Identifying microRNA targets in different gene regions
Open accessAbstract
BACKGROUND: Currently available microRNA (miRNA) target prediction algorithms require the presence of a conserved seed match to the 5' end of the miRNA and limit the target sites to the 3' untranslated regions of mRNAs. However, it has been noted that these requirements may be too stringent, leading to a substantial number of missing targets. RESULTS: We have developed TargetS, a novel computational approach for predicting miRNA targets with the target sites located along entire gene sequences, which permits finding additional targets that are not located in the 3' un-translated regions. Our model is based on both canonical seed matching and non-canonical seed pairing, which discovers targets that allow one bit GU wobble. It does not rely on evolutionary conservation, so it allows the detection of species-specific miRNA-mRNA interactions and makes it suitable for analyzing un-conserved gene sequences. To test the performance of our approach, we have imported the widely used benchmark dataset revealing fold-changes in protein production corresponding to each of the five selected microRNAs. Compared to well-known miRNA target prediction tools, including TargetScanS, PicTar and MicroT_CDS, our method yields the highest sensitivity, while achieving a comparable level of accuracy. Human miRNA target predictions using our computational approach are available online at http://liubioinfolab.org/targetS/mirna.html CONCLUSIONS: A simple but powerful computational miRNA target prediction method is developed that is solely based on canonical and non-canonical seed matches without requiring evolutionary conservation of the target sites. Our method also expands the target search space to different gene regions, rather than limiting to 3'UTR only. This improves the sensitivity of miRNA target identification, while achieving a comparable accuracy with existing methods.
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miRNA binding sites have also been detected in other mRNA regions including the 5' UTR and coding sequence, as well as within promoter regions.
“miRNA binding sites have also been detected in other mRNA regions including the 5′ UTR and coding sequence, as well as within promoter regions (42).”
From Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation (2018) · cites this paper as [42]
In many cases, a functional miRNA:MRE interaction occurs via the 5' seed region (nucleotides 2-8).
“In many cases, a functional miRNA:MRE interaction occurs via the 5' seed region (nucleotides 2–8) (42, 51).”
From Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation (2018) · cites this paper as [42]
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Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538 · see citing works
Argonaute—a database for gene regulation by mammalian microRNAs
Shahi, P., Loukianiouk, S., Bohne-Lang, A., Kenzelmann, M., Küffer, S., Maertens, S., Eils, R., Gröne, H.-J., Gretz, N., & Brors, B. (2005) · Nucleic Acids Res. · doi:10.1093/nar/gkj093 · Cited by 45,811 · see citing works
Bartel (2004) · doi:10.1016/s0092-8674(04)00045-5 · Cited by 34,714 · see citing works
MicroRNAs: Target Recognition and Regulatory Functions
Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.01.002 · Cited by 20,068 · see citing works
Lewis, B. P., Burge, C. B., & Bartel, D. P. (2005) · Cell · doi:10.1016/j.cell.2004.12.035 · Cited by 11,855 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
Siepel, A., Bejerano, G., Pedersen, J. S., Hinrichs, A. S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L. W., Richards, S., et al. (2005) · Genome Research · doi:10.1101/gr.3715005 · Cited by 4,408 · cited 1× · see citing works
“To evaluate the effect of this feature in miRNA target prediction, we simply imported the conservation score of different seed match types calculated by phastCons [35] and set a cutoff value to identify the miRNA targets.”
MethodPrediction 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 4,333 · see citing works
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 · see citing works
MicroRNA Targeting Specificity in Mammals: Determinants beyond Seed Pairing
Grimson, A., Farh, K. K.-H., Johnston, W. K., Garrett-Engele, P., Lim, L. P., & Bartel, D. P. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.06.017 · Cited by 3,766 · see citing works
A 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 · see citing works
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 · see citing works
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 5× · see citing works
“Identification of mRNAs and proteins that are upregulated upon inhibition or the removal of an endogenous miRNA demonstrate that non-conserved targeting is even more widespread than conserved targeting [5,27].”
