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Research Paper

miRNA target identification and prediction as a function of time in gene expression data

ORCID Icon, , , , ORCID Icon &
Pages 990-1000 | Received 11 Mar 2019, Accepted 23 Mar 2020, Published online: 22 Apr 2020

References

  • Kozomara A, Griffiths-Jones S. MiRBase: annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Res. 2014;42:68–73.
  • Griffiths-Jones S. The microRNA registry. Nucleic Acids Research. 2004;32(90001):109D-111.
  • Bobbili MR, Mader RM, Grillari J, et al. OncomiR-17-5p: alarm signal in cancer? Oncotarget. 2017;8(41):71206–71222.
  • Dellago H, Bobbili MR, Grillari J. MicroRNA-17-5p: at the Crossroads of cancer and aging - a mini-review. Gerontology. 2016;63:20–28.
  • Tan L, Yu JT, Tan L. Causes and consequences of microRNA dysregulation in neurodegenerative diseases. Mol. Neurobiol. 2015;51(3):1249–1262.
  • Hu Z, Du J, Ying Y, et al. Single-molecule analysis of colorectal cancer-associated microRNAs via a biological nanopore. Acta Chim. Sin. 2017;75:1087.
  • Liu HH, Tian X, Li YJ, et al. Microarray-based analysis of stress-regulated microRNAs in Arabidopsis thaliana. RNA. 2008. DOI:10.1261/rna.895308
  • Helwak A, Kudla G, Dudnakova T, et al. Mapping the human miRNA interactome by CLASH reveals frequent noncanonical binding. Cell. 2013;153(3):654–665.
  • Chou CH, Shrestha S, Yang CD, et al. MiRTarBase update 2018: A resource for experimentally validated microRNA-target interactions. Nucleic Acids Res. 2018. DOI:10.1093/nar/gkx1067.
  • Da Hsu S, Lin FM, Wu WY, et al. MiRTarBase: A database curates experimentally validated microRNA-target interactions. Nucleic Acids Res. 2011. DOI:10.1093/nar/gkq1107.
  • Peterson SM, Thompson JA, Ufkin ML, et al. Common features of microRNA target prediction tools. Front Genet. 2014;5:1–10.
  • Leoni G, Tramontano A. A structural view of microRNA-target recognition. Nucleic Acids Res. 2016;44:1–8.
  • Gan HH, Gunsalus KC. Tertiary structure-based analysis of microRNA-target interactions. RNA. 2013;19:539–551.
  • Reczko M, Maragkakis M, Alexiou P, et al. Functional microRNA targets in protein coding sequences. Bioinformatics. 2012;28:771–776.
  • Paraskevopoulou MD, Georgakilas G, Kostoulas N, et al. DIANA-microT web server v5.0: service integration into miRNA functional analysis workflows. Nucleic Acids Res. 2013;41:169–173.
  • Hsu JB, Chiu CM, Da HS, et al. MiRTar: an integrated system for identifying miRNA-target interactions in human. BMC Bioinformatics. 2011;12. DOI:10.1186/1471-2105-12-300
  • Vejnar CE, Zdobnov EM. MiRmap: comprehensive prediction of microRNA target repression strength. Nucleic Acids Res. 2012;40:11673–11683.
  • Agarwal V, Bell GW, Nam JW, et al. Predicting effective microRNA target sites in mammalian mRNAs. Elife. 2015;4:1–38.
  • Wang XW. Improving microRNA target prediction by modeling with unambiguously identified microRNA-target pairs from CLIP-ligation studies. Bioinformatics. 2016. DOI:10.1093/bioinformatics/btw002
  • Fiannaca A, La Rosa M, La Paglia L, et al. MiRNATIP: a SOM-based miRNA-target interactions predictor. BMC Bioinformatics. 2016;17:321.
  • Ding J, Li X, Hu H. TarPmiR: A new approach for microRNA target site prediction. Bioinformatics. 2016;32:2768–2775.
  • Sethupathy P, Megraw M, Hatzigeorgiou AG. A guide through present computational approaches for the identification of mammalian microRNA targets. Nat Methods. 2006;3(11):881–886.
  • Cloonan N, Brown MK, Steptoe AL, et al. The miR-17-5p microRNA is a key regulator of the G1/S phase cell cycle transition. Genome Biol. 2008. DOI:10.1186/gb-2008-9-8-r127
  • Parker BJ, Wen J. Predicting microRNA targets in time-series microarray experiments via functional data analysis. BMC Bioinformatics. 2009;10(S1):1–10.
  • Pinzón N, Li B, Martinez L, et al. MicroRNA target prediction programs predict many false positives. Genome Res. 2017;27:234–245.
  • Baek D, Villén J, Shin C, et al. The impact of microRNAs on protein output. Nature. 2008;455(7209):64–71.
  • Lim LP, Lau NC, Garrett-Engele P, et al. Microarray analysis shows that some microRNAs downregulate large numbers of target mRNAs. Nature. 2005;433:769–773.
  • Selbach M, Schwanhäusser B, Thierfelder N, et al. Widespread changes in protein synthesis induced by microRNAs. Nature. 2008;455(7209):58–63.
  • Seitz H. Issues in current microRNA target identification methods. RNA Biol. 2017;14:831–834.
  • Tabas-Madrid D, Muniategui A, Sánchez-Caballero I, et al. Improving miRNA-mRNA interaction predictions. BMC Genomics. 2014;15(Suppl 10):S2.
