The DOI matches its Crossref record; 52 of the 53 references it cites were found in a registry or an index.
Animal MicroRNAs Confer Robustness to Gene Expression and Have a Significant Impact on 3′UTR Evolution
Open accessAbstract
MicroRNAs are small noncoding RNAs that serve as posttranscriptional regulators of gene expression in higher eukaryotes. Their widespread and important role in animals is highlighted by recent estimates that 20%-30% of all genes are microRNA targets. Here, we report that a large set of genes involved in basic cellular processes avoid microRNA regulation due to short 3'UTRs that are specifically depleted of microRNA binding sites. For individual microRNAs, we find that coexpressed genes avoid microRNA sites, whereas target genes and microRNAs are preferentially expressed in neighboring tissues. This mutually exclusive expression argues that microRNAs confer accuracy to developmental gene-expression programs, thus ensuring tissue identity and supporting cell-lineage decisions.
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“The miRNAs in the first class are in line with studies showing that the expression level of the predicted targets is generally higher before differentiation, and that some miRNAs dampen the output of the transcriptionally down-regulated mRNAs to facilitate a faster transition in gene expression (Stark et al., 2005).”
From Identification of Dynamically Regulated MicroRNA and mRNA Networks in Developing Oligodendrocytes (2008) · cites this paper as Stark et al., 2005
In the citing paper
“As the silencing of loci is generally efficient, one might conclude that for most of the time in most mature neurons, some miRNAs are doing very little indeed, consistent with the idea that miRNAs confer robustness to programs of gene expression [11,12].”
From MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system (2007) · cites this paper as [12]
In the citing paper
“mRNAs from genes required for general cellular machinery are protected from miRNA action through possession of short 3' UTRs that are poor miRNA targets and genes required for specific cellular functions of the specific cell type are often miRNA anti-targets - that is, their 3' UTRs lack sequences that would enable binding of co-expressed miRNAs [12].”
From MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system (2007) · cites this paper as [12]
In the citing paper
“For instance, in zebrafish, miR-430 targets a large number of maternally deposited transcripts at the onset of zygotic transcription [6] and many examples of spatially exclusive expression domains of miRNAs and their targets have been documented (for example, [12,53]).”
From MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system (2007) · cites this paper as [12]
In the citing paper
“A common feature of miRNA function is one of mutually exclusive expression of miRNAs and their target mRNAs [11,12].”
From MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system (2007) · cites this paper as [12]
In the citing paper
“This profile is one of the best conserved miRNA patterns, as a similar restriction to mature neurons is seen for mouse and fly miR-124 [12,30].”
From MicroRNAs show a wide diversity of expression profiles in the developing and mature central nervous system (2007) · cites this paper as [12]
In the citing paper
“A change in the expression levels of miRNAs can tip the balance and result in repression or activation of many functionally important target genes101,102.”
