Computational analysis of noncoding RNAs

Wiley Interdisciplinary Reviews: RNA

Volumn 3, Issue 6, 2012, Pages 759-778

  Washietl, Stefan ^a,b   Will, Sebastian ^a   Hendrix, David A ^a   Goff, Loyal A ^a,c   Rinn, John L ^b,c   Berger, Bonnie ^a,b,d   Kellis, Manolis ^a,b  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b BROAD INSTITUTE OF MIT AND HARVARD   (United States)

^c HARVARD UNIVERSITY   (United States)

^d MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MICRORNA; UNTRANSLATED RNA;

GENE EXPRESSION; MATHEMATICAL ANALYSIS; MOLECULAR MODEL; PRIORITY JOURNAL; PROTEIN RNA BINDING; REVIEW; RNA ANALYSIS; RNA FOLDING; RNA SEQUENCE; RNA STRUCTURE; RNA TRANSCRIPTION; THERMODYNAMICS;

ANIMALS; COMPUTATIONAL BIOLOGY; DATA MINING; DATABASES, NUCLEIC ACID; GENOMICS; HUMANS; MICRORNAS; MOLECULAR SEQUENCE ANNOTATION; NUCLEIC ACID CONFORMATION; RNA FOLDING; RNA, UNTRANSLATED;

EID: 84867603353     PISSN: 17577004     EISSN: 17577012     Source Type: Journal    
DOI: 10.1002/wrna.1134     Document Type: Review

References (172)

1. Amaral P, Dinger M, Mercer T, Mattick J. The eukaryotic genome as an RNA machine. Science 2008, 319:1787-1789.
2. Pasquinelli A, Reinhart B, Slack F, Martindale M, Kuroda M, Maller B, Hayward D, Ball E, Degnan B, Müller P, et al. Conservation of the sequence and temporal expression of let-7 heterochronic regulatory RNA. Nature 2000, 408:86-89.
3. Lau N, Lim L, Weinstein E, Bartel D. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 2001, 294:858-862.
4. ENCODE Project Consortium. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 2007, 447:799-816.
5. van Bakel H, Nislow C, Blencowe BJ, Hughes TR. Most "dark matter" transcripts are associated with known genes. PLoS Biol 2010, 8:e1000371.
6. Clark MB, Amaral PP, Schlesinger FJ, Dinger ME, Taft RJ, Rinn JL, Ponting CP, Stadler PF, Morris KV, Morillon A, et al. The reality of pervasive transcription. PLoS Biol 2011, 9:e1000625.
7. Guttman M, Donaghey J, Carey BW, Garber M, Grenier JK, Munson G, Young G, Lucas AB, Ach R, Bruhn L, et al. lincRNAs act in the circuitry controlling pluripotency and differentiation. Nature 2011, 477: 295-300.
8. Mattick JS. Challenging the dogma: the hidden layer of non-protein-coding RNAs in complex organisms. Bioessays 2003, 25:930-939.
9. Breaker RR. Riboswitches and the RNA World. Cold Spring Harb Perspect Biol 2012, 4:a003566. doi:10.1101/cshperspect.a003566.
10. Frhlich KS, Vogel J. Activation of gene expression by small RNA. Curr Opin Microbiol 2009, 12:674-682.
11. Weinberg Z, Perreault J, Meyer MM, Breaker RR. Exceptional structured noncoding RNAs revealed by bacterial metagenome analysis. Nature 2009, 462: 656-659.
12. Nussinov R, Jacobson A. Fast algorithm for predicting the secondary structure of single-stranded RNA. Proc Natl Acad Sci U S A 1980, 77:6309-6313.
13. Mathews D, Sabina J, Zuker M, Turner D. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J Mol Biol 1999, 288:911-940.
14. Xia T, SantaLucia J, Jr. Burkard M, Kierzek R, Schroeder S, Jiao X, Cox C, Turner D. Thermodynamic parameters for an expanded nearest-neighbor model for formation of RNA duplexes with Watson-Crick base pairs. Biochemistry 1998, 37: 14719-14735.
15. Zuker M, Stiegler P. Optimal computer folding of larger RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res 1981, 9:133-148.
