In silico identification of MicroRNAs in 13 medicinal plants
Avşar, Bihter and Esmaeilialiabadi, Danial (2017) In silico identification of MicroRNAs in 13 medicinal plants. In: 28th National Biochemistry Congress, Erzurum, Turkey
Official URL: http://dx.doi.org/10.1515/tjb-2017-s108
OBJECTIVES: MicroRNAs are endogenous, non-coding small RNAs and they play important roles in plant regulatory pathways, development, stress tolerance and growth. With the advent of next-generation sequencing technologies, the microRNA identification studies by computational methods have been increased and have become effective. In this study, we predicted microRNA repertoires from 13 medicinal plants by using their transcriptome atlas. MATERIALS -METHODS: The transcriptome sequences of 13 medicinal plants were retrieved and the miRNA identification was conducted based on homology conservation method. Phylogenetic tree was constructed to show the level of similarity /dissimilarity between 13 medicinal plants (Atropa belladonna, Camptotheca acuminate, Cannabis sativa, Digitalis purpurea, Dioscorea villosa, Echinacea purpurea, Ginkgo biloba, Hoodia gordonii, Hypericum perforatum , Panax quinquefolius , Rauvolfia serpentina, Rosmarinus officinalis , Valeriana officinalis ) by Minitab statistical software. The transcriptome of Arabidopsis thaliana organism was used as a model organism. Target annotations of predicted putative microRNAs were performed by psRNA target and Blast2Go software. RESULTS: As a total number, 168 putative miRNAs were identified. The highest number of microRNAs were found in Camptotheca acuminate (28 miRNA families) transcriptome whereas Atropa belladonna had the lowest amount of putative miRNAs (three miRNA families) in its transcriptome. Digitalis purpurea and Rosmarinus officinalis showed the highest similarities. Targets of putative miRNAs in biological processes and molecular functions revealed us different profiles in different organisms. CONCLUSIONS: Since medicinal plants have some important therapeutic properties, these findings might help to elucidate metabolic and regulatory pathways in medicinal plants to use them efficiently in biotechnological and pharmacological applications.
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