Abstract
Long noncoding RNAs (lncRNAs) are important regulators of cell fate, yet little is known about mechanisms controlling lncRNA expression. Here we show that transcription is quantitatively different for lncRNAs and mRNAs—as revealed by deficiency of Dicer (Dcr), a key RNase that generates microRNAs (miRNAs). Dcr loss in mouse embryonic stem cells led unexpectedly to decreased levels of hundreds of lncRNAs. The canonical Dgcr8-Dcr-miRNA pathway is required for robust lncRNA transcriptional initiation and elongation. Computational and genetic epistasis analyses demonstrated that Dcr activation of the oncogenic transcription factor cMyc is partly responsible for lncRNA expression. A quantitative metric of mRNA-lncRNA decoupling revealed that Dcr and cMyc differentially regulate lncRNAs versus mRNAs in diverse cell types and in vivo. Thus, numerous lncRNAs may be modulated as a class in development and disease, notably where Dcr and cMyc act.
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References
Rinn, J.L. & Chang, H.Y. Genome regulation by long noncoding RNAs. Annu. Rev. Biochem. 81, 145–166 (2012).
Batista, P.J. & Chang, H.Y. Long noncoding RNAs: cellular address codes in development and disease. Cell 152, 1298–1307 (2013).
Bartel, D.P. MicroRNAs: target recognition and regulatory functions. Cell 136, 215–233 (2009).
Jeggari, A., Marks, D.S. & Larsson, E. miRcode: a map of putative microRNA target sites in the long non-coding transcriptome. Bioinformatics 28, 2062–2063 (2012).
Cesana, M. et al. A long noncoding RNA controls muscle differentiation by functioning as a competing endogenous RNA. Cell 147, 358–369 (2011).
Braconi, C. et al. microRNA-29 can regulate expression of the long non-coding RNA gene MEG3 in hepatocellular cancer. Oncogene 30, 4750–4756 (2011).
Tay, Y., Rinn, J. & Pandolfi, P.P. The multilayered complexity of ceRNA crosstalk and competition. Nature 505, 344–352 (2014).
Calabrese, J.M., Seila, A.C., Yeo, G.W. & Sharp, P.A. RNA sequence analysis defines Dicer's role in mouse embryonic stem cells. Proc. Natl. Acad. Sci. USA 104, 18097–18102 (2007).
Zheng, G.X. et al. A latent pro-survival function for the mir-290–295 cluster in mouse embryonic stem cells. PLoS Genet. 7, e1002054 (2011).
Guttman, M. et al. lincRNAs act in the circuitry controlling pluripotency and differentiation. Nature 477, 295–300 (2011).
Guttman, M. et al. Ab initio reconstruction of cell type–specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat. Biotechnol. 28, 503–510 (2010).
Trapnell, C., Pachter, L. & Salzberg, S.L. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25, 1105–1111 (2009).
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).
Ponting, C.P., Oliver, P.L. & Reik, W. Evolution and functions of long noncoding RNAs. Cell 136, 629–641 (2009).
Ulitsky, I. & Bartel, D.P. lincRNAs: genomics, evolution, and mechanisms. Cell 154, 26–46 (2013).
Leung, A.K. et al. Genome-wide identification of Ago2 binding sites from mouse embryonic stem cells with and without mature microRNAs. Nat. Struct. Mol. Biol. 18, 237–244 (2011).
Rabani, M. et al. Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells. Nat. Biotechnol. 29, 436–442 (2011).
Sharova, L.V. et al. Database for mRNA half-life of 19 977 genes obtained by DNA microarray analysis of pluripotent and differentiating mouse embryonic stem cells. DNA Res. 16, 45–58 (2009).
Melton, C., Judson, R.L. & Blelloch, R. Opposing microRNA families regulate self-renewal in mouse embryonic stem cells. Nature 463, 621–626 (2010).
Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603–607 (2012).
Cabili, M.N. et al. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev. 25, 1915–1927 (2011).
Harrow, J. et al. GENCODE: the reference human genome annotation for The ENCODE Project. Genome Res. 22, 1760–1774 (2012).
Davis, A.C., Wims, M., Spotts, G.D., Hann, S.R. & Bradley, A. A null c-myc mutation causes lethality before 10.5 days of gestation in homozygotes and reduced fertility in heterozygous female mice. Genes Dev. 7, 671–682 (1993).
Rahl, P.B. et al. c-Myc regulates transcriptional pause release. Cell 141, 432–445 (2010).
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).
Parkhomchuk, D. et al. Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Res. 37, e123 (2009).