BackgroundMethodInfluentialmiRBase: integrating microRNA annotation and deep-sequencing data
Kozomara, A., & Griffiths-Jones, S. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1027 · Cited by 3,042 · see citing works
Transcriptome-wide Identification of RNA-Binding Protein and MicroRNA Target Sites by PAR-CLIP
Hafner, M., Landthaler, M., Burger, L., Khorshid, M., Hausser, J., Berninger, P., Rothballer, A., Ascano, M., Jungkamp, A.-C., Munschauer, M., et al. (2010) · Cell · doi:10.1016/j.cell.2010.03.009 · Cited by 2,873 · see citing works
Fast and effective prediction of microRNA/target duplexes
REHMSMEIER, M., STEFFEN, P., HÖCHSMANN, M., & GIEGERICH, R. (2004) · RNA · doi:10.1261/rna.5248604 · Cited by 2,560 · see citing works
The microRNA.org resource: targets and expression
Betel, D., Wilson, M. T., Gabow, A. P., Marks, D. S., & Sander, C. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm995 · Cited by 2,490 · see citing works
The role of site accessibility in microRNA target recognition
Kertesz, M., Iovino, N., Unnerstall, U., Gaul, U., & Segal, E. (2007) · Nature Genetics · doi:10.1038/ng2135 · Cited by 2,460 · see citing works
Principles of MicroRNA–Target Recognition
Brennecke, J., Stark, A., Russell, R. B., & Cohen, S. M. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030085 · Cited by 2,384 · see citing works
The UCSC Genome Browser Database
Karolchik, D. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg129 · Cited by 1,887 · see citing works
Argonaute HITS-CLIP decodes microRNA–mRNA interaction maps
Chi, S. W., Zang, J. B., Mele, A., & Darnell, R. B. (2009) · Nature · doi:10.1038/nature08170 · Cited by 1,791 · see citing works
RNAhybrid: microRNA target prediction easy, fast and flexible
Kruger, J., & Rehmsmeier, M. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl243 · Cited by 1,716 · see citing works
Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5′ UTR as in the 3′ UTR
Lytle, J., Yario, T. A., & STEITZ, J. A. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0703820104 · Cited by 1,196 · see citing works
Revisiting the principles of microRNA target recognition and mode of action
Brodersen, P., & Voinnet, O. (2009) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2619 · Cited by 657 · see citing works
Prediction of both conserved and nonconserved microRNA targets in animals
Wang, X., & Naqa, I. E. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm595 · Cited by 529 · see citing works
Functional microRNA targets in protein coding sequences
Reczko, M., Maragkakis, M., Alexiou, P., Große, I., & Hatzigeorgiou, A. G. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts043 · Cited by 503 · see citing works
New class of microRNA targets containing simultaneous 5′-UTR and 3′-UTR interaction sitesPreprint
Lee, I., Ajay, S. S., Yook, J. I., Kim, H. S., Hong, S. H., Kim, N. H., Dhanasekaran, S. M., Chinnaiyan, A. M., & Athey, B. D. (2009) · Genome Research · doi:10.1101/gr.089367.108 · Cited by 485 · see citing works
Analysis of CDS-located miRNA target sites suggests that they can effectively inhibit translationPreprint
Hausser, J., Syed, A. P., Bilen, B., & Zavolan, M. (2013) · Genome Research · doi:10.1101/gr.139758.112 · Cited by 336 · see citing works
Accurate microRNA target prediction correlates with protein repression levels
Maragkakis, M., Alexiou, P., Papadopoulos, G. L., Reczko, M., Dalamagas, T., Giannopoulos, G., Goumas, G., Koukis, E., Kourtis, K., Simossis, V. A., et al. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-295 · Cited by 330 · see citing works
Prediction of microRNA targets
Mazière, P., & Enright, A. J. (2007) · Drug Discovery Today · doi:10.1016/j.drudis.2007.04.002 · Cited by 300 · see citing works
Targeting of mRNAs by multiple miRNAs: the next step
Peter, M. E. (2010) · Oncogene · doi:10.1038/onc.2010.59 · Cited by 299 · see citing works
The Impact of miRNA Target Sites in Coding Sequences and in 3′UTRs
Fang, Z., & Rajewsky, N. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018067 · Cited by 280 · see citing works
Current tools for the identification of miRNA genes and their targets
Mendes, N. D., Freitas, A. T., & Sagot, M. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp145 · Cited by 237 · see citing works
Bandyopadhyay, S., & Mitra, R. (2009) · Bioinform. · doi:10.1093/bioinformatics/btp503 · Cited by 225 · see citing works
Hammell, M., Long, D., Zhang, L., Lee, A., Carmack, C. S., Han, M., Ding, Y., & Ambros, V. (2008) · Nature Methods · doi:10.1038/nmeth.1247 · Cited by 202 · see citing works
Wu, Y., Wei, B., Liu, H., Li, T., & Rayner, S. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-107 · Cited by 186 · see citing works
Improving performance of mammalian microRNA target prediction
Liu, H., Yue, D., Chen, Y., Gao, S., & Huang, Y. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-476 · Cited by 102 · see citing works
(2009) · Nucleic Acids Research · doi:10.1093/nar/gkp564 · Cited by 95 · see citing works
MiRTif: a support vector machine-based microRNA target interaction filter
Yang, Y., Wang, Y., & Li, K.-B. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s12-s4 · Cited by 76 · see citing works
microPIR: An Integrated Database of MicroRNA Target Sites within Human Promoter Sequences
Piriyapongsa, J., Bootchai, C., Ngamphiw, C., & Tongsima, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0033888 · Cited by 39 · see citing works
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Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation
O'Brien, J., Hayder, H., Zayed, Y., & Peng, C. (2018) · Frontiers in Endocrinology · doi:10.3389/fendo.2018.00402 · Cited by 5,287 · see citing works
- Authors
- Xu, W., San Lucas, A., Wang, Z., & Liu, Y.
- Affiliations
- The University of Texas Health Science Center at Houston (US)
- Venue
- BMC Bioinformatics
- Published
- 2014-05
- Volume
- 15
- Issue
- S7
- Pages
- S4-S4
- ISSN
- 1471-2105 (ISSN-L)
- PMC
- PMC4110731
- OpenAlex
- W2065920909
- Cited by
- 159
- References
- 42
- Citations by year
- 2026: 6 · 2025: 8 · 2024: 18 · 2023: 23 · 2022: 19 · 2021: 21 · 2020: 15 · 2019: 10 · 2018: 8 · 2017: 12 · 2016: 6 · 2015: 9 · 2014: 3 · 2013: 1
- FWCI
- 3.20
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Bioinformatics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- University of Texas Health Science Center at Houston
- 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 › Cancer Research › Cancer-related molecular mechanisms research
- Keywords
- miRNA target prediction, targets, wobble pairing, 3' untranslated region
- MeSH terms
- Algorithms, Humans, Proteins, Regulatory Sequences, Nucleic Acid, RNA, Messenger, Protein Biosynthesis, Genomics, MicroRNAs
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