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.

  • Article
  • Published:

Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters

Nature Genetics volume 43, pages 621–629 (2011)Cite this article

Subjects

Abstract

Transcription of long noncoding RNAs (lncRNAs) within gene regulatory elements can modulate gene activity in response to external stimuli, but the scope and functions of such activity are not known. Here we use an ultrahigh-density array that tiles the promoters of 56 cell-cycle genes to interrogate 108 samples representing diverse perturbations. We identify 216 transcribed regions that encode putative lncRNAs, many with RT-PCR–validated periodic expression during the cell cycle, show altered expression in human cancers and are regulated in expression by specific oncogenic stimuli, stem cell differentiation or DNA damage. DNA damage induces five lncRNAs from the CDKN1A promoter, and one such lncRNA, named PANDA, is induced in a p53-dependent manner. PANDA interacts with the transcription factor NF-YA to limit expression of pro-apoptotic genes; PANDA depletion markedly sensitized human fibroblasts to apoptosis by doxorubicin. These findings suggest potentially widespread roles for promoter lncRNAs in cell-growth control.

Access through your institution
Buy or subscribe

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

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Figure 1: Identification of ncRNAs near and within cell-cycle genes.
Figure 2: ncRNA expression across diverse cell cycle perturbations.
Figure 3: Functional associations of ncRNAs.
Figure 4: Validated expression of ncRNAs in cell cycle progression, ESC differentiation and human cancers.
Figure 5: ncRNAs at the CDKN1A locus are induced by DNA damage.
Figure 6: PANDA lncRNA regulates the apoptotic response to DNA damage.
Figure 7: PANDA regulates transcription factor NF-YA.
Figure 8: Model of coding and noncoding transcripts at the CDKN1A locus coordinating the DNA damage response.

Similar content being viewed by others

Accession codes

Accessions

Gene Expression Omnibus

References

  1. Bertone, P. et al. Global identification of human transcribed sequences with genome tiling arrays. Science 306, 2242–2246 (2004).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  3. Calin, G.A. et al. Ultraconserved regions encoding ncRNAs are altered in human leukemias and carcinomas. Cancer Cell 12, 215–229 (2007).

    Article  CAS  Google Scholar 

  4. Carninci, P. Non-coding RNA transcription: turning on neighbours. Nat. Cell Biol. 10, 1023–1024 (2008).

    Article  CAS  Google Scholar 

  5. Mattick, J.S. & Makunin, I.V. Small regulatory RNAs in mammals. Hum. Mol. Genet. 14 Spec No 1, R121–R132 (2005).

    Article  CAS  Google Scholar 

  6. He, L. & Hannon, G.J. MicroRNAs: small RNAs with a big role in gene regulation. Nat. Rev. Genet. 5, 522–531 (2004).

    Article  CAS  Google Scholar 

  7. Hutvagner, G. & Simard, M.J. Argonaute proteins: key players in RNA silencing. Nat. Rev. Mol. Cell Biol. 9, 22–32 (2008).

    Article  CAS  Google Scholar 

  8. 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 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  11. 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 

  12. Ponjavic, J., Ponting, C.P. & Lunter, G. Functionality or transcriptional noise? Evidence for selection within long noncoding RNAs. Genome Res. 17, 556–565 (2007).

    Article  CAS  Google Scholar 

  13. Struhl, K. Transcriptional noise and the fidelity of initiation by RNA polymerase II. Nat. Struct. Mol. Biol. 14, 103–105 (2007).

    Article  CAS  Google Scholar 

  14. Guttman, M. et al. Chromatin signature reveals over a thousand highly conserved large non-coding RNAs in mammals. Nature 458, 223–227 (2009).

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  17. De Santa, F. et al. A large fraction of extragenic RNA pol II transcription sites overlap enhancers. PLoS Biol. 8, e1000384 (2010).

    Article  Google Scholar 

  18. Wang, X. et al. Induced ncRNAs allosterically modify RNA-binding proteins in cis to inhibit transcription. Nature 454, 126–130 (2008).

