The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
MicroRNA binding sites in the coding region of mRNAs: Extending the repertoire of post‐transcriptional gene regulation
Abstract
It is well established that microRNAs (miRNAs) induce mRNA degradation by binding to 3′ untranslated regions (UTRs). The functionality of sites in the coding domain sequence (CDS), on the other hand, remains under discussion. Such sites have limited impact on target mRNA abundance and recent work suggests that miRNAs bind in the CDS to inhibit translation. What then could be the regulatory benefits of translation inhibition through CDS targeting compared to mRNA degradation following 3′ UTR binding? We propose that these domain‐dependent effects serve to diversify the functional repertoire of post‐transcriptional gene expression control. Possible regulatory benefits may include tuning the time‐scale and magnitude of post‐transcriptional regulation, regulating protein abundance depending on or independently of the cellular state, and regulation of the protein abundance of alternative splice variants. Finally, we review emerging evidence that these ideas may generalize to RNA‐binding proteins beyond miRNAs and Argonaute proteins.
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“These results are consistent with the mechanism of miRNA action, which is to inhibit the translation of their target mRNA and to mediate its degradation.40”
From Improving mRNA-Based Therapeutic Gene Delivery by Expression-Augmenting 3′ UTRs Identified by Cellular Library Screening (2019) · cites this paper as [40]
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Cites
Global quantification of mammalian gene expression control
Schwanhäusser, B., Busse, D., Li, N., Dittmar, G., Schuchhardt, J., Wolf, J., Chen, W., & Selbach, M. (2011) · Nature · doi:10.1038/nature10098 · Cited by 6,566 · cited 6×
“Post-transcriptional regulation is emerging as a major determinant of gene expression in metazoans [1, 2].”
BackgroundMethodInfluentialWightman, B., Ha, I., & Ruvkun, G. (1993) · Cell · doi:10.1016/0092-8674(93)90530-4 · Cited by 4,292
Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling
Ingolia, N. T., Ghaemmaghami, S., Newman, J. R. S., & Weissman, J. S. (2009) · Science · doi:10.1126/science.1168978 · Cited by 3,853
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
Verkerk, A. J. M. H., Pieretti, M., Sutcliffe, J. S., Fu, Y.-H., Kuhl, D. P. A., Pizzuti, A., Reiner, O., Richards, S., Victoria, M. F., Zhang, F., et al. (1991) · Cell · doi:10.1016/0092-8674(91)90397-h · Cited by 3,481
Widespread changes in protein synthesis induced by microRNAs
Selbach, M., Schwanhäusser, B., Thierfelder, N., Fang, Z., Khanin, R., & Rajewsky, N. (2008) · Nature · doi:10.1038/nature07228 · Cited by 3,429 · cited 2×
“An interesting example involves the let-7 miRNA, which targets the CDS of theDicer enzyme – an essential enzyme for miRNA biogenesis – hence establishing an auto-regulatory negative feedback loop [22, 32].”
BackgroundGene silencing by microRNAs: contributions of translational repression and mRNA decay
Huntzinger, E., & Izaurralde, E. (2011) · Nature Reviews Genetics · doi:10.1038/nrg2936 · Cited by 2,339
FMRP Stalls Ribosomal Translocation on mRNAs Linked to Synaptic Function and Autism
Darnell, J. C., Van Driesche, S. J., Zhang, C., Hung, K. Y. S., Mele, A., Fraser, C. E., Stone, E. F., Chen, C., Fak, J. J., Chi, S. W., et al. (2011) · Cell · doi:10.1016/j.cell.2011.06.013 · Cited by 2,072
Mayr, C., & Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.06.016 · Cited by 1,613
A compendium of RNA-binding motifs for decoding gene regulation
Ray, D., Kazan, H., Cook, K. B., Weirauch, M. T., Najafabadi, H. S., Li, X., Gueroussov, S., Albu, M., Zheng, H., Yang, A., et al. (2013) · Nature · doi:10.1038/nature12311 · Cited by 1,480
