Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Base-pair-resolution genome-wide mapping of active RNA polymerases using precision nuclear run-on (PRO-seq)

Abstract

We provide a protocol for precision nuclear run-on sequencing (PRO-seq) and its variant, PRO-cap, which map the location of active RNA polymerases (PRO-seq) or transcription start sites (TSSs) (PRO-cap) genome-wide at high resolution. The density of RNA polymerases at a particular genomic locus directly reflects the level of nascent transcription at that region. Nuclei are isolated from cells and, under nuclear run-on conditions, transcriptionally engaged RNA polymerases incorporate one or, at most, a few biotin-labeled nucleotide triphosphates (biotin-NTPs) into the 3′ end of nascent RNA. The biotin-labeled nascent RNA is used to prepare sequencing libraries, which are sequenced from the 3′ end to provide high-resolution positional information for the RNA polymerases. PRO-seq provides much higher sensitivity than ChIP-seq, and it generates a much larger fraction of usable sequence reads than ChIP-seq or NET-seq (native elongating transcript sequencing). Similarly to NET-seq, PRO-seq maps the RNA polymerase at up to base-pair resolution with strand specificity, but unlike NET-seq it does not require immunoprecipitation. With the protocol provided here, PRO-seq (or PRO-cap) libraries for high-throughput sequencing can be generated in 4–5 working days. The method has been applied to human, mouse, Drosophila melanogaster and Caenorhabditis elegans cells and, with slight modifications, to yeast.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Flowchart of the PRO-seq and PRO-cap protocol.
Figure 2: Gel images of library products.
Figure 3: Genome browser examples of PRO-seq and PRO-cap results.

Similar content being viewed by others

References

  1. Fuda, N.J., Ardehali, M.B. & Lis, J.T. Defining mechanisms that regulate RNA polymerase II transcription in vivo. Nature 461, 186–192 (2009).

    Article  CAS  Google Scholar 

  2. Adelman, K. & Lis, J.T. Promoter-proximal pausing of RNA polymerase II: emerging roles in metazoans. Nat. Rev. Genet. 13, 720–731 (2012).

    Article  CAS  Google Scholar 

  3. Core, L.J. et al. Analysis of nascent RNA identifies a unified architecture of initiation regions at mammalian promoters and enhancers. Nat. Genet. 46, 1311–1320 (2014).

    Article  CAS  Google Scholar 

  4. Heinz, S., Romanoski, C.E., Benner, C. & Glass, C.K. The selection and function of cell type-specific enhancers. Nat. Rev. Mol. Cell Biol. 16, 144–154 (2015).

    Article  CAS  Google Scholar 

  5. Vahedi, G. et al. Super-enhancers delineate disease-associated regulatory nodes in T cells. Nature 520, 558–562 (2015).

    Article  CAS  Google Scholar 

  6. Churchman, L.S. & Weissman, J.S. Nascent transcript sequencing visualizes transcription at nucleotide resolution. Nature 469, 368–373 (2011).

    Article  CAS  Google Scholar 

  7. Larson, M.H. et al. A pause sequence enriched at translation start sites drives transcription dynamics in vivo. Science 344, 1042–1047 (2014).

    Article  CAS  Google Scholar 

  8. Nojima, T. et al. Mammalian NET-Seq reveals genome-wide nascent transcription coupled to RNA processing. Cell 161, 526–540 (2015).

    Article  CAS  Google Scholar 

  9. Weber, C.M., Ramachandran, S. & Henikoff, S. Nucleosomes are context-specific, H2A.Z-modulated barriers to RNA polymerase. Mol. Cell. 53, 819–830 (2014).

    Article  CAS  Google Scholar 

  10. Core, L.J., Waterfall, J.J. & Lis, J.T. Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters. Science 322, 1845–1848 (2008).

    Article  CAS  Google Scholar 

  11. Kwak, H., Fuda, N.J., Core, L.J. & Lis, J.T. Precise maps of RNA polymerase reveal how promoters direct initiation and pausing. Science 339, 950–953 (2013).

    Article  CAS  Google Scholar 

  12. Jonkers, I., Kwak, H. & Lis, J.T. Genome-wide dynamics of Pol II elongation and its interplay with promoter proximal pausing, chromatin, and exons. Elife 3, e02407 (2014).

    Article  Google Scholar 

  13. Kwak, H. & Lis, J.T. Control of transcriptional elongation. Annu. Rev. Genet. 47, 483–508 (2013).

    Article  CAS  Google Scholar 

  14. Hah, N. et al. A rapid, extensive, and transient transcriptional response to estrogen signaling in breast cancer cells. Cell 145, 622–634 (2011).

    Article  CAS  Google Scholar 

  15. Min, I.M. et al. Regulating RNA polymerase pausing and transcription elongation in embryonic stem cells. Genes Dev. 25, 742–754 (2011).

    Article  CAS  Google Scholar 

  16. Larschan, E. et al. X chromosome dosage compensation via enhanced transcriptional elongation in Drosophila. Nature 471, 115–118 (2011).