16. Markham NR, Zuker M. UNAFold: software for nucleic acid folding and hybridization. Methods Mol Biol 2008, 453:3-31.
17. Gruber A, Lorenz R, Bernhart S, Neuböck R, Hofacker I. The Vienna RNA websuite. Nucleic Acids Res 2008, 36:W70-W74.
18. Reuter J, Mathews D. RNAstructure: software for RNA secondary structure prediction and analysis. BMC Bioinform 2010, 11:129.
19. Wuchty S, Fontana W, Hofacker IL, Schuster P. Complete suboptimal folding of RNA and the stability of secondary structures. Biopolymers 1999, 49: 145-165.
20. Zuker M. On finding all suboptimal foldings of an RNA molecule. Science 1989, 244:48-52.
21. McCaskill J. The equilibrium partition function and base pair binding probabilities for RNA secondary structure. Biopolymers 1990, 29:1105-1119.
22. Ding Y, Chan CY, Lawrence CE. RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble. RNA 2005, 11:1157-1166.
23. Do CB, Woods DA, Batzoglou S. CONTRAfold: RNA secondary structure prediction without physics-based models. Bioinformatics 2006, 22:e90-e98.
24. Lu Z, Gloor J, Mathews D. Improved RNA secondary structure prediction by maximizing expected pair accuracy. RNA 2009, 15:1805-1813.
25. Dowell RD, Eddy SR. Evaluation of several lightweight stochastic context-free grammars for RNA secondary structure prediction. BMC Bioinform 2004, 5:71.
26. Andronescu M, Condon A, Hoos H, Mathews D, Murphy K. Computational approaches for RNA energy parameter estimation. RNA 2010, 16:2304-2318.
27. Andronescu M, Condon A, Hoos H, Mathews D, Murphy K. Efficient parameter estimation for RNA secondary structure prediction. Bioinformatics 2007, 23:i19-i28.
28. Weeks K. Advances in RNA structure analysis by chemical probing. Curr Opin Struct Biol 2010, 20: 295-304.
29. Mathews DH, Disney MD, Childs JL, Schroeder SJ, Zuker M, Turner DH. Incorporating chemical modification constraints into a dynamic programming algorithm for prediction of RNA secondary structure. Proc Natl Acad Sci U S A 2004, 101:7287-7292.
30. Deigan KE, Li TW, Mathews DH, Weeks KM. Accurate SHAPE-directed RNA structure determination. Proc Natl Acad Sci U S A 2009, 106:97-102.
31. Washietl S, Hofacker IL, Stadler PF, Kellis M. RNA folding with soft constraints: reconciliation of probing data and thermodynamic secondary structure prediction. Nucleic Acids Res 2012, 40:4261-4272.
32. Kertesz M, Wan Y, Mazor E, Rinn J, Nutter R, Chang H, Segal E. Genome-wide measurement of RNA secondary structure in yeast. Nature 2010, 467: 103-107.
33. Underwood J, Uzilov A, Katzman S, Onodera C, Mainzer J, Mathews D, Lowe T, Salama S, Haussler D. FragSeq: transcriptome-wide RNA structure probing using high-throughput sequencing. Nat Methods 2010, 7:995-1001.
34. Lucks J, Mortimer S, Trapnell C, Luo S, Aviran S, Schroth G, Pachter L, Doudna J, Arkin A. Multiplexed RNA structure characterization with selective 2′-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq). Proc Natl Acad Sci U S A 2011, 108:11063-11068.
35. Noller HF, Kop J, Wheaton V, Brosius J, Gutell RR, Kopylov AM, Dohme F, Herr W, Stahl DA, Gupta R, et al. Secondary structure model for 23S ribosomal RNA. Nucleic Acids Res 1981, 9:6167-6189.
36. Bernhart S, Hofacker I, Will S, Gruber A, Stadler P. RNAalifold: improved consensus structure prediction for RNA alignments. BMC Bioinform 2008, 9:474.
37. Knudsen B, Hein J. Pfold: RNA secondary structure prediction using stochastic context-free grammars. Nucleic Acids Res 2003, 31:3423-3428.
38. Seemann S, Gorodkin J, Backofen R. Unifying evolutionary and thermodynamic information for RNA folding of multiple alignments. Nucleic Acids Res 2008, 36:6355-6362.
39. Harmanci AO, Sharma G, Mathews DH. TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequences. BMC Bioinform 2011, 12:108.
40. Gardner PP, Wilm A, Washietl S. A benchmark of multiple sequence alignment programs upon structural RNAs. Nucleic Acids Res 2005, 33:2433-2439.
