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Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs


MicroRNAs (miRNAs) are a class of noncoding RNAs that post-transcriptionally regulate gene expression in plants and animals1,2. To investigate the influence of miRNAs on transcript levels, we transfected miRNAs into human cells and used microarrays to examine changes in the messenger RNA profile. Here we show that delivering miR-124 causes the expression profile to shift towards that of brain, the organ in which miR-124 is preferentially expressed, whereas delivering miR-1 shifts the profile towards that of muscle, where miR-1 is preferentially expressed. In each case, about 100 messages were downregulated after 12 h. The 3′ untranslated regions of these messages had a significant propensity to pair to the 5′ region of the miRNA, as expected if many of these messages are the direct targets of the miRNAs3. Our results suggest that metazoan miRNAs can reduce the levels of many of their target transcripts, not just the amount of protein deriving from these transcripts. Moreover, miR-1 and miR-124, and presumably other tissue-specific miRNAs, seem to downregulate a far greater number of targets than previously appreciated, thereby helping to define tissue-specific gene expression in humans.

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Figure 1: Tissue-specific gene expression rankings for downregulated genes.
Figure 2: Over-represented motifs in the 3′ UTRs of downregulated genes.
Figure 3: Microarray analysis of the effects of miRNA mutations.
Figure 4: MicroRNA-directed repression of renilla luciferase reporter genes bearing 3′ UTR segments from predicted target genes.


  1. Bartel, D. P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116, 281–297 (2004)

    Article  CAS  Google Scholar 

  2. Carrington, J. C. & Ambros, V. Role of microRNAs in plant and animal development. Science 301, 336–338 (2003)

    Article  ADS  CAS  Google Scholar 

  3. Lewis, B. P., Shih, I. H., Jones-Rhoades, M. W., Bartel, D. P. & Burge, C. B. Prediction of mammalian microRNA targets. Cell 115, 787–798 (2003)

    Article  CAS  Google Scholar 

  4. Palatnik, J. F. et al. Control of leaf morphogenesis by microRNAs. Nature 425, 257–263 (2003)

    Article  ADS  CAS  Google Scholar 

  5. Jackson, A. L. et al. Expression profiling reveals off-target gene regulation by RNAi. Nature Biotechnol. 21, 635–637 (2003)

    Article  CAS  Google Scholar 

  6. Hutvagner, G. & Zamore, P. D. A microRNA in a multiple-turnover RNAi enzyme complex. Science 297, 2056–2060 (2002)

    Article  ADS  CAS  Google Scholar 

  7. Zeng, Y., Yi, R. & Cullen, B. R. MicroRNAs and small interfering RNAs can inhibit mRNA expression by similar mechanisms. Proc. Natl Acad. Sci. USA 100, 9779–9784 (2003)

    Article  ADS  CAS  Google Scholar 

  8. Doench, J. G., Petersen, C. P. & Sharp, P. A. siRNAs can function as miRNAs. Genes Dev. 17, 438–442 (2003)

    Article  CAS  Google Scholar 

  9. Yekta, S., Shih, I. H. & Bartel, D. P. MicroRNA-directed cleavage of HOXB8 mRNA. Science 304, 594–596 (2004)

    Article  ADS  CAS  Google Scholar 

  10. Lagos-Quintana, M. et al. Identification of tissue-specific microRNAs from mouse. Curr. Biol. 12, 735–739 (2002)

    Article  CAS  Google Scholar 

  11. Sempere, L. F. et al. Expression profiling of mammalian microRNAs uncovers a subset of brain-expressed microRNAs with possible roles in murine and human neuronal differentiation. Genome Biol. 5, R13 (2004)

    Article  Google Scholar 

  12. Pruitt, K. D. & Maglott, D. R. RefSeq and LocusLink: NCBI gene-centered resources. Nucleic Acids Res. 29, 137–140 (2001)

    Article  CAS  Google Scholar 

  13. Johnson, J. M. et al. Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays. Science 302, 2141–2144 (2003)

    Article  ADS  CAS  Google Scholar 

  14. Bailey, T. L. & Elkan, C. Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proc. Int. Conf. Intell. Syst. Mol. Biol. 2, 28–36 (1994)

    CAS  PubMed  Google Scholar 

  15. Lim, L. P. et al. The microRNAs of Caenorhabditis elegans . Genes Dev. 17, 991–1008 (2003)

    Article  CAS  Google Scholar 

  16. Wightman, B., Ha, I. & Ruvkun, G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans . Cell 75, 855–862 (1993)

    Article  CAS  Google Scholar 

  17. Lai, E. C. Micro RNAs are complementary to 3′ UTR sequence motifs that mediate negative post-transcriptional regulation. Nature Genet. 30, 363–364 (2002)

