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Principles for RNA metabolism and alternative transcription initiation within closely spaced promoters

Nature Genetics volume 48, pages 984–994 (2016)Cite this article

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Abstract

Mammalian transcriptomes are complex and formed by extensive promoter activity. In addition, gene promoters are largely divergent and initiate transcription of reverse-oriented promoter upstream transcripts (PROMPTs). Although PROMPTs are commonly terminated early, influenced by polyadenylation sites, promoters often cluster so that the divergent activity of one might impact another. Here we found that the distance between promoters strongly correlates with the expression, stability and length of their associated PROMPTs. Adjacent promoters driving divergent mRNA transcription support PROMPT formation, but owing to polyadenylation site constraints, these transcripts tend to spread into the neighboring mRNA on the same strand. This mechanism to derive new alternative mRNA transcription start sites (TSSs) is also evident at closely spaced promoters supporting convergent mRNA transcription. We suggest that basic building blocks of divergently transcribed core promoter pairs, in combination with the wealth of TSSs in mammalian genomes, provide a framework with which evolution shapes transcriptomes.

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Figure 1: A general building block for transcription initiation.
Figure 2: Common organization of divergent RNA-RNA TSS pairs.
Figure 3: PROMPT generation and properties between divergent mRNA TSSs.
Figure 4: Organization of TSS pairs forming NAT and nNAT constellations.
Figure 5: Properties of NATs and nNATs.
Figure 6: PROMPT properties in convergent constellations.
Figure 7: Models for PROMPT and alternative TSS generation in bidirectional constellations.

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Gene Expression Omnibus

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Gene Expression Omnibus

Sequence Read Archive

References

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

    Article  CAS  PubMed  Google Scholar 

  2. Taft, R.J. et al. Tiny RNAs associated with transcription start sites in animals. Nat. Genet. 41, 572–578 (2009).

    Article  CAS  PubMed  Google Scholar 

  3. Preker, P. et al. RNA exosome depletion reveals transcription upstream of active human promoters. Science 322, 1851–1854 (2008).

    Article  CAS  PubMed  Google Scholar 

  4. 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  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Sigova, A.A. et al. Divergent transcription of long noncoding RNA/mRNA gene pairs in embryonic stem cells. Proc. Natl. Acad. Sci. USA 110, 2876–2881 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Ntini, E. et al. Polyadenylation site–induced decay of upstream transcripts enforces promoter directionality. Nat. Struct. Mol. Biol. 20, 923–928 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Almada, A.E., Wu, X., Kriz, A.J., Burge, C.B. & Sharp, P.A. Promoter directionality is controlled by U1 snRNP and polyadenylation signals. Nature 499, 360–363 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. 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  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Scruggs, B.S. et al. Bidirectional transcription arises from two distinct hubs of transcription factor binding and active chromatin. Mol. Cell 58, 1101–1112 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Flynn, R.A., Almada, A.E., Zamudio, J.R. & Sharp, P.A. Antisense RNA polymerase II divergent transcripts are P-TEFb dependent and substrates for the RNA exosome. Proc. Natl. Acad. Sci. USA 108, 10460–10465 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kaida, D. et al. U1 snRNP protects pre-mRNAs from premature cleavage and polyadenylation. Nature 468, 664–668 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Duttke, S.H. et al. Human promoters are intrinsically directional. Mol. Cell 57, 674–684 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kim, T.-K. et al. Widespread transcription at neuronal activity-regulated enhancers. Nature 465, 182–187 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Andersson, R. et al. Nuclear stability and transcriptional directionality separate functionally distinct RNA species. Nat Commun. 5, 5336 (2014).

    Article  CAS  PubMed  Google Scholar 

  19. Trinklein, N.D. et al. An abundance of bidirectional promoters in the human genome. Genome Res. 14, 62–66 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Li, Y.-Y. et al. Systematic analysis of head-to-head gene organization: evolutionary conservation and potential biological relevance. PLoS Comput. Biol. 2, e74 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Katayama, S. et al. Antisense transcription in the mammalian transcriptome. Science 309, 1564–1566 (2005).

    Article  PubMed  Google Scholar 

  22. Engström, P.G. et al. Complex loci in human and mouse genomes. PLoS Genet. 2, e47 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lehner, B., Williams, G., Campbell, R.D. & Sanderson, C.M. Antisense transcripts in the human genome. Trends Genet. 18, 63–65 (2002).

    Article  CAS  PubMed  Google Scholar 

  24. Andersson, R. et al. Human gene promoters are intrinsically bidirectional. Mol. Cell 60, 346–347 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kadonaga, J.T. Perspectives on the RNA polymerase II core promoter. Wiley Interdiscip. Rev. Dev. Biol. 1, 40–51 (2012).

    CAS  PubMed  Google Scholar 

  26. Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  28. Thurman, R.E. et al. The accessible chromatin landscape of the human genome. Nature 489, 75–82 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Fenouil, R. et al. CpG islands and GC content dictate nucleosome depletion in a transcription-independent manner at mammalian promoters. Genome Res. 22, 2399–2408 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Pugh, B.F. & Venters, B.J. Genomic organization of human transcription initiation complexes. PLoS One 11, e0149339 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Valen, E. et al. Biogenic mechanisms and utilization of small RNAs derived from human protein-coding genes. Nat. Struct. Mol. Biol. 18, 1075–1082 (2011).