41. Sankoff D. Simultaneous solution of the RNA folding, alignment and protosequence problems. SIAM J Appl Math 1985, 45:810-825.
42. Mathews DH, Turner DH. Dynalign: an algorithm for finding the secondary structure common to two RNA sequences. J Mol Biol 2002, 317:191-203.
43. Havgaard JH, Torarinsson E, Gorodkin J. Fast pairwise structural RNA alignments by pruning of the dynamical programming matrix. PLoS Comput Biol 2007, 3:1896-1908.
44. Hofacker IL, Bernhart SH, Stadler PF. Alignment of RNA base pairing probability matrices. Bioinformatics 2004, 20:2222-2227.
45. Will S, Reiche K, Hofacker IL, Stadler PF, Backofen R. Inferring non-coding RNA families and classes by means of genome-scale structure-based clustering. PLoS Comput Biol 2007, 3:e65.
46. Torarinsson E, Havgaard JH, Gorodkin J. Multiple structural alignment and clustering of RNA sequences. Bioinformatics 2007, 23:926-932.
47. Do CB, Foo CS, Batzoglou S. A max-margin model for efficient simultaneous alignment and folding of RNA sequences. Bioinformatics 2008, 24:i68-i76.
48. Will S, Joshi T, Hofacker IL, Stadler PF, Backofen R. LocARNA-P: accurate boundary prediction and improved detection of structural RNAs. RNA 2012, 18:900-914.
49. Will S, Yu M, Berger B. Structure-based Whole Genome Realignment Reveals Many Novel Non-coding RNAs. Proceedings of the 16th International Conference on Research in Computational Molecular Biology (RECOMB 2012), Volume 7262 of LNCS. Heidelberg: Springer-Verlag; 2012.
50. Lyngso RB, Pedersen CNS. Pseudoknots in RNA Secondary Structures. Proc. of the Fourth Annual International Conferences on Computational Molecular Biology (RECOMB'00). Washington, DC: ACM Press; 2000, [BRICS Report Series RS-00-1].
51. Rivas E, Eddy SR. A dynamic programming algorithm for RNA structure prediction including pseudoknots. J Mol Biol 1999, 285:2053-2068.
52. Reeder J, Giegerich R. Design, implementation and evaluation of a practical pseudoknot folding algorithm based on thermodynamics. BMC Bioinform 2004, 5:104.
53. Ruan J, Stormo GD, Zhang W. An iterated loop matching approach to the prediction of RNA secondary structures with pseudoknots. Bioinformatics 2004, 20:58-66.
54. Ren J, Rastegari B, Condon A, Hoos HH. HotKnots: heuristic prediction of RNA secondary structures including pseudoknots. RNA 2005, 11:1494-1504.
55. Sperschneider J, Datta A. KnotSeeker: heuristic pseudoknot detection in long RNA sequences. RNA 2008, 14:630-640.
56. Sato K, Kato Y, Hamada M, Akutsu T, Asai K. IPknot: fast and accurate prediction of RNA secondary structures with pseudoknots using integer programming. Bioinformatics 2011, 27:i85-i93.
57. Seetin MG, Mathews DH. TurboKnot: rapid prediction of conserved RNA secondary structures including pseudoknots. Bioinformatics 2012, 28:792-798.
58. Bon M, Vernizzi G, Orland H, Zee A. Topological classification of RNA structures. J Mol Biol 2008, 379:900-911.
59. Bon M, Orland H. TT2NE: a novel algorithm to predict RNA secondary structures with pseudoknots. Nucleic Acids Res 2011, 39:e93.
60. Uemura Y, Hasegawa A, Kobayashi S, Yokomori T. Tree adjoining grammars for RNA structure prediction. Theoret Comput Sci 1999, 210:277-303 [Paper as Print Copy].
61. Akutsu T. Dynamic programming algorithms for RNA secondary structure prediction with pseudoknots. Disc Appl Math 2000, 104:45-62.
62. Dirks RM, Pierce NA. A partition function algorithm for nucleic acid secondary structure including pseudoknots. J Comput Chem 2003, 24:1664-1677.
63. Chen HL, Condon A, Jabbari H. An O(n(5)) algorithm for MFE prediction of kissing hairpins and 4-chains in nucleic acids. J Comput Biol 2009, 16:803-815.
