A novel class of microRNA-recognition elements that function only within open reading frames

Abstract

MicroRNAs (miRNAs) are well known to target 3′ untranslated regions (3′ UTRs) in mRNAs, thereby silencing gene expression at the post-transcriptional level. Multiple reports have also indicated the ability of miRNAs to target protein-coding sequences (CDS); however, miRNAs have been generally believed to function through similar mechanisms regardless of the locations of their sites of action. Here, we report a class of miRNA-recognition elements (MREs) that function exclusively in CDS regions. Through functional and mechanistic characterization of these ‘unusual’ MREs, we demonstrate that CDS-targeted miRNAs require extensive base-pairing at the 3′ side rather than the 5′ seed; cause gene silencing in an Argonaute-dependent but GW182-independent manner; and repress translation by inducing transient ribosome stalling instead of mRNA destabilization. These findings reveal distinct mechanisms and functional consequences of miRNAs that target CDS versus the 3′ UTR and suggest that CDS-targeted miRNAs may use a translational quality-control-related mechanism to regulate translation in mammalian cells.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: A miR-20a-target site in DAPK3 functions exclusively in CDS.
Fig. 2: CDS- and 3′-UTR-targeted miRNAs require distinct base-pairing at the 3′ end and 5′ seed.
Fig. 3: CDS-targeted miRNAs function in an Ago-dependent but GW182-independent manner.
Fig. 4: Inefficient recruitment of GW182 to CDS RISC.
Fig. 5: CDS-targeted miRNA induces aborted translation.
Fig. 6: Effects of CDS-targeted miRNAs on ribosome binding.

Data availability

All deep-sequencing data generated in this study have been deposited in the Gene Expression Omnibus database under accession number GSE115146. Source data for the graphs in all figures are available online. Other data are available from the corresponding author upon reasonable request.

References

  1. 1.

    Pasquinelli, A. E. MicroRNAs and their targets: recognition, regulation and an emerging reciprocal relationship. Nat. Rev. Genet. 13, 271–282 (2012).

  2. 2.

    Jonas, S. & Izaurralde, E. Towards a molecular understanding of microRNA-mediated gene silencing. Nat. Rev. Genet. 16, 421–433 (2015).

  3. 3.

    Bartel, D. P. MicroRNAs: target recognition and regulatory functions. Cell 136, 215–233 (2009).

  4. 4.

    Wang, Y. et al. A new transmyocardial degradable stent combined with growth factor, heparin, and stem cells in acute myocardial infarction. Cardiovasc. Res. 84, 461–469 (2009).

  5. 5.

    Schirle, N. T. & MacRae, I. J. The crystal structure of human Argonaute2. Science 336, 1037–1040 (2012).

  6. 6.

    Rajewsky, N. microRNA target predictions in animals. Nat. Genet. 38, S8–S13 (2006).

  7. 7.

    Lal, A. et al. miR-24 inhibits cell proliferation by targeting E2F2, MYC, and other cell-cycle genes via binding to “seedless” 3’UTR microRNA recognition elements. Mol. Cell 35, 610–625 (2009).

  8. 8.

    Helwak, A., Kudla, G., Dudnakova, T. & Tollervey, D. Mapping the human miRNA interactome by CLASH reveals frequent noncanonical binding. Cell 153, 654–665 (2013).

  9. 9.

    van Kouwenhove, M., Kedde, M. & Agami, R. MicroRNA regulation by RNA-binding proteins and its implications for cancer. Nat. Rev. Cancer 11, 644–656 (2011).

  10. 10.

    Gu, S., Jin, L., Zhang, F., Sarnow, P. & Kay, M. A. Biological basis for restriction of microRNA targets to the 3′ untranslated region in mammalian mRNAs. Nat. Struct. Mol. Biol. 16, 144–150 (2009).

  11. 11.

    Duursma, A. M., Kedde, M., Schrier, M., le Sage, C. & Agami, R. miR-148 targets human DNMT3b protein coding region. RNA 14, 872–877 (2008).

  12. 12.