    Article  CAS  Google Scholar 

  18. Doench, J. G. & Sharp, P. A. Specificity of microRNA target selection in translational repression. Genes Dev. 18, 504–511 (2004)

    Article  CAS  Google Scholar 

  19. John, B. et al. Human MicroRNA targets. PLoS Biol. 2, e363 (2004)

    Article  Google Scholar 

  20. Rhoades, M. W. et al. Prediction of plant microRNA targets. Cell 110, 513–520 (2002)

    Article  CAS  Google Scholar 

  21. Haley, B. & Zamore, P. D. Kinetic analysis of the RNAi enzyme complex. Nature Struct. Mol. Biol. 11, 599–606 (2004)

    Article  CAS  Google Scholar 

  22. Martinez, J. & Tuschl, T. RISC is a 5′ phosphomonoester-producing RNA endonuclease. Genes Dev. 18, 975–980 (2004)

    Article  CAS  Google Scholar 

  23. Janz, R. & Sudhof, T. C. Cellugyrin, a novel ubiquitous form of synaptogyrin that is phosphorylated by pp60c-src. J. Biol. Chem. 273, 2851–2857 (1998)

    Article  CAS  Google Scholar 

  24. Vartiainen, M. K., Sarkkinen, E. M., Matilainen, T., Salminen, M. & Lappalainen, P. Mammals have two twinfilin isoforms whose subcellular localizations and tissue distributions are differentially regulated. J. Biol. Chem. 278, 34347–34355 (2003)

    Article  CAS  Google Scholar 

  25. Bartel, D. P. & Chen, C. Z. Micromanagers of gene expression: the potentially widespread influence of metazoan microRNAs. Nature Rev. Genet. 5, 396–400 (2004)

    Article  CAS  Google Scholar 

  26. Ashburner, M. et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genet. 25, 25–29 (2000)

    Article  CAS  Google Scholar 

  27. Schwarz, D. S. et al. Asymmetry in the assembly of the RNAi enzyme complex. Cell 115, 199–208 (2003)

    Article  CAS  Google Scholar 

  28. Khvorova, A., Reynolds, A. & Jayasena, S. D. Functional siRNAs and miRNAs exhibit strand bias. Cell 115, 209–216 (2003)

    Article  CAS  Google Scholar 

  29. Hughes, T. R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109–126 (2000)

    Article  CAS  Google Scholar 

  30. Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994)

    Article  CAS  Google Scholar 

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Thanks to S. Baskerville, M. Cleary and P. Sharp for comments on the manuscript, C. Armour, S. Bartz, J. Burchard, G. Cavet, D. Haynor, A. Jackson, M. Pellegrini, E. Schadt and Y. Wang for their assistance, the Rosetta Gene Expression Laboratory for microarray work, M. Jones-Rhoades for primer design, and W. Johnston for plasmid construction.

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Correspondence to Lee P. Lim.

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Supplementary information

Supplementary Discussion

Analysis of overlaps with computational predictions. (DOC 45 kb)

Supplementary Note

Sequences cloned into reporter vectors. (DOC 53 kb)

Supplementary Figure 1

Quantitative northern blot analysis of miR-1 and miR-124 expression. (PDF 359 kb)

Supplementary Figure 2

Tissue analysis for mutant microRNAs. (PDF 28 kb)

Supplementary Figure 3

Expected and observed seed match counts in different regions of miR-1 or miR-124 downregulated genes. (PDF 8 kb)

Supplementary Figure 4

p-values of enrichment for hexamers complementary to miR-124 in the 3' UTRs of the miR-124 downregulated genes. (PDF 8 kb)

Supplementary Figure 5

Motif and tissue analysis for miR-373. (PDF 43 kb)

Supplementary Table 1

Genes downregulated by miR-1 at a p-value < 0.001 at both 12 and 24 h. (DOC 209 kb)

Supplementary Table 2

Genes downregulated by miR-124 at a p-value < 0.001 at both 12 and 24 h. (DOC 342 kb)

Supplementary Table 3

Hexamers enriched in the 3' UTRs of the downregulated sets. (DOC 52 kb)

Supplementary Table 4

Genes downregulated by miR-373 at a p-value < 0.001 at both 12 and 24 h. (DOC 155 kb)

Supplementary Methods

This file contains MIAME (Minimum Information About a Microarray Experiment) methods data. (DOC 44 kb)

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Lim, L., Lau, N., Garrett-Engele, P. et al. Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature 433, 769–773 (2005).

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