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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 7, Issue:5, May, 2018

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com /
submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(5): 1275-1284
DOI: https://doi.org/10.20546/ijcmas.2018.705.154


In Silico Identification and Target Prediction of microRNAs in Sesame (Sesamum indicum L.) Expressed Sequence Tags
Halak Joshi* and M.K. Mandavia
Department of Biotechnology, Junagadh Agricultural University, Junagadh-362001, India
*Corresponding author
Abstract:

Sesame (Sesamum indicum L.), a member of the Pedaliaceae family, is one of the oldest oilseed crops. For its high oil content, it is known as the “queen of oilseeds”. MicroRNAs (miRNAs) represent a class of endogenous non-coding small RNAs that play important roles in multiple biological processes by degrading targeted mRNAs or repressing mRNA translation. Thousands of miRNAs have been identified in many plant species by computational methods, whereas there is no report of miRNAs in S. indicum till date. In present study, previously known plant miRNAs were BLASTed against the Expressed Sequence Tag (EST) database of sesame genes. The aligned miRNA hits were further aligned to protein database and BLASTX was carried out to remove protein coding primary miRNAs. The non-coding precursor miRNAs were subjected to online MF old server in order to predict their secondary structures. After applying the filtering criteria, a total of 12 potential miRNAs belonging to 6miRNAs families were detected. 203 unique miRNA: target pairs were predicted online by psRNA Target web server. Most of the targets were found to encode transcription factors or enzymes that participate in the regulation of development, growth, metabolism, and other physiological processes and stress response.


Keywords: Sesame, MicroRNA (miRNA), Expressed Sequence Tag (EST), Stem-loop secondary structure, M fold, Minimum Folding Free Energy (MFE), psRNA target

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How to cite this article:

Halak Joshi and Mandavia, M.K. 2018. In Silico Identification and Target Prediction of microRNAs in Sesame (Sesamum indicum L.) Expressed Sequence Tags.Int.J.Curr.Microbiol.App.Sci. 7(5): 1275-1284. doi: https://doi.org/10.20546/ijcmas.2018.705.154
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

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