Research works printed but not linked: 73
- 10.1101/gad.1248505 · DOI
- 10.1016/j.ydbio.2011.11.015 · DOI
- 10.1038/nature03702 · DOI
- 10.1126/science.1096781 · DOI
- 10.1016/j.stem.2011.03.001 · DOI
- 10.1146/annurev.cellbio.23.090506.123406 · DOI · Paper page
- 10.1016/j.cell.2009.01.002 · DOI · Paper page
- 10.1126/science.1215691 · DOI · Paper page
- 10.1038/embor.2012.82 · DOI
- 10.1101/gr.133330.111 · DOI
- 10.1038/nature09267 · DOI · Paper page
- 10.1007/s00239-005-0273-2 · DOI
- 10.1016/S0092-8674(03)01018-3 · DOI · Paper page
- 10.1073/pnas.0803230105 · DOI · Paper page
- 10.1073/pnas.1006172107 · DOI
- 10.1101/gr.139758.112 · DOI · Paper page
- 10.1038/nature08170 · DOI · Paper page
- 10.1016/j.cell.2010.03.009 · DOI · Paper page
- 10.1038/nature07299 · DOI
- 10.1261/rna.972008 · DOI
- 10.1371/journal.pone.0009429 · DOI
- 10.1371/journal.pone.0016250 · DOI
- 10.1091/mbc.E12-12-0891 · DOI
- 10.1371/journal.pone.0018067 · DOI
- 10.1038/nsmb.1552 · DOI
- 10.1093/nar/gkq564 · DOI
- 10.1101/gr.121210.111 · DOI
- 10.1038/msb.2013.68 · DOI
- 10.1093/bioinformatics/bts043 · DOI
- 10.1261/rna.035634.112 · DOI
- 10.1016/j.molcel.2007.06.017 · DOI · Paper page
- 10.1261/rna.768207 · DOI
- 10.1038/msb.2010.89 · DOI
- 10.1093/nar/gkr532 · DOI · Paper page
- 10.1186/1471-2105-8-69 · DOI
- 10.1093/bioinformatics/btp565 · DOI
- 10.1186/1471-2105-11-292 · DOI
- 10.1128/MCB.02005-06 · DOI · Paper page
- 10.1002/gcc.20709 · DOI
- 10.1038/leu.2009.246 · DOI · Paper page
- 10.1097/JTO.0b013e31820db125 · DOI
- 10.1016/j.ydbio.2004.02.019 · DOI
- 10.1038/nature03552 · DOI
- 10.1093/nar/gkp542 · DOI · Paper page
- Alon U, 2007, An Introduction to Systems Biology: Design Principles of Biological Circuits
- 10.1126/science.1199784 · DOI
- 10.1093/nar/gkn693 · DOI
- 10.1016/j.molcel.2013.04.001 · DOI
- 10.1126/science.1155390 · DOI · Paper page
- 10.1101/gad.17268411 · DOI
- 10.1093/nar/25.13.2547 · DOI
- 10.1101/gr.190501 · DOI
- 10.1186/gb-2005-6-12-r100 · DOI
- 10.1073/pnas.0900028106 · DOI
- 10.1093/nar/gkn522 · DOI
- 10.1038/nsmb.2635 · DOI
- 10.1016/j.febslet.2008.03.004 · DOI · Paper page
- 10.3389/fnins.2012.00144 · DOI
- 10.1105/tpc.112.104232 · DOI
- 10.1242/jcs.038208 · DOI
- 10.1038/nsmb.2214 · DOI
- 10.1139/G09-090 · DOI
- 10.1101/gad.915901 · DOI
- 10.1101/gad.1188404 · DOI
- 10.1016/j.molcel.2011.11.009 · DOI
- 10.1371/journal.pgen.1002742 · DOI
- 10.1261/rna.037531.112 · DOI
- 10.1006/dbio.1996.0293 · DOI
- 10.1016/j.cell.2012.04.031 · DOI · Paper page
- 10.1371/journal.pcbi.0030131 · DOI
- 10.1371/journal.pcbi.1001101 · DOI
- 10.1038/nbt.1861 · DOI · Paper page
- 10.1096/fasebj.3.12.2676679 · DOI
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Orlandini von Niessen, A. G., Poleganov, M. A., Rechner, C., Plaschke, A., Kranz, L. M., Fesser, S., Diken, M., Löwer, M., Vallazza, B., Beissert, T., et al. (2019) · Molecular Therapy · doi:10.1016/j.ymthe.2018.12.011 · Cited by 365
miRNAs in depression vulnerability and resilience: novel targets for preventive strategies
Lopizzo, N., Zonca, V., Cattane, N., Pariante, C. M., & Cattaneo, A. (2019) · Journal of Neural Transmission · doi:10.1007/s00702-019-02048-2 · Cited by 37
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Metadata
- Authors
- Brümmer, A., & Hausser, J.
- Affiliations
- Biozentrum University of Basel Basel Switzerland
- Department of Molecular Cell Biology Weizmann Institute of Science Rehovot Israel
- Venue
- BioEssays
- Publisher
- Wiley
- Published
- 2014-04-15
- Volume
- 36
- Issue
- 6
- Pages
- 617-626
- ISSN
- 0265-9247
- 1521-1878
- Cited by
- 170
- References
- 14
- Language
- en
- Funders
- European Molecular Biology Organization (ALTF 1160-2012)
- Swiss National Science Foundation (PBBSP3_146961)
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