Abstract

MicroRNAs (miRNAs) are small non-coding RNAs that modulate gene expression transcriptionally (transcriptional activation or inactivation) and/or post-transcriptionally (translation inhibition or degradation of their target mRNAs). This phenomenon has significant roles in growth and developmental processes in plants and animals. Bos taurus is one of the most important livestock animals, having great importance in food and economical sciences and industries. However, limited information is available on Bos taurus constituent miRNAs because its whole genome assembly has been only recently published. Therefore, computational methods have been essential tools in miRNA gene prediction and discovery. Among these, machine-learning-based approaches are used to characterize genome scale pre-miRNAs from expressed sequence tags (ESTs). In this study, a support vector machine model was used to classify 33 structural and thermodynamic features of pre-miRNA genes. Public bovine EST data were obtained from different tissues in various developmental stages. A new algorithm, called BosFinder, was developed to identify and annotate the whole genome's derived pre-miRNAs. We found 18 776 highly potential pre-miRNA sequences. This is the first genome survey report of Bos taurus based on a machine-learning method for pre-miRNA gene finding. The BOSFINDER program is freely available at http://lbb.ut.ac.ir/Download/LBBsoft/BosFinder/.