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Fingerprints of Modified RNA Bases from Deep Sequencing Profiles.

Anna M KietrysWillem A VelemaEric T Kool
Published in: Journal of the American Chemical Society (2017)
Posttranscriptional modifications of RNA bases are not only found in many noncoding RNAs but have also recently been identified in coding (messenger) RNAs as well. They require complex and laborious methods to locate, and many still lack methods for localized detection. Here we test the ability of next-generation sequencing (NGS) to detect and distinguish between ten modified bases in synthetic RNAs. We compare ultradeep sequencing patterns of modified bases, including miscoding, insertions and deletions (indels), and truncations, to unmodified bases in the same contexts. The data show widely varied responses to modification, ranging from no response, to high levels of mutations, insertions, deletions, and truncations. The patterns are distinct for several of the modifications, and suggest the future use of ultradeep sequencing as a fingerprinting strategy for locating and identifying modifications in cellular RNAs.
Keyphrases
  • single cell
  • electronic health record
  • current status
  • deep learning
  • loop mediated isothermal amplification