articleNature CommunicationsSep 9, 2019GOLD OA

Accurate detection of m6A RNA modifications in native RNA sequences

HLHuanle LiuOBOguzhan BegikMCMorghan C. LucasJMJosé Miguel RamírezCEChristopher E. Mason

Garvan Institute of Medical Research · Centre for Genomic Regulation · +8 more institutions

PubMed
Indexed incrossrefdoajpubmed

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, 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…

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543
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Authors

10

Topics & keywords

Topics
Keywords
  • RNA
  • Computational biology
  • Context (archaeology)
  • Transcriptome
  • Biology
  • Genetics
  • Computer science
  • Gene
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