Identifying microRNA targets in different gene regions
Tóm tắt
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. 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
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.
Tài liệu tham khảo
Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell. 2004, 116 (2): 281-297. 10.1016/S0092-8674(04)00045-5.
Landgraf P, Rusu M, Sheridan R, Sewer A, Iovino N, Aravin A, Pfeffer S, Rice A, Kamphorst AO, Landthaler M: A mammalian microRNA expression atlas based on small RNA library sequencing. Cell. 2007, 129 (7): 1401-1414. 10.1016/j.cell.2007.04.040.
Kozomara A, Griffiths-Jones S: miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic acids research. 2011, 39 (Database): D152-157. 10.1093/nar/gkq1027.
Friedman RC, Farh KK-H, Burge CB, Bartel DP: Most mammalian mRNAs are conserved targets of microRNAs. Genome research. 2009, 19 (1): 92-105.
Selbach M, Schwanhäusser B, Thierfelder N, Fang Z, Khanin R, Rajewsky N: Widespread changes in protein synthesis induced by microRNAs. Nature. 2008, 455 (7209): 58-63. 10.1038/nature07228.
Lewis BP, Shih I-h, Jones-Rhoades MW, Bartel DP, Burge CB: Prediction of mammalian microRNA targets. Cell. 2003, 115 (7): 787-798. 10.1016/S0092-8674(03)01018-3.
Lewis BP, Burge CB, Bartel DP: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell. 2005, 120 (1): 15-20. 10.1016/j.cell.2004.12.035.
Grimson A, Farh KK-H, Johnston WK, Garrett-Engele P, Lim LP, Bartel DP: MicroRNA targeting specificity in mammals: determinants beyond seed pairing. Molecular cell. 2007, 27 (1): 91-105. 10.1016/j.molcel.2007.06.017.
Krek A, Grün D, Poy MN, Wolf R, Rosenberg L, Epstein EJ, MacMenamin P, da Piedade I, Gunsalus KC, Stoffel M: Combinatorial microRNA target predictions. Nature genetics. 2005, 37 (5): 495-500. 10.1038/ng1536.
Maragkakis M, Alexiou P, Papadopoulos GL, Reczko M, Dalamagas T, Giannopoulos G, Goumas G, Koukis E, Kourtis K, Simossis VA: Accurate microRNA target prediction correlates with protein repression levels. BMC bioinformatics. 2009, 10 (1): 295-10.1186/1471-2105-10-295.
Reczko M, Maragkakis M, Alexiou P, Grosse I, Hatzigeorgiou AG: Functional microRNA targets in protein coding sequences. Bioinformatics. 2012, 28 (6): 771-776. 10.1093/bioinformatics/bts043.
Betel D, Wilson M, Gabow A, Marks DS, Sander C: The microRNA. org resource: targets and expression. Nucleic acids research. 2008, 36 (suppl 1): D149-D153.
John B, Enright AJ, Aravin A, Tuschl T, Sander C, Marks DS: Human microRNA targets. PLoS biology. 2004, 2 (11): e363-10.1371/journal.pbio.0020363.
Krüger J, Rehmsmeier M: RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic acids research. 2006, 34 (suppl 2): W451-W454.
Wang X, El Naqa IM: Prediction of both conserved and nonconserved microRNA targets in animals. Bioinformatics. 2008, 24 (3): 325-332. 10.1093/bioinformatics/btm595.
Bandyopadhyay S, Mitra R: TargetMiner: microRNA target prediction with systematic identification of tissue-specific negative examples. Bioinformatics. 2009, 25 (20): 2625-2631. 10.1093/bioinformatics/btp503.
Liu H, Yue D, Chen Y, Gao S-J, Huang Y: Improving performance of mammalian microRNA target prediction. BMC bioinformatics. 2010, 11 (1): 476-10.1186/1471-2105-11-476.
Wu Y, Wei B, Liu H, Li T, Rayner S: MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences. BMC bioinformatics. 2011, 12 (1): 107-10.1186/1471-2105-12-107.
Kertesz M, Iovino N, Unnerstall U, Gaul U, Segal E: The role of site accessibility in microRNA target recognition. Nature genetics. 2007, 39 (10): 1278-1284. 10.1038/ng2135.
Hammell M, Long D, Zhang L, Lee A, Carmack CS, Han M, Ding Y, Ambros V: mirWIP: microRNA target prediction based on microRNA-containing ribonucleoprotein-enriched transcripts. Nature methods. 2008, 5 (9): 813-819. 10.1038/nmeth.1247.
