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The impact of microRNAs on protein output
Open accessAbstract
MicroRNAs are endogenous approximately 23-nucleotide RNAs that can pair to sites in the messenger RNAs of protein-coding genes to downregulate the expression from these messages. MicroRNAs are known to influence the evolution and stability of many mRNAs, but their global impact on protein output had not been examined. Here we use quantitative mass spectrometry to measure the response of thousands of proteins after introducing microRNAs into cultured cells and after deleting mir-223 in mouse neutrophils. The identities of the responsive proteins indicate that targeting is primarily through seed-matched sites located within favourable predicted contexts in 3' untranslated regions. Hundreds of genes were directly repressed, albeit each to a modest degree, by individual microRNAs. Although some targets were repressed without detectable changes in mRNA levels, those translationally repressed by more than a third also displayed detectable mRNA destabilization, and, for the more highly repressed targets, mRNA destabilization usually comprised the major component of repression. The impact of microRNAs on the proteome indicated that for most interactions microRNAs act as rheostats to make fine-scale adjustments to protein output.
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“Other systemwide studies, including a separate analysis by Schwanhausser et al. (2011), also suggest that the differential regulation of translation may be limited to modest changes at a subset of genes”
From System wide analyses have underestimated protein abundances and the importance of transcription in mammals (2014) · cites this paper as Baek et al., 2008
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“MicroRNA sites have also been validated in coding sequence (CDS) regions, albeit with typically weaker repressive activity (Baek et al., 2008;Grimson et al., 2007).”
From Scalable and deep profiling of mRNA targets for individual microRNAs with chimeric eCLIP (2022) · cites this paper as Baek et al., 2008
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“Global measurements indicate that miRNA targeting causes mostly mRNA destabilization, with translational repression comprising a detectable but minor component of the overall repression33–36.”
From Poly(A)-tail profiling reveals an embryonic switch in translational control (2014) · cites this paper as [33]
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“We conclude that when poly(A)-tail length is uncoupled from TE, the translational repression often detected as a minor component of the overall repression33–35 arises from a mechanism different from the one that dominates pre-gastrulation.”
From Poly(A)-tail profiling reveals an embryonic switch in translational control (2014) · cites this paper as [33]
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Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855
Self-citation<tt>BLAT</tt> —The <tt>BLAST</tt> -Like Alignment Tool
Kent, W. J. (2002) · Genome Research · doi:10.1101/gr.229202 · Cited by 8,480
Bolstad, B. M., Irizarry, R. A., Åstrand, M., & Speed, T. P. (2003) · Bioinformatics · doi:10.1093/bioinformatics/19.2.185 · Cited by 8,314
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Prediction of Mammalian MicroRNA Targets
Lewis, B. P., Shih, I.-H., Jones-Rhoades, M. W., Bartel, D. P., & Burge, C. B. (2003) · Cell · doi:10.1016/s0092-8674(03)01018-3 · Cited by 5,199
Self-citationMicroarray analysis shows that some microRNAs downregulate large numbers of target mRNAs
Lim, L. P., Lau, N. C., Garrett-Engele, P., Grimson, A., Schelter, J. M., Castle, J., Bartel, D. P., Linsley, P. S., & Johnson, J. M. (2005) · Nature · doi:10.1038/nature03315 · Cited by 4,755
Self-citationCombinatorial microRNA target predictions
Krek, A., Grün, D., Poy, M. N., Wolf, R., Rosenberg, L., Epstein, E. J., MacMenamin, P., da Piedade, I., Gunsalus, K. C., Stoffel, M., et al. (2005) · Nature Genetics · doi:10.1038/ng1536 · Cited by 4,603
miRBase: tools for microRNA genomics
Griffiths‐Jones, S., Saini, H. K., van Dongen, S., & Enright, A. J. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm952 · Cited by 4,349
Silencing of microRNAs in vivo with ‘antagomirs’
