Dissecting epitranscriptomic signal from complex tissues

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Title: Dissecting epitranscriptomic signal from complex tissues PROJECT SUMMARY: “RNA epigenetics” or “epitranscriptomics” has emerged in recent years as an exciting and active research field to study post-transcriptional regulation of gene expressions. The RNA modifications play important roles in gene expression regulation, and are involved in neurodevelopment and a number of neurological diseases. Methylated RNA Immunoprecipitation Sequencing (MeRIP-seq) is a newly developed technology for transcriptome-wise profiling of the RNA epigenetic modifications. MeRIP-seq leads to an expansion of applications in both basic and clinical research, but faces a number of challenges in analysis with its unique data characteristics, including 1) the presence of technical artifacts due to sequence content and sample preparation procedures unique to MeRIP; 2) lack of appropriate methods for identification and comparison of RNA methylated regions; and 3) lack of methods to account for the heterogeneity of tissue samples. In this proposal, we will address these challenges and develop a series of novel statistical methods for MeRIP-seq data preprocessing and analyses. They include a data normalization procedure to remove technical bias, accurate and efficient methods for RNA methylation site detection and comparison, and signal deconvolution methods to draw cell type specific inferences based on data from tissue samples. All methods developed in this project will be implemented and released as free, open source software to benefit the epigenomics research community, including basic scientists working on genetics, epigenetics, gene regulation and cell development, as well as clinicians looking for disease biomarkers.