS  Google Scholar 

  5. Suzuki, H. et al. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line. Nat. Genet. 41, 553–562 (2009).

    Article  CAS  Google Scholar 

  6. Affymetrix/Cold Spring Harbor Laboratory ENCODE Transcriptome Project et al. Post-transcriptional processing generates a diversity of 5′-modified long and short RNAs. Nature 457, 1028–1032 (2009).

  7. Kapranov, P. et al. RNA maps reveal new RNA classes and a possible function for pervasive transcription. Science 316, 1484–1488 (2007).

    Article  CAS  Google Scholar 

  8. Fullwood, M.J., Wei, C., Liu, E.T. & Ruan, Y. Next-generation DNA sequencing of paired-end tags (PET) for transcriptome and genome analyses. Genome Res. 19, 521–532 (2009).

    Article  CAS  Google Scholar 

  9. Valen, E. et al. Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE. Genome Res. 19, 255–265 (2009).

    Article  CAS  Google Scholar 

  10. Zhu, Y.Y., Machleder, E.M., Chenchik, A., Li, R. & Siebert, P.D. Reverse transcriptase template switching: a SMART approach for full-length cDNA library construction. Biotechniques 30, 892–897 (2001).

    Article  CAS  Google Scholar 

  11. Hirzmann, J., Luo, D., Hahnen, J. & Hobom, G. Determination of messenger RNA 5′-ends by reverse transcription of the cap structure. Nucleic Acids Res. 21, 3597–3598 (1993).

    Article  CAS  Google Scholar 

  12. Ohtake, H., Ohtoko, K., Ishimaru, Y. & Kato, S. Determination of the capped site sequence of mRNA based on the detection of cap-dependent nucleotide addition using an anchor ligation method. DNA Res. 11, 305–309 (2004).

    Article  CAS  Google Scholar 

  13. Cheng, J. et al. Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution. Science 308, 1149–1154 (2005).

    Article  CAS  Google Scholar 

  14. Meisel, A., Bickle, T.A., Krüger, D.H. & Schroeder, C. Type III restriction enzymes need two inversely oriented recognition sites for DNA cleavage. Nature 355, 467–469 (1992).

    Article  CAS  Google Scholar 

  15. Maeda, N. et al. Development of a DNA barcode tagging method for monitoring dynamic changes in gene expression by using an ultra high-throughput sequencer. Biotechniques 45, 95–97 (2008).

    Article  CAS  Google Scholar 

  16. Bentley, D.R. et al. Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456, 53–59 (2008).

    Article  CAS  Google Scholar 

  17. Forrest, A.R.R. & Carninci, P. Whole genome transcriptome analysis. RNA Biol. 6, 107–112 (2009).

    Article  CAS  Google Scholar 

  18. International Human Genome Sequencing Consortium. Finishing the euchromatic sequence of the human genome. Nature 431, 931–945 (2004).

  19. Cloonan, N. et al. Stem cell transcriptome profiling via massive-scale mRNA sequencing. Nat. Methods 5, 613–619 (2008).

    Article  CAS  Google Scholar 

  20. Ozsolak, F. et al. Digital transcriptome profiling from attomole-level RNA samples. Genome Res. 20, 519–525 (2010).

    Article  CAS  Google Scholar 

  21. Pruitt, K.D., Tatusova, T. & Maglott, D.R. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 35, D61–D65 (2007).

    Article  CAS  Google Scholar 

  22. Olivarius, S., Plessy, C. & Carninci, P. High-throughput verification of transcriptional starting sites by Deep-RACE. Biotechniques 46, 130–132 (2009).

    Article  CAS  Google Scholar 

  23. Fromont-Racine, M., Bertrand, E., Pictet, R. & Grange, T. A highly sensitive method for mapping the 5′ termini of mRNAs. Nucleic Acids Res. 21, 1683–1684 (1993).

    Article  CAS  Google Scholar 

  24. Faulkner, G.J. et al. The regulated retrotransposon transcriptome of mammalian cell. Nat. Genet. 41, 563–571 (2009).

    Article  CAS  Google Scholar 

  25. Carninci, P. Molecular biology: The long and short of RNAs. Nature 457, 974–975 (2009).

    Article  CAS  Google Scholar 

  26. Gingeras, T.R. Implications of chimaeric non-co-linear transcripts. Nature 461, 206–211 (2009).

    Article  CAS  Google Scholar 

  27. Stangegaard, M., Dufva, I.H. & Dufva, M. Reverse transcription using random pentadecamer primers increases yield and quality of resulting cDNA. Biotechniques 40, 649–657 (2006).

