Characteristic comparison between two types of miRNA precursors in metazoan species

BioSystems

Volumn 100, Issue 2, 2010, Pages 144-149

  Zhang, Xiaobai ^a   Song, Xiaofeng ^a   Wang, Huinan ^a  

^a NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

Author keywords

MiRNA precursors; Statistical analysis; Structure characteristics

Indexed keywords

MESSENGER RNA; MICRORNA; MICRORNA PRECURSOR; RIBOSOME RNA; RNA PRECURSOR; TRANSFER RNA; UNCLASSIFIED DRUG;

GENE EXPRESSION; METAZOAN; RNA; STATISTICAL ANALYSIS;

AMINO ACID SEQUENCE; ARTICLE; CLASSIFICATION; GENETIC DIFFERENCE; GENOME; METAZOON; NONHUMAN; PREDICTION; PROTEIN ANALYSIS; PROTEIN FUNCTION; PROTEIN SECONDARY STRUCTURE; REGULATORY MECHANISM; RNA HAIRPIN; RNA SEQUENCE; RNA STRUCTURE; VALIDATION PROCESS;

METAZOA;

EID: 77952959311     PISSN: 03032647     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.biosystems.2010.02.009     Document Type: Article

References (31)

1. Ambros V. MicroRNA pathways in flies and worms: growth, death, fat, stress, and timing. Cell 2003, 113:673-676.
2. 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., Matzke M., Ruvkun G., Tuschl T. A uniform system for microRNA annotation. RNA 2003, 9:277-279.
3. Bartel D.P. MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004, 116:281-297.
4. 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.
5. Carrington J.C., Ambros V. Role of microRNAs in plant and animal development. Science 2003, 301:336-338.
6. Chan P.P., Lowe T.M. GtRNAdb: a database of transfer RNA genes detected in genomic sequence. Nucleic Acids Res. 2009, 37:D93-97.
7. Du T., Zamore P.D. microPrimer: the biogenesis and function of microRNA. Development 2005, 132:4645-4652.
8. Gregory R.I., Shiekhattar R. MicroRNA biogenesis and cancer. Cancer Res. 2005, 65:3509-3512.
9. Griffiths-Jones S. The microRNA registry. Nucleic Acids Res. 2004, 32:D109-111.
10. Griffiths-Jones S., Grocock R.J., van Dongen S., Bateman A., Enright A.J. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 2006, 34:D140-144.
11. Griffiths-Jones S., Saini H.K., van Dongen S., Enright A.J. miRBase: tools for microRNA genomics. Nucleic Acids Res. 2008, 36:D154-158.
12. Hofacker I., Fontana W., Stadler P., Bonhoeffer L., Tacker M., Schuster P. Fast folding and comparison of RNA secondary structures. Chem. Mon. 1994, 125:167-188.
13. Kusenda B., Mraz M., Mayer J., Pospisilova S. MicroRNA biogenesis, functionality and cancer relevance. Biomed. Pap. Med. Fac. Univ. Palacky Olomouc. Czech. Repub. 2006, 150:205-215.
14. Lagos-Quintana M., Rauhut R., Lendeckel W., Tuschl T. Identification of novel genes coding for small expressed RNAs. Science 2001, 294:853-858.
15. Lau N.C., Lim L.P., Weinstein E.G., Bartel D.P. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science 2001, 294:858-862.
16. Lee R.C., Ambros V. An extensive class of small RNAs in Caenorhabditis elegans. Science 2001, 294:862-864.
17. 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.
18. Lim L.P., Glasner M.E., Yekta S., Burge C.B., Bartel D.P. Vertebrate microRNA genes. Science 2003, 299:1540.
19. Lim L.P., Lau N.C., Weinstein E.G., Abdelhakim A., Yekta S., Rhoades M.W., Burge C.B., Bartel D.P. The microRNAs of Caenorhabditis elegans. Genes Dev. 2003, 17:991-1008.
20. Lindow M., Gorodkin J. Principles and limitations of computational microRNA gene and target finding. DNA Cell Biol. 2007, 26:339-351.
21. Mathews D.H., Sabina J., Zuker M., Turner D.H. Expanded sequence dependence of thermodynamic parameters improves prediction of RNA secondary structure. J. Mol. Biol. 1999, 288:911-940.
22. Ng Kwang Loong S., Mishra S.K. Unique folding of precursor microRNAs: quantitative evidence and implications for de novo identification. RNA 2007, 13:170-187.
23. Qiu C., Xie F., Zhu Y., Guo K., Huang S., Nie L., Yang Z. Computational identification of microRNAs and their targets in Gossypium hirsutum expressed sequence tags. Gene 2007, 395:49-61.
24. Seffens W., Digby D. mRNAs have greater negative folding free energies than shuffled or codon choice randomized sequences. Nucl. Acids Res. 1999, 27:1578.
25. Wightman B., Ha I., Ruvkun G. Posttranscriptional regulation of the heterochronic gene lin-14 by lin-4 mediates temporal pattern formation in C. elegans. Cell 1993, 75:855-862.
26. Xie F., Huang S., Guo K., Xiang A., Zhu Y., Nie L., Yang Z. Computational identification of novel microRNAs and targets in Brassica napus. FEBS Lett. 2007, 581:1464-1474.
27. Zeng Y., Cullen B. Structural requirements for pre-microRNA binding and nuclear export by Exportin 5. Nucleic Acids Res. 2004, 32:4776.
28. Zhang B., Pan X., Cobb G.P., Anderson T.A. microRNAs as oncogenes and tumor suppressors. Dev. Biol. 2007, 302:1-12.
29. Zhang B., Pan X., Cox S., Cobb G., Anderson T. Evidence that miRNAs are different from other RNAs. Cell. Mol. Life Sci. 2006, 63:246-254.
30. Zhang B., Pan X., Wang Q., Cobb G., Anderson T. Computational identification of microRNAs and their targets. Comput. Biol. Chem. 2006, 30:395-407.
31. Zuker M., Stiegler P. Optimal computer folding of large RNA sequences using thermodynamics and auxiliary information. Nucleic Acids Res. 1981, 9:133.