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MicroRNAs: Target Recognition and Regulatory Functions
Open accessAbstract
MicroRNAs (miRNAs) are endogenous approximately 23 nt RNAs that play important gene-regulatory roles in animals and plants by pairing to the mRNAs of protein-coding genes to direct their posttranscriptional repression. This review outlines the current understanding of miRNA target recognition in animals and discusses the widespread impact of miRNAs on both the expression and evolution of protein-coding genes.
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“miR-106b was predicted to have a binding site at the near end of 3′ UTR of ABCA1 with an 8mer perfect match (an exact match to positions 2–8 of the mature miRNA followed by an adenosine nucleotide) (Fig. 1A) (Bartel, 2009).”
From miR-106b impairs cholesterol efflux and increases Aβ levels by repressing ABCA1 expression (2012) · cites this paper as Bartel, 2009
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“MicroRNAs (miRNAs) have been shown to play important roles in both brain development and the regulation of adult neural cell functions.”
From Comprehensive expression analyses of neural cell-type-specific miRNAs identify new determinants of the specification and maintenance of neuronal phenotypes (2013) · cites this paper as Bartel, 2009
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“a class of noncoding RNAs, termed microRNAs (miRNAs), has emerged as critical regulators of gene expression acting predominantly at the posttranscriptional level (8–10).”
From miR-33a/b contribute to the regulation of fatty acid metabolism and insulin signaling (2011) · cites this paper as [9]
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“miRNA targeting of mRNAs inhibits their expression through mRNA destabilization, repression of translation, or a combination of both processes (8–10).”
From miR-33a/b contribute to the regulation of fatty acid metabolism and insulin signaling (2011) · cites this paper as [9]
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“miRNAs are frequently found in genomic clusters (Bartel, 2009).”
From Comprehensive expression analyses of neural cell-type-specific miRNAs identify new determinants of the specification and maintenance of neuronal phenotypes (2013) · cites this paper as Bartel, 2009
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“MicroRNAs (miRNAs) are 22-nt RNAs that pair to sites in mRNAs to target these messages for posttranscriptional repression32.”
From Poly(A)-tail profiling reveals an embryonic switch in translational control (2014) · cites this paper as [32]
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“Computational approaches to predict physical interactions can partly circumvent bias (TABLE 1), but they do not address tissue specificity, and there may be relatively low reproducibility across different methods 58,59.”
From Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015) · cites this paper as [58]
In the citing paper
“RBPs, such as human antigen R (HuR), AU-binding factor 1 (AUF1), and tristetraprolin (TTP), can directly or indirectly control the turnover and translation of mRNAs that encode senescence proteins [181,182,183].”
From Mechanisms and Regulation of Cellular Senescence (2021) · cites this paper as [182]
In the citing paper
“MicroRNAs (miRNAs) are small non-coding RNAs that negatively regulate the expression of genes in a sequence-specific manner, binding to the 3′-untranslated region (3′UTR) to initiate cleavage or translational repression of target transcripts [5,6].”
From miR-10b-5p expression in Huntington’s disease brain relates to age of onset and the extent of striatal involvement (2015) · cites this paper as [6]
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Citations
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Circular 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
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Regulation of microRNA biogenesis
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The widespread regulation of microRNA biogenesis, function and decay
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Mammalian 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-citation
Metadata
- Authors
- Bartel, D. P.
- Affiliations
- Howard Hughes Medical Institute (US)
- Corresponding author
- Bartel, David P.
- ORCID
- Bartel, David P.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2009-01
- Volume
- 136
- Issue
- 2
- Pages
- 215-233
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC3794896
- OpenAlex
- W2162674813
- Cited by
- 20,068
- References
- 114
- Citations by year
- 2026: 479 · 2025: 559 · 2024: 821 · 2023: 841 · 2022: 1188 · 2021: 1453 · 2020: 1508 · 2019: 1438 · 2018: 1500 · 2017: 1523 · 2016: 1508 · 2015: 1555 · 2014: 1483 · 2013: 1380 · 2012: 1184
- FWCI
- 59.02
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
- Elsevier eBooks
- Funders
- National Institutes of Health
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › MicroRNA in disease regulation
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Plant Molecular Biology Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- microRNA, miRNA target recognition, post-transcriptional regulation, mRNA silencing, gene expression regulation, gene evolution, protein-coding genes, animals, plants
- MeSH terms
- Animals, Gene Expression Regulation, Humans, 3' Untranslated Regions, MicroRNAs
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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