In Silico MicroRNA Identification from Stevia rebaudiana Transcriptome Assembly

Aditya Mehta *

Xcelris Labs Ltd., Ahmedabad, Gujarat, India and Department of Bioinformatics, Gujarat University, Ahmedabad, India

Hemant Gupta

Eurofins Genomics India Pvt. Ltd, India

Rakesh Rawal

Medicinal Chemistry, Gujarat Cancer and Research Institute, Ahmedabad, Gujarat, India

Archana Mankad

Department of Bioinformatics, Gujarat University, Ahmedabad, India

Tanushree Tiwari

Xcelris Labs Ltd., Ahmedabad, Gujarat, India

Maulik Patel

Xcelris Labs Ltd., Ahmedabad, Gujarat, India

Arpita Ghosh

Xcelris Labs Ltd., Ahmedabad, Gujarat, India

*Author to whom correspondence should be addressed.


Abstract

MicroRNAs are a class of endogenous, approximately 22 nucleotides in length noncoding RNA, which is evolutionary conserved and mediates post-transcriptional gene regulation. MicroRNA play a crucial role in development of plant, cellular processes, biological processes, cell proliferation and stress response. Stevia rebaudiana is an economically important and medicinal plant of the Asteraceae family. A total of 1,418,58 unigenes from Stevia transcriptome data were used for homology search against known plant miRNA database miRBase version 21. The functionally annotated unigenes were excluded from the studies. Total 381 non-protein coding unigenes were considered for candidates of miRNA precursor in Stevia. One potential miRNA from miR168 family with secondary structure was identified through the sequel of stringent filtering criteria. The target prediction of novel miRNA was carried out for using psRNATarget program based on their sequence complementarities. A total of 31 potential gene targets were predicted for identified novel miRNA, which playing crucial role in various biological processes like development of plant, DNA repair, splicing, post-translational gene silencing, plant defense response, cell growth and proliferation. The phylogenetic analysis was also carried out to study the conserved nature of miRNA. These findings provide significant insights of miRNA and their potential role in Stevia as well as their regulatory mechanisms.

Keywords: miRNA, circos plot, psRNATarget, MFEI, MFE, EST, Stevia rebaudiana, small RNA


How to Cite

Mehta, Aditya, Hemant Gupta, Rakesh Rawal, Archana Mankad, Tanushree Tiwari, Maulik Patel, and Arpita Ghosh. 2016. “In Silico MicroRNA Identification from Stevia Rebaudiana Transcriptome Assembly”. European Journal of Medicinal Plants 15 (2):1-14. https://doi.org/10.9734/EJMP/2016/25221.

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