Analysis of miRNAseq data to identify disease-related miRNA (KAP210049)

Study goal: The final goal of this study is the identification of disease related miRNAs by analyzing miRNA sequencing data. To meet this goal, we set up five specific objectives. 1. Identification of total miRNAs from disease model systems 2. Identification of miRNAs influencing diseases 3. Prediction of target genes of disease-related miRNAs 4. Prediction of functional relevance of candidate genes to diseases 5. Development of database for disease miRNAs . Study contents 1. Development of the miRNA sequencing data analysis pipeline to facilitate the identification of disease-related miRNAs. Unraveling molecular mechanisms of disease development by the integrated analysis of miRNA-mRNA sequencing data 2. Identification of disease-related miRNAs by employing sequencing data analysis pipeline developed in this study 3. identification of disease-related miRNAs by using miRNA-related SNPs in the human populations . Conducting association analysis between miRNA-related SNPs and disease of interest in the large human populations 4. Construction of disease miRNA DB containing the information of disease-related miRNAs that is linked to the information of miRNA-related SNPs. Results 1. Identification of miRNAs for cancer stem cells by employing miRNA sequencing data analysis pipeline that was developed in this study 2. Identification of molecular markers involved in bone differentiation by employing RNA sequencing data analysis pipeline that was developed in this study 3. Development of integrated miRNA-mRNA sequencing data analysis pipeline 4. Identification of miRNA-related SNPs influencing kidney function related traits in human populations 5. Development of disease miRNA DB that links disease miRNA information and miRNA-related SNPs. Expected contribution 1. The identification of disease-related miRNAs will contribute to the improvement of understanding in molecular mechanisms involved in disease development. 2. The development of disease miRNA DB will contribute to understanding of genetic heritability of disease. 3. The results from this study will be useful to develop the new types of drugs to treat numerous types of diseases. 4. The results from this study will contribute to the preparation of new methods to replace or compensate the defect of pre-existing drugs.