    Article  CAS  PubMed  Google Scholar 

  33. Pelechano, V., Wei, W. & Steinmetz, L.M. Extensive transcriptional heterogeneity revealed by isoform profiling. Nature 497, 127–131 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Lubas, M. et al. Interaction profiling identifies the human nuclear exosome targeting complex. Mol. Cell 43, 624–637 (2011).

    Article  CAS  PubMed  Google Scholar 

  35. Faghihi, M.A. & Wahlestedt, C. Regulatory roles of natural antisense transcripts. Nat. Rev. Mol. Cell Biol. 10, 637–643 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Carninci, P. et al. The transcriptional landscape of the mammalian genome. Science 309, 1559–1563 (2005).

    Article  CAS  PubMed  Google Scholar 

  37. Wu, X. & Sharp, P.A. Divergent transcription: a driving force for new gene origination? Cell 155, 990–996 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Jensen, T.H., Jacquier, A. & Libri, D. Dealing with pervasive transcription. Mol. Cell 52, 473–484 (2013).

    Article  CAS  PubMed  Google Scholar 

  39. Djebali, S. et al. Landscape of transcription in human cells. Nature 489, 101–108 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. FANTOM Consortium and the RIKEN PMI and CLST (DGT). A promoter-level mammalian expression atlas. Nature 507, 462–470 (2014).

  41. Karolchik, D. et al. The UCSC Genome Browser database: 2014 update. Nucleic Acids Res. 42, D764–D770 (2014).

    Article  CAS  PubMed  Google Scholar 

  42. Andersen, P.R. et al. The human cap-binding complex is functionally connected to the nuclear RNA exosome. Nat. Struct. Mol. Biol. 20, 1367–1376 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Pelechano, V., Wei, W., Jakob, P. & Steinmetz, L.M. Genome-wide identification of transcript start and end sites by transcript isoform sequencing. Nat. Protoc. 9, 1740–1759 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Anders, S., Pyl, P.T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

    Article  CAS  PubMed  Google Scholar 

  45. Wu, T.D. & Nacu, S. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 26, 873–881 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. 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).

    PubMed  PubMed Central  Google Scholar 

  47. Marstrand, T.T. et al. Asap: a framework for over-representation statistics for transcription factor binding sites. PLoS ONE 3, e1623 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Frith, M.C. et al. A code for transcription initiation in mammalian genomes. Genome Res. 18, 1–12 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Robinson, J.T. et al. Integrative genomics viewer. Nat. Biotechnol. 29, 24–26 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, 2009).

Download references

Acknowledgements

Work in the T.H.J. laboratory was supported by the European Research Council (ERC) (grant 339953) as well as the Danish National Research Foundation (grant DNRF58), the Lundbeck Foundation and the Novo Nordisk Foundation. Work in the A.S. laboratory was supported by grants from the Lundbeck Foundation, the Novo Nordisk-Foundation and the Innovation Fund Denmark. J.H. was supported by a Boehringer-Ingelheim PhD fellowship. R.A. was supported by ERC grant 638273. Work in the L.M.S. laboratory was supported by the Deutsche Forschungsgemeinschaft (grant 1422/3-1). A.A.P. was supported by a Jane Coffin Childs postdoctoral fellowship. We thank the European Molecular Biology Laboratory Genomics Core Facility for technical support.

Author information

Author notes

  1. Aino I Järvelin & Vicent Pelechano

    Present address: Present addresses: Department of Biochemistry, Oxford University, Oxford, United Kingdom (A.I.J.) and SciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden (V.P.).,

Authors and Affiliations

  1. Department of Biology, The Bioinformatics Centre, University of Copenhagen, Copenhagen, Denmark

    Yun Chen, Robin Andersson & Albin Sandelin

  2. Biotech Research and Innovation Centre, University of Copenhagen, Copenhagen, Denmark

    Yun Chen, Michal Lubas & Albin Sandelin

  3. Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Athma A Pai

  4. Department of Molecular Biology and Genetics, Centre for mRNP Biogenesis and Metabolism, Aarhus University, Aarhus, Denmark

    Jan Herudek, Michal Lubas, Nicola Meola & Torben Heick Jensen

  5. European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany

    Aino I Järvelin, Vicent Pelechano & Lars M Steinmetz

  6. Stanford Genome Technology Center, Palo Alto, California, USA

    Lars M Steinmetz

  7. Department of Genetics, Stanford University School of Medicine, Stanford, California, USA

    Lars M Steinmetz

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Contributions

Y.C. analyzed the data. A.A.P. performed exploratory computational analyses for divergent mRNAs. M.L. performed exploratory computational analyses for convergent loci constellations. N.M. and V.P. produced the TIF-seq libraries. A.I.J. processed TIF-seq reads. J.H. conducted RT-qPCR validations. R.A. assisted with enhancer definitions, co-guidance of analyses and interpretation of results. L.M.S. supervised A.I.J. and V.P.. Y.C. and A.S. produced images. T.H.J. and A.S. conceived and supervised the project. Y.C., T.H.J. and A.S. wrote the paper. All authors read and approved of the manuscript.

Corresponding authors

Correspondence to Torben Heick Jensen or Albin Sandelin.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–5, Supplementary Tables 1–2 and Supplementary Note 1 (PDF 20121 kb)

Supplementary Dataset 1

Genomic coordinates for analyzed regions. (XLSX 388 kb)

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Chen, Y., Pai, A., Herudek, J. et al. Principles for RNA metabolism and alternative transcription initiation within closely spaced promoters. Nat Genet 48, 984–994 (2016). https://doi.org/10.1038/ng.3616

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