Abstract—Plant microRNAs (miRNAs) are small non-coding RNAs, about 21-24 nucleotides, which have important regulatory roles in growth, development, metabolic and defense processes. These critical elements regulate pathways either by inducing translational repression or messenger RNA (mRNA) decay. With the advent of the next-generation sequencing technologies and newly developed bioinformatics tools, the identification of microRNA studies by computational methods have been increased. Thus, the sequencing information provides us information for mining some known and unknown miRNAs in plants. In this study, we predict 34 putative miRNAs from Spinacia oleracea genome and two putative miRNA families from spinach transcriptome by using homology-based conservation method. RepeatMasker program is utilized to mask and eliminate five miRNA families out of 34 putative miRNA families from spinach genome. Finally, we analyze the targets of putatively identified miRNAs and their representation of genes (the copy number of each miRNA) throughout the genome.

Index Terms—In silico prediction, microRNA, miRNA, spinach, Spinacia oleracea.

The authors are with Sabanci University, Faculty of Engineering and Natural Sciences, Istanbul, Turkey (email: bihteravsar@sabanciuniv.edu).

Cite: Bihter Avsar, Danial Esmaeili Aliabadi, "In silico Analysis of MicroRNAs in Spinacia oleracea Genome and Transcriptome," International Journal of Bioscience, Biochemistry and Bioinformatics vol. 7, no. 2, pp. 84-92, 2017.