Mendes N, Freitas AT, Sagot M-F: Current tools for the identification of miRNA genes and their targets. Nucleic acids research. 2009, 37 (8): 2419-2433. 10.1093/nar/gkp145.
Peter M: Targeting of mRNAs by multiple miRNAs: the next step. Oncogene. 2010, 29 (15): 2161-2164. 10.1038/onc.2010.59.
Bartel DP: MicroRNAs: target recognition and regulatory functions. Cell. 2009, 136 (2): 215-233. 10.1016/j.cell.2009.01.002.
Brodersen P, Voinnet O: Revisiting the principles of microRNA target recognition and mode of action. Nature reviews Molecular cell biology. 2009, 10 (2): 141-148. 10.1038/nrm2619.
Reinhart BJ, Slack FJ, Basson M, Pasquinelli AE, Bettinger JC, Rougvie AE, Horvitz HR, Ruvkun G: The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature. 2000, 403 (6772): 901-906. 10.1038/35002607.
Brennecke J, Stark A, Russell RB, Cohen SM: Principles of microRNA-target recognition. PLoS biology. 2005, 3 (3): e85-10.1371/journal.pbio.0030085.
Baek D, Villén J, Shin C, Camargo FD, Gygi SP, Bartel DP: The impact of microRNAs on protein output. Nature. 2008, 455 (7209): 64-71. 10.1038/nature07242.
Lytle JR, Yario TA, Steitz JA: Target mRNAs are repressed as efficiently by microRNA-binding sites in the 5′ UTR as in the 3′ UTR. Proceedings of the National Academy of Sciences. 2007, 104 (23): 9667-9672. 10.1073/pnas.0703820104.
Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano M, Jungkamp A-C, Munschauer M: Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell. 2010, 141 (1): 129-141. 10.1016/j.cell.2010.03.009.
Chi SW, Zang JB, Mele A, Darnell RB: Argonaute HITS-CLIP decodes microRNA-mRNA interaction maps. Nature. 2009, 460 (7254): 479-486.
Lee I, Ajay SS, Yook JI, Kim HS, Hong SH, Kim NH, Dhanasekaran SM, Chinnaiyan AM, Athey BD: New class of microRNA targets containing simultaneous 5′-UTR and 3′-UTR interaction sites. Genome research. 2009, 19 (7): 1175-1183. 10.1101/gr.089367.108.
Piriyapongsa J, Bootchai C, Ngamphiw C, Tongsima S: MicroPIR: an integrated database of microRNA target sites within human promoter sequences. PloS one. 2012, 7 (3): e33888-10.1371/journal.pone.0033888.
Fang Z, Rajewsky N: The impact of miRNA target sites in coding sequences and in 3′ UTRs. PloS one. 2011, 6 (3): e18067-10.1371/journal.pone.0018067.
Hausser J, Syed AP, Bilen B, Zavolan M: Analysis of CDS-located miRNA target sites suggests that they can effectively inhibit translation. Genome research. 2013, 23 (4): 604-615. 10.1101/gr.139758.112.
Siepel A, Bejerano G, Pedersen JS, Hinrichs AS, Hou M, Rosenbloom K, Clawson H, Spieth J, Hillier LW, Richards S: Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome research. 2005, 15 (8): 1034-1050. 10.1101/gr.3715005.
Yang Y, Wang Y-P, Li K-B: MiRTif: a support vector machine-based microRNA target interaction filter. BMC bioinformatics. 2008, 9 (Suppl 12): S4-10.1186/1471-2105-9-S12-S4.
Maziere P, Enright AJ: Prediction of microRNA targets. Drug discovery today. 2007, 12 (11): 452-458.
Breiman L: Random forests. Machine learning. 2001, 45 (1): 5-32. 10.1023/A:1010933404324.
Shahi P, Loukianiouk S, Bohne-Lang A, Kenzelmann M, Küffer S, Maertens S, Eils R, Gröne H-J, Gretz N, Brors B: Argonaute--a database for gene regulation by mammalian microRNAs. Nucleic acids research. 2006, 34 (suppl 1): D115-D118.
Karolchik D, Baertsch R, Diekhans M, Furey TS, Hinrichs A, Lu Y, Roskin KM, Schwartz M, Sugnet CW, Thomas DJ: The UCSC genome browser database. Nucleic acids research. 2003, 31 (1): 51-54. 10.1093/nar/gkg129.
Rehmsmeier M, Steffen P, Höchsmann M, Giegerich R: Fast and effective prediction of microRNA/target duplexes. Rna. 2004, 10 (10): 1507-1517. 10.1261/rna.5248604.