O'Geen, H., Echipare, L. & Farnham, P.J. Using ChIP-seq technology to generate high-resolution profiles of histone modifications. Methods Mol. Biol. 791, 265–286 (2011).
Karolchik, D. et al. The UCSC Table Browser data retrieval tool. Nucleic Acids Res. 32, D493–D496 (2004).
Anders, S. & Huber, W. Differential expression analysis for sequence count data. Genome Biol. 11, R106 (2010).
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).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Chen, X., Vega, V.B. & Ng, H.H. Transcriptional regulatory networks in embryonic stem cells. Cold Spring Harb. Symp. Quant. Biol. 73, 203–209 (2008).
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).
Webster, D.E. et al. Enhancer-targeted genome editing selectively blocks innate resistance to oncokinase inhibition. Genome Res. 24, 751–760 (2014).
Acknowledgements
We thank members of the Chang laboratory, and P. Sharp (Massachusetts Institute of Technology) and A. Giraldez (Yale) for discussion, and for sharing unpublished data. We thank R. Blelloch (University of California, San Francisco) and A. Bradley (Wellcome Trust Sanger Institute) for sharing DGCR8 WT and KO mESCs, and cMyc KO mESCs respectively. G.X.Y.Z. was supported by the Leukemia and Lymphoma Society (grant 5549-13 to G.X.Y.Z.) and a Dean's Fellowship from Stanford University. The study was supported by the US National Institutes of Health (grant R01-CA118750 to H.Y.C.) and California Institute for Regenerative Medicine (grant RB4-05763 to H.Y.C.). H.Y.C. is supported as an Early Career Scientist of the Howard Hughes Medical Institute.
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G.X.Y.Z. and H.Y.C. initiated the project. G.X.Y.Z. and H.Y.C. designed the experiments. G.X.Y.Z. performed the experiments and the computational analysis. B.T.D., D.E.W. and P.A.K. designed and implemented bioinformatics and microarray screens. The manuscript was prepared by G.X.Y.Z. and H.Y.C. with input from all authors.
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Integrated supplementary information
Supplementary Figure 1 Validation of sequencing data.
Sequencing tracks of (a) Casp2, (b) cMyc, (c) lncRNA NR_015519, and (d) lnc543. The y-axis represents number of reads per million. Transcript structure is shown at the bottom in black, and exons are shown in black boxes. (e) Cdfs of LFC of lncRNAs (red) and coding genes (blue) between Dcr WT and KO mESCs. The expression of coding genes in WT mESCs is matched to that of lncRNAs. lncRNAs are significantly downregulated in Dcr KO mESCs relative to coding genes (p<2.2x10-16). (f) Cdfs of LFC of mRNA expression between Dcr WT and KO mESCs. Plots include “predicted coding targets” of miR-295 (blue line), and “coding control” (grey line). “predicted coding targets” include mRNAs that have a miR-295 target in their 3' UTRs. The “coding control” mRNA set was selected to match the predicted targets in expression, 3' UTR length and composition. “predicted coding targets” are derepressed in Dcr KO mESCs (p≤ 2.2x10−16 by rank sum test). (g) Cdfs of LFC of coding targets of miR-295, using the full-length sequence. Similarly, “predicted coding targets” are depressed in Dcr KO mESCs (p = 1.33x10−10). (h) Cdfs of LFC in lncRNA expression between Dcr WT and KO mESCs. Plots include “predicted lncRNA targets” of miR-295 (red line), and “lncRNA control” (grey line). “predicted lncRNA targets” include lncRNAs that have a miR-295 target in their full length sequences. “predicted lncRNA targets” are derepressed in Dcr KO mESCs (p = 1.66x10−3).
Supplementary Figure 2 lncRNAs are regulated by DGCR8, DCR and miR-295.
(a) Validation of Nanostring data against the RNA-seq data. X-axis, LFC of lncRNAs in Dcr KO and WT mESCs calculated from the RNA-seq data. Y-axis, LFC of lncRNAs detected by nanostring. r = 0.75. (b) Overexpression of Dcr and miR-295 can rescue the expression of miR-295 in Dcr KO mESCs. RT-qPCR of miR-295 after transfection of Dcr, Dcr Mutant (DcrMut), miR-295 or control mimics (ctl). (c) Overexpression of miR-295 can rescue the expression of miR-295 in Dgcr8 KO mESCs. RT-qPCR of miR-295 after transfection of miR-295 or control mimics (ctl) in Dgcr8 KO mESCs. (d) miR-295 and Dcr can rescue the expression of down-regulated lncRNAs. RT-qPCR of lncRNAs after miR-295 overexpression (blue) and Dcr overexpression (pink). Their LFC between Dcr KO and WT cells is plotted (in green) as a comparison. (e) miR-96 cannot rescue the expression of down-regulated lncRNAs. RT-qPCR of lncRNAs after miR-295 overexpression (blue) and miR-96 overexpression (grey). (f) miR-295 can rescue the expression of downregulated lncRNAs in DGCR8 KO mESCs. RT-qPCR of lncRNAs after miR-295 overexpression in DGCR8 KO cells (blue). Their LFC between DGCR8 KO and WT cells is plotted (in green) as a comparison. (g) Scatter plot of LFC of lncRNAs in Dcr KO and Dgcr8 KO cells measured by Nanostring. X-axis, LFC of lncRNAs in Dcr KO and WT mESCs. Y-axis, LFC of lncRNAs in Dgcr8 KO and WT mESCs. r = 0.72. For b-f, n≥3, mean ± S.E.M.
