Unique folding of precursor microRNAs: Quantitative evidence and implications for de novo identification

RNA

Volumn 13, Issue 2, 2007, Pages 170-187

  Loong, Stanley Ng Kwang ^a,b   Mishra, Santosh K ^a,b  

^a BIOINFORMATICS INSTITUTE   (Singapore)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Minimum free energy of folding; Precursor microRNAs; Second eigenvalue; Shannon entropy; Z scores

Indexed keywords

MICRORNA; RNA PRECURSOR; UNTRANSLATED RNA; VIRUS RNA;

ARTICLE; CONTROLLED STUDY; ENTROPY; GENOMICS; NONHUMAN; NUCLEOTIDE SEQUENCE; PRIORITY JOURNAL; PROBABILITY; RNA SEQUENCE; RNA STRUCTURE; STRUCTURE ANALYSIS;

ANIMALS; HUMANS; MICRORNAS; NUCLEIC ACID CONFORMATION; RNA PRECURSORS; RNA PROCESSING, POST-TRANSCRIPTIONAL; RNA, MESSENGER; RNA, PLANT; RNA, UNTRANSLATED;

VERTEBRATA;

EID: 33846437079     PISSN: 13558382     EISSN: 14699001     Source Type: Journal    
DOI: 10.1261/rna.223807     Document Type: Article

References (103)

