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Title

Computational prediction of submergence responsive microRNA and their binding position within the genome of Oryza sativa

 

Authors

Prosenjit Paul & Supriyo Chakraborty*

 

Affiliation

Department of Biotechnology, Assam University, Silchar-788011, Assam, India

 

Email

supriyoch_2008@rediffmail.com; *Corresponding author

 

Article Type

Hypothesis

 

Date

Received August 29, 2013; Accepted August 31, 2013; Published October 16, 2013

 

Abstract

Background: MicroRNAs (miRNAs) are small noncoding RNAs which play crucial role in response to the adverse biotic and abiotic stress conditions at the post transcriptional level. The functions of the miRNAs are generally based on complementarity to their target region. Results: We used the online tool psRNA Target for the identification of submergence responsive miRNA using the gene expression profile related to the submergence condition. We wrote a perl script for the prediction of miRNA target gene. The position based feature of the script increases the overall specificity of the program. Our perl script performed well on the genomic data of Oryza sativa and produced significant results with their positions. These results were analyzed on the basis of complementarity and the statistical scores are used to find out the most probable binding regions. These predicted binding regions are aligned with their respective miRNAs to find out the consensus sequence. We scored the alignment using a position dependent, mismatch penalty system. We also identified the rate of conservation of bases at a particular position for all the predicted binding regions and it was found that all the predicted binding regions maintain above 70% rate of conservation of bases. Conclusion: Our approach provides a novel framework for screening the genome of Oryza sativa. It can be broadly applied to identify complementarity specific miRNA targets computationally by doing a little modification of the script depending on the type of the miRNA.

 

Citation

Paul & Chakraborty,   Bioinformation 9(17): 858-863 (2013)

 

Edited by

P Kangueane

 

ISSN

0973-2063

 

Publisher

Biomedical Informatics

 

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.