Journal Article

Accurate detection of m6A RNA modifications in native RNA sequences

Schwartz, Schraga, Novoa, Eva Maria, Mattick, John S., Begik, Oguzhan, Wiener, David, Smith, Martin A., Ramirez, Jose Miguel, Mason, Christopher E., Liu, Huanle, Lucas, Morghan C.

2019

Overview

The epitranscriptomics field has undergone an enormous expansion in the last few years; however, a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Here, we show that using direct RNA sequencing, N 6 -methyladenosine (m 6 A) RNA modifications can be detected with high accuracy, in the form of systematic errors and decreased base-calling qualities. Specifically, we find that our algorithm, trained with m 6 A-modified and unmodified synthetic sequences, can predict m 6 A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m 6 A RNA modifications in vivo with an accuracy of 87%. Moreover, we further validate our method by showing that these ‘errors’ are typically not observed in yeast ime4 -knockout strains, which lack m 6 A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context. We currently lack generic methods to map RNA modifications across the entire transcriptome. Here, the authors demonstrate that m 6 A RNA modifications can be detected with high accuracy using nanopore direct RNA sequencing.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 38 / 38/91 / 45 / 45/91 / 49 / 49/91 / 631/114/794 / 631/337/1645/2570 / Accuracy / Algorithms / Gene expression / Gene sequencing / Humanities and Social Sciences / In vivo methods and tests / multidisciplinary / N6-methyladenosine / Ribonucleic acid / RNA / Science / Science (multidisciplinary) / Systematic errors / Yeast