1. Adai, A., Johnson, C., Mlotshwa, S., Archer-Evans, S., Manocha, V., Vance, V., and Sundaresan, V. 2005. Computational prediction of miRNAs in Arabidopsis thaliana. Genome Res. 15: 78-91.
2. Altschul, S.F. and Erickson, B.W. 1985. Significance of nucleotide sequence alignments: A method for random sequence permutation that preserves dinucleotide and codon usage. Mol. Biol. Evol. 2: 526-538.
3. Ambros, V. 2001. microRNAs: Tiny regulators with great potential. Cell 107: 823-826.
4. Ambros, V., Bartel, B., Bartel, D.P., Burge, C.B., Carrington, J.C., Chen, X., Dreyfuss, G., Eddy, S.R., Griffiths-Jones, S., Marshall, M., et al. 2003. A uniform system for microRNA annotation. RNA 9: 277-279.
5. Anthony, A.M. and Peter, M.W. 2005. Plant and animal microRNAs: Similarities and differences. Funct. Integr. Genomics 5: 129-135.
6. Banerjee, D. and Slack, F. 2002. Control of developmental timing by small temporal RNAs: A paradigm for RNA-mediated regulation of gene expression. Bioessays 24: 119-129.
7. Barash, D. 2003. Deleterious mutation prediction in the secondary structure of RNAs. Nucleic Acids Res. 31: 6578-6584.
8. Barash, D. 2004. Spectral decomposition for the search and analysis of RNA secondary structure. J. Comput. Biol. 11: 1169-1174.
9. Bartel, D.P. 2004. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 116: 281-297.
10. Benson, D.A., Karsch-Mizrachi, I., Lipman, D.J., Ostell, J., and Wheeler, D.L. 2005. GenBank. Nucleic Acids Res. 33: D34-D38.
11. Bentwich, I., Avniel, A., Karov, Y., Aharonov, R., Gilad, S., Barad, O., Barzilai, A., Einat, P., Einav, U., Meiri, E., et al. 2005. Identification of hundreds of conserved and nonconserved human micro-RNAs. Nat. Genet. 37: 766-770.
12. Berezikov, E., Guryev, V., van de, B.J., Wienholds, E., Plasterk, R.H., and Cuppen, E. 2005. Phylogenetic shadowing and computational identification of human microRNA genes. Cell 120: 21-24.
13. Berezikov, E., Cuppen, E., and Plasterk, R.H. 2006. Approaches to microRNA discovery. Nat. Genet. (Suppl) 38: S2-S7.
14. Bonen, L. and Vogel, J. 2001. The ins and outs of group II introns. Trends Genet. 17: 322-331.
15. Bonnet, E., Wuyts, J., Rouze, P., and Van de Peer, Y. 2004a. Detection of 91 potential conserved plant microRNAs in Arabidopsis thaliana and Oryza sativa identifies important target genes. Proc. Natl. Acad. Sci. 101: 11511-11516.
16. Bonnet, E., Wuyts, J., Rouze, P., and Van de Peer, Y. 2004b. Evidence that microRNA precursors, unlike other non-coding RNAs, have lower folding free energies than random sequences. Bioinformatics 20: 2911-2917.
17. Brennecke, J., Hipfner, D.R., Stark, A., Russell, R.B., and Cohen, S.M. 2003. bantam encodes a developmentally regulated microRNA that controls cell proliferation and regulates the proapoptotic gene hid in Drosophila. Cell 113: 25-36.
18. Brenner, S., Johnson, M., Bridgham, J., Golda, G., Lloyd, D.H., Johnson, D., Luo, S., McCurdy, S., Foy, M., Ewan, M., et al. 2000. Gene expression analysis by massively parallel signature sequencing (MPSS) on microbead arrays. Nat. Biotechnol. 18: 630-634.
19. Cech, T.R. 1990. Self-splicing of group I introns. Annu. Rev. Biochem. 59: 543-568.
20. Chen, C.Z., Li, L., Lodish, H.F., and Bartel, D.P. 2004. MicroRNAs modulate hematopoietic lineage differentiation. Science 303: 83-86.
21. Clote, P. 2005. RNALOSS: A web server for RNA locally optimal secondary structures. Nucleic Acids Res. 33: W600-W604.
22. Clote, P., Ferre, F., Kranakis, E., and Krizanc, D. 2005. Structural RNA has lower folding energy than random RNA of the same dinucleotide frequency. RNA 11: 578-591.
23. Coward, E. 1999. Shufflet: Shuffling sequences while conserving the k-let counts. Bioinformatics 15: 1058-1059.
24. Cullen, B.R. 2004. Transcription and processing of human microRNA precursors. Mol. Cell 16: 861-865.
25. Cummins, J.M., He, Y., Leary, R.J., Pagliarini, R., Diaz Jr., L.A., Sjoblom, T., Barad, O., Bentwich, Z., Szafranska, A.E., Labourier, E., et al. 2006. The colorectal microRNAome. Proc. Natl. Acad. Sci. 103: 3687-3692.
