Identification of microRNA-like RNAs from Curvularia lunata associated with maize leaf spot by bioinformation analysis and deep sequencing

Deep sequencing of small RNAs is a useful tool to identify novel small RNAs that may be involved in fungal growth and pathogenesis. In this study, we used HiSeq deep sequencing to identify 747,487 unique small RNAs from Curvularia lunata. Among these small RNAs were 1012 microRNA-like RNAs (milRNAs), which are similar to other known microRNAs, and 48 potential novel milRNAs without homologs in other organisms have been identified using the miRBase© database. We used quantitative PCR to analyze the expression of four of these milRNAs from C. lunata at different developmental stages. The analysis revealed several changes associated with germinating conidia and mycelial growth, suggesting that these milRNAs may play a role in pathogen infection and mycelial growth. A total of 8334 target mRNAs for the 1012 milRNAs that were identified, and 256 target mRNAs for the 48 novel milRNAs were predicted by computational analysis. These target mRNAs of milRNAs were also performed by gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. To our knowledge, this study is the first report of C. lunata's milRNA profiles. This information will provide a better understanding of pathogen development and infection mechanism.