  • Wong N, Wang X. miRDB: an online resource for microRNA target prediction and functional annotations. Nucleic Acids Res. 2015;43:D146–D152.
  • Serva A, Knapp B, Tsai Y-T, et al. miR-17-5p regulates endocytic trafficking through targeting TBC1D2/armus. PLoS One. 2012;7(12):e52555.
  • Aakula A, Leivonen S, Hintsanen P, et al. MicroRNA-135b regulates ERα, AR and HIF1AN and affects breast and prostate cancer cell growth. Mol Oncol. 2015;9:1287–1300.
  • Kallio MA, Tuimala JT, Hupponen T, et al. Chipster: user-friendly analysis software for microarray and other high-throughput data. BMC Genomics. 2011;12(1). DOI:10.1186/1471-2164-12-507
  • Haft DH, DiCuccio M, Badretdin A, et al. RefSeq: an update on prokaryotic genome annotation and curation. Nucleic Acids Res. 2018;46(D1):D851-D860.
  • Camacho C, Coulouris G, Avagyan V, et al. BLAST+: architecture and applications. BMC Bioinformatics. 2009;10(1):421.
  • Zerbino DR, Achuthan P, Akanni W, et al. Ensembl 2018. Nucleic Acids Res. 2018;46(D1):D754-D761.
  • Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–780.
  • Liu ZP, Wu C, Miao H, et al. RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse. Database. 2015;2015:bav095.
  • Keshava Prasad TS, Goel R, Kandasamy K, et al. Human protein reference database - 2009 update. Nucleic Acids Res. 2009;37:D767-D772.
  • Jin J, Zhou S, Li C, et al. MiR-517a-3p accelerates lung cancer cell proliferation and invasion through inhibiting FOXJ3 expression. Life Sciences. 2014;108:48–53.
  • Wang X, Wang X. Systematic identification of microRNA functions by combining target prediction and expression profiling. Nucleic Acids Res. 2006;34:1646–1652.
  • Fang -L-L, Wang X-H, Sun B-F, et al. Expression, regulation and mechanism of action of the miR-17-92 cluster in tumor cells (Review). International Journal of Molecular Medicine. 2017;40(6):1624–1630.
  • Du WW, Yang W, Fang L, et al. MiR-17 extends mouse lifespan by inhibiting senescence signaling mediated by MKP7. Cell Death Dis. 2014. DOI:10.1038/cddis.2014.305
  • Lu Y, Thomson JM, Wong HYF, et al. Transgenic over-expression of the microRNA miR-17-92 cluster promotes proliferation and inhibits differentiation of lung epithelial progenitor cells. Dev Biol. 2007. DOI:10.1016/j.ydbio.2007.08.007
  • Li H, Miao D, Zhu Q, et al. MicroRNA-17-5p contributes to osteoarthritisprogression by binding p62/SQSTM1. Exp Ther Med. 2018. DOI:10.3892/etm.2017.5622
  • Wang W, Zhang L, Zheng K, et al. MiR-17-5p promotes the growth of osteosarcoma in a BRCC2-dependent mechanism. Oncol Rep. 2016. DOI:10.3892/or.2016.4542
  • Schwentner R, Herrero-Martin D, Kauer MO, et al. The role of miR-17-92 in the miRegulatory landscape of Ewing sarcoma. Oncotarget. 2017;8(7). DOI:10.18632/oncotarget.14091
  • Xu Y, Fang F, Zhang J, et al. Mir-17* suppresses tumorigenicity of prostate cancer by inhibiting mitochondrial antioxidant enzymes. PLoS One. 2010;5(12):e14356.
  • Li Y, Choi PS, Casey SC, et al. MYC through miR-17-92 suppresses specific target genes to maintain survival, autonomous proliferation, and a Neoplastic state. Cancer Cell. 2014;26(2):262–272.
  • Li L, Shi JY, Zhu GQ, et al. MiR-17-92 cluster regulates cell proliferation and collagen synthesis by targeting TGFB pathway in mouse palatal mesenchymal cells. J Cell Biochem. 2012. DOI:10.1002/jcb.23457
  • Volinia S, Calin GA, Liu C-G, et al. A microRNA expression signature of human solid tumors defines cancer gene targets. Proc. Natl. Acad. Sci. 2006;103(7):2257–2261.
  • Hausser J, Syed AP, Bilen B, et al. Analysis of CDS-located miRNA target sites suggests that they can effectively inhibit translation. Genome Research. 2013;23(4):604–615.
  • Brümmer A, Hausser J. MicroRNA binding sites in the coding region of mRNAs: extending the repertoire of post-transcriptional gene regulation. BioEssays. 2014;36(6):617–626.
  • Poliseno L, Salmena L, Zhang J, et al. A coding-independent function of gene and pseudogene mRNAs regulates tumour biology. Nature. 2010;465(7301):1033–1038.
  • Bosson AD, Zamudio JR, Sharp PA. Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. Mol Cell. 2014;56:347–359.
  • Tian W, Du Y, Ma Y, et al. MALAT1–miR663a negative feedback loop in colon cancer cell functions through direct miRNA–lncRNA binding. Cell Death Dis. 2018;9. DOI:10.1038/s41419-018-0925-y.
  • Eichhorn SW, Guo H, McGeary SE, et al. mRNA destabilization is the dominant effect of mammalian microRNAs by the time substantial repression ensues. Mol Cell. 2014;56:104–115.
  • Gennarino VA, Sardiello M, Avellino R, et al. MicroRNA target prediction by expression analysis of host genes. Genome Res. 2009. DOI:10.1101/gr.084129.108

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