26. Delihas, N. and Forst, S. 2001. MicF: An anti-sense RNA gene involved in response of Escherichia coli to global stress factors. J. Mol. Biol. 313: 1-12.
27. Doench, J.G. and Sharp, P.A. 2004. Specificity of microRNA target selection in translational repression. Genes & Dev. 18: 504-511.
28. Eddy, S.R. 2001. Non-coding RNA genes and the modern RNA world. Nat. Rev. Genet. 2: 919-929.
29. Fera, D., Kim, N., Shiffeldrim, N., Zorn, J., Laserson, U., Gan, H., and Schlick, T. 2004. RAG: RNA-As-Graphs web resource. BMC Bioinformatics 5: 88.
30. Freyhult, E., Gardner, P., and Moulton, V. 2005. A comparison of RNA folding measures. BMC Bioinformatics 6: 241.
31. Fu, H., Tie, Y., Xu, C., Zhang, Z., Zhu, J., Shi, Y., Jiang, H., Sun, Z., and Zheng, X. 2005. Identification of human fetal liver miRNAs by a novel method. FEBS Lett. 579: 3849-3854.
32. Gan, H.H., Fera, D., Zorn, J., Shiffeldrim, N., Tang, M., Laserson, U., Kim, N., and Schlick, T. 2004. RAG: RNA-As-Graphs database - Concepts, analysis, and features. Bioinformatics 20: 1285-1291.
33. Grad, Y., Aach, J., Hayes, G.D., Reinhart, B.J., Church, G.M., Ruvkun, G., and Kim, J. 2003. Computational and experimental identification of C. elegans microRNAs. Mol. Cell 11: 1253 1263.
34. Grey, F., Antoniewicz, A., Allen, E., Saugstad, J., McShea, A., Carrington, J.C., and Nelson, J. 2005. Identification and characterization of human cytomegalovirus-encoded microRNAs. J. Virol. 79: 12095-12099.
35. Griffiths-Jones, S., Moxon, S., Marshall, M., Khanna, A., Eddy, S.R., and Bateman, A. 2005. Rfam: Annotating non-coding RNAs in complete genomes. Nucleic Acids Res. 33: D121-D124.
36. 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.
37. Hertel, J. and Stadler, P.F. 2006. Hairpins in a haystack: Recognizing microRNA precursors in comparative genomics data. Bioinformatics 22: e197-e202.
38. Hesselberth, J.R. and Ellington, A.D. 2002. A (ribo) switch in the paradigms of genetic regulation. Nat. Struct. Biol. 9: 891-893.
39. Hofacker, I.L. 2003. Vienna RNA secondary structure server. Nucleic Acids Res. 31: 3429-3431.
40. Huynen, M., Gutell, R., and Konings, D. 1997. Assessing the reliability of RNA folding using statistical mechanics. J. Mol. Biol. 267: 1104-1112.
41. Johansson, J., Mandin, P., Renzoni, A., Chiaruttini, C., Springer, M., and Cossart, P. 2002. An RNA thermosensor controls expression of virulence genes in Listeria monocytogenes. Cell 110: 551-561.
42. Johnston, R.J. and Hobert, O. 2003. A microRNA controlling left/right neuronal asymmetry in Caenorhabditis elegans. Nature 426: 845-849.
43. Jones-Rhoades, M.W. and Bartel, D.P. 2004. Computational identification of plant microRNAs and their targets, including a stress-induced miRNA. Mol. Cell 14: 787-799.
44. Karolchik, D., Baertsch, R., Diekhans, M., Furey, T.S., Hinrichs, A., Lu, Y.T., Roskin, K.M., Schwartz, M., Sugnet, C.W., Thomas, D.J., et al. 2003. The UCSC Genome Browser Database. Nucleic Acids Res. 31: 51-54.
45. Kim, V.N. 2005. MicroRNA biogenesis: Coordinated cropping and dicing. Nat. Rev. Mol. Cell Biol. 6: 376-385.
46. Lagos-Quintana, M., Rauhut, R., Lendeckel, W., and Tuschl, T. 2001. Identification of novel genes coding for small expressed RNAs. Science 294: 853-858.
47. Lagos-Quintana, M., Rauhut, R., Yalcin, A., Meyer, J., Lendeckel, W., and Tuschl, T. 2002. Identification of tissue-specific microRNAs from mouse. Curr. Biol. 12: 735-739.
48. Lai, E.C. 2003. RNA sensors and riboswitches: Self-regulating messages. Curr. Biol. 13: R285-R291.
49. Lai, E., Tomancak, P., Williams, R., and Rubin, G. 2003. Computational identification of Drosophila microRNA genes. Genome Biol. 4: R42.
50. Lau, N.C., Lim, L.P., Weinstein, E.G., and Bartel, D.P. 2001. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 294: 858-862.
51. Lee, R.C. and Ambros, V. 2001. An extensive class of small RNAs in Caenorhabditis elegans. Science 294: 862-864.
