2026-04-18T04:38:00Zhttps://recercat.cat/oai/request

oai:recercat.cat:10230/441342025-12-12T02:46:51Zcom_2072_6col_2072_452952

00925njm 22002777a 4500 dc Liu, Huanle author Begik, Oguzhan author Lucas, Morghan C. author Ramirez, Jose Miguel author Mason, Christopher E. author Wiener, David author Schwartz, Schraga author Mattick, John S. author Smith, Martin A. author Novoa, Eva Maria author 2020-04-01T08:42:52Z 2020-04-01T08:42:52Z 2019 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. RNA modification Software Accurate detection of m6A RNA modifications in native RNA sequences