Identification of Novel MicroRNAs in Primates by Using the Synteny Information and Small RNA Deep Sequencing Data

Current technologies that are used for genome-wide microRNA (miRNA) prediction are mainly based on BLAST tool. They often produce a large number of false positives. Here, we describe an effective approach for identifying orthologous pre-miRNAs in several primates based on syntenic information. Some of them have been validated by small RNA high throughput sequencing data. This approach uses the synteny information and experimentally validated miRNAs of human, and incorporates currently available algorithms and tools to identify the pre-miRNAs in five other primates. First, we identified 929 potential pre-miRNAs in the marmoset in which miRNAs have not yet been reported. Then, we predicted the miRNAs in other primates, and we successfully re-identified most of the published miRNAs and found 721, 979, 650 and 639 new potential pre-miRNAs in chimpanzee, gorilla, orangutan and rhesus macaque, respectively. Furthermore, the miRNA transcriptome in the four primates have been re-analyzed and some novel predicted miRNAs have been supported by the small RNA sequencing data. Finally, we analyzed the potential functions of those validated miRNAs and explored the regulatory elements and transcription factors of some validated miRNA genes of interest. The results show that our approach can effectively identify novel miRNAs and some miRNAs that supported by small RNA sequencing data maybe play roles in the nervous system