64. Mohl M, Salari R, Will S, Backofen R, Sahinalp SC. Sparsification of RNA structure prediction including pseudoknots. Algor Mol Biol 2010, 5:39.
65. Tabaska JE, Cary RB, Gabow HN, Stormo GD. An RNA folding method capable of identifying pseudoknots and base triples. Bioinformatics 1998, 14: 691-699.
66. Chen SJ. RNA folding: conformational statistics, folding kinetics, and ion electrostatics. Annu Rev Biophys 2008, 37:197-214.
67. Andronescu MS, Pop C, Condon AE. Improved free energy parameters for RNA pseudoknotted secondary structure prediction. RNA 2010, 16:26-42.
68. Parisien M, Major F. The MC-Fold and MC-Sym pipeline infers RNA structure from sequence data. Nature 2008, 452:51-55.
69. zu Siederdissen CH, Bernhart SH, Stadler PF, Hofacker IL. A folding algorithm for extended RNA secondary structures. Bioinformatics 2011, 27: i129-i136.
70. Laing C, Schlick T. Computational approaches to 3D modeling of RNA. J Phys Condens Matter 2010, 22:283101.
71. Alkan C, Karakoc E, Nadeau JH, Sahinalp SC, Zhang K. RNA-RNA interaction prediction and antisense RNA target search. J Comput Biol 2006, 13:267-282.
72. Kruger J, Rehmsmeier M. RNAhybrid: microRNA target prediction easy, fast and flexible. Nucleic Acids Res 2006, 34:W451-W454.
73. Hofacker IL, Fontana W, Stadler PF, Bonhoeffer S, Tacker M, Schuster P. Fast folding and comparison of RNA secondary structures. Monatshefte Chem 1994, 125:167-188.
74. Pervouchine DD. IRIS: intermolecular RNA interaction search. Genome Inform 2004, 15:92-101.
75. Salari R, Möhl M, Will S, Sahinalp S, Backofen R. Time and space efficient RNA-RNA interaction prediction via sparse folding. In: Berger B, ed. Proc. of RECOMB 2010, Volume 6044 of Lecture Notes in Computer Science. Berlin/Heidelberg: Springer; 2010, 473-490
76. Mückstein U, Tafer H, Hackermüller J, Bernhart SH, Stadler PF, Hofacker IL. Thermodynamics of RNA-RNA binding. Bioinformatics 2006, 22:1177-1182.
77. Busch A, Richter AS, Backofen R. IntaRNA: efficient prediction of bacterial sRNA targets incorporating target site accessibility and seed regions. Bioinformatics 2008, 24:2849-2856.
78. Li AX, Marz M, Qin J, Reidys CM. RNA-RNA interaction prediction based on multiple sequence alignments. Bioinformatics 2011, 27:456-463.
79. Seemann SE, Richter AS, Gesell T, Backofen R, Gorodkin J. PETcofold: predicting conserved interactions and structures of two multiple alignments of RNA sequences. Bioinformatics 2011, 27:211-219.
80. Nagel JHA, Pleij CWA. Self-induced structural switches in RNA. Biochimie 2002, 84:913-923.
81. Hofacker IL, Flamm C, Heine C, Wolfinger MT, Scheuermann G, Stadler PF. BarMap: RNA folding on dynamic energy landscapes. RNA 2010, 16: 1308-1316.
82. Wolfinger MT, Svrcek-Seiler WA, Flamm C, Hofacker IL, Stadler PF. Efficient computation of RNA folding dynamics. J Phys A: Math Gen 2004, 37:4731-4741. [http://stacks.iop.org/0305-4470/37/4731].
83. Flamm C, Hofacker I. Beyond energy minimization: approaches to the kinetic folding of RNA. Chem Mon 2008, 139:447-457.
84. Chen SJ, Dill KA. RNA folding energy landscapes. Proc Natl Acad Sci USA 2000, 97:646-651.
85. Lorenz WA, Clote P. Computing the partition function for kinetically trapped RNA secondary structures. PLoS One 2011, 6:e16178.
86. Tang X, Thomas S, Tapia L, Giedroc DP, Amato NM. Simulating RNA folding kinetics on approximated energy landscapes. J Mol Biol 2008, 381:1055-1067.