    Tay, Y., Zhang, J., Thomson, A. M., Lim, B. & Rigoutsos, I. MicroRNAs to Nanog, Oct4 and Sox2 coding regions modulate embryonic stem cell differentiation. Nature 455, 1124–1128 (2008).

  13. 13.

    Hausser, J., Syed, A. P., Bilen, B. & Zavolan, M. Analysis of CDS-located miRNA target sites suggests that they can effectively inhibit translation. Genome Res. 23, 604–615 (2013).

  14. 14.

    Xue, Y. et al. Direct conversion of fibroblasts to neurons by reprogramming PTB-regulated microRNA circuits. Cell 152, 82–96 (2013).

  15. 15.

    Chi, S. W., Zang, J. B., Mele, A. & Darnell, R. B. Argonaute HITS-CLIP decodes microRNA–mRNA interaction maps. Nature 460, 479–486 (2009).

  16. 16.

    Filipowicz, W., Bhattacharyya, S. N. & Sonenberg, N. Mechanisms of post-transcriptional regulation by microRNAs: are the answers in sight? Nat. Rev. Genet. 9, 102–114 (2008).

  17. 17.

    Wu, L., Fan, J. & Belasco, J. G. MicroRNAs direct rapid deadenylation of mRNA. Proc. Natl Acad. Sci. USA 103, 4034–4039 (2006).

  18. 18.

    Bagga, S. et al. Regulation by let-7 and lin-4 miRNAs results in target mRNA degradation. Cell 122, 553–563 (2005).

  19. 19.

    Giraldez, A. J. et al. Zebrafish MiR-430 promotes deadenylation and clearance of maternal mRNAs. Science 312, 75–79 (2006).

  20. 20.

    Guo, H., Ingolia, N. T., Weissman, J. S. & Bartel, D. P. Mammalian microRNAs predominantly act to decrease target mRNA levels. Nature 466, 835–840 (2010).

  21. 21.

    Djuranovic, S., Nahvi, A. & Green, R. miRNA-mediated gene silencing by translational repression followed by mRNA deadenylation and decay. Science 336, 237–240 (2012).

  22. 22.

    Huntzinger, E. & Izaurralde, E. Gene silencing by microRNAs: contributions of translational repression and mRNA decay. Nat. Rev. Genet. 12, 99–110 (2011).

  23. 23.

    Pillai, R. S. et al. Inhibition of translational initiation by Let-7 microRNA in human cells. Science 309, 1573–1576 (2005).

  24. 24.

    Humphreys, D. T., Westman, B. J., Martin, D. I. K. & Preiss, T. MicroRNAs control translation initiation by inhibiting eukaryotic initiation factor 4E/cap and poly(A) tail function. Proc. Natl Acad. Sci. USA 102, 16961–16966 (2005).

  25. 25.

    Seggerson, K., Tang, L. & Moss, E. G. Two genetic circuits repress the Caenorhabditis elegans heterochronic gene lin-28 after translation initiation. Dev. Biol. 243, 215–225 (2002).

  26. 26.

    Petersen, C. P., Bordeleau, M. E., Pelletier, J. & Sharp, P. A. Short RNAs repress translation after initiation in mammalian cells. Mol. Cell 21, 533–542 (2006).

  27. 27.

    Nottrott, S., Simard, M. J. & Richter, J. D. Human let-7a miRNA blocks protein production on actively translating polyribosomes. Nat. Struct. Mol. Biol. 13, 1108–1114 (2006).

  28. 28.

    Maroney, P. A., Yu, Y. & Nilsen, T. W. MicroRNAs, mRNAs, and translation. Cold Spring Harb. Symp. Quant. Biol. 71, 531–535 (2006).

  29. 29.

    Tat, T. T., Maroney, P. A., Chamnongpol, S., Coller, J. & Nilsen, T. W. Cotranslational microRNA mediated messenger RNA destabilization. eLife 5, e12880 (2016).

  30. 30.

    Cai, Z. et al. Oncogenic miR-17/20a forms a positive feed-forward loop with the p53 kinase DAPK3 to promote tumorigenesis. J. Biol. Chem. 290, 19967–19975 (2015).

  31. 31.