    Article  CAS  Google Scholar 

  19. Pasmant, E. et al. Characterization of a germ-line deletion, including the entire INK4/ARF locus, in a melanoma-neural system tumor family: identification of ANRIL, an antisense noncoding RNA whose expression coclusters with ARF. Cancer Res. 67, 3963–3969 (2007).

    Article  CAS  Google Scholar 

  20. Yu, W. et al. Epigenetic silencing of tumour suppressor gene p15 by its antisense RNA. Nature 451, 202–206 (2008).

    Article  CAS  Google Scholar 

  21. Lee, J.T. Lessons from X-chromosome inactivation: long ncRNA as guides and tethers to the epigenome. Genes Dev. 23, 1831–1842 (2009).

    Article  CAS  Google Scholar 

  22. Rinn, J.L. et al. Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs. Cell 129, 1311–1323 (2007).

    Article  CAS  Google Scholar 

  23. Gupta, R.A. et al. Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature 464, 1071–1076 (2010).

    Article  CAS  Google Scholar 

  24. Huarte, M. et al. A large intergenic noncoding RNA induced by p53 mediates global gene repression in the p53 response. Cell 142, 409–419 (2010).

    Article  CAS  Google Scholar 

  25. Sherr, C.J. & Roberts, J.M. CDK inhibitors: positive and negative regulators of G1-phase progression. Genes Dev. 13, 1501–1512 (1999).

    Article  CAS  Google Scholar 

  26. Hall, M. & Peters, G. Genetic alterations of cyclins, cyclin-dependent kinases, and Cdk inhibitors in human cancer. Adv. Cancer Res. 68, 67–108 (1996).

    Article  CAS  Google Scholar 

  27. Johnson, D.G. & Walker, C.L. Cyclins and cell cycle checkpoints. Annu. Rev. Pharmacol. Toxicol. 39, 295–312 (1999).

    Article  CAS  Google Scholar 

  28. Rando, O.J. & Chang, H.Y. Genome-wide views of chromatin structure. Annu. Rev. Biochem. 78, 245–271 (2009).

    Article  CAS  Google Scholar 

  29. Bock, C., Halachev, K., Buch, J. & Lengauer, T. EpiGRAPH: user-friendly software for statistical analysis and prediction of (epi)genomic data. Genome Biol. 10, R14 (2009).

    Article  Google Scholar 

  30. Lin, M., Jungreis, I. & Kellis, M. PhyloCSF: a comparative genomics method to distinguish protein-coding and non-coding regions. Nature Precedings published online, doi:10.1038/npre.2010.4784.1 (18 August 2010).

  31. Wong, D.J. et al. Module map of stem cell genes guides creation of epithelial cancer stem cells. Cell Stem Cell 2, 333–344 (2008).

    Article  CAS  Google Scholar 

  32. Segal, E., Friedman, N., Koller, D. & Regev, A. A module map showing conditional activity of expression modules in cancer. Nat. Genet. 36, 1090–1098 (2004).

    Article  CAS  Google Scholar 

  33. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102, 15545–15550 (2005).

    Article  CAS  Google Scholar 

  34. Whitfield, M.L. et al. Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol. Biol. Cell 13, 1977–2000 (2002).

    Article  CAS  Google Scholar 

  35. Wei, C.L. et al. A global map of p53 transcription-factor binding sites in the human genome. Cell 124, 207–219 (2006).

    Article  CAS  Google Scholar 

  36. Geisler, S. et al. Influence of TP53 gene alterations and c-erbB-2 expression on the response to treatment with doxorubicin in locally advanced breast cancer. Cancer Res. 61, 2505–2512 (2001).

    CAS  PubMed  Google Scholar 

  37. Olive, K.P. et al. Mutant p53 gain of function in two mouse models of Li-Fraumeni syndrome. Cell 119, 847–860 (2004).

    Article  CAS  Google Scholar 

  38. Agarwal, M.L., Agarwal, A., Taylor, W.R. & Stark, G.R. p53 controls both the G2/M and the G1 cell cycle checkpoints and mediates reversible growth arrest in human fibroblasts. Proc. Natl. Acad. Sci. USA 92, 8493–8497 (1995).

    Article  CAS  Google Scholar 

  39. Di Leonardo, A., Linke, S.P., Clarkin, K. & Wahl, G.M. DNA damage triggers a prolonged p53-dependent G1 arrest and long-term induction of Cip1 in normal human fibroblasts. Genes Dev. 8, 2540–2551 (1994).

