Identification of Human Viral Micrornas and Its Targets by Using Small RNA Sequencing Data Based on RNA Sequence and Structure Features

Project: A - Government Institutionb - National Science and Technology Council

Project Details

Description

Recent work has demonstrated that microRNAs (miRNAs) play an important role in development, oncogenesis and apoptosis by binding on mRNAs for regulating post-transcriptional level of coding genes in mammals, plants and insects. Notably, miRNAs also modulate viral existence in mammals by targeting viruses. Conversely, miRNAs are known to be produced from viruses. Recent studies have demonstrated that the expression of viral miRNAs is associated with its infection ability to host. Additionally, some studies discovered that the viral miRNAs is associated with human diseases. For examples, the hepatitis B/C virus (HBV/HCV), human papillomavirus (HPV), the Epstein–Barr virus (EBV) are associated with gastric and nasopharyngeal carcinoma, liver cancer, and cervical cancer, respectively. However, most previous study focused on deciphering the regulation mechanisms between human endogenous miRNAs and human genome. There is a lack of studies focused on the human viral miRNAs and its targets. Accordingly, this study focuses on determining the potential relationships between viral miRNAs and host genome including predicting viral miRNA precursors and mature miRNAs, and identifying human viral miRNA and its targets. The project is composed of three subprojects: “Development of prediction model of viral miRNA precursor”, “Discovery of human viral miRNAs using high-throughput sequence data”, and “Identification of human viral miRNA targets”. The specific aims of our project are listed as follows: 1. Development of prediction model of viral miRNA precursor (year 1): The known viral microRNA data are collected from the related databases and paper survey. The RNA secondary structure and sequence features of miRNA precursor are extracted using bioinformatics analysis methods, and the machine learning method is applied for developing the prediction model. 2. Discovery of human viral miRNAs (year 2): The human small RNA sequencing data are collected from NCBI SRA and TCGA databases, and the virus genome sequences are collected from ICTVdb, VirGen and etc. A predictive platform is constructed by integrating sequencing analysis tools and our prediction model of viral miRNA precursor for identifying human viral miRNAs. 3. Identification of human viral miRNA targets (year 3): The experimental validated viral miRNA and its targets are collected from the related database and paper survey. A prediction module is constructed by integrating miRNA target prediction tools, such as miRanda, TarScan and PicTar, for generating viral miRNA-specific module to identify the human viral miRNA targets. Additionally, further analysis of target genes, such as Gene Ontology analysis and pathway analysis, are also performed for deciphering the regulatory mechanism between viral miRNA and human disease. 4. Establishment of human viral miRNA targets database (year 1~3): A human viral miRNA target database is constructed by collecting the known viral miRNAs and targets, and the predicted viral miRNA and its targets is also included. The related biological information and further analysis are also provided in the database.
StatusFinished
Effective start/end date8/1/147/31/15

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