    Article  CAS  Google Scholar 

  28. Spiess, A. & Ivell, R. A highly efficient method for long-chain cDNA synthesis using trehalose and betaine. Anal. Biochem. 301, 168–174 (2002).

    Article  CAS  Google Scholar 

  29. Salimullah, M. et al. Tunable fractionation of nucleic acids. Biotechniques 47, 1041–1043 (2009).

    Article  CAS  Google Scholar 

  30. Bhorjee, J.S. & Pederson, T. Chromatin: its isolation from cultured mammalian cells with particular reference to contamination by nuclear ribnucleoprotein particles. Biochemistry 12, 2766–2773 (1973).

    Article  CAS  Google Scholar 

  31. Faulkner, G.J. et al. A rescue strategy for multimapping short sequence tags refines surveys of transcriptional activity by CAGE. Genomics 91, 281–288 (2008).

    Article  CAS  Google Scholar 

  32. Hashimoto, T. et al. Probabilistic resolution of multi-mapping reads in massively parallel sequencing data using MuMRescueLite. Bioinformatics 25, 2613–2614 (2009).

    Article  CAS  Google Scholar 

  33. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  Google Scholar 

  34. Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).

    Article  CAS  Google Scholar 

  35. Severin, J. et al. FANTOM4 EdgeExpressDB: an integrated database of promoters, genes, microRNAs, expression dynamics and regulatory interactions. Genome Biol. 10, R39 (2009).

    Article  Google Scholar 

  36. Jurka, J. et al. Repbase update, a database of eukaryotic repetitive elements. Cytogenet. Genome Res. 110, 462–467 (2005).

    Article  CAS  Google Scholar 

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This work was funded by a grant of the 6th Framework of the European Union commission to the Neuro Functional Genomics consortium, by a grant of the 7th Framework to P.C. and S.G. (Dopaminet), a Grant-in-Aids for Scientific Research (A) 20241047 for P.C. and a Research Grant for RIKEN Omics Science Center from the Japanese Ministry of Education, Culture, Sports, Science and Technology to Y.H. This project was also partially supported by the U.S. National Human Genome Research Institute grant U54 HG004557. C.P. was supported by the Japanese Society for the Promotion of Science long-term fellowship P05880. S.G. was funded by a career developmental award from The Giovanni Armenise-Harvard Foundation. We thank A. Forrest for critical discussions, M. Josserand for experimental assistance and RIKEN Genome Network Analysis Service for data production.

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Authors and Affiliations



C.P., R.S. and P.C. conceived the nanoCAGE technology. C.P. and P.C. conceived the CAGEscan technology. C.P., H.T., R.S., M.S. and S.O. designed and performed the experiments. C.P., N.B., H.T., T.L. and M.V. analyzed data and interpreted results. C.P., N.B., S.G. and P.C. supervised the study. D.L., N.H., V.O., I.B., H.G., J.D., P.K., H.W., C.A.D. and T.R.G. provided material. J.S. provided software. J.K., Y.H., S.G. and P.C. provided salary support. P.C., N.B., H.T. and M.V. drafted the text and figures. C.P., N.B., T.L., C.O.D. and P.C. edited the text and figures. General correspondence should be addressed to S.G. or P.C.; correspondence about experiments, to C.P.; and correspondence about bioinformatics, to N.B.

Corresponding authors

Correspondence to Charles Plessy, Nicolas Bertin, Stefano Gustincich or Piero Carninci.

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Competing interests

C.P., P.C. and R.S. are inventors of the Japanese patent application held by RIKEN on the moderately suppressive PCR step of the nanoCAGE protocol. P.K. is currently an employee of Helicos BioSciences.

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Supplementary Figures 1–7 and Supplementary Tables 1–8 (PDF 2743 kb)

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Plessy, C., Bertin, N., Takahashi, H. et al. Linking promoters to functional transcripts in small samples with nanoCAGE and CAGEscan. Nat Methods 7, 528–534 (2010).

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