    Article  CAS  Google Scholar 

  40. Morachis, J.M., Murawsky, C.M. & Emerson, B.M. Regulation of the p53 transcriptional response by structurally diverse core promoters. Genes Dev. 24, 135–147 (2010).

    Article  CAS  Google Scholar 

  41. Michlewski, G. & Caceres, J.F. RNase-assisted RNA chromatography. RNA 16, 1673–1678 (2010).

    Article  CAS  Google Scholar 

  42. Khalil, A.M. et al. Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proc. Natl. Acad. Sci. USA 106, 11667–11672 (2009).

    Article  CAS  Google Scholar 

  43. Tsai, M.C. et al. Long noncoding RNA as modular scaffold of histone modification complexes. Science 329, 689–693 (2010).

    Article  CAS  Google Scholar 

  44. Kanhere, A. et al. Short RNAs are transcribed from repressed polycomb target genes and interact with polycomb repressive complex-2. Mol. Cell 38, 675–688 (2010).

    Article  CAS  Google Scholar 

  45. Han, J., Kim, D. & Morris, K.V. Promoter-associated RNA is required for RNA-directed transcriptional gene silencing in human cells. Proc. Natl. Acad. Sci. USA 104, 12422–12427 (2007).

    Article  CAS  Google Scholar 

  46. Schwartz, J.C. et al. Antisense transcripts are targets for activating small RNAs. Nat. Struct. Mol. Biol. 15, 842–848 (2008).

    Article  CAS  Google Scholar 

  47. Mattick, J.S. Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms. Bioessays 25, 930–939 (2003).

    Article  CAS  Google Scholar 

  48. Taylor, J., Schenck, I., Blankenberg, D. & Nekrutenko, A. Using galaxy to perform large-scale interactive data analyses. Curr. Protoc. Bioinformatics Chapter 10, Unit 10.5 (2007).

    PubMed  Google Scholar 

  49. Lin, M.F. et al. Revisiting the protein-coding gene catalog of Drosophila melanogaster using 12 fly genomes. Genome Res. 17, 1823–1836 (2007).

    Article  CAS  Google Scholar 

  50. Lin, M.F., Deoras, A.N., Rasmussen, M.D. & Kellis, M. Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes. PLOS Comput. Biol. 4, e1000067 (2008).

    Article  Google Scholar 

  51. Kosiol, C., Holmes, I. & Goldman, N. An empirical codon model for protein sequence evolution. Mol. Biol. Evol. 24, 1464–1479 (2007).

    Article  CAS  Google Scholar 

  52. van de Vijver, M.J. et al. A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009 (2002).

    Article  CAS  Google Scholar 

  53. Rinn, J.L., Bondre, C., Gladstone, H.B., Brown, P.O. & Chang, H.Y. Anatomic demarcation by positional variation in fibroblast gene expression programs. PLoS Genet. 2, e119 (2006).

    Article  Google Scholar 

Download references

Acknowledgements

We thank J. Rinn, M. Guttman and A. Regev for discussions, L. Attardi for careful reading of the manuscript and P. Khavari for reagents. Y.W., B.K. and Yu Wang are employees of Life Technologies. This work was supported by grants from the US National Institutes of Health (NIH)/National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) (K08-AR054615 to D.J.W.), NIH/National Cancer Institute (NCI) (R01-CA118750 to H.Y.C.and R01-CA130795 to M.L.W.), the Juvenile Diabetes Research Foundation (S.K.K. and H.Y.C.) and the American Cancer Society (H.Y.C.). H.Y.C. is an Early Career Scientist of the Howard Hughes Medical Institute. T.H. is supported by the Stanford Graduate Fellowship, the National Science Foundation (NSF) Graduate Research Fellowship and the Department of Defense (DoD) National Defense Science & Engineering Graduate Fellowship (NDSEG).

