Accurate detection of m6A RNA modifications in native RNA sequences

Huanle Liu, Oguzhan Begik, Morghan C. Lucas, Jose Miguel Ramirez, Christopher E. Mason, David Wiener, Schraga Schwartz, John S. Mattick, Martin A. Smith and Eva Maria Novoa ()
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Huanle Liu: The Barcelona Institute of Science and Technology
Oguzhan Begik: The Barcelona Institute of Science and Technology
Morghan C. Lucas: The Barcelona Institute of Science and Technology
Jose Miguel Ramirez: The Barcelona Institute of Science and Technology
Christopher E. Mason: Weill Cornell Medicine
David Wiener: Weizmann Institute of Science
Schraga Schwartz: Weizmann Institute of Science
John S. Mattick: Garvan Institute of Medical Research
Martin A. Smith: St-Vincent’s Clinical School, UNSW Sydney
Eva Maria Novoa: The Barcelona Institute of Science and Technology

Nature Communications, 2019, vol. 10, issue 1, 1-9

Abstract: Abstract 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, N6-methyladenosine (m6A) 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 m6A-modified and unmodified synthetic sequences, can predict m6A RNA modifications with ~90% accuracy. We then extend our findings to yeast data sets, finding that our method can identify m6A 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 m6A modifications. Our results open avenues to investigate the biological roles of RNA modifications in their native RNA context.

Date: 2019
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DOI: 10.1038/s41467-019-11713-9

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