Raja Shekar Varma Kadumuri: Accurate transcriptome-wide identification of m5C RNA modification events at single molecule resolution from direct RNA sequencing of human cell lines
Lightning talk: Raja Shekar Varma Kadumuri from Indiana University, shared his work utilising direct RNA sequencing to identify transcriptome-wide N5-methyl cytosine (m5C) modification events at single molecule resolution in human cell lines. Unlike alternative sequencing technologies that require additional sample processing to capture base modifications, direct RNA sequencing using nanopore technology allows simultaneous detection of nucleotide sequence and base modifications. The m5C RNA modification is known to regulate RNA processing, stability, mRNA export and translational processes. Raja and the team at Indiana University developed RAVEN, a deep neural network-based framework for the detection of m5C modifications from nanopore sequencing data. RAVAN utilises known m5C genomic locations and their modification frequency to support base modification detection. The framework has been validated on approximately 10,000 known m5C and unmodified cytosine signals from HeLa cells. Raja presented data showing that RAVAN predicts the m5C modification at single base resolution with an accuracy of 85%. Key features of the framework is that is provides a read-level probability score for each modification loci and the extent of methylation for each loci based on read depth. Raja now plans to test the RAVEN on additional human cell lines, validate results with bisulfite sequencing and examine other RNA modification types. RAVEN, which utilises albacore basecalled fast5 files, is freely available to download from GitHub.