The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Assessing the ceRNA Hypothesis with Quantitative Measurements of miRNA and Target Abundance
Open accessAbstract
SUMMARY Recent studies have reported that competitive endogenous RNAs (ceRNAs) can act as sponges for a microRNA (miRNA) through their binding sites and that changes in ceRNA abundances from individual genes can modulate the miRNA’s activity. Consideration of this hypothesis would benefit from knowing the quantitative relationship between a miRNA and its endogenous target sites. Here, we altered intracellular target-site abundance through expression of a miR-122 target in hepatocytes and livers, and analyzed the effects on miR-122 target genes. Target repression was released in a threshold-like manner at high target-site abundance (≥1.5×105 added target sites per cell), and this threshold was insensitive to the effective levels of the miRNA. Furthermore, in response to extreme metabolic liver disease models, global target-site abundance of hepatocytes did not change sufficiently to affect miRNA-mediated repression. Thus, modulation of miRNA target abundance is unlikely to cause significant effects on gene expression and metabolism through a ceRNA effect.
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Most mammalian mRNAs are conserved targets of microRNAs
Friedman, R. C., Farh, K. K.-H., Burge, C. B., & Bartel, D. P. (2009) · Genome Research · doi:10.1101/gr.082701.108 · Cited by 8,462
Self-citationCircular RNAs are a large class of animal RNAs with regulatory potency
Memczak, S., Jens, M., Elefsinioti, A., Torti, F., Krueger, J., Rybak, A., Maier, L., Mackowiak, S. D., Gregersen, L. H., Munschauer, M., et al. (2013) · Nature · doi:10.1038/nature11928 · Cited by 7,990
Natural RNA circles function as efficient microRNA sponges
Hansen, T. B., Jensen, T. I., Clausen, B. H., Bramsen, J. B., Finsen, B., Damgaard, C. K., & Kjems, J. (2013) · Nature · doi:10.1038/nature11993 · Cited by 7,985
A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language?
Salmena, L., Poliseno, L., Tay, Y., Kats, L., & Pandolfi, P. P. (2011) · Cell · doi:10.1016/j.cell.2011.07.014 · Cited by 7,262
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
Self-citationMammalian microRNAs predominantly act to decrease target mRNA levels
Guo, H., Ingolia, N. T., Weissman, J. S., & Bartel, D. P. (2010) · Nature · doi:10.1038/nature09267 · Cited by 3,886
Self-citationA Mammalian microRNA Expression Atlas Based on Small RNA Library Sequencing
Landgraf, P., Rusu, M., Sheridan, R., Sewer, A., Iovino, N., Aravin, A., Pfeffer, S., Rice, A., Kamphorst, A. O., Landthaler, M., et al. (2007) · Cell · doi:10.1016/j.cell.2007.04.040 · Cited by 3,626
The impact of microRNAs on protein output
Baek, D., Villén, J., Shin, C., Camargo, F. D., Gygi, S. P., & Bartel, D. P. (2008) · Nature · doi:10.1038/nature07242 · Cited by 3,592
Self-citationmiR-122 regulation of lipid metabolism revealed by in vivo antisense targeting
Esau, C., Davis, S., Murray, S. F., Yu, X. X., Pandey, S. K., Pear, M., Watts, L., Booten, S. L., Graham, M., McKay, R., et al. (2006) · Cell Metabolism · doi:10.1016/j.cmet.2006.01.005 · Cited by 2,082
Zebrafish MiR-430 Promotes Deadenylation and Clearance of Maternal mRNAs
Giraldez, A. J., Mishima, Y., Rihel, J., Grocock, R. J., Van Dongen, S., Inoue, K., Enright, A. J., & Schier, A. F. (2006) · Science · doi:10.1126/science.1122689 · Cited by 1,647
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Predicting effective microRNA target sites in mammalian mRNAs
Agarwal, V., Bell, G. W., Nam, J.-W., & Bartel, D. P. (2015) · eLife · doi:10.7554/elife.05005 · Cited by 7,318
Self-citationGene regulation by long non-coding RNAs and its biological functions
Statello, L., Guo, C.-J., Chen, L.-L., & Huarte, M. (2021) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-020-00315-9 · Cited by 4,991
The biogenesis, biology and characterization of circular RNAs
Kristensen, L. S., Andersen, M. S., Stagsted, L. V. W., Ebbesen, K. K., Hansen, T. B., & Kjems, J. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0158-7 · Cited by 4,823
Bartel, D. P. (2018) · Cell · doi:10.1016/j.cell.2018.03.006 · Cited by 3,751
Self-citationRegulation of microRNA function in animals
Gebert, L. F. R., & MacRae, I. J. (2019) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-018-0045-7 · Cited by 2,284
Metadata
- Authors
- Denzler, R., Agarwal, V., Stefano, J., Bartel, D. P., & Stoffel, M.
- Venue
- Molecular Cell
- Publisher
- Elsevier BV
- Published
- 2014-06
- Volume
- 54
- Issue
- 5
- Pages
- 766-776
- ISSN
- 1097-2765 (ISSN-L)
- OpenAlex
- W2037691883
- Cited by
- 713
- References
- 13
- FWCI
- 20.12
- Type
- journal article
- Language
- en
- Open access
- bronze
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