Abstract
Eukaryotic gene expression is heavily regulated at the transcriptional and post-transcriptional levels. An additional layer of regulation occurs co-transcriptionally through processing and decay of nascent transcripts physically associated with chromatin. This process involves RNA interference (RNAi) machinery and is well documented in yeast, but little is known about its conservation in mammals. Here we show that Dgcr8 and Drosha physically associate with chromatin in murine embryonic stem cells (mES), specifically with a subset of transcribed coding and noncoding genes. Dgcr8 recruitment to chromatin is dependent on transcription as well as methyltransferase-like 3 (Mettl3), which catalyzes RNA N6-methyladenosine (m6A). Intriguingly, we found that acute temperature stress causes radical relocalization of Dgcr8 and Mettl3 to heat-shock genes, where they act to co-transcriptionally mark mRNAs for subsequent RNA degradation. Together, our findings elucidate a novel mode of co-transcriptional gene regulation, in which m6A serves as a chemical mark that instigates subsequent post-transcriptional RNA-processing events.
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Acknowledgements
We thank F. Mohn for discussion and critical feedback on the manuscript and H. Pickersgill (Life Science Editors) for editorial assistance. We thank M. Chong (St. Vincent's Institute of Medical Research) for providing Drosha cKO mES cells, N. Laschet for excellent technical assistance, and R. Villaseñor for assistance in the first step of cloning SpCas9-2A-mCherry and immunofluorescence sample preparation. We would like to thank the FMI Functional Genomics facility for assistance in library construction and next generation sequencing. This work was supported by funds from the Swiss National Science Foundation NCCR RNA & Disease (grant no. 141735). The Friedrich Miescher Institute for Biomedical Research is supported by the Novartis Research Foundation.
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P.K. performed experiments and analyzed data. A.W. generated mES cell lines. M.M. and C.N. performed m6A analysis by MS. Bioinformatic and computational analysis was performed by S.H.C. P.K. and M.B. designed experiments, prepared figures, and wrote the manuscript. All authors discussed the results and commented on the manuscript.
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Integrated supplementary information
Supplementary Figure 1 Endogenous gene tagging to study subcellular localization and chromatin binding.
a, b, Schematic of experimental set-up to endogenously tag RNAi factors using the CRISPR Cas9 technology, and to study protein localization by microscopy and chromatin interactions by ChIP-sequencing. c, Immunofluorescent labelling of 3xFLAG tagged Dgcr8, Drosha, Dicer, and untagged cell line as background control. DAPI was used to counterstain nuclei. Zoom-in of 3xFLAG stained cells highlighting varying nuclear/cytoplasmic ratios of different factors, scale bar = 20μm.
Supplementary Figure 2 DSG cross-linking dramatically improves sensitivity of Microprocessor ChIP-sequencing.
a, Scatter plot comparing Dgcr8 chromatin binding to input sample. Cells were cross-linked with Formaldehyde (FA) only. Enrichment represents log2 ratios of IP vs. input in 5-kb windows tiled across the genome, both normalized for library size and GC content, with a pseudo-count of 8 added. Color as in Fig. 1b; points outlined with white circles represent bins with >= 4-fold enrichment vs. input. b, Dgcr8-FLAG-Avi cells were cross-linked with Disuccinimidyl Glutarate (DSG) and FA. Scatter plot as in a. c, ChIP-qPCR analysis of binding at the mir-290 cluster for Dgcr8 and Dicer (left), or Drosha and untagged cells (right, untagged IP and input DNA respectively). Cells were cross-linked with FA or DSG followed by FA as indicated. Bars represent mean of 3 technical replicates for 2 independent experiments; Error bars= s.d; for Dgcr8. For Drosha bars represent mean of 3 technical replicates for Drosha, Error bars= s.d. d, Dicer-FLAG-Avi tagged cells were cross-linked with DSG and FA and ChIP material sequenced. No significant enrichments over input samples were detected. e, UCSC Genome browser shot of Dgcr8 locus displaying RNA-seq profiles in untreated vs. 4OHT treated conditional KO Drosha mES cells (top). Below, ChIP profile of Dgcr8 and input. Scale is mapped reads in 50bp bins normalized to mean library size. f, Meta-plot depicting Drosha ChIP-seq enrichments at genes aligned to the transcription start site (TSS) and transcription end site (TES). Enrichment is calculated as the Log2 ratio of IP against the parental input. GC normalization was done over 1-kb windows, and the plot shows enrichments averaged over 50-bp bins.
Supplementary Figure 3 Mettl3 binding to chromatin, including miRNA-encoding loci, is dependent on transcription.
a, Scatter plot comparing Mettl3 chromatin binding to input sample. Enrichment represents log2 ratios of IP vs. input in 5-kb windows tiled across the genome, both normalized for library size and GC content, with a pseudo-count of 8 added. b, UCSC Genome browser shots of Mettl3 ChIP profiles and Input samples at the Zfp57 locus. Scale is mapped reads in 50bp bins normalized to mean library size. c, Meta-plot of m6A-RNA-seq from (Batista et. al., Cell Stem Cell 15, 707-719, 2014) at genes aligned to coding sequence start and end. Mean profile (Top) shows a sharp peak towards the 3’ of genes. d, ChIP-qPCR analysis of Mettl3 binding at the mir-290 cluster and treatment with 15μg/μl of α-amanitin to block transcription. Bars represent mean of 3 technical replicates for 2 experiments; Εrror bars = s.d. e, Scatter plot comparing Dgcr8 to Mettl3 enrichments (defined as in a,) at miRNA-encoding loci. Highlighted in red are members of the mir-290 cluster.