From Molecular regulation of stem cell quiescence (2013) · cites this paper as [101]
Citations
Cites
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714
The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14
Lee, R. C., Feinbaum, R. L., & Ambros, V. (1993) · Cell · doi:10.1016/0092-8674(93)90529-y · Cited by 12,948
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855
The functions of animal microRNAs
Ambros, V. (2004) · Nature · doi:10.1038/nature02871 · Cited by 10,728
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
The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans
Reinhart, B. J., Slack, F. J., Basson, M., Pasquinelli, A. E., Bettinger, J. C., Rougvie, A. E., Horvitz, H. R., & Ruvkun, G. (2000) · Nature · doi:10.1038/35002607 · Cited by 4,989
Microarray 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
Combinatorial 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
Wightman, B., Ha, I., & Ruvkun, G. (1993) · Cell · doi:10.1016/0092-8674(93)90530-4 · Cited by 4,292
John, B., Enright, A. J., Aravin, A., Tuschl, T., Sander, C., & Marks, D. S. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020363 · Cited by 3,796
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Hu, W., Li, T., Wu, L., Li, M., & Meng, X. (2014) · Biotechnology Letters · doi:10.1007/s10529-013-1428-7 · Cited by 16
Zare, H., Khodursky, A. B., & Sartorelli, V. (2014) · BMC Evolutionary Biology · doi:10.1186/1471-2148-14-74 · Cited by 17
Zhang, W., Edwards, A., Zhu, D., Flemington, E. K., Deininger, P. L., & Zhang, K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031429 · Cited by 16
Wehrspaun, C. C., Ponting, C. P., & Marques, A. C. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00041 · Cited by 17
Faiza, M., Tanveer, K., Fatihi, S., Wang, Y., & Raza, K. (2019) · Current Bioinformatics · doi:10.2174/1574893614666190103101033 · Cited by 16
Small regulatory noncoding RNAs in Drosophila melanogaster: biogenesis and biological functions
Soleimani, S., Arshad, V., Moradi, S., Ahmadi, A., Davarpanah, S. J., & Jamalkandi, S. A. (2020) · Briefings in Functional Genomics · doi:10.1093/bfgp/elaa005 · Cited by 16
MicroRNAs and Developmental Robustness: A New Layer Is Revealed
Shomron, N. (2010) · PLoS Biology · doi:10.1371/journal.pbio.1000397 · Cited by 16
Enrichment Analysis of miRNA Targets
Xu, J., & Wong, C. (2012) · Methods in molecular biology · doi:10.1007/978-1-62703-083-0_8 · Cited by 16
Shu, W., Bo, X., Ni, M., Zheng, Z., & Wang, S. (2007) · BMC Evolutionary Biology · doi:10.1186/1471-2148-7-223 · Cited by 16
siRNA screening reveals JNK2 as an evolutionary conserved regulator of triglyceride homeostasis
Grimard, V., Massier, J., Richter, D., Schwudke, D., Kalaidzidis, Y. L., Fava, E., Hermetter, A., & Thiele, C. (2008) · Journal of Lipid Research · doi:10.1194/jlr.m800168-jlr200 · Cited by 16
Locked Nucleic Acid: Properties and Therapeutic Aspects
Koch, T., Rosenbohm, C., Hansen, H. F., Hansen, B. R., Straarup, E. M., & Kauppinen, S. (2008) · Royal Society of Chemistry eBooks · doi:10.1039/9781847558275-00103 · Cited by 16
Zhao, Y., Chen, L., Jiang, S., Wu, Z., Xiang, Q., Lin, J., Tian, S., Sun, Z., Sun, C., & Li, W. (2025) · Bioactive Materials · doi:10.1016/j.bioactmat.2025.02.046 · Cited by 17
Xie, J., Chen, H., Zheng, W., Cai, Z., Li, X., & Zhang, H. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010418 · Cited by 17
Croft, L., Szklarczyk, D., Jensen, L. J., & Gorodkin, J. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-90 · Cited by 15
Toledano, H., Nir, R., Volohonsky, G., & Volk, T. (2007) · Development · doi:10.1242/dev.006080 · Cited by 15
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Quah, S., Breuker, C. J., & Holland, P. W. H. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142243 · Cited by 15
Yang, B., Wang, X., Ying, C., Peng, F., Xu, M. L., Chen, F., & Cai, B. (2020) · Journal of Atherosclerosis and Thrombosis · doi:10.5551/jat.52274 · Cited by 15
