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:

Human cells contain natural double-stranded RNAs with potential regulatory functions

Abstract

Recent evidence has suggested the existence of sense-antisense transcription in mammals, but the existence of double-stranded RNAs endowed with biological function has remained elusive. Herein we show that hundreds of putative natural double-stranded RNAs (ndsRNAs) are expressed from interspersed genomic locations and respond to cellular cues. We demonstrate that a subset of ndsRNAs localize in the nucleus and, in their double-stranded form, interact with nuclear proteins. Detailed characterization of an ndsRNA (nds-2a) revealed that this molecule displays differential localization throughout the cell cycle and directly interacts with RCC1 and RAN and, through the latter, with the mitotic RANGAP1–SUMO1–RANBP2 complex. Notably, altering nds-2a levels led to postmitotic abnormalities, mitotic catastrophe and cell death, thus supporting a mitosis-related role. Altogether, our study reveals a hitherto-unrecognized class of RNAs that potentially participate in major biological processes in human cells.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Identification of RAM-derived RNAs.
Figure 2: nds-2a establishes specific RNA-protein interactions.
Figure 3: Subcellular localization of nds-2a, RAN, RANGAP1 and RANBP2.
Figure 4: nds-2a overexpression leads to a range of mitotic defects and pronounced changes in nuclear shape.
Figure 5: Depletion of endogenous nds-2a results in cell-cycle defects and mitotic catastrophe.
Figure 6: Depletion of endogenous nds-2a leads to mitotic abnormalities.
Figure 7: Genome-wide expression of ndsRNAs.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

References

  1. Simons, R.W. Naturally occurring antisense RNA control: a brief review. Gene 72, 35–44 (1988).

    Article  CAS  PubMed  Google Scholar 

  2. Wagner, E.G. & Simons, R.W. Antisense RNA control in bacteria, phages, and plasmids. Annu. Rev. Microbiol. 48, 713–742 (1994).

    Article  CAS  PubMed  Google Scholar 

  3. Farnham, P.J., Abrams, J.M. & Schimke, R.T. Opposite-strand RNAs from the 5′ flanking region of the mouse dihydrofolate reductase gene. Proc. Natl. Acad. Sci. USA 82, 3978–3982 (1985).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Volloch, V. Cytoplasmic synthesis of globin RNA in differentiated murine erythroleukemia cells: possible involvement of RNA-dependent RNA polymerase. Proc. Natl. Acad. Sci. USA 83, 1208–1212 (1986).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Williams, T. & Fried, M. A mouse locus at which transcription from both DNA strands produces mRNAs complementary at their 3′ ends. Nature 322, 275–279 (1986).

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  Google Scholar 

  7. Munroe, S.H. & Lazar, M.A. Inhibition of c-erbA mRNA splicing by a naturally occurring antisense RNA. J. Biol. Chem. 266, 22083–22086 (1991).

    CAS  PubMed  Google Scholar 

  8. Hastings, M.L., Milcarek, C., Martincic, K., Peterson, M.L. & Munroe, S.H. Expression of the thyroid hormone receptor gene, erbAalpha, in B lymphocytes: alternative mRNA processing is independent of differentiation but correlates with antisense RNA levels. Nucleic Acids Res. 25, 4296–4300 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Borsani, G. et al. Characterization of a murine gene expressed from the inactive X chromosome. Nature 351, 325–329 (1991).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Li, L.C. et al. Small dsRNAs induce transcriptional activation in human cells. Proc. Natl. Acad. Sci. USA 103, 17337–17342 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Bühler, M. & Moazed, D. Transcription and RNAi in heterochromatic gene silencing. Nat. Struct. Mol. Biol. 14, 1041–1048 (2007).

    Article  CAS  PubMed  Google Scholar 

  13. Sleutels, F., Zwart, R. & Barlow, D.P. The non-coding Air RNA is required for silencing autosomal imprinted genes. Nature 415, 810–813 (2002).

    Article  CAS  PubMed  Google Scholar 

  14. Nagano, T. et al. The Air noncoding RNA epigenetically silences transcription by targeting G9a to chromatin. Science 322, 1717–1720 (2008).

    Article  CAS  PubMed  Google Scholar 

  15. Pandey, R.R. et al. Kcnq1ot1 antisense noncoding RNA mediates lineage-specific transcriptional silencing through chromatin-level regulation. Mol. Cell 32, 232–246 (2008).

    Article  CAS  PubMed  Google Scholar 

  16. Watanabe, T. et al. Endogenous siRNAs from naturally formed dsRNAs regulate transcripts in mouse oocytes. Nature 453, 539–543 (2008).

    CAS  PubMed  Google Scholar 

  17. Tam, O.H. et al. Pseudogene-derived small interfering RNAs regulate gene expression in mouse oocytes. Nature 453, 534–538 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Matsui, K. et al. Natural antisense transcript stabilizes inducible nitric oxide synthase messenger RNA in rat hepatocytes. Hepatology 47, 686–697 (2008).

    Article  CAS  PubMed  Google Scholar 

  19. Ebralidze, A.K. et al. PU.1 expression is modulated by the balance of functional sense and antisense RNAs regulated by a shared cis-regulatory element. Genes Dev. 22, 2085–2092 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Faghihi, M.A. et al. Evidence for natural antisense transcript-mediated inhibition of microRNA function. Genome Biol. 11, R56 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Yin, W., Rossin, A., Clifford, J.L. & Gronemeyer, H. Co-resistance to retinoic acid and TRAIL by insertion mutagenesis into RAM. Oncogene 25, 3735–3744 (2006).

    Article  CAS  PubMed  Google Scholar 

  22. Kiemeney, L.A. et al. Sequence variant on 8q24 confers susceptibility to urinary bladder cancer. Nat. Genet. 40, 1307–1312 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Radtke, I. et al. Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia. Proc. Natl. Acad. Sci. USA 106, 12944–12949 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Schoemaker, M.J. et al. Interaction between 5 genetic variants and allergy in glioma risk. Am. J. Epidemiol. 171, 1165–1173 (2010).

    Article  PubMed  Google Scholar 

  25. Shete, S. et al. Genome-wide association study identifies five susceptibility loci for glioma. Nat. Genet. 41, 899–904 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Simon, M. et al. Genetic risk profiles identify different molecular etiologies for glioma. Clin. Cancer Res. 16, 5252–5259 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Tomlinson, I. et al. A genome-wide association scan of tag SNPs identifies a susceptibility variant for colorectal cancer at 8q24.21. Nat. Genet. 39, 984–988 (2007).

    Article  CAS  PubMed  Google Scholar 

  28. Jenkins, R.B. et al. A low-frequency variant at 8q24.21 is strongly associated with risk of oligodendroglial tumors and astrocytomas with IDH1 or IDH2 mutation. Nat. Genet. 44, 1122–1125 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Guttman, M. & Rinn, J.L. Modular regulatory principles of large non-coding RNAs. Nature 482, 339–346 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Memczak, S. et al. Circular RNAs are a large class of animal RNAs with regulatory potency. Nature 495, 333–338 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Mercer, T.R. et al. Targeted RNA sequencing reveals the deep complexity of the human transcriptome. Nat. Biotechnol. 30, 99–104 (2012).

    Article  CAS  Google Scholar 

  32. Fletcher, O. & Houlston, R.S. Architecture of inherited susceptibility to common cancer. Nat. Rev. Cancer 10, 353–361 (2010).

    Article  CAS  PubMed  Google Scholar 

  33. Greenman, C. et al. Patterns of somatic mutation in human cancer genomes. Nature 446, 153–158 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Levin, J.Z. et al. Targeted next-generation sequencing of a cancer transcriptome enhances detection of sequence variants and novel fusion transcripts. Genome Biol. 10, R115 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Hahn, W.C. et al. Creation of human tumour cells with defined genetic elements. Nature 400, 464–468 (1999).

    Article  CAS  PubMed  Google Scholar 

  36. Perocchi, F., Xu, Z., Clauder-Munster, S. & Steinmetz, L.M. Antisense artifacts in transcriptome microarray experiments are resolved by actinomycin D. Nucleic Acids Res. 35, e128 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Belostotsky, D. Exosome complex and pervasive transcription in eukaryotic genomes. Curr. Opin. Cell Biol. 21, 352–358 (2009).

    Article  CAS  PubMed  Google Scholar 

  38. Flynt, A.S., Greimann, J.C., Chung, W.J., Lima, C.D. & Lai, E.C. MicroRNA biogenesis via splicing and exosome-mediated trimming in Drosophila. Mol. Cell 38, 900–907 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Yang, J.S. & Lai, E.C. Alternative miRNA biogenesis pathways and the interpretation of core miRNA pathway mutants. Mol. Cell 43, 892–903 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Czech, B. & Hannon, G.J. Small RNA sorting: matchmaking for Argonautes. Nat. Rev. Genet. 12, 19–31 (2011).

    Article  CAS  PubMed  Google Scholar 

  41. Djuranovic, S., Nahvi, A. & Green, R. A parsimonious model for gene regulation by miRNAs. Science 331, 550–553 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Clarke, P.R. & Zhang, C. Spatial and temporal coordination of mitosis by Ran GTPase. Nat. Rev. Mol. Cell Biol. 9, 464–477 (2008).

    Article  CAS  PubMed  Google Scholar 

  43. Li, H.Y., Ng, W.P., Wong, C.H., Iglesias, P.A. & Zheng, Y. Coordination of chromosome alignment and mitotic progression by the chromosome-based Ran signal. Cell Cycle 6, 1886–1895 (2007).

    Article  CAS  PubMed  Google Scholar 

  44. Moore, J.D. The Ran-GTPase and cell-cycle control. BioEssays 23, 77–85 (2001).

    Article  CAS  PubMed  Google Scholar 

  45. Huang, S., Mayeda, A., Krainer, A.R. & Spector, D.L. RCC1 and nuclear organization. Mol. Biol. Cell 8, 1143–1157 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Hutchins, J.R. et al. Phosphorylation regulates the dynamic interaction of RCC1 with chromosomes during mitosis. Curr. Biol. 14, 1099–1104 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Joseph, J., Liu, S.T., Jablonski, S.A., Yen, T.J. & Dasso, M. The RanGAP1-RanBP2 complex is essential for microtubule-kinetochore interactions in vivo. Curr. Biol. 14, 611–617 (2004).

    Article  CAS  PubMed  Google Scholar 

  48. Hashizume, C., Kobayashi, A. & Wong, R.W. Down-modulation of nucleoporin RanBP2/Nup358 impaired chromosomal alignment and induced mitotic catastrophe. Cell Death Dis. 4, e854 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Joseph, J., Tan, S.H., Karpova, T.S., McNally, J.G. & Dasso, M. SUMO-1 targets RanGAP1 to kinetochores and mitotic spindles. J. Cell Biol. 156, 595–602 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Ho, C.Y., Wong, C.H. & Li, H.Y. Perturbation of the chromosomal binding of RCC1, Mad2 and survivin causes spindle assembly defects and mitotic catastrophe. J. Cell. Biochem. 105, 835–846 (2008).

    Article  CAS  PubMed  Google Scholar 

  51. Vakifahmetoglu, H., Olsson, M. & Zhivotovsky, B. Death through a tragedy: mitotic catastrophe. Cell Death Differ. 15, 1153–1162 (2008).

    Article  CAS  PubMed  Google Scholar 

  52. Morris, K.V. & Mattick, J.S. The rise of regulatory RNA. Nat. Rev. Genet. 15, 423–437 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Lee, J.T., Davidow, L.S. & Warshawsky, D. Tsix, a gene antisense to Xist at the X-inactivation centre. Nat. Genet. 21, 400–404 (1999).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  55. Fedoroff, N., Wellauer, P.K. & Wall, R. Intermolecular duplexes in heterogeneous nuclear RNA from HeLa cells. Cell 10, 597–610 (1977).

    Article  CAS  PubMed  Google Scholar 

  56. Calvet, J.P. & Pederson, T. Secondary structure of heterogeneous nuclear RNA: two classes of double-stranded RNA in native ribonucleoprotein. Proc. Natl. Acad. Sci. USA 74, 3705–3709 (1977).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. White, E., Schlackow, M., Kamieniarz-Gdula, K., Proudfoot, N.J. & Gullerova, M. Human nuclear Dicer restricts the deleterious accumulation of endogenous double-stranded RNA. Nat. Struct. Mol. Biol. 21, 552–559 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Tian, B., Bevilacqua, P.C., Diegelman-Parente, A. & Mathews, M.B. The double-stranded-RNA-binding motif: interference and much more. Nat. Rev. Mol. Cell Biol. 5, 1013–1023 (2004).

    Article  CAS  PubMed  Google Scholar 

  59. Weber, F., Kochs, G. & Haller, O. Inverse interference: how viruses fight the interferon system. Viral Immunol. 17, 498–515 (2004).

    Article  CAS  PubMed  Google Scholar 

  60. Laudet, V. & Gronemeyer, H. The Nuclear Receptor Factsbook (Academic Press, San Diego, 2002).

  61. Trapnell, C. et al. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat. Biotechnol. 28, 511–515 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hummel, M., Bonnin, S., Lowy, E. & Roma, G. TEQC: an R package for quality control in target capture experiments. Bioinformatics 27, 1316–1317 (2011).

    Article  CAS  PubMed  Google Scholar 

  64. 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 

  65. Karolchik, D. et al. The UCSC Table Browser data retrieval tool. Nucleic Acids Res. 32, D493–D496 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  67. Karro, J.E. et al. Pseudogene.org: a comprehensive database and comparison platform for pseudogene annotation. Nucleic Acids Res. 35, D55–D60 (2007).

    Article  CAS  PubMed  Google Scholar 

  68. Mituyama, T. et al. The Functional RNA Database 3.0: databases to support mining and annotation of functional RNAs. Nucleic Acids Res. 37, D89–D92 (2009).

    Article  CAS  PubMed  Google Scholar 

  69. Moison, C., Arimondo, P.B. & Guieysse-Peugeot, A.L. Commercial reverse transcriptase as source of false-positive strand-specific RNA detection in human cells. Biochimie 93, 1731–1737 (2011).

    Article  CAS  PubMed  Google Scholar 

  70. Griffiths-Jones, S. The microRNA Registry. Nucleic Acids Res. 32, D109–D111 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Mi, H. & Thomas, P. PANTHER pathway: an ontology-based pathway database coupled with data analysis tools. Methods Mol. Biol. 563, 123–140 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Mi, H. et al. PANTHER version 7: improved phylogenetic trees, orthologs and collaboration with the Gene Ontology Consortium. Nucleic Acids Res. 38, D204–D210 (2010).

    Article  CAS  PubMed  Google Scholar 

  73. Raj, A. & Tyagi, S. Detection of individual endogenous RNA transcripts in situ using multiple singly labeled probes. Methods Enzymol. 472, 365–386 (2010).

    Article  CAS  PubMed  Google Scholar 

  74. Kimura, H. & Cook, P.R. Kinetics of core histones in living human cells: little exchange of H3 and H4 and some rapid exchange of H2B. J. Cell Biol. 153, 1341–1353 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank B. Vogelstein (Ludwig Center and Howard Hughes Medical Institute at Johns Hopkins Kimmel Cancer Center) and W.C. Hahn (Department of Medical Oncology, Dana-Farber Cancer Institute, and Department of Medicine, Brigham and Women's Hospital) for providing BJ and BJELR cell lines. We are grateful to M. Lieb for technical assistance in flow cytometry analysis and W. Van Gool for initial technical support in informatics. We thank the IGBMC Mass Spectrometry, Microscopy and High-Throughput Sequencing facilities. Sequencing was performed by the IGBMC Microarray and Sequencing platform, a member of the France Génomique consortium (ANR-10-INBS-0009). M.M.P. and V.P. were supported as postdoctoral fellows of the Ligue Nationale Contre le Cancer. This work was supported by funds from the Alliance Nationale pour les Sciences de la Vie et de la Santé–Institut Thématique Multi-organismes Cancer–Institut National du Cancer (INCa) grant 'Epigenomics of breast cancer', the Ligue National Contre le Cancer (to H.G.; Equipe Labellisée), the INCa and the European Community contract LSHC-CT-2005-518417 'EPITRON'. Support from the Agence Nationale de la Recherche (ANRT-07-PCVI-0031-01, ANR-10-LABX-0030-INRT and ANR-10-IDEX-0002-02) is also acknowledged.

Author information

Authors and Affiliations

Authors

Contributions

M.M.P. and H.G. designed the research project. M.M.P. designed experiments and performed experiments and bioinformatics analysis. V.P. designed and performed experiments. C.E. performed experiments. M.M.P., V.P. and H.G. wrote the manuscript.

Corresponding authors

Correspondence to Maximiliano M Portal or Hinrich Gronemeyer.

Ethics declarations

Competing interests

A European patent application, ‘Methods for sequencing and identifying RNAs’, (EP 14 305 822.0) has been filed by M.M.P. and H.G.

Integrated supplementary information

Supplementary Figure 1 Identification and validation of RAM-derived ndsRNAs.

(a) Schematic representation of RNA capture approach. (b) Graph representing the fraction of target bases covered in the RAM region by at least 1x, 2x, 3x, 5x, 10x and 15x reads from Global and TRAP derived libraries using TEQC pipeline63.(c) Schematic representation of stsRT-PCR using T7-tagged primers. (d,i) Schematic representation and agarose gel electrophoresis showing PCR products (stsRT-PCR) of the expected molecular weight for validation of ndsRNAs (nds-2a: C1-C2, nds-2b: C3-C4, nds-2c: C5-C6, nds-2d: C7-C8, nds-2f: C9-C10, nds-2g: C11-C12, nds-2e: C13-C14, nds-2j: D1-D2 and nds-2k: D3-D4) and nds-derived sRNAs (sRNA1-11) in PLB985 and BJELR cells. (h,i) stsRT reaction was supplemented with actinomycin D. Uncropped images are depicted in Supplementary Data Set.

Supplementary Figure 2 Levels of RAM-derived ndsRNA and nds-derived sRNA are not modulated by the exosome or the miRNA pathway.

(a) Histograms showing the levels of canonical miRNAs in A.U upon Drosha, Dicer, AGO2 and EXOSC3 knock-down. Error bars, s.d. (n= 3 technical replicates) from one representative experiment out of three repeats with independent cell cultures. (b) Western blots assessing levels of Drosha, Dicer, AGO2 and EXOSC3 in non-transfected (mock) scrambled transfected (Sc) or cells transfected with indicated siRNAs. Actin levels are shown as loading control. (c,f) Histograms showing the levels of RAM-derived ndsRNAs and nds-derived sRNAs upon EXOSC3 (c) Drosha (d) Dicer (e) or AGO2 (f) knock-down in BJELR cells. miR-93 levels are depicted as a positive sRNA control for functional knock-down efficiency. The expression level of each RNA in scrambled siRNAs-transfected (Sc) samples was arbitrary set to 1. Values upon knock-down are expressed relative to the Sc sample. Error bars, s.d. (n = 3 technical replicates) from one representative experiment out of three repeats with independent cell cultures. (g) Gels showing silver staining and Western blot for AGO2 in whole cell lysates (input) and AGO2-immunoprecipitated material (AGO2 IP). AGO2, heavy (hc) and light (lc) chains of the IP-antibody are indicated. (h) Histograms showing the levels of nds-derived sRNAs in RNA extracted from whole cell lysates (input) or AGO2-immunoprecipitated material from PLB985 cells (stsRT-qPCR). let-7c and U6 snoRNA are included as AGO2-loaded positive and negative controls, respectively. Error bars, s.d. (n = 3 technical replicates) from one representative experiment out of two repeats with independent cell cultures.

Supplementary Figure 3 RAM region–derived RNAs subjected to RNase protection assays.

(a,b) Agarose gel electrophoresis of products obtained from RNAse ONE or RNAse III protection assays followed by stsRT-PCR for ndsRNA validation. GAPDH mRNA levels were measured either as internal positive control for RNAse ONE treatment or negative control for RNAse III digestion. (c) Northern blot images for nds-2a and nds-2e using radiolabeled strand-specific small oligonucleotide probes. Ethidium Bromide (EtBr) staining is depicted as loading control. (d) Sequence alignment of PLA-obtained PCR products for nds-2a (PLA-nds-2a-seq) and nds-2e (PLA-nds-2e-seq) with PLA-predicted reference (PLA-nds-2a-ref or PLA-nds-2e-ref). Consensus sequence obtained after alignment (consensus) for nds-2a and nds-2e Fw and Rv strands as well as PLA-adaptor position are depicted.

Supplementary Figure 4 nds-2a levels and subcellular localization throughout the cell cycle.

(a,b) Western blot assessing RAN, RCC1, RANGAP1 and RANBP2 in a non-transfected (mock), scrambled (Sc) or siRNAs (si) transfected cells and b whole cell lysates (input) and upon immunoprecipitation using specific antibodies or isotype IgG1. (c) Flow cytometry of cycling or sorted (G1, S, G2-M phase) BJELR cells. (d) nds-2a forward (2a Fw) and reverse (2a Rv) strand levels (stsRTqPCR) in BJELR sorted cells depicted in c. Error bars, s.d. (n = 3 technical replicates) from one representative experiment out of two repeats with independent cell cultures. * P < 0.05, two-tailed Student’s t-test. (e,f) RNA-FISH confocal microscopy for nds-2a forward (red channel) or reverse (green channel) strands in interphase BJ cells. Samples subjected (Heat) or not (NO Heat) to heat denaturation are depicted in e. ATTO-594 (Fw) or ATTO-647 (Rv) small nucleotide labelled probes were used in f. Co-localization (2a Fw/2a Rv) is depicted. Inset images are enlargements of the areas indicated by white squares. The intensity profile distribution along the indicated vectors within inset 1 and 2 are shown. (g) Confocal microscopy images of interphase and metaphase BJ cells processed for nds-2a RNA-FISH (red channel) coupled to immunocytochemistry for RCC1 (green channel). (h) Confocal microscopy images of nds-2a RNA-FISH (red channel) coupled to immunocytochemistry for the indicated proteins (green channel) in interphase HeLa cells. α-Tubulin and DAPI staining are shown merged to delineate the cell. Scale bars, 40 μm (e) 40 μm and 5 μm (f, g Interphase and h; merge and inset, respectively) and 10 μm and 6 μm (g, Metaphase; merge and inset, respectively).

Supplementary Figure 5 nds-2a overexpression and knockdown in HeLa cells.

(a) Histogram analyzing transfection efficiency, calculated as the percentage of cells displaying a positive labeling for GFP (depicted in the up right corner) in HeLa cells co-transfected with the indicated plasmids (blue). Non-transfected cells were used as background control of autofluorescence (red channel). (b) Flow cytometry images for cell cycle profile of HeLa cells transfected with the indicated plasmid pairs. (c) Microscopy images showing the population distribution of CtrlG fluorescence allowing the assessment of in-well transfection efficiency of one representative panel out of 30 images analyzed from CtrlG, FwG-CtrlG or RvG-CtrlG transfected cells. Scale bars, 50 μm.

Supplementary Figure 6 Quality controls of global PLB985-derived stsRNA-seq libraries and modulation of ndsRNA levels by retinoic acid.

(a,b) Intensity correlation plots of technical replicates at 20 nt resolution of long fragmented RNAs (50-70 nt) and naturally occurring small RNAs (18-30 nt) from global stsRNA-Seq libraries. Results are displayed as log 2 of original values. Pearson's correlation coefficient values (R) are shown. (c,e) Screenshots of long stsRNA-Seq showing the profile obtained for known genes (HSP90B1 in forward (Fw) strand and c12orf73 in reverse (Rv) strand), lincRNAs (chr6:141071891-141249602; Rv strand) and several SNAR RNAs precursors and its corresponding small RNAs (SNAR-A3; Rv strand; small stsRNA-Seq). (f) Flow cytometry analysis of PLB985 cells treated either with vehicle (EtOH) or retinoic acid (RA). Percentage of differentiated cells was determined by CD11c-CD14 immunolabeling and is indicated in the up right corner. Fluorescent background signal was assessed with fluorescently labeled non-specific isotypic antibodies. (g) Histograms showing RNA levels (stsRT-qPCR) of forward (Fw) and reverse (Rv) strands of ndsRNAs transcripts modulated upon RA treatment in PLB985. C11orf31, PRC, ICAM1 and TRPT1 were used as RA modulated controls. Error bars, s.d. (n = 3 technical replicates) from one representative experiment out of two repeats with independent cell cultures. Genome positions for the displayed examples are shown in Supplementary Table 2.

Supplementary Figure 7 Mapping of trap-derived libraries with Bowtie and TopHat aligners.

Strand-specific profiles in the RAM-region are depicted for two independent libraries (TRAP1 and TRAP2).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–7 and Supplementary Tables 1, 3, 6 and 7 (PDF 2604 kb)

Supplementary Table 2

RAM-identified long and small RNAs (XLSX 39 kb)

Supplementary Table 4

nds-2a potential interacting proteins identified by LC-MS/MS (XLSX 21 kb)

Supplementary Table 5

nds-2e potential interacting proteins identified by LC-MS/MS (XLSX 30 kb)

Supplementary Data Set 1

Original images of gels, autoradiographs and blots used in this study. (PDF 156 kb)

Video microscopy of FwG-transfected HeLa cells

Movies from one representative CtrlG and one representative FwG transfected field out of 3 biological replicates (independent cell cultures and transfections) are displayed. (AVI 239070 kb)

Video microscopy of RvG-transfected HeLa cells

Movies from one representative CtrlG and one representative RvG transfected field out of 3 biological replicates (independent cell cultures and transfections) are displayed. (AVI 279978 kb)

Video microscopy of FwG-transfected HeLa H2B-GFP cells

Movies from a representative normal mitosis in CtrlG and four altered mitosis in FwG transfected cells out of 3 biological replicates (independent cell cultures and transfections) are displayed. (AVI 44028 kb)

Video microscopy of RvG-transfected HeLa H2B-GFP cells

Movies from a representative normal mitosis in CtrlG and four altered mitosis in RvG transfected cells out of 3 biological replicates (independent cell cultures and transfections) are displayed. (AVI 44028 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Portal, M., Pavet, V., Erb, C. et al. Human cells contain natural double-stranded RNAs with potential regulatory functions. Nat Struct Mol Biol 22, 89–97 (2015). https://doi.org/10.1038/nsmb.2934

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nsmb.2934

This article is cited by

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