    O’Donnell, K. A., Wentzel, E. A., Zeller, K. I., Dang, C. V. & Mendell, J. T. c-Myc-regulated microRNAs modulate E2F1 expression. Nature 435, 839–843 (2005).

  32. 32.

    Forman, J. J., Legesse-Miller, A. & Coller, H. A. A search for conserved sequences in coding regions reveals that the let-7 microRNA targets Dicer within its coding sequence. Proc. Natl Acad. Sci. USA 105, 14879–14884 (2008).

  33. 33.

    Elcheva, I., Goswami, S., Noubissi, F. K. & Spiegelman, V. S. CRD-BP protects the coding region of betaTrCP1 mRNA from miR-183-mediated degradation. Mol. Cell 35, 240–246 (2009).

  34. 34.

    Takagi, S. et al. MicroRNAs regulate human hepatocyte nuclear factor 4α, modulating the expression of metabolic enzymes and cell cycle. J. Biol. Chem. 285, 4415–4422 (2010).

  35. 35.

    Broughton, J. P., Lovci, M. T., Huang, J. L., Yeo, G. W. & Pasquinelli, A. E. Pairing beyond the seed supports microRNA targeting specificity. Mol. Cell 64, 320–333 (2016).

  36. 36.

    Eichhorn, S. W. et al. mRNA destabilization is the dominant effect of mammalian microRNAs by the time substantial repression ensues. Mol. Cell 56, 104–115 (2014).

  37. 37.

    Behm-Ansmant, I. et al. mRNA degradation by miRNAs and GW182 requires both CCR4:NOT deadenylase and DCP1:DCP2 decapping complexes. Genes Dev. 20, 1885–1898 (2006).

  38. 38.

    Jakymiw, A. et al. Disruption of GW bodies impairs mammalian RNA interference. Nat. Cell Biol. 7, 1267–1274 (2005).

  39. 39.

    Liu, J. et al. Argonaute2 is the catalytic engine of mammalian RNAi. Science 305, 1437–1441 (2004).

  40. 40.

    Liu, J. et al. A role for the P-body component GW182 in microRNA function. Nat. Cell Biol. 7, 1261–1266 (2005).

  41. 41.

    Zhao, Y. et al. MicroRNA-mediated repression of nonsense mRNAs. eLife 3, e03032 (2014).

  42. 42.

    Meijer, H. A. et al. Translational repression and eIF4A2 activity are critical for microRNA-mediated gene regulation. Science 340, 82–85 (2013).

  43. 43.

    Donnelly, M. L. et al. The ‘cleavage’ activities of foot-and-mouth disease virus 2A site-directed mutants and naturally occurring `2A-like' sequences. J. Gen. Virol. 82, 1027–1041 (2001).

  44. 44.

    Kim, J. H. et al. High cleavage efficiency of a 2A peptide derived from porcine teschovirus-1 in human cell lines, zebrafish and mice. PLoS One 6, e18556 (2011).

  45. 45.

    Ishimura, R. et al. Ribosome stalling induced by mutation of a CNS-specific tRNA causes neurodegeneration. Science 345, 455–459 (2014).

  46. 46.

    Buskirk, A. R. & Green, R. Ribosome pausing, arrest and rescue in bacteria and eukaryotes. Phil. Trans. R. Soc. Lond. B 372, 20160183 (2017).

  47. 47.

    Hafner, M. et al. Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 141, 129–141 (2010).

  48. 48.

    Grosswendt, S. et al. Unambiguous identification of miRNA:target site interactions by different types of ligation reactions. Mol. Cell 54, 1042–1054 (2014).

  49. 49.

    Ishigaki, Y., Li, X., Serin, G. & Maquat, L. E. Evidence for a pioneer round of mRNA translation: mRNAs subject to nonsense-mediated decay in mammalian cells are bound by CBP80 and CBP20. Cell 106, 607–617 (2001).

  50. 50.

    Doma, M. K. & Parker, R. Endonucleolytic cleavage of eukaryotic mRNAs with stalls in translation elongation. Nature 440, 561–564 (2006).

  51. 51.

    Shoemaker, C. J., Eyler, D. E. & Green, R. Dom34:Hbs1 promotes subunit dissociation and peptidyl-tRNA drop-off to initiate no-go decay. Science 330, 369–372 (2010).