87. Xayaphoummine A, Bucher T, Isambert H. Kinefold web server for RNA/DNA folding path and structure prediction including pseudoknots and knots. Nucleic Acids Res 2005, 33:W605-W610.
88. Rivas E, Eddy SR. Secondary structure alone is generally not statistically significant for the detection of noncoding RNAs. Bioinformatics 2000, 16:583-605.
89. Washietl S, Hofacker IL. Consensus folding of aligned sequences as a new measure for the detection of functional RNAs by comparative genomics. J Mol Biol 2004, 342:19-30.
90. Rivas E, Eddy SR. Noncoding RNA gene detection using comparative sequence analysis. BMC Bioinform 2001, 2:8.
91. del Val C, Rivas E, Torres-Quesada O, Toro N, Jimnez-Zurdo JI. Identification of differentially expressed small non-coding RNAs in the legume endosymbiont Sinorhizobium meliloti by comparative genomics. Mol Microbiol 2007, 66:1080-1091.
92. Rivas E, Klein RJ, Jones TA, Eddy SR. Computational identification of noncoding RNAs in E. coli by comparative genomics. Curr Biol 2001, 11:1369-1373.
93. Coventry A, Kleitman DJ, Berger B. MSARI: multiple sequence alignments for statistical detection of RNA secondary structure. Proc Natl Acad Sci U S A 2004, 101:12102-12107.
94. Washietl S, Hofacker IL, Stadler PF. Fast and reliable prediction of noncoding RNAs. Proc Natl Acad Sci U S A 2005, 102:2454-2459.
95. Pedersen JS, Bejerano G, Siepel A, Rosenbloom K, Lindblad-Toh K, Lander ES, Kent J, Miller W, Haussler D. Identification and classification of conserved RNA secondary structures in the human genome. PLoS Comput Biol 2006, 2:e33.
96. Washietl S, Pedersen JS, Korbel JO, Stocsits C, Gruber AR, Hackermller J, Hertel J, Lindemeyer M, Reiche K, Tanzer A, et al. Structured RNAs in the ENCODE selected regions of the human genome. Genome Res 2007, 17:852-864.
97. Mourier T, Carret C, Kyes S, Christodoulou Z, Gardner PP, Jeffares DC, Pinches R, Barrell B, Berriman M, Griffiths-Jones S, et al. Genome-wide discovery and verification of novel structured RNAs in Plasmodium falciparum. Genome Res 2008, 18:281-292.
98. Weinberg Z, Barrick JE, Yao Z, Roth A, Kim JN, Gore J, Wang JX, Lee ER, Block KF, Sudarsan N, et al. Identification of 22 candidate structured RNAs in bacteria using the CMfinder comparative genomics pipeline. Nucleic Acids Res 2007, 35:4809-4819.
99. Yao Z, Weinberg Z, Ruzzo WL. CMfinder-a covariance model based RNA motif finding algorithm. Bioinformatics 2006, 22:445-452.
100. Freyhult EK, Bollback JP, Gardner PP. Exploring genomic dark matter: a critical assessment of the performance of homology search methods on noncoding RNA. Genome Res 2007, 17:117-125.
101. Menzel P, Gorodkin J, Stadler PF. The tedious task of finding homologous noncoding RNA genes. RNA 2009, 15:2075-2082.
102. Gautheret D, Major F, Cedergren R. Pattern searching/ alignment with RNA primary and secondary structures: an effective descriptor for tRNA. Comput Appl Biosci 1990, 6:325-331.
103. Macke TJ, Ecker DJ, Gutell RR, Gautheret D, Case DA, Sampath R. RNAMotif, an RNA secondary structure definition and search algorithm. Nucleic Acids Res 2001, 29:4724-4735.
104. Nawrocki EP, Kolbe DL, Eddy SR. Infernal 1.0: inference of RNA alignments. Bioinformatics 2009, 25:1335-1337.
105. Lowe TM, Eddy SR. tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 1997, 25:955-964.
106. Lagesen K, Hallin P, Rodland EA, Staerfeldt HH, Rognes T, Ussery DW. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res 2007, 35:3100-3108.
107. Lowe TM, Eddy SR. A computational screen for methylation guide snoRNAs in yeast. Science 1999, 283:1168-1171.
108. Schattner P, Decatur WA, Davis CA, Fournier MJ, Lowe TM. Genome-wide searching for pseudouridylation guide snoRNAs: analysis of the Saccharomyces cerevisiae genome. Nucleic Acids Res 2004, 32: 4281-4296.