Li, R., He, J., Chen, X.-M., Long, C., Yang, D.-H., Ding, Y., Qi, H., & Liu, X. (2014) · Molecular Biology Reports · doi:10.1007/s11033-014-3045-5 · Cited by 16
Soares, A. R., Reverendo, M., Pereira, P. M., Nivelles, O., Pendeville, H., Bezerra, A. R., Moura, G. R., Struman, I., & Santos, M. A. S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0039417 · Cited by 15
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Hu, W., Wang, X., Bi, Y., Bao, J., Shang, M., & Zhang, L. (2023) · Cells · doi:10.3390/cells12060943 · Cited by 14
Lemons, D., Paré, A. C., & McGinnis, W. J. (2012) · PLoS ONE · doi:10.1371/journal.pone.0031365 · Cited by 14
Barh, D., Parida, S., Parida, B. P., & Viswanathan, G. (2008) · Cited by 14
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Chang, Y., Juan, H., Lee, T.-Y., Chang, Y., Yeh, Y., Li, W., & Shih, A. C.-C. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0809151105 · Cited by 14
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Siomi, H., & Siomi, M. C. (2007) · Genes & Development · doi:10.1101/gad.1559707 · Cited by 13
Gu, J., & Xuan, Z. (2013) · PLoS ONE · doi:10.1371/journal.pone.0081032 · Cited by 12
Xu, W., Liu, J., Qi, H., Si, R., Zhao, Z., Tao, Z., Bai, Y., Hu, S., Sun, X., Cong, Y., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47055-4 · Cited by 14
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Huang, J., Wang, T., Qiu, Y., Hassanyar, A. K., Zhang, Z., Sun, Q., Ni, X., Yu, K., Guo, Y., Yang, C., et al. (2023) · Genes · doi:10.3390/genes14051000 · Cited by 12
Zhang, Q., Song, J., Cao, L., Sun, M., Xu, T., Yang, S., Li, S., Wang, H., & Fu, X. (2023) · Experimental Cell Research · doi:10.1016/j.yexcr.2023.113632 · Cited by 11
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Bryant, W. B., Mills, M. K., Olson, B. J. S. C., & Michel, K. (2019) · G3 Genes Genomes Genetics · doi:10.1534/g3.119.400104 · Cited by 12
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Cohen, S. M., & Brennecke, J. (2006) · Science · doi:10.1126/science.1126400 · Cited by 12
Self-citationLiu, X., Yang, S., Wang, L., Wu, X., Wang, X., Ou, C., Yang, J. P., Song, L., Zhou, S., Wu, Q., et al. (2023) · Theranostics · doi:10.7150/thno.81776 · Cited by 11
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Falcone, E., Grandoni, L., Garibaldi, F., Manni, I., Filligoi, G., Piaggio, G., & Gurtner, A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0153658 · Cited by 11
Tang, C., Yuan, P., Wang, J., Zhang, Y., Chang, X., Jin, D., Peng, L., Lu, Z., & Chen, B. (2021) · 3 Biotech · doi:10.1007/s13205-021-02650-w · Cited by 11
Hu, W., Li, M., Hu, R., Li, T., & Meng, X. (2015) · DNA and Cell Biology · doi:10.1089/dna.2014.2421 · Cited by 11
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Tao, L., Wang, Y., Shen, Z., Cai, J., Zheng, J., Xia, S., Lin, Z., Wan, Z., Qi, H., Jin, R., et al. (2023) · Hepatology International · doi:10.1007/s12072-023-10552-7 · Cited by 10
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Tomasi, T. B., Magner, W. J., Wiesen, J. L., Oshlag, J. Z., Cao, F., Pontikos, A. N., & Gregorie, C. J. (2009) · Immunologic Research · doi:10.1007/s12026-009-8128-3 · Cited by 10
Regulation of V-ATPase Expression in Mammalian Cells
Lee, B. S. (2012) · Current Protein and Peptide Science · doi:10.2174/138920312800493188 · Cited by 10
microRNAs as prime players in a combinatorial view of evolution
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Leon, K. E., Gallay, N., Anne Poupon, B., Reiter, É., Dalbiès‐Tran, R., & Crépieux, P. (2013) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2013.00003 · Cited by 10
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Mori, M. A. (2020) · Anais da Academia Brasileira de Ciências · doi:10.1590/0001-3765202020200437 · Cited by 10
Control of tissue size and development by a regulatory element in the yorkie 3'UTR.