  52. 52.

    Presnyak, V. et al. Codon optimality is a major determinant of mRNA stability. Cell 160, 1111–1124 (2015).

  53. 53.

    Iwakawa, H. O. & Tomari, Y. Molecular insights into microRNA-mediated translational repression in plants. Mol. Cell 52, 591–601 (2013).

  54. 54.

    Woolstenhulme, C. J., Guydosh, N. R., Green, R. & Buskirk, A. R. High-precision analysis of translational pausing by ribosome profiling in bacteria lacking EFP. Cell Rep. 11, 13–21 (2015).

  55. 55.

    Bhattacharyya, S. N., Habermacher, R., Martine, U., Closs, E. I. & Filipowicz, W. Relief of microRNA-mediated translational repression in human cells subjected to stress. Cell 125, 1111–1124 (2006).

  56. 56.

    Parker, R. & Sheth, U. P bodies and the control of mRNA translation and degradation. Mol. Cell 25, 635–646 (2007).

  57. 57.

    Decker, C. J. & Parker, R. P-bodies and stress granules: possible roles in the control of translation and mRNA degradation. Cold Spring Harb. Perspect. Biol. 4, a012286 (2012).

  58. 58.

    Aizer, A. et al. Quantifying mRNA targeting to P-bodies in living human cells reveals their dual role in mRNA decay and storage. J. Cell Sci. 127, 4443–4456 (2014).

  59. 59.

    Ishimura, R., Nagy, G., Dotu, I., Chuang, J. H. & Ackerman, S. L. Activation of GCN2 kinase by ribosome stalling links translation elongation with translation initiation. eLife 5, e14295 (2016).

  60. 60.

    Van Nostrand, E. L. et al. Robust transcriptome-wide discovery of RNA-binding protein binding sites with enhanced CLIP (eCLIP). Nat. Methods 13, 508–514 (2016).

  61. 61.

    Adiconis, X. et al. Comparative analysis of RNA sequencing methods for degraded or low-input samples. Nat. Methods 10, 623–629 (2013).

  62. 62.

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

  63. 63.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013)..

  64. 64.

    Loeb, G. B. et al. Transcriptome-wide miR-155 binding map reveals widespread noncanonical microRNA targeting. Mol. Cell 48, 760–770 (2012).

  65. 65.

    Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

  66. 66.

    Robinson, M. D., McCarthy, D. J. & Smyth, G. K. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

  67. 67.

    Rehmsmeier, M., Steffen, P., Hochsmann, M. & Giegerich, R. Fast and effective prediction of microRNA/target duplexes. RNA 10, 1507–1517 (2004).

  68. 68.

    Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).

Download references

Acknowledgements

This work was supported by grants from the Ministry of Science and Technology of China (2017YFA0506400, Y. Zhou and X.-D.F.), the National Natural Science Foundation of China (31670827 and 91640115, Y. Zhou), the Chinese 111 program grant (B06018, X.-D.F.), Chinese Academy of Science foundation grant (22KJZD-EW-L12, X.Z.) and NIH grants (HG004659, GM049369 and GM052872, X.-D.F.). pRL-SV40 plasmids carrying IRESs from EMCV, HCV, and CrPV were generous gifts from M. Bushell (Medical Research Council Toxicology Unit, UK).

Author information

Z. Cai, K.Z., X.Z., Y. Zhou, T.N., and X.-D.F. designed the experiments; Z. Cai, K.Z., X.Z., and W.R. performed most experiments; J.Z., B.Z., Z. Chen, D.W., and Y. Zhou analyzed the data; Y. Zhao and L.W. performed the deadenylation assay; R.C., G.L., Q.Z., Y.X., and Y.Q. contributed additional data. Z. Cai, K.Z., Y. Zhou, T.N., and X.-D.F. wrote the paper.

