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Current Genomics

Editor-in-Chief

ISSN (Print): 1389-2029
ISSN (Online): 1875-5488

Mini-Review Article

A Mini-review of the Computational Methods Used in Identifying RNA 5- Methylcytosine Sites

Author(s): Jianwei Li, Yan Huang and Yuan Zhou*

Volume 21, Issue 1, 2020

Page: [3 - 10] Pages: 8

DOI: 10.2174/2213346107666200219124951

open access plus

Abstract

RNA 5-methylcytosine (m5C) is one of the pillars of post-transcriptional modification (PTCM). A growing body of evidence suggests that m5C plays a vital role in RNA metabolism. Accurate localization of RNA m5C sites in tissue cells is the premise and basis for the in-depth understanding of the functions of m5C. However, the main experimental methods of detecting m5C sites are limited to varying degrees. Establishing a computational model to predict modification sites is an excellent complement to wet experiments for identifying m5C sites. In this review, we summarized some available m5C predictors and discussed the characteristics of these methods.

Keywords: 5-methylcytosine, RNA modification, machine learning, prediction, sequence encoding, pseudo dinucleotide composition.

Graphical Abstract
[1]
Motorin, Y.; Lyko, F.; Helm, M. 5-methylcytosine in RNA: detection, enzymatic formation and biological functions. Nucleic Acids Res., 2010, 38(5), 1415-1430.
[http://dx.doi.org/10.1093/nar/gkp1117] [PMID: 20007150]
[2]
Bohnsack, K.E.; Höbartner, C.; Bohnsack, M.T. Eukaryotic 5-methylcytosine (m5C) RNA methyltransferases: mechanisms, cellular functions, and links to disease. Genes (Basel), 2019, 10(2)E102
[http://dx.doi.org/10.3390/genes10020102] [PMID: 30704115]
[3]
Amort, T.; Sun, X.; Khokhlova-Cubberley, D.; Lusser, A. Transcriptome-wide detection of 5-methylcytosine by bisulfite sequencing. Methods Mol. Biol., 2017, 1562, 123-142.
[http://dx.doi.org/10.1007/978-1-4939-6807-7_9] [PMID: 28349458]
[4]
Amort, T.; Lusser, A. Detection of 5-methylcytosine in specific poly(A) RNAs by bisulfite sequencing. Methods Mol. Biol., 2017, 1562, 107-121.
[http://dx.doi.org/10.1007/978-1-4939-6807-7_8] [PMID: 28349457 ]
[5]
Helm, M. Post-transcriptional nucleotide modification and alternative folding of RNA. Nucleic Acids Res., 2006, 34(2), 721-733.
[http://dx.doi.org/10.1093/nar/gkj471] [PMID: 16452298]
[6]
Kadaba, S.; Krueger, A.; Trice, T.; Krecic, A.M.; Hinnebusch, A.G.; Anderson, J. Nuclear surveillance and degradation of hypomodified initiator tRNAMet in S. cerevisiae. Genes Dev., 2004, 18(11), 1227-1240.
[http://dx.doi.org/10.1101/gad.1183804] [PMID: 15145828]
[7]
Alexandrov, A.; Chernyakov, I.; Gu, W.; Hiley, S.L.; Hughes, T.R.; Grayhack, E.J.; Phizicky, E.M. Rapid tRNA decay can result from lack of nonessential modifications. Mol. Cell, 2006, 21(1), 87-96.
[http://dx.doi.org/10.1016/j.molcel.2005.10.036] [PMID: 16387656]
[8]