Supplementary Figure 3 Validation of half-life and chromatin data.
(a) Half life of 7 mRNAs was compared to published half life data. The correlation is 0.83. (b) Synthesis rate of 7 mRNAs as positive controls. (c) Half life of 7 mRNAs as positive controls. For a-c, n≥3, mean ± S.E.M. (d) Down-regulated coding genes have a similar H3K4me3 signal in WT and Dcr KO cells. Average signal intensity of H3K4me3 across down-regulated mRNA genes in WT (magenta) and Dcr KO (green) mESCs. Y-axis represents average log2 value of normalized reads. (e) Average signal intensity of H3K36me3 across down-regulated mRNA genes in WT (magenta) and Dcr KO (green) mESCs. Y-axis represents average log2 value of normalized reads.
Supplementary Figure 4 cMyc has an important role in lncRNA expression of mESCs.
(a) Relative expression change (RPKM) of candidate factors between Dcr KO and WT mESCs. (b) Heatmap of cMyc ChIP-seq signals at down-regulated and up-regulated lncRNAs. (c) Cdfs of LFC in lncRNA expression between Dcr WT and KO mESCs are plotted. Plots include “coding genes” (blue line), “lncRNAs” (dark red line), and “lncRNAs with cMyc binding sites (red line). lncRNAs with cMyc binding sites are much more down-regulated than the rest of lncRNAs (p ≤ 2.2x10−16 by rank sum test). (d) Cdfs of LFC in mRNA expression between Dcr WT and KO mESCs are plotted. Plots include “mRNAs with cMyc binding sites” (dark blue line) and “coding genes without cMyc binding sites” (black line). (e) Average signal intensity of H3K4me3 across mRNA genes with (top) and without (bottom) cMyc binding sites in WT (magenta) and Dcr KO (green) mESCs. (f) Average signal intensity of H3K36me3 across mRNA genes with (top) and without (bottom) cMyc binding sites in WT (magenta) and Dcr KO (green) mESCs. Y-axis represents average log2 value of normalized reads. (g) Average signal intensity of Pol2 occupancy across lncRNAs with cMyc binding sites (top) and lncRNAs without cMyc binding sites (bottom) before (black) and after (green) the treatment with cMyc inhibitor. Y-axis represents average value of rank normalized reads.
Supplementary Figure 5 Genomic organization of lncRNAs affects their sensitivity to Dcr loss.
(a) Sequencing track of a divergent lncRNA (red)-coding gene (blue) pair expression in WT (magenta) and Dcr KO (green) mESCs. (b) Classification of 2229 lncRNAs based on their orientation and distances to neighboring coding genes. (c) Cdfs of divergent lncRNAs (black) and their corresponding coding gene pair (dark blue). (d) lncRNAs that are divergent from coding genes tend to be downregulated in Dcr KO mESCs. There are 41% of them relative to 14% of them in up-regulated lncRnAs. (e) Cdfs of LFC in lncRNA expression between Dcr WT and KO mESCs are plotted. “cMyc-only lncRNAs” (red) are lncRNAs that only have cMyc binding sites. “divergent-only lncRNAs” (black) are lncRNAs that are only divergent from coding genes. “cMyc + divergent” (purple) lncRNAs are lncRNAs that have both cMyc binding sites and are divergent from coding genes. All 3 classes of lncRNAs are significantly more downregulated (p < 2.2x10−16) in Dcr KO mESCs relative to “all lncRNAs” (dark red), although they are not significantly different from each other.
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Zheng, G., Do, B., Webster, D. et al. Dicer-microRNA-Myc circuit promotes transcription of hundreds of long noncoding RNAs. Nat Struct Mol Biol 21, 585–590 (2014). https://doi.org/10.1038/nsmb.2842
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DOI: https://doi.org/10.1038/nsmb.2842
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