COMPUTATIONAL PREDICTION OF microRNAs AND THEIR TARGET GENES IN RAINBOW TROUT (ONCORHYNCHUS MYKISS)
© 2016 Yong Huang#, Xiao Chan Gao, Hong Tao Ren, and Chun Nuan Zhang
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College of Animal Science and Technology, Henan University of Science and Technology, Luoyang, China
Received October 01, 2015; in final form, October 26, 2015
MicroRNAs (miRNA) are non-coding small RNA molecules consisting of 20–24 nucleotides (nt), which regulate gene expression negatively at the post-transcriptional levels depending on the extent of complementation between miRNA and mRNA in a variety of eukaryotic organisms. They have attracted increasing attention recently. To date, a total of 1637 mature miRNAs from fishes have been deposited in the miRBase database (Release 21) and they are just a small portion of the miRNAs described in fish species. Especially in rainbow trout (Oncorhynchus mykiss) miRNAs, it is far from the numbers of miRNAs found in other fishes and many more miRNA remain to be discovered. In present study, we used known animal miRNAs to systematically search miRNA homologs in available expressed sequence tags (EST), genomic survey sequences (GSS), and transcript sequence assemblies (TSA) of O. mykiss based on the conservation of miRNA sequences. Following the filtering with a combination of stringent criteria, 39 miRNAs belonging to 25 independent families were identified, of which 14 are novel identified miRNAs firstly in O. mykiss. The randomly selected 13 miRNAs were verified by stem-loop RT-PCR indicating that the prediction method that we used to identify the miRNAs was effective. Furthermore, total of 94 target genes were predicted and their probable functions were illustrated. Their target genes are involved in transcription factors, development, metabolism, signaling, immunity, and cell division. The current study has provided an update on O. mykiss miRNAs and their targets, which will be helpful for future research on miRNA-mediated gene regulation in this important fish species.
Keywords: microRNA, Oncorhynchus mykiss, computational prediction, target gene.
Биоорг. химия 2016, 42 (3): 315-326