52. 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.
53. Li, W. and Godzik, A. 2006. Cd-hit: A fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22: 1658-1659.
54. Li, X. and Zhang, Y.Z. 2005. Computational detection of microRNAs targeting transcription factor genes in Arabidopsis thaliana. Comput. Biol. Chem. 29: 360-367.
55. Lim, L.P., Glasner, M.E., Yekta, S., Burge, C.B., and Bartel, D.P. 2003a. Vertebrate microRNA genes. Science 299: 1540.
56. Lim, L.P., Lau, N.C., Weinstein, E.G., Abdelhakim, A., Yekta, S., Rhoades, M.W., Burge, C.B., and Bartel, D.P. 2003b. The micro-RNAs of Caenorhabditis elegans. Genes & Dev. 17: 991-1008.
57. Mallory, A.C. and Vaucheret, H. 2004. MicroRNAs: Something important between the genes. Curr. Opin. Plant Biol. 7: 120-125.
58. Mandal, M. and Breaker, R.R. 2004. Gene regulation by riboswitches. Nat. Rev. Mol. Cell Biol. 5: 451-463.
59. Mathews, D.H. 2004. Using an RNA secondary structure partition function to determine confidence in base pairs predicted by free energy minimization. RNA 10: 1178-1190.
60. Mathews, D.H., Sabina, J., Zuker, M., and Turner, D.H. 1999. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J. Mol. Biol. 288: 911-940.
61. Moss, E.G., Lee, R.C., and Ambros, V. 1997. The cold shock domain protein LIN-28 controls developmental timing in C. elegans and is regulated by the lin-4 RNA. Cell 88: 637-646.
62. Moulton, V., Zuker, M., Steel, M., Pointon, R., and Penny, D. 2000. Metrics on RNA secondary structures. J. Comput. Biol. 7: 277-292.
63. Nam, J.W., Shin, K.R., Han, J., Lee, Y., Kim, V.N., and Zhang, B.T. 2005. Human microRNA prediction through a probabilistic co-learning model of sequence and structure. Nucleic Acids Res. 33: 3570-3581.
64. Nudler, E. and Mironov, A.S. 2004. The riboswitch control of bacterial metabolism. Trends Biochem. Sci. 29: 11-17.
65. Pervouchine, D.D., Graber, J.H., and Kasif, S. 2003. On the normalization of RNA equilibrium free energy to the length of the sequence. Nucleic Acids Res. 31: e49.
66. Pfeffer, S., Zavolan, M., Grasser, F.A., Chien, M., Russo, J.J., Ju, J., John, B., Enright, A.J., Marks, D., Sander, C., et al. 2004. Identification of virus-encoded microRNAs. Science 304: 734-736.
67. Pfeffer, S., Sewer, A., Lagos-Quintana, M., Sheridan, R., Sander, C., Grasser, F.A., van Dyk, L.F., Ho, C.K., Shuman, S., Chien, M., et al. 2005. Identification of microRNAs of the herpesvirus family. Nat. Methods 2: 269-276.
68. Pruitt, K.D. and Maglott, D.R. 2001. RefSeq and LocusLink: NCBI gene-centered resources. Nucleic Acids Res. 29: 137-140.
69. Puerta-Fernandez, E., Romero-Lopez, C., Barroso-delJesus, A., and Berzal-Herranz, A. 2003. Ribozymes: Recent advances in the development of RNA tools. FEMS Microbiol. Rev. 27: 75-97.
70. Reinhart, B.J., Slack, F.J., Basson, M., Pasquinelli, A.E., Bettinger, J.C., Rougvie, A.E., Horvitz, H.R., and Ruvkun, G. 2000. The 21-nucleotide let-7 RNA regulates developmental timing in Caenorhabditis elegans. Nature 403: 901-906.
71. Rivas, E. and Eddy, S.R. 2000. Secondary structure alone is generally not statistically significant for the detection of noncoding RNAs. Bioinformatics 16: 583-605.
72. Rodriguez, A., Griffiths-Jones, S., Ashurst, J.L., and Bradley, A. 2004. Identification of mammalian microRNA host genes and transcription units. Genome Res. 14: 1902-1910.
73. Samols, M.A., Hu, J., Skalsky, R.L., and Renne, R. 2005. Cloning and identification of a microRNA cluster within the latency-associated region of Kaposi's sarcoma-associated herpesvirus. J. Virol. 79: 9301-9305.
74. Sarnow, P., Jopling, C.L., Norman, K.L., Schutz, S., and Wehner, K.A. 2006. MicroRNAs: Expression, avoidance and subversion by vertebrate viruses. Nat. Rev. Microbiol. 4: 651-659.
75. Schultes, E.A., Hraber, P.T., and LaBean, T.H. 1999. Estimating the contributions of selection and self-organization in RNA secondary structure. J. Mol. Evol. 49: 76-83.
