Large-scale information entropy analysis of important sites in mature and precursor miRNA sequences

Science in China, Series C: Life Sciences

Volumn 52, Issue 8, 2009, Pages 771-779

  Du, Jiang Feng ^a   Wu, Yong Jun ^a   Zhang, Yin Xia ^a   Wu, Lei ^a   Wang, Xiao Long ^a   Tao, Shi Heng ^a  

^a NORTHWEST A F UNIVERSITY   (China)

Author keywords

Base correlation degree; Conservative; Evolution; Information entropy; miRNA; Precursor

Indexed keywords

MICRORNA; PLANT RNA; RNA PRECURSOR; VIRUS RNA;

ANIMAL; ARTICLE; CHEMISTRY; COMPUTER SIMULATION; ENTROPY; GENETICS; NUCLEOTIDE SEQUENCE;

ANIMALS; BASE SEQUENCE; COMPUTER SIMULATION; CONSERVED SEQUENCE; ENTROPY; MICRORNAS; RNA PRECURSORS; RNA, PLANT; RNA, VIRAL;

ANIMALIA;

EID: 70350783949     PISSN: 10069305     EISSN: 18622798     Source Type: Journal    
DOI: 10.1007/s11427-009-0099-z     Document Type: Article

References (31)

1. Lee R C, Feinbaum R L, Ambros V. The C. elegans heterochronic gene lin-4 encodes small RNAs with antisense complementarity to lin-14. Cell, 1993, 75: 843-854.
2. Bartel D P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell, 2004, 116: 281-297.
3. Lagos-Quintana M, Rauhut R, Lendeckel W, et al. Identification of novel genes coding for small expressed RNAs. Science, 2001, 294: 853-858.
4. Lau N C, Lim L P, Weinstein E G, et al. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science, 2001, 294: 858-862.
5. Cullen B R. Transcription and processing of human microRNA precursors. Mol Cell, 2004, 16: 861-865.
6. Kong Y, Han J H. MicroRNA: biological and computational perspective. Genomics Proteomics Bioinformatics, 2005, 3: 62-72.
7. Pasquinelli A E, Ruvkun G. Control of developmental timing by micrornas and their targets. Annu Rev Cell Dev Biol, 2002, 18: 495-513.
8. Seggerson K, Tang L, Moss E G. Two genetic circuits repress the Caenorhabditis elegans heterochronic gene lin-28 after translation initiation. Dev Biol, 2002, 243: 215-225.
9. Ambros V. microRNAs: tiny regulators with great potential. Cell, 2001, 107: 823-826.
10. Palatnik J F, Allen E, Wu X, et al. Control of leaf morphogenesis by microRNAs. Nature, 2003, 425: 257-263.
11. Adai A, Johnson C, Mlotshwa S, et al. Computational prediction of miRNAs in Arabidopsis thaliana. Genome Res, 2005, 15: 78-91.
12. Wang X J, Reyes J L, Chua N H, et al. Prediction and identification of Arabidopsis thaliana microRNAs and their mRNA targets. Genome Biol, 2004, 5: R65.
13. Kawahara Y, Zinshteyn B, Chendrimada T P, et al. RNA editing of the microRNA-151 precursor blocks cleavage by the Dicer-TRBP complex. EMBO Rep, 2007, 8: 763-769.
14. Lund E, Guttinger S, Calado A, et al. Nuclear export of microRNA precursors. Science, 2004, 303: 95-98.
15. Le S V, Chen J H, Currey K M, et al. A program for predicting significant RNA secondary structures. Comput Appl Biosci, 1988, 4: 153-159.
16. Le S Y, Chen J H, Maizel J V. Thermodynamic stability and statistical significance of potential stem-loop structures situated at the frameshift sites of retroviruses. Nucleic Acids Res, 1989, 17: 6143-6152.
17. Chen J H, Le S Y, Shapiro B, et al. A computational procedure for assessing the significance of RNA secondary structure. Comput Appl Biosci, 1990, 6: 7-18.
18. Seffens W, Digby D. mRNAs have greater negative folding free energies than shuffled or codon choice randomized sequences. Nucleic Acids Res, 1999, 27: 1578-1584.
19. Bonnet E, Wuyts J, Rouze P, et al. Evidence that microRNA precursors, unlike other non-coding RNAs, have lower folding free energies than random sequences. Bioinformatics, 2004, 20: 2911-2917.
20. Zhang B H, Pan X P, Cox S B, et al. Evidence that miRNAs are different from other RNAs. Cell Mol Life Sci, 2006, 63: 246-254.
21. Cai X, Hagedorn C H, Cullen B R. Human microRNAs are processed from capped, polyadenylated transcripts that can also function as mRNAs. RNA, 2004, 10: 1957-1966.
22. Ambros V, Bartel B, Bartel D P, et al. A uniform system for microRNA annotation. RNA, 2003, 9: 277-279.
23. Griffiths-Jones S. The microRNA Registry. Nucleic Acids Res, 2004, 32(Database issue): D109-111.
24. Griffiths-Jones S, Grocock R J, van Dongen S, et al. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res, 2006, 34(Database issue): D140-144.
25. Kozak M. An analysis of 5′-noncoding sequences from 699 vertebrate messenger RNAs. Nucleic Acids Res, 1987, 15: 8125-8148.
26. Lu J, Li H, Ma K J. An information entropy analysis of conservative sites of E.coli, yeast and drosophila genes. Acta Biophysica Sinica, 2002, 18: 71-75.
27. Domingo E, Holland J J. Mutation rates and rapid evolution of RNA virus. New York: Raven Press. 1994. 161-184.
28. Domingo E, Escarmis C, Sevilla N, et al. Basic concepts in RNA virus evolution. FASEB J, 1996, 10: 859-864.
29. Omoto S, Fujii Y R. Regulation of human immunodeficiency virus 1 transcription by nef microRNA. J Gen Virol, 2005, 86(Pt 3): 751-755.
30. Sullivan C S, Grundhoff A T, Tevethia S, et al. SV40-encoded microRNAs regulate viral gene expression and reduce susceptibility to cytotoxic T cells. Nature, 2005, 435: 682-686.
31. Sullivan C S, Ganem D. MicroRNAs and viral infection. Mol Cell, 2005, 20: 3-7.