Krützfeldt, J., Rajewsky, N., Braich, R., Rajeev, K. G., Tuschl, T., Manoharan, M., & Stoffel, M. (2005) · Nature · doi:10.1038/nature04303 · Cited by 3,949
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Items 801–900 of 1,013
Clark, A., Goldstein, L. D., Tevlin, M., Tavaré, S., Shaham, S., & Miska, E. A. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq083 · Cited by 95
Guess, M. G., Bjorkman, K. K., Harrison, B. C., & Leinwand, L. A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0118229 · Cited by 94
Danger, R., Paul, C., Giral, M., Lavault, A., Foucher, Y., Degauque, N., Pallier, A., Durand, M., Castagnet, S., Huyen, J. D. V., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060702 · Cited by 94
Engineered RNA viral synthesis of microRNAs
Varble, A., Chua, M. A., Perez, J. T., Manicassamy, B., García‐Sastre, A., & tenOever, B. R. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1003115107 · Cited by 97
Grigoryev, Y. A., Kurian, S. M., Hart, T., Nakorchevsky, A., Chen, C., Campbell, D., Head, S. R., Yates, J. R., & Salomon, D. R. (2011) · The Journal of Immunology · doi:10.4049/jimmunol.1101233 · Cited by 95
Structure-mediated modulation of mRNA abundance by A-to-I editing
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MicroRNA-221–222 Regulate the Cell Cycle in Mast Cells
Mayoral, R. J., Pipkin, M. E., Pachkov, M. V., van Nimwegen, E., Rao, A., & Monticelli, S. (2009) · The Journal of Immunology · doi:10.4049/jimmunol.182.1.433 · Cited by 95
Regulation of fibrinogen production by microRNAs
Fort, A., Borel, C., Migliavacca, E., Antonarakis, S. E., Fish, R. J., & Neerman‐Arbez, M. (2010) · Blood · doi:10.1182/blood-2010-02-268011 · Cited by 94
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Wilm, M. S. (2009) · PROTEOMICS · doi:10.1002/pmic.200900299 · Cited by 99
Understanding How miRNAs Post-Transcriptionally Regulate Gene Expression
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Mayoral, R. J., Dehò, L., Rusca, N., Bartoniček, N., Saini, H. K., Enright, A. J., & Monticelli, S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026133 · Cited by 93
Argonaute CLIP-Seq reveals miRNA targetome diversity across tissue types
Clark, P., Loher, P., Quann, K., Brody, J. R., Londin, E. R., & Rigoutsos, I. (2014) · Scientific Reports · doi:10.1038/srep05947 · Cited by 93
miRNA expression in diffuse large B-cell lymphoma treated with chemoimmunotherapy
Montes‐Moreno, S., Martı́nez, N., Sánchez‐Espiridión, B., Díaz‐Uriarte, R., Rodríguez, M. E., Sáez, A., Montalbán, C., Goméz-López, G., Pisano, D. G., García, J. F., et al. (2011) · Blood · doi:10.1182/blood-2010-11-321554 · Cited by 93
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Dong, J., Jiang, G., Asmann, Y. W., Tomaszek, S. C., Jen, J., Kislinger, T., & Wigle, D. A. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010854 · Cited by 93
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Metadata
- Authors
- Baek, D., Villén, J., Shin, C., Camargo, F. D., Gygi, S. P., & Bartel, D. P.
- Affiliations
- Whitehead Institute for Biomedical Research (US)
- Harvard University (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Gygi, Steven P.
- Bartel, David P.
- Venue
- Nature
- Published
- 2008-07-30
- Volume
- 455
- Issue
- 7209
- Pages
- 64-71
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC2745094
- OpenAlex
- W1988163167
- Cited by
- 3,592
- References
- 50
- Citations by year
- 2026: 39 · 2025: 65 · 2024: 82 · 2023: 98 · 2022: 137 · 2021: 138 · 2020: 140 · 2019: 150 · 2018: 164 · 2017: 198 · 2016: 208 · 2015: 257 · 2014: 287 · 2013: 328 · 2012: 342
- FWCI
- 108.87
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Damon Runyon Cancer Research Foundation
- National Human Genome Research Institute (R01HG003456)
- National Institute of General Medical Sciences (R01GM067031)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Molecular Biology Research
- Keywords
- microRNA, protein production, protein synthesis inhibition, mRNA destabilization, 3' untranslated region, miR-223, neutrophils, gene expression regulation, SILAC
- MeSH terms
- Animals, Gene Expression Regulation, HeLa Cells, Humans, Isotope Labeling, Male, Neutrophils, Transfection, Protein Biosynthesis, Oligonucleotide Array Sequence Analysis, MicroRNAs, Proteomics, Mice
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