Umegawachi, T., Yoshida, H., 大夢, 越., Yamada, M., Ohkawa, Y., Sato, T., Suyama, M., Krause, H. M., & Yamaguchi, M. (2017) · PubMed Central · Cited by 9
Zhang, S., Gao, X., Jiang, Y., Shen, Y., Xie, H., Pan, P., Huang, Y., Wei, Y., & Jiang, Q. (2021) · Archives animal breeding/Archiv für Tierzucht · doi:10.5194/aab-64-375-2021 · Cited by 10
Vand‐Rajabpour, F., Savage, M., Belote, R. L., & Judson‐Torres, R. L. (2023) · Epigenomes · doi:10.3390/epigenomes7020009 · Cited by 9
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Cheng, G., Danquah, M. K., & Mahato, R. I. (2009) · Springer eBooks · doi:10.1007/978-1-4419-0131-6_14 · Cited by 9
Sun, H., Zhou, Z., Dong, Y., Yang, A., Pan, Y., Jiang, J., Chen, Z., Guan, X., Wang, B., Gao, S., et al. (2018) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2018.05.020 · Cited by 9
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Mutalib, N. A., Sulaiman, S. A., & Jamal, R. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-814513-5.00006-4 · Cited by 9
Yan, G., Li, C., Zhao, Y., Yue, M., & Wang, L. (2019) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2019.4245 · Cited by 9
RetractedPan, J. H., Kim, H., Tang, J., Beane, K. E., Park, J., Kong, S., Kong, B. C., Kim, Y. J., Shin, E., Kim, J. H., et al. (2019) · Alcohol · doi:10.1016/j.alcohol.2019.10.008 · Cited by 9
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Martignetti, L., Laud-Duval, K., Tirode, F., Pierron, G., Reynaud, S., Barillot, E., Delattre, O., & Zinovyev, A. Y. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041770 · Cited by 9
Majer, A., & Booth, S. A. (2010) · Brain Research · doi:10.1016/j.brainres.2010.03.095 · Cited by 9
Lim, L. P., & Linsley, P. S. (2007) · Nature Biotechnology · doi:10.1038/nbt0907-996 · Cited by 9
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Metadata
- Authors
- Stark, A., Brennecke, J., Bushati, N., Russell, R. B., & Cohen, S. M.
- Affiliations
- European Molecular Biology Laboratory (DE)
- Corresponding author
- Cohen, Stephen M.
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2005-12
- Volume
- 123
- Issue
- 6
- Pages
- 1133-1146
- ISSN
- 0092-8674 (ISSN-L)
- OpenAlex
- W2034500416
- Cited by
- 1,080
- References
- 53
- Citations by year
- 2026: 4 · 2025: 17 · 2024: 14 · 2023: 21 · 2022: 15 · 2021: 38 · 2020: 20 · 2019: 29 · 2018: 37 · 2017: 34 · 2016: 30 · 2015: 51 · 2014: 68 · 2013: 88 · 2012: 82
- FWCI
- 30.34
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 2821 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- 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, microRNA binding sites, post-transcriptional regulation, tissue-specific gene expression, co-expressed genes, cell lineage specification, tissue identity, non-coding RNA
- MeSH terms
- Animals, Base Sequence, Cell Line, Drosophila, Embryo, Nonmammalian, Membrane Proteins, Molecular Sequence Data, Muscles, Nerve Tissue Proteins, Nervous System, Nuclear Proteins, RNA, Messenger, Sequence Homology, Nucleic Acid, Tropomyosin, In Situ Hybridization, Homeodomain Proteins, Gene Expression Regulation, Developmental, Evolution, Molecular, 3' Untranslated Regions, Vacuolar Proton-Translocating ATPases, Drosophila Proteins, MicroRNAs, Basic Helix-Loop-Helix Transcription Factors, Basic Helix-Loop-Helix Proteins
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