A NEW METHOD TO DISCOVER MICRORNAS FROM HIGN THROUGHPUT SEQUENCING DATA BASED ON 'SEED SEQUENCES' OF MICRORNAS

摘要

High throughput sequencing technology was widely applied to identify microRNAs (miRNAs). However, the identification of miRNAs from the large pool of sequenced transcripts still remains a major challenge. In this study, we developed a bioinformatics approach based on "seed sequences" of miRNAs to discover known miRNAs and predict novel miRNAs from high throughput sequencing data. To detect more potential candidate miRNAs, as much as possible homologous seed sequences were selected as filtering sequences. By mapping to precursor sequences and genome, the pathway provides sensitive and accurate method to detect known miRNAs, discover candidate miRNAs that have the same identities with known miRNAs in other animal species, and predict novel miRNAs by analyzing high throughput sequencing data. The approach increases the sensitivity and possibility to discover more candidate miRNAs especially for the species that is still not detected miRNAs.