Chernyakov, I.; Whipple, J.M.; Kotelawala, L.; Grayhack, E.J.; Phizicky, E.M. Degradation of several hypomodified mature tRNA species in Saccharomyces cerevisiae is mediated by Met22 and the 5′-3′ exonucleases Rat1 and Xrn1. Genes Dev., 2008, 22(10), 1369-1380.
[http://dx.doi.org/10.1101/gad.1654308] [PMID: 18443146]
[9]
Schosserer, M.; Minois, N.; Angerer, T.B.; Amring, M.; Dellago, H.; Harreither, E.; Calle-Perez, A.; Pircher, A.; Gerstl, M.P.; Pfeifenberger, S.; Brandl, C.; Sonntagbauer, M.; Kriegner, A.; Linder, A.; Weinhäusel, A.; Mohr, T.; Steiger, M.; Mattanovich, D.; Rinnerthaler, M.; Karl, T.; Sharma, S.; Entian, K.D.; Kos, M.; Breitenbach, M.; Wilson, I.B.; Polacek, N.; Grillari-Voglauer, R.; Breitenbach-Koller, L.; Grillari, J. Methylation of ribosomal RNA by NSUN5 is a conserved mechanism modulating organismal lifespan. Nat. Commun., 2015, 6, 6158.
[http://dx.doi.org/10.1038/ncomms7158] [PMID: 25635753]
[10]
Yang, X.; Yang, Y.; Sun, B.F.; Chen, Y.S.; Xu, J.W.; Lai, W.Y.; Li, A.; Wang, X.; Bhattarai, D.P.; Xiao, W.; Sun, H.Y.; Zhu, Q.; Ma, H.L.; Adhikari, S.; Sun, M.; Hao, Y.J.; Zhang, B.; Huang, C.M.; Huang, N.; Jiang, G.B.; Zhao, Y.L.; Wang, H.L.; Sun, Y.P.; Yang, Y.G. 5-methylcytosine promotes mRNA export - NSUN2 as the methyltransferase and ALYREF as an m5C reader. Cell Res., 2017, 27(5), 606-625.
[http://dx.doi.org/10.1038/cr.2017.55] [PMID: 28418038]
[11]
Tang, H.; Fan, X.; Xing, J.; Liu, Z.; Jiang, B.; Dou, Y.; Gorospe, M.; Wang, W. NSun2 delays replicative senescence by repressing p27 (KIP1) translation and elevating CDK1 translation. Aging (Albany NY), 2015, 7(12), 1143-1158.
[http://dx.doi.org/10.18632/aging.100860] [PMID: 26687548]
[12]
Li, Q.; Li, X.; Tang, H.; Jiang, B.; Dou, Y.; Gorospe, M.; Wang, W. NSUN2-Mediated m5C methylation and METTL3/METTL14-mediated m6A methylation cooperatively enhance p21 translation. J. Cell. Biochem., 2017, 118(9), 2587-2598.
[http://dx.doi.org/10.1002/jcb.25957] [PMID: 28247949]
[13]
Schaefer, M.; Pollex, T.; Hanna, K.; Lyko, F. RNA cytosine methylation analysis by bisulfite sequencing. Nucleic Acids Res., 2009, 37(2)e12
[http://dx.doi.org/10.1093/nar/gkn954] [PMID: 19059995]
[14]
Edelheit, S.; Schwartz, S.; Mumbach, M.R.; Wurtzel, O.; Sorek, R. Transcriptome-wide mapping of 5-methylcytidine RNA modifications in bacteria, archaea, and yeast reveals m5C within archaeal mRNAs. PLoS Genet., 2013, 9(6)e1003602
[http://dx.doi.org/10.1371/journal.pgen.1003602] [PMID: 23825970]
[15]
Khoddami, V.; Cairns, B.R. Identification of direct targets and modified bases of RNA cytosine methyltransferases. Nat. Biotechnol., 2013, 31(5), 458-464.
[http://dx.doi.org/10.1038/nbt.2566] [PMID: 23604283]
[16]
Hussain, S.; Sajini, A.A.; Blanco, S.; Dietmann, S.; Lombard, P.; Sugimoto, Y.; Paramor, M.; Gleeson, J.G.; Odom, D.T.; Ule, J.; Frye, M. NSun2-mediated cytosine-5 methylation of vault noncoding RNA determines its processing into regulatory small RNAs. Cell Rep., 2013, 4(2), 255-261.
[http://dx.doi.org/10.1016/j.celrep.2013.06.029] [PMID: 23871666]
[17]