    Article  CAS  Google Scholar 

  17. Cock, P.J.A., Fields, C.J., Goto, N., Heuer, M.L. & Rice, P.M. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucl. Acids Res. 38, 1767–1771 (2010).

    Article  CAS  Google Scholar 

  18. Core, L.J. et al. Defining the status of RNA polymerase at promoters. Cell Rep. 2, 1025–1035 (2012).

    Article  CAS  Google Scholar 

  19. Seila, A.C. et al. Divergent transcription from active promoters. Science 322, 1849–1851 (2008).

    Article  CAS  Google Scholar 

  20. Carninci, P. et al. High-efficiency full-length cDNA cloning by biotinylated CAP trapper. Genomics 37, 327–336 (1996).

    Article  CAS  Google Scholar 

  21. Andersson, R. et al. An atlas of active enhancers across human cell types and tissues. Nature 507, 455–461 (2014).

    Article  CAS  Google Scholar 

  22. Forrest, A.R.R. et al. A promoter-level mammalian expression atlas. Nature 507, 462–470 (2014).

    Article  CAS  Google Scholar 

  23. Wang, D. et al. Reprogramming transcription by distinct classes of enhancers functionally defined by eRNA. Nature 474, 390–394 (2011).

    Article  CAS  Google Scholar 

  24. Hah, N., Murakami, S., Nagari, A., Danko, C.G. & Kraus, W.L. Enhancer transcripts mark active estrogen receptor binding sites. Genome Res. 23, 1210–1223 (2013).

    Article  CAS  Google Scholar 

  25. Fejes-Toth, K. et al. Post-transcriptional processing generates a diversity of 5-modified long and short RNAs. Nature 457, 1028–1032 (2009).

    Article  CAS  Google Scholar 

  26. Rhee, H.S. & Pugh, B.F. Genome-wide structure and organization of eukaryotic pre-initiation complexes. Nature 483, 295–301 (2012).

    Article  CAS  Google Scholar 

  27. Li, J. et al. Kinetic competition between elongation rate and binding of NELF controls promoter-proximal pausing. Mol. Cell 50, 711–722 (2013).

    Article  CAS  Google Scholar 

  28. Mayer, A. et al. Native elongating transcript sequencing reveals human transcriptional activity at nucleotide resolution. Cell 161, 541–554 (2015).

    Article  CAS  Google Scholar 

  29. Mahat, D.B., Salamanca, H.H., Duarte, F.M., Danko, C.G. & Lis, J.T. Mammalian heat shock response and mechanisms underlying its genome-wide transcriptional regulation. Mol. Cell 62, 63–78 (2016).

    Article  CAS  Google Scholar 

  30. García-Martínez, J., Aranda, A. & Pérez-Ortín, J.E. Genomic run-on evaluates transcription rates for all yeast genes and identifies gene regulatory mechanisms. Mol. Cell 15, 303–313 (2004).

    Article  Google Scholar 

  31. Collart, M.A. & Oliviero, S. Preparation of yeast RNA. Curr. Protoc. Mol. Biol. Chapter 13, Unit13.12 (2001).

  32. Job, D. et al. Complex RNA chain elongation kinetics by wheat germ RNA polymerase II. Nucleic Acids Res. 12, 3303–3319 (1984).

    Article  CAS  Google Scholar 

  33. Fu, G.K. et al. Molecular indexing enables quantitative targeted RNA sequencing and reveals poor efficiencies in standard library preparations. Proc. Natl. Acad. Sci. USA 111, 1891–1896 (2014).

    Article  CAS  Google Scholar 

  34. Marcel, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12 (2011).

    Google Scholar 

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

    Article  CAS  Google Scholar 

  36. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    Article  Google Scholar 

  37. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  Google Scholar 

  38. Quinlan, A.R. & Hall, I.M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank all the present and former members of the Lis lab who provided advice and support for this work. We especially thank N. Fuda, a former member of our lab, for help at many steps of this protocol. Research reported in this publication was supported by National Institutes of Health (NIH) grant R01GM25232 to J.T.L. and European Research Council Advanced Grant ERCadv-671274 to I.H.J. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Author information

Authors and Affiliations

Authors

Contributions

H.K., L.J.C. and J.T.L. conceived the method and designed the experiments. H.K. and D.B.M. carried out the experiments that generated the data. G.T.B., I.H.J., R.K.P., C.T.W., K.M. and L.J.C. carried out experiments that optimized the protocol. C.G.D. contributed in generating the pipelines for the computational analysis. H.K., D.B.M. and J.T.L. wrote the manuscript.

Corresponding authors

Correspondence to Leighton J Core or John T Lis.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mahat, D., Kwak, H., Booth, G. et al. Base-pair-resolution genome-wide mapping of active RNA polymerases using precision nuclear run-on (PRO-seq). Nat Protoc 11, 1455–1476 (2016). https://doi.org/10.1038/nprot.2016.086

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2016.086

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing