Technical Report

RNA-DamID reveals cell-type-specific binding of roX RNAs at chromatin-entry sites

  • Nature Structural & Molecular Biologyvolume 25pages109114 (2018)
  • doi:10.1038/s41594-017-0006-4
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Thousands of long noncoding RNAs (lncRNAs) have been identified in eukaryotic genomes, many of which are expressed in spatially and temporally restricted patterns. Nonetheless, the roles of the majority of these transcripts are still unknown. One of the mechanisms by which lncRNAs function is through the modulation of chromatin states. To assess the functions of lncRNAs, we developed RNA-DamID, a novel approach that detects lncRNA–genome interactions in a cell-type-specific manner in vivo with high sensitivity and accuracy. Identifying the cell-type-specific genome occupancy of lncRNAs is vital to understanding their mechanisms of action in development and disease. We used RNA-DamID to investigate targeting of the lncRNAs in the Drosophila dosage-compensation complex (DCC) and show that initial targeting is cell-type specific.

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We thank M. Kuroda (Harvard University), V. Meller (Wayne State University), T. Megraw (Florida State University) and P. Amaral (Gurdon Institute) for reagents, T. Leonardi for advice on data visualization and P. Amaral, T. Southall, O. Marshall and members of the Brand Lab for advice and discussion. This work was funded by the Royal Society Darwin Trust Research Professorship, a Wellcome Trust Senior Investigator Award 103792 and Wellcome Trust Programme Grant 092545 to A.H.B. S.W.C. was funded by a Herchel Smith Research Studentship. A.H.B acknowledges core funding to the Gurdon Institute from the Wellcome Trust (092096) and CRUK (C6946/A14492).

Author information

Author notes

    • Seth W. Cheetham

    Present address: Mater Research Institute, University of Queensland, Wooloongabba, Queensland, Australia


  1. The Gurdon Institute and Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK

    • Seth W. Cheetham
    •  & Andrea H. Brand


  1. Search for Seth W. Cheetham in:

  2. Search for Andrea H. Brand in:


S.W.C. and A.H.B. designed the experiments. S.W.C. performed the experiments. S.W.C. and A.H.B. analyzed the data. S.W.C. and A.H.B. wrote the manuscript. Both authors reviewed the manuscript before submission.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrea H. Brand.

Integrated supplementary information

  1. Supplementary Figure 1 Constructs used for RNA-DamID.

    (a) An MCP tandem dimer fused to two nuclear localisation signals and Dam is expressed under the control of UAS. Expression is reduced by an upstream open reading frame (uORF, also called LT3) followed by two stop codons upstream of the Dam-fusion gene. Mini-white is used a selectable marker to identify transgenic flies. An attB site allows site-specific integration in attP containing fly lines using the ϕC31 integrase. (b) A lncRNA fused to the 3 tandem 5’ MS2 tags is expressed under the control of UAS. Mini-white is used a selectable marker to identify transgenic flies. An attB site allows site-specific integration in attP containing fly lines using the ϕC31 integrase. (c) 3 tandem 5’ MS2 tags are expressed under the control of UAS. This construct is used as a negative control to eliminate any non-specific signal caused by the association of the MS2 tags with specific regions of chromatin. Mini-white is used a selectable marker to identify transgenic flies. An attB site allows site-specific integration in attP containing fly lines using the ϕC31 integrase.

  2. Supplementary Figure 2 Normalization of RNA-DamID data.

    (a) RNA-DamID data is normalised by comparing enrichment of an MS2-tagged lncRNA, co-expressed with Dam-MCP over an 3xMS2 transcript co-expressed with Dam-MCP. (b) Genome browser tracks of negative control (3xMS2, Dam-MCP) and RNA-DamID (3xMS2-roX2, Dam-MCP) displayed in reads per million mapped. The negative control predominantly methylates open chromatin regions. RNA-DamID preferentially methylates roX2 targets on the X chromosome. Generating a ratio of the test over control reduces autosomal peaks. (c) roX2 RNA-DamID signal normalised to the negative control is highly correlated to roX2 RNA-DamID normalised to Dam-alone. Data is plotted as log2 normalised RNA-DamID signal enrichment over negative control.

  3. Supplementary Figure 3 RNA-DamID is highly reproducible.

    roX2 RNA-DamID biological replicates are highly correlated on the X chromosome but not on the autosomes where little signal is detected. Data is plotted as log2 normalized RNA-DamID signal enrichment over negative control.

  4. Supplementary Figure 4 RNA-DamID identifies 563 novel roX2-binding sites.

    RNA-DamID enables the identification of novel roX2 binding sites. These novel sites roX2 RNA-DamID co-localise with roX2 ChIRP, Msl3 TaDa and H4K16ac ChIP. RNA-DamID scale represents log2 fold change of 3xMS2-roX2, Dam-MCP compared to 3xMS2, Dam-MCP (average of two biological replicates). Msl3 TaDa scale is log2 fold change of Msl3-Dam fusion compared to Dam-alone. ChIRP signal is log2 transformed. H4K16ac represents log2 fold change of H4K16ac ChIP over input.

  5. Supplementary Figure 5 roX2 does not spread in cis.

    (a) roX2 does not spread from the integration site into flanking chromatin on chromosome 3L. Data is shown as reads mapped per million for roX2 and the negative control mapped separately from replicate 1. (b) Regions upstream and downstream of the site of transcription are methylated in both the negative control and 3xMS2-roX2. The roX2 transgene is highly methylated when co-expressed with Dam-MCP (this sequence is absent from the negative control).

  6. Supplementary Figure 6 roX1 and roX2 occupancy are highly correlated.

    roX1 and roX2 binding is whole larvae is highly correlated across the X chromosome. Data is plotted as log2 normalised RNA-DamID signal enrichment over negative control.

Supplementary information