核糖核酸
计算生物学
背景(考古学)
转录组
生物
遗传学
计算机科学
基因
基因表达
古生物学
作者
Huanle Liu,Oguzhan Begik,Morghan C. Lucas,José Miguel Ramírez,Christopher E. Mason,David Wiener,Schraga Schwartz,John S. Mattick,Martin A. Smith,Eva Maria Novoa
标识
DOI:10.1038/s41467-019-11713-9
摘要
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 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.
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