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Accurate detection of m(6)A RNA modifications in native RNA sequences


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.

Type Journal
ISBN 2041-1723 (Electronic) 2041-1723 (Linking)
Authors Liu, H.; Begik, O.; Lucas, M. C.; Ramirez, J. M.; Mason, C. E.; Wiener, D.; Schwartz, S.; Mattick, J. S.; Smith, M. A.; Novoa, E. M.
Responsible Garvan Author (missing name)
Publisher Name Nature Communications
Published Date 2019-09-09
Published Volume 10
Published Issue 1
Published Pages 4079
Status Published in-print
DOI 10.1038/s41467-019-11713-9
URL link to publisher's version
OpenAccess link to author's accepted manuscript version