76. Seffens, W. and Digby, D. 1999. mRNAs have greater negative folding free energies than shuffled or codon choice randomized sequences. Nucleic Acids Res. 27: 1578-1584.
77. Sewer, A., Paul, N., Landgraf, P., Aravin, A., Pfeffer, S., Brownstein, M., Tuschl, T., van Nimwegen, E., and Zavolan, M. 2005. Identification of clustered microRNAs using an ab initio prediction method. BMC Bioinformatics 6: 267.
78. Soukup, J.K. and Soukup, G.A. 2004. Riboswitches exert genetic control through metabolite-induced conformational change. Curr. Opin. Struct. Biol. 14: 344-349.
79. Sprinzl, M. and Vassilenko, K.S. 2005. Compilation of tRNA sequences and sequences of tRNA genes. Nucleic Acids Res. 33: D139-D140.
80. Stormo, G.D. 2003. New tricks for an old dogma: Riboswitches as cis-only regulatory systems. Mol. Cell 11: 1419-1420.
81. Storz, G. 2002. An expanding universe of noncoding RNAs. Science 296: 1260-1263.
82. Storz, G., Altuvia, S., and Wassarman, K.M. 2005. An abundance of RNA regulators. Annu. Rev. Biochem. 74: 199-217.
83. Svoboda, P. and Cara, A.D. 2006. Hairpin RNA: A secondary structure of primary importance. Cell. Mol. Life Sci. 63: 901-908.
84. Tang, G. 2005. siRNA and miRNA: An insight into RISCs. Trends Biochem. Sci. 30: 106-114.
85. Tijsterman, M. and Plasterk, R.H. 2004. Dicers at RISC; the mechanism of RNAi. Cell 117: 1-3.
86. Vitreschak, A.G., Rodionov, D.A., Mironov, A.A., and Gelfand, M.S. 2004. Riboswitches: The oldest mechanism for the regulation of gene expression? Trends Genet. 20: 44-50.
87. Wang, X.J., Reyes, J., Chua, N.H., and Gaasterland, T. 2004. Prediction and identification of Arabidopsis thaliana microRNAs and their mRNA targets. Genome Biol. 5: R65.
88. 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.
89. Washietl, S. and Hofacker, I.L. 2004. Consensus folding of aligned sequences as a new measure for the detection of functional RNAs by comparative genomics. J. Mol. Biol. 342: 19-30.
90. Weinstein, L.B. and Steitz, J.A. 1999. Guided tours: From precursor snoRNA to functional snoRNP. Curr. Opin. Cell Biol. 11: 378-384.
91. Wheeler, G., Ntounia-Fousara, S., Granda, B., Rathjen, T., and Dalmay, T. 2006. Identification of new central nervous system specific mouse microRNAs. FEBS Lett. 580: 2195-2200.
92. Winkler, W.C. and Breaker, R.R. 2003. Genetic control by metabolite-binding riboswitches. ChemBioChem 4: 1024-1032.
93. Winkler, W.C., Grundy, F.J., Murphy, B.A., and Henkin, T.M. 2001. The GA motif: An RNA element common to bacterial antitermination systems, rRNA, and eukaryotic RNAs. RNA 7: 1165-1172.
94. Workman, C. and Krogh, A. 1999. No evidence that mRNAs have lower folding free energies than random sequences with the same dinucleotide distribution. Nucleic Acids Res. 27: 4816-4822.
95. Xu, P., Vernooy, S.Y., Guo, M., and Hay, B.A. 2003. The Drosophila MicroRNA Mir-14 suppresses cell death and is required for normal fat metabolism. Curr. Biol. 13: 790-795.
96. 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.
97. Yekta, S., Shih, I.H., and Bartel, D.P. 2004. MicroRNA-directed cleavage of HOXB8 mRNA. Science 304: 594-596.
98. Yousef, M., Nebozhyn, M., Shatkay, H., Kanterakis, S., Showe, L.C., and Showe, M.K. 2006. Combining multi-species genomic data for microRNA identification using a Naive Bayes classifier. Bioinformatics 22: 1325-1334.
99. Zeng, Y. and Cullen, B.R. 2004. Structural requirements for pre-microRNA binding and nuclear export by Exportin 5. Nucleic Acids Res. 32: 4776-4785.
100. Zhang, B., Pan, X., Cobb, G.P., and Anderson, T.A. 2006a. Plant microRNA: A small regulatory molecule with big impact. Dev. Biol. 289: 3-16.
101. Zhang, B., Pan, X., Cox, S., Cobb, G., and Anderson, T. 2006b. Evidence that miRNAs are different from other RNAs. Cell. Mol. Life Sci. 63: 246-254.
102. Zuker, M. 2003. Mfold web server for nucleic acid folding and hybridization prediction. Nucleic Acids Res. 31: 3406-3415.
103. Zuker, M. and Stiegler, P. 1981. Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res. 9: 133-148.