miRRim: A novel system to find conserved miRNAs with high sensitivity and specificity

RNA

Volumn 13, Issue 12, 2007, Pages 2081-2090

  Terai, Goro ^a,b   Komori, Takashi ^a,b   Asai, Kiyoshi ^c,d   Kin, Taishin ^c  

^a INTEC Web and Genome Informatics Corporation   (Japan)

^b Koto ku   (Japan)

^c NATIONAL INSTITUTE OF ADVANCED INDUSTRIAL SCIENCE AND TECHNOLOGY AIST   (Japan)

^d UNIVERSITY OF TOKYO   (Japan)

Author keywords

Conservation; Hairpin; HMM; HTK; miRNA; Secondary structure

Indexed keywords

MICRORNA;

ACCURACY; ARTICLE; CLUSTER ANALYSIS; EVOLUTION; GENETIC CONSERVATION; GENOMICS; HUMAN; MOUSE; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROBABILITY; RAT; SENSITIVITY AND SPECIFICITY; STRUCTURE ANALYSIS; VERTEBRATE;

CONSERVED SEQUENCE; GENOME, HUMAN; HUMANS; MARKOV CHAINS; MICRORNAS; NUCLEIC ACID CONFORMATION; REPRODUCIBILITY OF RESULTS; RNA INTERFERENCE; SENSITIVITY AND SPECIFICITY; TRANSCRIPTION, GENETIC;

VERTEBRATA;

EID: 36249010340     PISSN: 13558382     EISSN: 14699001     Source Type: Journal    
DOI: 10.1261/rna.655107     Document Type: Article

References (40)

