A homology-based approach for identifying Plant MicroRNAs from Next-Generation Sequencing Data

• Main Authors: Fa-Jen Liu, 劉發仁
• Other Authors: Li-Ching Hsieh
• Format: Others
• Language: zh-TW
• Published: 2019
• Online Access: http://ndltd.ncl.edu.tw/cgi-bin/gs32/gsweb.cgi/login?o=dnclcdr&s=id=%22107NCHU5105030%22.&searchmode=basic

碩士 === 國立中興大學 === 基因體暨生物資訊學研究所 === 107 === MicroRNAs (miRNAs) are short non-coding RNAs with about 22 nt in length. Their main function is to regulate the expression of messenger ribonucleic acids (mRNAs) that can be translated into proteins in organisms. Due to the development of next-generation sequencing (NGS) technology, small RNA sequencing (sRNA-Seq) can be used to help miRNAs prediction. Among the sRNA-Seq-based prediction methods, the reference genome-guided methods express higher precision; on the other hand, most of the genome-free methods utilize the machine learning technology to do prediction, however, the result has a higher false positive rate. This study developed a homology-based approach which is independent of the reference genome to analyze sRNA-Seq data. Previously published sRNA-Seq data of Arabidopsis thaliana were used to test the performance of the new appoach. The results from the new approach were compared with the previously published results by the reference genome-guided method. 83% the miRNA families obtained from the previous study can be identified in the new approach. In addition, the two approaches show similar miRNA expression profiles. We then utilized the new apporach to analyze the miRNAs of Phalaenopsis and Oncidium, and predicted their target genes. In addition, differently expressed miRNAs were identified from different samples and the target genes of most of the differently expressed miRNAs could be predicted. A total of 13 conserved miRNA families, 19 novel miRNA families, and 210 target genes were identified in Phalaenopsis. A total of 17 conserved miRNA families, 1 novel miRNA family, and 35 target genes were identified in the Oncidium. From the miRNA prediction results of Arabidopsis thaliana and the orchids, the feasibility and accuracy of the homology-based approach are demonstrated.Thus this apporach will help to improve the miRNA prediction ability with no reference required, and help researchers to understand the more comprehensive regulatory mechanisms in each organism through miRNA prediction.