109. Hertel J, Hofacker IL, Stadler PF. SnoReport: computational identification of snoRNAs with unknown targets. Bioinformatics 2008, 24:158-164.
110. Laslett D, Canback B, Andersson S. BRUCE: a program for the detection of transfer-messenger RNA genes in nucleotide sequences. Nucleic Acids Res 2002, 30:3449-3453.
111. Regalia M, Rosenblad MA, Samuelsson T. Prediction of signal recognition particle RNA genes. Nucleic Acids Res 2002, 30:3368-3377.
112. Cabili MN, Trapnell C, Goff L, Koziol M, Tazon-Vega B, Regev A, Rinn JL. Integrative annotation of human large intergenic noncoding RNAs reveals global properties and specific subclasses. Genes Dev 2011, 25:1915-1927.
113. Findei S, Engelhardt J, Prohaska SJ, Stadler PF. Protein-coding structured RNAs: A computational survey of conserved RNA secondary structures overlapping coding regions in drosophilids. Biochimie 2011, 93:2019-2023.
114. Dinger ME, Pang KC, Mercer TR, Mattick JS. Differentiating protein-coding and noncoding RNA: challenges and ambiguities. PLoS Comput Biol 2008, 4:e1000176.
115. Frith MC, Bailey TL, Kasukawa T, Mignone F, Kummerfeld SK, Madera M, Sunkara S, Furuno M, Bult CJ, Quackenbush J, et al. Discrimination of non-protein-coding transcripts from protein-coding mRNA. RNA Biol 2006, 3:40-48.
116. Lin MF, Jungreis I, Kellis M. PhyloCSF: a comparative genomics method to distinguish protein coding and non-coding regions. Bioinformatics 2011, 27: i275-i282.
117. Washietl S, Findeiss S, Müller SA, Kalkhof S, von Bergen M, Hofacker IL, Stadler PF, Goldman N. RNAcode: robust discrimination of coding and noncoding regions in comparative sequence data. RNA 2011, 17: 578-594.
118. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 2009, 25:1105-1111.
119. Wu TD, Nacu S. Fast and SNP-tolerant detection of complex variants and splicing in short reads. Bioinformatics 2010, 26:873-881.
120. Au KF, Jiang H, Lin L, Xing Y, Wong WH. Detection of splice junctions from paired-end RNA-seq data by SpliceMap. Nucleic Acids Res 2010, 38:4570-4578.
121. Guttman M, Garber M, Levin JZ, Donaghey J, Robinson J, Adiconis X, Fan L, Koziol MJ, Gnirke A, Nusbaum C, et al. Ab initio reconstruction of cell type-specific transcriptomes in mouse reveals the conserved multi-exonic structure of lincRNAs. Nat Biotechnol 2010, 28:503-510.
122. Trapnell C, Williams BA, Pertea G, Mortazavi A, Kwan G, van Baren MJ, Salzberg SL, Wold BJ, Pachter L. Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation. Nat Biotechnol 2010, 28:511-515.
123. Zerbino DR, Birney E. Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 2008, 18:821-829.
124. Robertson G, Schein J, Chiu R, Corbett R, Field M, Jackman SD, Mungall K, Lee S, Okada HM, Qian JQ, et al. De novo assembly and analysis of RNA-seq data. Nat Methods 2010, 7:909-912.
125. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 2008, 5:621-628.
126. Griffith M, Griffith OL, Mwenifumbo J, Goya R, Morrissy AS, Morin RD, Corbett R, Tang MJ, Hou YC, Pugh TJ, et al. Alternative expression analysis by RNA sequencing. Nat Methods 2010, 7:843-847.
127. Wang X, Wu Z, Zhang X. Isoform abundance inference provides a more accurate estimation of gene expression levels in RNA-seq. J Bioinform Comput Biol 2010, 8 (Suppl 1):177-192.
128. Katz Y, Wang ET, Airoldi EM, Burge CB. Analysis and design of RNA sequencing experiments for identifying isoform regulation. Nat Methods 2010, 7:1009-1015.
129. Roberts A, Trapnell C, Donaghey J, Rinn JL, Pachter L. Improving RNA-Seq expression estimates by correcting for fragment bias. Genome Biol 2011, 12:R22.
130. Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol 2010, 11:R106.
131. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26:139-140.
132. Ambros V. The functions of animal microRNAs. Nature 2004, 431:350-355.
133. Bartel D. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004, 116:281-297.
134. Schnall-Levin M, Zhao Y, Perrimon N, Berger B. Conserved microRNA targeting in Drosophila is as widespread in coding regions as in 3′UTRs. Proc Natl Acad Sci U S A 2010, 107:15751-15756.
135. Schnall-Levin M, Rissland OS, Johnston WK, Perrimon N, Bartel DP, Berger B. Unusually effective microRNA targeting within repeat-rich coding regions of mammalian mRNAs. Genome Res 2011, 21:1395-1403.
136. Grishok A, Pasquinelli A, Conte D, Li N, Parrish S, Ha I, Baillie D, Fire A, Ruvkun G, Mello C. Genes and mechanisms related to RNA interference regulate expression of the small temporal RNAs that control C. elegans developmental timing. Cell 2001, 106:23-34.
137. Berezikov E, Cuppen E, Plasterk R. Approaches to microRNA discovery. Nat Genet 2006, 38(Suppl.): S2-S7.
138. Lim L, Lau N, Weinstein E, Abdelhakim A, Yekta S, Rhoades M, Burge C, Bartel D. The microRNAs of Caenorhabditis elegans. Genes Dev 2003, 17:991-1008.
139. Grad Y, Aach J, Hayes G, Reinhart B, Church G, Ruvkun G, Kim J. Computational and experimental identification of C. elegans microRNAs. Mol Cell 2003, 11:1253-1263.
140. Lai E, Tomancak P, Williams R, Rubin G. Computational identification of Drosophila microRNA genes. Genome Biol 2003, 4:R42.
141. Xie X, Lu J, Kulbokas E, Golub T, Mootha V, Lindblad-Toh K, Lander E, Kellis M. Systematic discovery of regulatory motifs in human promoters and 3' UTRs by comparison of several mammals. Nature 2005, 434:338-345.
142. Stark A, Kheradpour P, Parts L, Brennecke J, Hodges E, Hannon G, Kellis M. Systematic discovery and characterization of fly microRNAs using 12 Drosophila genomes. Genome Res 2007, 17:1865-1879.
143. Nam J, Shin K, Han J, Lee Y, Kim V, Zhang B. Human microRNA prediction through a probabilistic co-learning model of sequence and structure. Nucleic Acids Res 2005, 33:3570-3581.
144. Wang X, Zhang J, Li F, Gu J, He T, Zhang X, Li Y. MicroRNA identification based on sequence and structure alignment. Bioinformatics 2005, 21:3610-3614.
145. Bonnet E, Wuyts J, Rouzé P, Van de Peer Y. Evidence that microRNA precursors, unlike other non-coding RNAs, have lower folding free energies than random sequences. Bioinformatics 2004, 20:2911-2917.
146. Washietl S, Hofacker I, Lukasser M, Hüttenhofer A, Stadler P. Mapping of conserved RNA secondary structures predicts thousands of functional noncoding RNAs in the human genome. Nat Biotechnol 2005, 23:1383-1390.
147. Hertel J, Stadler P. Hairpins in a Haystack: recognizing microRNA precursors in comparative genomics data. Bioinformatics 2006, 22:e197-e202.
148. Bentwich I. Prediction and validation of microRNAs and their targets. FEBS Lett 2005, 579:5904-5910.
149. Xue C, Li F, He T, Liu G, Li Y, Zhang X. Classification of real and pseudo microRNA precursors using local structure-sequence features and support vector machine. BMC Bioinform 2005, 6:310.
150. Pfeffer S, Sewer A, Lagos-Quintana M, Sheridan R, Sander C, Grässer F, van Dyk L, Ho C, Shuman S, Chien M, et al. Identification of microRNAs of the herpesvirus family. Nat Methods 2005, 2:269-276.
151. Ohler U, Yekta S, Lim L, Bartel D, Burge C. Patterns of flanking sequence conservation and a characteristic upstream motif for microRNA gene identification. RNA 2004, 10:1309-1322.
152. Seitz H, Royo H, Bortolin M, Lin S, Ferguson-Smith A, Cavaillé J. A large imprinted microRNA gene cluster at the mouse Dlk1-Gtl2 domain. Genome Res 2004, 14:1741-1748.