Correspondence to Yu Zhou or Xiang-Dong Fu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Integrated supplementary information

Supplementary Figure 1 MicroRNA represses target proteins without causing mRNA decay.

a,b, Western blotting analysis of miR-20a target genes in response to increasing doses of miR-20a mimic (a) or antagomir (b). c,d, RT-qPCR analysis of miR-20a levels in HeLa cells transfected with miR-20a mimic (c) or antagomir (d). e,f, RT-qPCR analysis of DAPK3 mRNA levels in HeLa cells transfected with miR-20a mimic (e) or antagomir (f). g, Luciferase reporter constructs containing the miR-20a MRE from DAPK3 (native) in Renilla 5’ UTR or mutated to restore base-pairing in the 5’ end (seed) coupled with progressive mismatches (3MM+seed) in the 3’ end. h,i, Results of the luciferase reporter assays (h) and quantification of luciferase mRNA (i). j,k, mRNA levels of luciferase reporters containing individual MREs from 4 indicated genes that function in both CDS and 3’UTR (j) or those that function only in CDS (k), as shown in main Fig. 2e,f. l,m, Luciferase activities from the reporters containing individual MREs from 4 indicated genes that function only in CDS in response to co-transfected Let-7b mimic (l) or antagomir (m). NC: Non-specific oligo control; SC: Scrambled RNA oligo control. n, Western blotting analysis of three additional Let-7b target genes. The three gene products were analyzed in HeLa cells transfected with non-specific RNA oligonucleotide control (NC), Let-7b mimic, or antagomir, as indicated. Actin served as loading control. The data in c,d,e,f,h,i,j,k,l,m were based on 3 independent experiments. *p<0.05; **p<0.01; ***p<0.001 (Student’s t-test). Source data

Supplementary Figure 2 Mutation analysis of multiple Let-7b MREs in CDS regions of individual genes.

a,b,c,d, Deduced base-paring between Let-7b and its targets in individual genes that function only in CDS, as described in main Fig. 2f. A panel of mutants in each targeting site is also shown with calculated base-pairing potential (∆G). The constructs on the left of each panel contain progressive mutations in 3’ side and the constructs on the right of each panel carry progressive mutations in 3’ side with restored base-pairing in 5’ seed (red-labeled nucleotides). e,f, Luciferase activities of individual reporters containing different mutations, without (e) or with restored seed (f), as indicated. The data in e and f were based on 3 independent experiments. *p<0.05; **p<0.01; ***p<0.001 (Student’s t-test). Source data

Supplementary Figure 3 Luciferase activities and mRNA levels of the reporters with or without restored seed.

a, Constructs containing various MREs after restoring seed base pairing (right) inserted in 3’UTR. b,c, Luciferase activities (b) and mRNA levels (c) in HeLa cells transfected with seed restored constructs in a. d, Constructs containing various ERAP2-derived MREs with decreasing base-pairing potentials (∆G) in 5’ seed inserted in CDS. e, Luciferase activities (upper panel) and mRNA levels (lower panel) in HeLa cells transfected with the constructs in d. The data in b,c,e were based on 3 independent experiments. *p<0.05; **p<0.01; ***p<0.001 (Student’s t-test). Source data

Supplementary Figure 4 Functional test for Ago2 or GW182 dependency and for CDS-targeted miRNA to induce translation abortion.

a, One miR-20a MRE and four Let-7b MREs were tested in wild-type or Ago2 knockout MEFs. Note that Ago2 knockout MEFs contain a small population of undeleted cells, which likely contributed to the basal level of Ago2, as shown by western blotting on top. The MREs inserted in both CDS (black bar) or 3’UTR (grey bar) were tested. b, One miR-20a MRE and four Let-7b MREs were tested in non-specific siRNA-treated (NC) or siGW182-treated HeLa cells. Knockdown efficiency was determined by western blotting, as shown on top. The MREs inserted in both CDS (black bar) or 3’UTR (gray bar) were tested. The data shown in a and b were based on 3 independent experiments. *p<0.05; **p<0.01; ***p<0.001 (Student’s t-test). c, Western blotting analysis of endogenous proteins in non-specific siRNA-treated (-) or siGW182-treated (+) HeLa in response to miR-20a mimic (left) or antagomir (right). d, Repeated experiments as in main Fig. 4b. Western blotting analysis of Ago2 and GW182 associated with the Renilla luciferase reporter carrying perfect seed base-pairing (“seed”) or imperfect seed with or without additional 3nt mismatches in 3’ end (“3p3MM+seed” and “3p3MM”) in CDS or 3’UTR. Equal amounts of captured reporter mRNAs were detected by RT-PCR and the Firfly reporter served as a negative control. e, Repeated experiments as in main Fig. 5b. Western blotting of the FLAG-tagged luciferase reporter proteins expressed in transfected HeLa cells. The second to last lane was from cells co-transfected with the reporter containing the miR-20a MRE and the miR-20a antagomir. f, Repeated experiments as in main Fig. 5c. Western blotting of GFP-2A-MRE-2A-mCherry reporter proteins expressed in transfected HeLa cells. Co-transfected FLAG-tagged Renilla served as a loading control. Source data

