Computational Prediction And Identification Of MiRNA Genes In Fungus

MicroRNA, as a family of non-coding small RNA 18-25nt in length, have been profoundly studied in recent years in plants, animals and virus. As an important regulator in eukaryote organism, many studies demonstrated that miRNA have significant performance in the development of organism involving many aspects of cell physiological activities. The character of miRNA is still attractive academic researchs for the cause that the number of identified miRNAs is far from saturation. With the complete sequencing of some fungi genome, and human/fungus genomic pair alignment, scientists discover that fungus is similar with human in some important proteins expression during the cell physiological function. Meanwhile, the species display extreme phenotypic diversity for variation, competition and selection. More importantly, no miRNA was registered in miRBase up to now. As a result, these terms above provide considerable academic and realistic meaning in identifying miRNAs in fungus.As for time- and tissue- speciality of miRNA expression and mis-leading of degradation of mRNA and other non-coding RNAs, there is limitation by using experimental RNomics. Therefore, we apply computational RNomics to predict miRNA in Saccharomyces cerevisiae based on sequence conservation of mature miRNAs and their precursor displaying hairpin structure, leading to identification of 32 novel miRNAs.