Qiu, W.R.; Jiang, S.Y.; Xu, Z.C.; Xiao, X.; Chou, K.C. iRNAm5C-PseDNC: identifying RNA 5-methylcytosine sites by incorporating physical-chemical properties into pseudo dinucleotide composition. Oncotarget, 2017, 8(25), 41178-41188.
[http://dx.doi.org/10.18632/oncotarget.17104] [PMID: 28476023]
[18]
Feng, P.; Ding, H.; Yang, H.; Chen, W.; Lin, H.; Chou, K.C. iRNA-PseColl: identifying the occurrence sites of different RNA modifications by incorporating collective effects of nucleotides into PseKNC. Mol. Ther. Nucleic Acids, 2017, 7, 155-163.
[http://dx.doi.org/10.1016/j.omtn.2017.03.006] [PMID: 28624191]
[19]
Li, J.; Huang, Y.; Yang, X.; Zhou, Y.; Zhou, Y. RNAm5Cfinder: a web-server for predicting RNA 5-methylcytosine (m5C) sites based on random forest. Sci. Rep., 2018, 8(1), 17299.
[http://dx.doi.org/10.1038/s41598-018-35502-4] [PMID: 30470762]
[20]
Song, J.; Zhai, J.; Bian, E.; Song, Y.; Yu, J.; Ma, C. Transcriptome-wide annotation of m5C RNA modifications using machine learning. Front. Plant Sci., 2018, 9, 519.
[http://dx.doi.org/10.3389/fpls.2018.00519] [PMID: 29720995]
[21]
Zhang, M.; Xu, Y.; Li, L.; Liu, Z.; Yang, X.; Yu, D.J. Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble. Anal. Biochem., 2018, 550, 41-48.
[http://dx.doi.org/10.1016/j.ab.2018.03.027] [PMID: 29649472 ]
[22]
Sun, W.J.; Li, J.H.; Liu, S.; Wu, J.; Zhou, H.; Qu, L.H.; Yang, J.H. RMBase: a resource for decoding the landscape of RNA modifications from high-throughput sequencing data. Nucleic Acids Res., 2016, 44(D1), D259-D265.
[http://dx.doi.org/10.1093/nar/gkv1036] [PMID: 26464443]
[23]
Xuan, J.J.; Sun, W.J.; Lin, P.H.; Zhou, K.R.; Liu, S.; Zheng, L.L.; Qu, L.H.; Yang, J.H. RMBase v2.0: deciphering the map of RNA modifications from epitranscriptome sequencing data. Nucleic Acids Res., 2018, 46(D1), D327-D334.
[http://dx.doi.org/10.1093/nar/gkx934] [PMID: 29040692]
[24]
Khoddami, V.; Yerra, A.; Mosbruger, T.L.; Fleming, A.M.; Burrows, C.J.; Cairns, B.R. Transcriptome-wide profiling of multiple RNA modifications simultaneously at single-base resolution. Proc. Natl. Acad. Sci. USA, 2019, 116(14), 6784-6789.
[http://dx.doi.org/10.1073/pnas.1817334116] [PMID: 30872485]
[25]
Chen, W.M.; Danziger, S.A.; Chiang, J.H.; Aitchison, J.D. PhosphoChain: a novel algorithm to predict kinase and phosphatase networks from high-throughput expression data. Bioinformatics, 2013, 29(19), 2435-2444.
[http://dx.doi.org/10.1093/bioinformatics/btt387] [PMID: 23832245]
[26]
Allman, E.S.; Rhodes, J.A.; Sullivant, S. Statistically consistent k-mer methods for phylogenetic tree reconstruction. J. Comput. Biol., 2017, 24(2), 153-171.
[http://dx.doi.org/10.1089/cmb.2015.0216] [PMID: 27387364]
[27]
Wen, J.; Zhang, Y.; Yau, S.S. k-mer sparse matrix model for genetic sequence and its applications in sequence comparison. J. Theor. Biol., 2014, 363, 145-150.
[http://dx.doi.org/10.1016/j.jtbi.2014.08.028] [PMID: 25158165]
[28]
Carvalho, A.B.; Dupim, E.G.; Goldstein, G. Improved assembly of noisy long reads by k-mer validation. Genome Res., 2016, 26(12), 1710-1720.