Supplementary Figure 5 Genome-wide analysis of Ago2 eCLIP, ribo-seq, and RNA-seq data.

a, The Pearson coefficient between two biological replicates of Ago2 eCLIP-seq on HeLa cells before (left) and after miR-20a overexpression (right). b, Percentage of sequences underlying Ago2 eCLIP peaks in 3’UTR that can base pair with miRNA seed. Left, Enriched Ago2 peaks in 3’UTR for top 20 mostly expressed miRNAs in comparison with non-enriched and random sites. Right, miR-20a induced Ago2 peaks in 3’UTR compared to uninduced and random sites. c, Meta-profiles of Ago2 binding on miR-20a induced (left) and uninduced (right) sites. d, Boxplots of ΔG between miR-20a and sequences underlying miR-20a induced Ago2 peaks (red) in CDS and 3’UTR in comparison with uninduced (blue) and random (gray) sites. Data from two independent eCLIP replicates are separately displayed. The median value for each group is shown with a horizontal gray line. Filled boxes extend from the first to the third quartile. The upper/lower whisker extends from the hinge to the highest/lowest value that is within 1.5 * IQR of the hinge, where IQR is the inter-quartile range. Data beyond the end of the whiskers are outliers and plotted as points. *p<0.05; **p<0.01; ***p<0.001 (Student’s t-test). e, The Pearson coefficient among three Ribo-seq and two RNA-seq experiments under before (WT) and after miR-20a overexpression (OE). f, Length distribution of ribosome protected fragments (RPFs) from three repeats under WT and OE conditions. g, The 3nt periodicity of RPFs with different lengths. h,i, Meta-gene analysis of RPFs on miR-20a induced Ago2 peaks (left) in comparison with uninduced Ago2 peaks (middle) and random sites (right). Data from two independent Ago2 eCLIP experiments (h, Repeat 1; i, Repeat 2) were used to perform the meta-gene analysis. See the data with combined data in main Fig. 6d.

Supplementary Figure 6 CDS-targeted miRNA does not alter overall polysome profiles.

a, Luciferase activities (upper panel) and relative mRNA levels determined by real-time RT-PCR (lower panel) in three stable HeLa cell lines expressing the luciferase reporter carrying the miR-20a MRE in different locations (note that, as shown in Fig. 2a, the native MRE is non-functional in 3’UTR, which served as control). b,c,d, Polysome profiling by sucrose gradients on the three stable HeLa cell lines. OD260 traces are shown below individual constructs and the distribution of mRNAs from individual reporters and the endogenous Actin gene is shown at bottom. The mRNA levels were determined by real-time RT-PCR on individual fractions and expressed as percentage of the sum. The data shown in a,b,c,d were based on 3 independent experiments. *p<0.05; **p<0.01; ***p<0.001 (Student’s t-test). Source data

Supplementary Information

Supplementary Figures 1–6 and Supplementary Table 1

Supplementary Figures 1–6 and Supplementary Table 1

Reporting Summary

Supplementary Data Set 1

Western blotting and original gel images

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhang, K., Zhang, X., Cai, Z. et al. A novel class of microRNA-recognition elements that function only within open reading frames. Nat Struct Mol Biol 25, 1019–1027 (2018). https://doi.org/10.1038/s41594-018-0136-3

Download citation

Further reading