Modeling Nuclease Digestion Coupled High-Throughput Sequencing for Genome-Wide Characterization of RNA Structure

• Activity Number: 331
• Type: Contributed
• Date/Time: Tuesday, August 5, 2014 : 10:30 AM to 12:20 PM
• Sponsor: Biopharmaceutical Section
• Author(s): Chenchen Zou*+ and Zhengqing Ouyang
• Companies: JAX LAB for Genomic Medicine and JAX LAB for Genomic Medicine
• Keywords: RNA secondary structure ; Next generation sequencing ; Genome-wide analysis ; Joint mixture modelling

Abstract

High-throughput sequencing technologies have emerged to dissect the secondary structures of RNAs genome-wide. Nuclease digestion coupled with sequencing is a powerful approach to capture structure-specific regions within RNAs cleaved by single-strand specific nuclease S1 and double-strand specific RNase V1. Such an experiment can generate millions of sequencing read for a comprehensive coverage of thousands of RNAs. Statistical modeling of read count data from nuclease digestion coupled with sequencing remains challenging because of the variability in and correlation between the footprint sequences of S1 and V1 along the transcript body. To address these issues, we propose a novel statistical approach for joint modeling of S1 and V1 data of the whole transcriptome. We apply our method to simulated and real datasets and demonstrate the unprecedented power of our method over previous approaches. Furthermore, the influence of the spatial conformation of RNA on nuclease digestion is revealed by our statistical modeling framework.