[http://dx.doi.org/10.1101/gr.209247.116] [PMID: 27831497]
[29]
Shen, H.B.; Chou, K.C. PseAAC: a flexible web server for generating various kinds of protein pseudo amino acid composition. Anal. Biochem., 2008, 373(2), 386-388.
[http://dx.doi.org/10.1016/j.ab.2007.10.012] [PMID: 17976365]
[30]
Feng, P.; Ding, H.; Chen, W.; Lin, H. Identifying RNA 5-methylcytosine sites via pseudo nucleotide compositions. Mol. Biosyst., 2016, 12(11), 3307-3311.
[http://dx.doi.org/10.1039/C6MB00471G] [PMID: 27531244]
[31]
Sabooh, M.F.; Iqbal, N.; Khan, M.; Khan, M.; Maqbool, H.F. Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou’s PseKNC. J. Theor. Biol., 2018, 452, 1-9.
[http://dx.doi.org/10.1016/j.jtbi.2018.04.037] [PMID: 29727634]
[32]
Feng, P.; Yang, H.; Ding, H.; Lin, H.; Chen, W.; Chou, K.C. iDNA6mA-PseKNC: Identifying DNA N6-methyladenosine sites by incorporating nucleotide physicochemical properties into PseKNC. Genomics, 2019, 111(1), 96-102.
[http://dx.doi.org/10.1016/j.ygeno.2018.01.005] [PMID: 29360500]
[33]
Yang, H.; Qiu, W.R.; Liu, G.; Guo, F.B.; Chen, W.; Chou, K.C.; Lin, H. iRSpot-Pse6NC: Identifying recombination spots in Saccharomyces cerevisiae by incorporating hexamer composition into general PseKNC. Int. J. Biol. Sci., 2018, 14(8), 883-891.
[http://dx.doi.org/10.7150/ijbs.24616] [PMID: 29989083]
[34]
Chen, W.; Feng, P.M.; Lin, H.; Chou, K.C. iSS-PseDNC: identifying splicing sites using pseudo dinucleotide composition. BioMed Res. Int., 2014, 2014623149
[http://dx.doi.org/10.1155/2014/623149] [PMID: 24967386]
[35]
Pérez, A.; Noy, A.; Lankas, F.; Luque, F.J.; Orozco, M. The relative flexibility of B-DNA and A-RNA duplexes: database analysis. Nucleic Acids Res., 2004, 32(20), 6144-6151.
[http://dx.doi.org/10.1093/nar/gkh954] [PMID: 15562006 ]
[36]
Goñi, J.R.; Pérez, A.; Torrents, D.; Orozco, M. Determining promoter location based on DNA structure first-principles calculations. Genome Biol., 2007, 8(12), R263.
[http://dx.doi.org/10.1186/gb-2007-8-12-r263] [PMID: 18072969]
[37]
Freier, S.M.; Kierzek, R.; Jaeger, J.A.; Sugimoto, N.; Caruthers, M.H.; Neilson, T.; Turner, D.H. Improved free-energy parameters for predictions of RNA duplex stability. Proc. Natl. Acad. Sci. USA, 1986, 83(24), 9373-9377.
[http://dx.doi.org/10.1073/pnas.83.24.9373] [PMID: 2432595]
[38]
Friedel, M.; Nikolajewa, S.; Sühnel, J.; Wilhelm, T. DiProDB: a database for dinucleotide properties. Nucleic Acids Res., 2009, 37(Database issue), D37-D40.
[http://dx.doi.org/10.1093/nar/gkn597] [PMID: 18805906]
[39]
Barzilay, I.; Sussman, J.L.; Lapidot, Y. Further studies on the chromatographic behaviour of dinucleoside monophosphates. J. Chromatogr. A, 1973, 79, 139-146.
[http://dx.doi.org/10.1016/S0021-9673(01)85282-1] [PMID: 4350764]
[40]
Ponnuswamy, P.K.; Gromiha, M.M. On the conformational stability of oligonucleotide duplexes and tRNA molecules. J. Theor. Biol., 1994, 169(4), 419-432.
[http://dx.doi.org/10.1006/jtbi.1994.1163] [PMID: 7526075]

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