153. Hendrix D, Levine M, Shi W. miRTRAP, a computational method for the systematic identification of miRNAs from high throughput sequencing data. Genome Biol 2010, 11:R39.
154. Lu C, Tej S, Luo S, Haudenschild C, Meyers B, Green P. Elucidation of the small RNA component of the transcriptome. Science 2005, 309:1567-1569.
155. Ruby J, Jan C, Player C, Axtell M, Lee W, Nusbaum C, Ge H, Bartel D. Large-scale sequencing reveals 21U-RNAs and additional microRNAs and endogenous siRNAs in C. elegans. Cell 2006, 127:1193-1207.
156. Aravin A, Gaidatzis D, Pfeffer S, Lagos-Quintana M, Landgraf P, Iovino N, Morris P, Brownstein M, Kuramochi-Miyagawa S, Nakano T, et al. A novel class of small RNAs bind to MILI protein in mouse testes. Nature 2006, 442:203-207.
157. Shi W, Hendrix D, Levine M, Haley B. A distinct class of small RNAs arises from pre-miRNA-proximal regions in a simple chordate. Nat Struct Mol Biol 2009, 16:183-189.
158. Friedländer M, Mackowiak S, Li N, Chen W, Rajewsky N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 2011.
159. Mathelier A, Carbone A. MIReNA: finding microRNAs with high accuracy and no learning at genome scale and from deep sequencing data. Bioinformatics 2010, 26:2226-2234.
160. Stark A, Brennecke J, Bushati N, Russell R, Cohen S. Animal MicroRNAs confer robustness to gene expression and have a significant impact on 3′UTR evolution. Cell 2005, 123:1133-1146.
161. Bartel D. MicroRNAs: target recognition and regulatory functions. Cell 2009, 136:215-233.
162. Washietl S, Hofacker IL. Nucleic acid sequence and structure databases. Methods Mol Biol 2010, 609:3-15.
163. Galperin MY, Cochrane GR. The 2011 Nucleic Acids Research Database Issue and the online Molecular Biology Database Collection. Nucleic Acids Res 2011, 39:D1-D6.
164. He S, Liu C, Skogerbø G, Zhao H, Wang J, Liu T, Bai B, Zhao Y, Chen R. NONCODE v2.0: decoding the non-coding. Nucleic Acids Res 2008, 36:D170-D172.
165. Pang KC, Stephen S, Engström PG, Tajul-Arifin K, Chen W, Wahlestedt C, Lenhard B, Hayashizaki Y, Mattick JS. RNAdb-a comprehensive mammalian noncoding RNA database. Nucleic Acids Res 2005, 33:D125-D130.
166. Mituyama T, Yamada K, Hattori E, Okida H, Ono Y, Terai G, Yoshizawa A, Komori T, Asai K. The Functional RNA Database 3.0: databases to support mining and annotation of functional RNAs. Nucleic Acids Res 2009, 37:D89-D92.
167. Amaral PP, Clark MB, Gascoigne DK, Dinger ME, Mattick JS. lncRNAdb: a reference database for long noncoding RNAs. Nucleic Acids Res 2011, 39:D146-D151.
168. Gardner PP, Daub J, Tate J, Moore BL, Osuch IH, Griffiths-Jones S, Finn RD, Nawrocki EP, Kolbe DL, Eddy SR, et al. Rfam: Wikipedia, clans and the "decimal" release. Nucleic Acids Res 2011, 39: D141-D145.
169. Kozomara A, Griffiths-Jones S. miRBase: integrating microRNA annotation and deep-sequencing data. Nucleic Acids Res 2011, 39:D152-D157.
170. Sethupathy P, Corda B, Hatzigeorgiou A. TarBase: a comprehensive database of experimentally supported animal microRNA targets. RNA 2006, 12:192-197.
171. Jiang Q, Wang Y, Hao Y, Juan L, Teng M, Zhang X, Li M, Wang G, Liu Y. miR2Disease: a manually curated database for microRNA deregulation in human disease. Nucleic Acids Res 2009, 37:D98-D104.
172. Bateman A, Agrawal S, Birney E, Bruford EA, Bujnicki JM, Cochrane G, Cole JR, Dinger ME, Enright AJ, Gardner PP, et al. RNAcentral: a vision for an international database of RNA sequences. RNA 2011, 17: 1941-1946.