Supplementary Figure 4 Generation of Mettl3 KO mES lines using CRISPR-Cas9.
a, Scheme of two CRISPR-Cas9 strategies (a single cut and integration of a 3X stop cassette, left; or two independent cuts removing parts of exon 2 and 3, right) to ablate the loci encoding Mettl3. b, Western blot analysis of Mettl3 and Mettl14 levels in mES cells where Mettl3 has been ablated with 2 cuts or a 3xStop integration. Clones where both Mettl3 and Mettl14 levels are low were selected for further analysis (highlighted in red boxes, clones 1d, 4d and 3f). c, Schematic of plasmid constructed for stable rescue of Mettl3. d, Western blot analysis of Mettl3 and Mettl14 levels in mES cells where Mettl3 has been ablated as well as puro-resistant stable clones where Mettl3 expression has been rescued stably from the plasmid described in c. e, ChIP-PCR assay of Dgcr8 at the 2 distinct miRNA clusters expressed in ES cells in Mettl3 KO cells and Mettl3 expression rescued from plasmid. Enrichments are expressed as % enrichment relative to the parental line. Bars represent mean of 4 independent experiments; Εrror bars = s.d. n=4; p value was calculated using two-tailed Student’s t-test.
Supplementary Figure 5 Impact of heat shock on Mettl3 and RNAi factor localization.
a, Quantification of Mettl3 nuclear foci within Z-stacks after heat shock (1hour 42oC; left panel) and number of foci that co-localize with strong αHSF1 staining (right panel; n= 119 cells). b and c, ChIP-qPCR analysis of Dgcr8 (b) and Mettl3 (c) binding at the mir-290 cluster and Hsp70 locus (for Hsp70, qPCR primers used amplify regions within Hspa1a and Hspa1b) comparing binding at 37oC vs. 42oC. Bars represent mean of 3 technical replicates; Εrror bars = s.d. for Dgcr8. For Mettl3, bars represents mean of 3 technical replicates for 2 independent experiments; Εrror bars = s.d. d, ChIP-qPCR analysis of Dgcr8 binding at Mir-290 and Hsp70 in control cells and Mettl3 KO clones after 42°C heat shock. Cells were cross-linked with FA and DSG. Bars represent mean of 4 independent experiments; Error bars = s.d; p values were calculated using two-tailed Student’s t-test.
Supplementary Figure 6 Mettl3 and the MP regulate Hsp70 mRNA stability and protein levels in response to heat stress.
a, Scheme describing temperature shifts and duration, followed by transcription inhibition using ActinomycinD and subsequent cell harvesting time points. b, Half-life measurements of control transcript Tbp in Mettl3 KO and a rescue clone. Cells were treated as described in a. Half-life estimation based on exponential regression line shows no significant difference between different lines. c, Half-life measurements of Hsp70 mRNA in Drosha cKO (4 days tamoxifen treatment) and control cells (no tamoxifen treatment). Cells were exposed to HS and treated as described in a. d, Hsp70 protein levels of unstressed cells (no HS) or cells harvested at 0, 2, or 4 hrs after exposure for 1h at 42oC. Wt cells (left) are compared to Mettl3 KO (top right panel) or Dgcr8 cKO (bottom right panel) and αTubulin was used as loading control. e, Hsp70 protein levels at 4 hours after exposure for 1h at 42oC in WT, Mettl3 KO, or Dgcr8 cKO.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–6. (PDF 786 kb)
Supplementary Table 1
Oligonucleotides used in this study. (XLSX 13 kb)
Supplementary Data Set 1
Original western blot images shown in Figure 5. a-d, Un-cropped immuno-blots from Figure 5g. αHSP70, αMettl3, αDgcr8 and αTubulin (a-d respectively) of cell lysates from WT, Mettl3 KO and Dgcr8 cKO cells after 42oC heat shock and 4 hrs recovery at 37oC. Two amounts of total protein were loaded in alternating wells,1.25μg and 2.5μg. Arrow in c indicates full-length Dgcr8 in nontamoxifen treated cells, whereas * indicates truncated inactive protein after recombination. # in d shows residual signal of αHSP70 antibody as blot was stripped and re-incubated with αTubulin. (PDF 2612 kb)
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Knuckles, P., Carl, S., Musheev, M. et al. RNA fate determination through cotranscriptional adenosine methylation and microprocessor binding. Nat Struct Mol Biol 24, 561–569 (2017). https://doi.org/10.1038/nsmb.3419
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DOI: https://doi.org/10.1038/nsmb.3419
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