Author information

Author notes

  1. David J Wong and Howard Y Chang: These authors contributed equally to this work.

Authors and Affiliations

  1. Program in Epithelial Biology, Stanford University School of Medicine, Stanford, California, USA

    Tiffany Hung, Ashley K Koegel, David J Wong & Howard Y Chang

  2. Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California, USA

    Tiffany Hung, Ashley K Koegel, Seung K Kim & Howard Y Chang

  3. Life Technologies, Foster City, California, USA

    Yulei Wang, Yu Wang & Benjamin Kong

  4. The Broad Institute, Cambridge, Massachusetts, USA

    Michael F Lin & Manolis Kellis

  5. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA

    Michael F Lin & Manolis Kellis

  6. Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

    Yojiro Kotake & Yue Xiong

  7. Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA

    Yojiro Kotake

  8. Department of Biochemistry 1, Hamamatsu University School of Medicine, Higashi-ku, Hamamatsu, Japan

    Yojiro Kotake

  9. Department of Genetics, Dartmouth Medical School, Hanover, New Hampshire, USA

    Gavin D Grant & Michael L Whitfield

  10. Department of Pathology, Academic Medical Center, Amsterdam, The Netherlands

    Hugo M Horlings & Marc van de Vijver

  11. Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Nilay Shah & Saraswati Sukumar

  12. Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA

    Christopher Umbricht

  13. Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, USA

    Pei Wang & Seung K Kim

  14. Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Montebello, Oslo, Norway

    Anita Langerød & Anne-Lise Børresen-Dale

  15. Institute for Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway

    Anne-Lise Børresen-Dale

Authors
  1. Tiffany Hung
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Yulei Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Michael F Lin
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Ashley K Koegel
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Yojiro Kotake
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Gavin D Grant
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Hugo M Horlings
    View author publications

    You can also search for this author inPubMed Google Scholar

  8. Nilay Shah
    View author publications

    You can also search for this author inPubMed Google Scholar

  9. Christopher Umbricht
    View author publications

    You can also search for this author inPubMed Google Scholar

  10. Pei Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  11. Yu Wang
    View author publications

    You can also search for this author inPubMed Google Scholar

  12. Benjamin Kong
    View author publications

    You can also search for this author inPubMed Google Scholar

  13. Anita Langerød
    View author publications

    You can also search for this author inPubMed Google Scholar

  14. Anne-Lise Børresen-Dale
    View author publications

    You can also search for this author inPubMed Google Scholar

  15. Seung K Kim
    View author publications

    You can also search for this author inPubMed Google Scholar

  16. Marc van de Vijver
    View author publications

    You can also search for this author inPubMed Google Scholar

  17. Saraswati Sukumar
    View author publications

    You can also search for this author inPubMed Google Scholar

  18. Michael L Whitfield
    View author publications

    You can also search for this author inPubMed Google Scholar

  19. Manolis Kellis
    View author publications

    You can also search for this author inPubMed Google Scholar

  20. Yue Xiong
    View author publications

    You can also search for this author inPubMed Google Scholar

  21. David J Wong
    View author publications

    You can also search for this author inPubMed Google Scholar

  22. Howard Y Chang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

H.Y.C. and D.J.W. initiated the project. H.Y.C., D.J.W. and T.H. designed the experiments. T.H. performed the experiments and the computational analysis. Yulei Wang, Yu Wang and B.K. conducted high-throughput TaqMan RT-PCRs. M.F.L. and M.K. contributed CSF analysis. The following authors contributed samples or reagents: A.K.K., Y.K., G.D.G., H.M.H., N.S., C.U., P.W., A.L., S.K.K., M.v.d.V., A.-L.B.-D., S.S., M.L.W. and Y.X. The manuscript was prepared by H.Y.C., T.H. and D.J.W. with input from all co-authors.

Corresponding authors

Correspondence to David J Wong or Howard Y Chang.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 and Supplementary Tables 1, 2 and 5. (PDF 1466 kb)

Supplementary Table 3

List of cell cycle promoter transcripts (XLSX 25 kb)

Supplementary Table 4

Combined expression of all transcripts across all tiling arrays (XLSX 107 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hung, T., Wang, Y., Lin, M. et al. Extensive and coordinated transcription of noncoding RNAs within cell-cycle promoters. Nat Genet 43, 621–629 (2011). https://doi.org/10.1038/ng.848

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.848

Search

Advanced search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer