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MicroRNAs (miRNAs) are small non-coding RNAs that have functional roles in posttranscriptional modification. They regulate gene expression by an RNA interfering pathway through cleavage or inhibition of the translation of target mRNA. Numerous miRNAs have been described for their important functions in developmental processes in numerous animals, but there is limited information about sheep and goat miRNAs. Sheep and goat are ideal model organisms for biological and comparative genomics studies in ruminants. Identification of miRNAs is crucial to understanding their biological mechanism. Computational identification approaches can supplement experimental approaches to quickly identify ncRNAs in novel genomes, chiefly miRNAs that are transcribed under particular conditions in specific cell types. Currently, machine learning approaches have been employed to predict novel miRNAs. In this study, we present a new SVM-based classifier. It demonstrated high accuracy, balanced sensitivity and specificity for the miRNA datasets, thus representing an ideal tool for miRNA identification from transcriptome sequencing data. In this research, we generated an optimized feature subset including 20 features using a support vector machine, and we developed a c # program to compute the features in the training sequences. In this study, an intelligent SVM model with RBF kernel and the SMO learning algorithm was the best classifier for predicting microRNA genes in sheep and goat. Sensitivity and specificity of this model were 88% and 85% respectively. Then, expressed sequence tag (EST) analysis was performed for finding sheep and goat mature miRNAs. Chromosome 1 was scanned for finding miRNA potential region. In sheep 23 miRNA genes and, in goat 15 miRNAs had been discovered by homology searching. Our finding demonstrate that the Sheep and goat miRNA sequences can be supplied useful information for investigating biological roles of miRNAs in ruminants.

Detecting of Functional Short Non-Coding RNAs using Bioinformatics Methods in Sheep and Goat