1. Baum, L.E. 1972. An equality and associated maximization technique in statistical estimation for probabilistic functions of Markov processes. Inequalities 3: 1-8.
2. Berezikov, E., Guryev, V., van de Belt, J., Wienholds, E., Plasterk, R.H., and Cuppen, E. 2005. Phylogenetic shadowing and computational identification of human microRNA genes. Cell 120: 21-24.
3. Bernhart, S.H., Hofacker, I.L., and Stadler, P.F. 2006. Local RNA base pairing probabilities in large sequences. Bioinformatics 22: 614-615.
4. Bonhoeffer, S., McCaskill, J.S., Stadler, P.F., and Schuster, P. 1993. RNA multi-structure landscapes. A study based on temperature dependent partition functions. Eur. Biophys. J. 22: 13-24.
5. Calin, G.A., Dumitru, C.D., Shimizu, M., Bichi, R., Zupo, S., Noch, E., Aldler, H., Rattan, S., Keating, M., Rai, K., et al. 2002. Frequent deletions and down-regulation of micro-RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc. Natl. Acad. Sci. 99: 15524-15529.
6. Calin, G.A., Sevignani, C., Dumitru, C.D., Hyslop, T., Noch, E., Yendamuri, S., Shimizu, M., Rattan, S., Bullrich, F., Negrini, M., et al. 2004. Human microRNA genes are frequently located at fragile sites and genomic regions involved in cancers. Proc. Natl. Acad. Sci. 101: 2999-3004.
7. Griffiths-Jones, S., Moxon, S., Marshall, M., Khanna, A., Eddy, S.R., and Bateman, A. 2005. Rfam: Annotating noncoding RNAs in complete genomes. Nucleic Acids Res. 33: D121-D124. doi: 10.1093/nar/gki081.
8. Griffiths-Jones, S., Grocock, R.J., van Dongen, S., Bateman, A., and Enright, A.J. 2006. miRBase: microRNA sequences, targets, and gene nomenclature. Nucleic Acids Res. 34: D140-D144. doi: 10.1093/nar/gkj112.
9. Hertel, J. and Stadler, P.F. 2006. Hairpins in a haystack: Recognizing microRNA precursors in comparative genomics data. Bioinformatics 22: e197-e202.
10. Hofacker, I.L., Bernhart, S.H., and Stadler, P.F. 2004. Alignment of RNA base pairing probability matrices. Bioinformatics 20: 2222-2227.
11. Hsu, P.W., Huang, H.D., Hsu, S.D., Lin, L.Z., Tsou, A.P., Tseng, C.P., Stadler, P.F., Washietl, S., and Hofacker, I.L. 2006. miRNAMap: Genomic maps of microRNA genes and their target genes in mammalian genomes. Nucleic Acids Res. 34: D135-D139. doi: 10.1093/nar/gki081.
12. John, B., Enright, A.J., Aravin, A., Tuschl, T., Sander, C., and Marks, D.S. 2004. Human MicroRNA targets. PLoS Biol. 2: e363. doi: 10.1371/journal.pbio.0020363.
13. Krek, A., Grun, D., Poy, M.N., Wolf, R., Rosenberg, L., Epstein, E.J., MacMenamin, P., da Piedade, I., Gunsalus, K.C., Stoffel, M., et al. 2005. Combinatorial microRNA target predictions. Nat. Genet. 37: 495-500.
14. Kryukov, G.V., Castellano, S., Novoselov, S.V., Lobanov, A.V., Zehtab, O., Guigo, R., and Gladyshev, V.N. 2003. Characterization of mammalian selenoproteomes. Science 300: 1439-1443.
15. Lai, E.C., Tomancak, P., Williams, R.W., and Rubin, G.M. 2003. Computational identification of Drosophila microRNA genes. Genome Biol. 4: R42. doi: 10.1186/gb-2003-4-7-r42.
16. Lee, Y., Jeon, K., Lee, J.T., Kim, S., and Kim, V.N. 2002. MicroRNA maturation: Stepwise processing and subcellular localization. EMBO J. 21: 4663-4670.
17. Legendre, M., Lambert, A., and Gautheret, D. 2005. Profile-based detection of microRNA precursors in animal genomes. Bioinformatics 21: 841-845.
18. Lewis, B.P., Burge, C.B., and Bartel, D.P. 2005. Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 120: 15-20.
19. Li, S.C., Pan, C.Y., and Lin, W.C. 2006. Bioinformatic discovery of microRNA precursors from human ESTs and introns. BMC Genomics 7: 164. doi: 10.1186/1471-2164-7-164.
20. Lim, L.P., Lau, N.C., Weinstein, E.G., Abdelhakim, A., Yekta, S., Rhoades, M.W., Burge, C.B., and Bartel, D.P. 2003. The micro-RNAs of Caenorhabditis elegans. Genes & Dev. 17: 991-1008.
21. McCaskill, J.S. 1990. The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 29: 1105-1119.
22. Metzler, M., Wilda, M., Busch, K., Viehmann, S., and Borkhardt, A. 2004. High expression of precursor microRNA-155/BIC RNA in children with Burkitt lymphoma. Genes Chromosomes Cancer 39: 167-169.
23. Michael, M.Z., O'Connor, S.M., van Holst Pellekaan, N.G., Young, G.P., and James, R.J. 2003. Reduced accumulation of specific microRNAs in colorectal neoplasia. Mol. Cancer Res. 1: 882-891.
24. Miranda, K.C., Huynh, T., Tay, Y., Ang, Y.S., Tam, W.L., Thomson, A.M., Lim, B., and Rigoutsos, I. 2006. A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes. Cell 126: 1203-1217.
25. Nam, J.W., Shin, K.R., Han, J., Lee, Y., Kim, V.N., and Zhang, B.T. 2005. Human microRNA prediction through a probabilistic colearning model of sequence and structure. Nucleic Acids Res. 33: 3570-3581. doi: 10.1093/nar/gki668.
26. Ohler, U., Yekta, S., Lim, L.P., Bartel, D.P., and Burge, C.B. 2004. Patterns of flanking sequence conservation and a characteristic upstream motif for microRNA gene identification. RNA 10: 1309-1322.
27. Rabiner, L. and Juang, B.H. 1993. Chapter 6, Theory and implementation of Hidden Markov Models. In Fundamentals of speech recognition, pp. 321-389. Prentice-Hall Inc., Englewood Cliffs, NJ.
28. Reiche, K. and Stadler, P.F. 2007. RNAstrand: Reading direction of structured RNAs in multiple sequence alignments. Algorithms Mol. Biol. 2: 6. doi: 10.1186/1748-7188-2-6.
29. Ruby, J.G., Jan, C.H., and Bartel, D.P. 2007. Intronic microRNA precursors that bypass Drosha processing. Nature 448: 83-86.
30. Sanchez, M., Galy, B., Dandekar, T., Bengert, P., Vainshtein, Y., Stolte, J., Muckenthaler, M.U., and Hentze, M.W. 2006. Iron regulation and the cell cycle: Identification of an iron-responsive element in the 39-untranslated region of human cell division cycle 14A mRNA by a refined microarray-based screening strategy. J. Biol. Chem. 281: 22865-22874.
31. Scott, G.K., Goga, A., Bhaumik, D., Berger, C.E., Sullivan, C.S., and Benz, C.C. 2007. Coordinate suppression of ERBB2 and ERBB3 by enforced expression of micro-RNA miR-125a or miR-125b. J. Biol. Chem. 282: 1479-1486.
32. Sewer, A., Paul, N., Landgraf, P., Aravin, A., Pfeffer, S., Brownstein, M.J., Tuschl, T., van Nimwegen, E., and Zavolan, M. 2005. Identification of clustered microRNAs using an ab initio prediction method. BMC Bioinformatics 6: 267. doi: 10.1186/1471-2105-6-267.
33. 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. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15: 1034-1050.
34. Song, L. and Tuan, R.S. 2006. MicroRNAs and cell differentiation in mammalian development. Birth Defects Res. C Embryo Today 78: 140-149.
35. Viterbi, A.J. 1967. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Trans. Inf. Theory 13: 260-269.
36. Wang, X., Zhang, J., Li, F., Gu, J., He, T., Zhang, X., and Li, Y. 2005. MicroRNA identification based on sequence and structure alignment. Bioinformatics 21: 3610-3614.
37. Washietl, S., Hofacker, I.L., and Stadler, P.F. 2005. Fast and reliable prediction of noncoding RNAs. Proc. Natl. Acad. Sci. 102: 2454-2459.
38. Xie, X., Lu, J., Kulbokas, E.J., Golub, T.R., Mootha, V., Lindblad-Toh, K., Lander, E.S., and Kellis, M. 2005. Systematic discovery of regulatory motifs in human promoters and 3′ UTRs by comparison of several mammals. Nature 434: 338-345.
39. Xue, C., Li, F., He, T., Liu, G.P., Li, Y., and Zhang, X. 2005. Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinformatics 6: 310. doi: 10.1186/1471-2105-6-310.
40. Yousef, M., Nebozhyn, M., Shatkay, H., Kanterakis, S., Showe, L.C., and Showe, M.K. 2006. Combining multispecies genomic data for microRNA identification using a Naive Bayes classifier. Bioinformatics 22: 1325-1334.