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Expressed sequence tags (ESTs)?based computational identification of novel and conserved microRNAs in turmeric (Curcuma longa L.)

Shekhar Rai, Peeyush, Chaudhary, Saurabh and Chand Sharma, Prakash 2018. Expressed sequence tags (ESTs)?based computational identification of novel and conserved microRNAs in turmeric (Curcuma longa L.). Journal of Applied Biotechnology & Bioengineering 5 (2) , pp. 112-119. 10.15406/jabb.2018.05.00125

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MicroRNAs (miRNAs) are endogenous, small, single stranded non‒coding 17‒24 nucleotide long RNAs that regulates gene expression in plants and animals either by direct degradation of mRNA or inhibition of translation. Conventional approaches employed for the detection of miRNA are costly and time consuming. On the other hand, comparative genomics assisted with modern tools of bioinformatics provide an efficient and cost‒effective identification of novel and conserved miRNAs via homology search within known miRNAs. The present study reports computational identification of miRNAs present in the Expressed Sequence Tags (ESTs) of turmeric (Curcuma longa L.), a plant known for its great medicinal and culinary value. A total of 12678 ESTs were assembled into 2710 contigs/unigenes and homology sequence search was performed against 4647 non‒redundant miRNAs of Viridiplantae. In total, 102 potential mature miRNAs showed homology with 51 contigs/unigenes. Subsequently, four novel miRNAs were identified in turmeric, which satisfied the potential miRNA criteria. These four miRNAs were further characterized for target gene prediction identifying 10 target genes with their putative functions. Our study provides a valuable resource on miRNAs in turmeric, and also suggests a methodology useful for the identification of novel and conserved miRNA in non‒model but important organisms, whose EST and genome sequence data are available in the public domain. Keywords: turmeric;, Curcuma longa, microRNA, expressed sequence tags

Item Type: Article
Date Type: Published Online
Status: Published
Schools: Biosciences
Additional Information: Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
ISSN: 2572-8466
Date of First Compliant Deposit: 23 November 2020
Date of Acceptance: 22 February 2018
Last Modified: 24 Nov 2020 15:30

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