Modified S-transform as a tool to identify secondary structure elements in RNA

• Autorzy: Singh N. , Sharma S. D. , Yennamalli R. M.

Identyfikatory

DOI

10.1515/bams-2017-0023

• Języki publikacji: EN

Abstrakty

EN

In this article, we describe the applicability of a signal processing method, specifically the modified S-transform (MST) method, on RNA sequences to identify periodicities between 2 and 11. MicroRNAs (miRNA) are associated with gene regulation and gene silencing and thus have wide applications in biological sciences. Also, the functionality of miRNA is highly associated with its secondary structures (stem, bulge and loop). Signal processing methods have been previously applied on genomic data to reveal the periodicities that determine a wide variety of biological functions, ranging from exon detection to microsatellite identification in DNA sequences. However, there has been less focus on RNA-based signal processing. Here, we show that the signal processing method can be successfully applied to miRNA sequences. We observed that these periodicities are highly correlated with the secondary structure of miRNA and such methods could possibly be used as indicators of secondary and tertiary structure formation.

Słowa kluczowe

EN

microRNA; miRNA; modified S-transform; RNA sequences; secondary structure elements

• Wydawca: Uniwersytet Jagielloński - Collegium Medicum ; De Gruyter
• Czasopismo: Bio-Algorithms and Med-Systems
• Rocznik: 2017
• Tom: Vol. 13, no. 4
• Strony: 182--193
• Opis fizyczny: Bibliogr. 18 poz., rys., tab.

Twórcy

autor

Singh N.

• Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Himachal Pradesh 173234, India

autor

Sharma S. D.

• Department of Electronics and Communication Engineering, Jaypee University of Information Technology, Waknaghat, Himachal Pradesh 173234, India

autor

Yennamalli R. M.

• Department of Biotechnology and Bioinformatics, Jaypee University of Information Technology, Waknaghat, Himachal Pradesh 173234, India

Bibliografia

• 1. Moura J. What is signal processing? [President’s message]. IEEE Signal Process Mag 2009;26:6.
• 2. Damasevicius R. Complexity estimation of genetic sequences using information-theoretic and frequency analysis methods. Informatica 2010;21:13–30.
• 3. Liu B, Fang L, Liu F, Wang X, Chen J, Chou KC. Identification of real microRNA precursors with a pseudo structure status composition approach. PLoS One 2015;10:e0121501.
• 4. Liu B, Childs-Disney JL, Znosko BM, Wang D, Fallahi M, Gallo SM, et al. Analysis of secondary structural elements in human microRNA hairpin precursors. BMC Bioinform 2016;17:112.
• 5. Ardenkani AM, Naeini MM. The role of microRNAs in human diseases’. Avicenna J Med Biotechnol 2010;2:161–79.
• 6. Yoon BJ, Vaidyanathan RP. Computational identification and analysis of noncoding RNAs – unearthing the buried treasures in the genome. IEEE Signal Process Mag 2007;24:64–74.
• 7. Svoboda P, Cara AD. Hairpin RNA: a secondary structure of primary importance. Cell Mol Life Sci 2006;63:901–8.
• 8. RNA structure (molecular biology). Available at: http://whatwhen-how.com/molecular-biology/rna-structure-molecularbiology/. Accessed: 18 Jun 2017.
• 9. Moss WN. Computational prediction of RNA secondary structure. In: Lorsch J, editor. Methods in Enzymology: RNA. San Diego, USA: Elsevier, 2013:3–65.
• 10. Stockwell RG, Mansinha L, Lowe RP. Localization of the complex spectrum: the S transform. IEEE Trans Signal Process 1996;44:998–1001.
• 11. Borkar PS, Mahajan AR. Different RNA secondary structure prediction methods. In: Electronic Systems, Signal Processing and Computing Technologies (ICESC), 2014 International Conference, 9 Jan 2014. Nagpur, India: IEEE, 2014:228–30.
• 12. Sharma SD, Saxena R, Sharma SN. Short tandem repeats detection in DNA sequences using modified S-transform. Int J Adv Eng Technol 2015;8:233–45.
• 13. Kozomara A, Griffiths-Jones S. miRBase: annotating high confidence microRNAs using deep sequencing data. Nucl Acids Res 2013;42:D68–73.
• 14. The Mfold web server. Available at: http://unafold.rna.albany. edu/?q=mfold. Accessed: 18 Jun 2017.
• 15. Zuker M. Mfold web server for nucleic acid folding and hybridization prediction. Nucl Acids Res 2003;31:3406–15.
• 16. Trifonov EN, Sussman JL. The pitch of chromatin DNA is reflected in its nucleotide sequence. Proc Natl Acad Sci USA 1980;77:3816–20.
• 17. Mrazek J. Comparative analysis of sequence periodicity among prokaryotic genomes points to differences in nucleoid structure and a relationship to gene expression. J Bacteriol 2010;192:3763–72.
• 18. Li Z, Rana TM. Therapeutic targeting of microRNAs: current status and future challenges. Nat Rev Drug Discov 2014;13:622–38.