In silico identification of miRNAs and their target prediction from Japanese encephalitis

MicroRNA is a family of small non-coding RNAs that regulate gene expression in a sequence-specific manner. miRNAs are a class of post-transcriptional regulators. miRNAs are a family of 19 to 25 small nucleotide RNAs. Since miRNAs have been discovered and their role in gene regulation established, it has been theorized that viruses could generate miRNAs as well and that these viral encoded miRNAs could regulate cellular mechanisms and viral replication. There are several lines of evidence to support this theory. Japanese encephalitis is a viral disease (Flavivirus) but its geographic strains differ by RNA sequencing neurotropic virus that primarily affects the central nervous system. That is why this work mainly focuses on finding out its function. An oligonucleotide drug candidate can be designed against this virus. Computational prediction is analyzed and estimation of evolutionary relationship among types of organism is done in this project. 25 precursors and eight potential miRNAs were found, and these miRNAs target 123 target sites in 13 genes in human.


INTRODUCTION
Mature microRNAs (miRNAs) are a class of naturally occurring small non-coding RNA molecules; about 21 to 25 nucleotides in length. MicroRNAs are partially complementary to one or more messenger RNA (mRNA) molecules, and their main function is to down-regulate gene expression in a variety of manners, including translational repression, mRNA cleavage and deadenylation. They were first described by Lee Y et al., 2003Lee Y et al., , 2004 and the term microRNA was coined in 2001. The genes encoding miRNAs are much longer than the processed mature miRNA molecule (Carthew et al., 2009). Based on the biogenesis of miRNA, many miRNAs are known to reside in introns of their pre-mRNA host genes and share their regulatory elements, primary transcript and have a similar expression profile (Chen, 2005). *Corresponding author. E-mail: vijaykanpur@rediffmail.com or alkabioinfo964@gmail.com. Tel: 915122530657. Fax: 0512-2530657. MicroRNAs are transcribed by RNA polymerase II as large RNA precursors called pri-miRNAs and comprise a 5' cap and poly-A tail (Erlanger et al., 2009). The pri-miRNAs are processed in the nucleus by the microprocessor complex, consisting of the RNase III enzyme Drosha and the double-stranded-RNA-binding protein, Pasha/DGCR8. The resulting pre-miRNAs are approximately 70-nucleotides in length and are folded into imperfect stem-loop structures (Hammond, 2000). The pre-miRNAs are then exported into the cytoplasm by the karyopherin exportin 5 (Exp5) and Ran-GTP complex Ran (ras-related nuclear protein), a small GTP binding protein belonging to the RNA superfamily that is essential for the translocation of RNA and proteins through the nuclear pore complex (Krek et al., 2005). The Ran GTPase binds Exp5 and forms a nuclear heterotrimer with pre-miRNAs; once in the cytoplasm, the pre-miRNAs undergo an additional processing step by the RNAse III enzyme dicer generating the miRNA, a double-stranded RNA approximately 22 nucleotides in length. Also, Japanese encephalitis virus (JEV), a neurotropic mosquito-borne flavivirus mainly prevalent in Asia, is the most important causative agent of acute viral encephalitis in humans. JEV is also one of the main causes of infectious reproductive failure in swine, (Murkami et al.,2005), resulting in significant economic losses in the pig industry; this virus has a normal zootomic transmission cycle between swine or birds and mosquitoes. Swine are the main amplifier hosts, from which infected mosquitoes transmit the virus to human (Figure 1).

METHODOLOGY
The genome sequences of J. encephalitis were retrieved from NCBI (www.ncbi.nlm.nihgov).Precursor predicting tools, Mireval (http://tagc.univ mrs.fr/mireval) and MiRPARA (http://www.whiov.ac.cn/bioinformatics/mirpara) were used to find out the precursor sequences; and then the secondary structure with optimal minimum free energy was found out with the help of different types of web servers such as Mfold web server (http://mfold.rit.albany.edu/doc/mfold-manual/), RNA fold web server (http://rna.tbi.univie.ac.at) and DINA melt web server (http://www.microrna.gr/microT). For validating the energy values, miRBASE (mirbase@manchester.ac.uk) was checked, where we browsed all the mature virus sequences and stem loop structure sequences in FASTA format. These sequences were already experimentally identified. Then we find out the optimal minimum energy value of viruses in the miRBASE (only precursors), based on multiple sequence alignment, and then find out the conserved regions for miRNA. This miRNA predicted the target sites, and the target prediction was completed with the help of DIANA tar web server (http://www.microrna.gr); it predicted the different types of target sites.

Precursor analysis
miRNA was the first to be discovered, a class of noncoding RNAs involved in gene regulation, transcribed as ~70 nucleotide precursors and subsequently processed by the dicer enzyme to give a 21 nucleotide product (Moore,1993). The extents of the hairpin precursors are not generally known and are estimated based on hairpin prediction (Ruykum, 1993;Siolas et al., 2005;Sui et al., 2002). This study is exclusively based on in silico firstly to find out the precursors from Japanese encephalitis having 1 to 25 precursors in a single whole genome (NC_001437.1); and then this sequence is submitted in miRevaluator and mirPARA software for precursor prediction (Table 1).

Potential miRNA analysis
Prediction of potential miRNA was based on (MSA) multiple sequence alignment (pair wise) and its alignment was completed with the help of EBI clastal-W and mirpara miRNA predicting software. The sequence was submitted in EBI which is retrieved from miRBases; and pair wise alignment was done with precursors of viruses and precursors of Japanese encephalitis ( Kozomara et al., 2011). Mainly, MSA focused on conserved regions for miRNA (Table 2).

Target prediction analysis
Based on observation, potential miRNA predicted the different types of target sites in a human gene. Then it predicted the different type of genes and those involved in different type of target sites with conserved information (Tables 3, 4 and 5).
All the tables explain the different types of analyses related to in silico prediction only, and the whole information of targeted genes in humans and targeted miRNA of Japanese encephalitis. Table 5 gives important information of genes for easy understanding of targeted genes by miRNA of Japanese encephalitis.

Conclusion
Finally in this study, eight potential miRNAs were predicted in silico and 123 target sites were found in 13 genes. Out of these thirteen genes, VPS13B, NAV1, IQSEC2 and NTRK3 played an important role in the regulation of the central nervous system and its activity in human brain and body; it is shown that if it is damaged it could lead to brain fever and ultimately, death. So, if we can control the malfunction protein at the transcription level, we would be able to save patients suffering from   attack of J. encephalitis. Since this is a prediction based method, it has to be proved experimentally.