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.

• PMID: 31501426
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Journal Article | Research Support, N.I.H., Extramural | Research Support, Non-U.S. Gov't | Research Support, U.S. Gov't, Non-P.H.S.

Authors

Liu H, Begik O, Lucas MC, Ramirez JM, Mason CE, Wiener D, Schwartz S, Mattick JS, Smith MA, Novoa EM

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