Accurate detection of m6A RNA modifications in native RNA sequences

Huanle Liu,Jose Miguel Ramirez,David Wiener,Martin A Smith,John S Mattick,Christopher E Mason,Eva Maria Novoa,Oguzhan Begik,Morghan C Lucas,Schraga Schwartz

doi:10.1038/s41467-019-11713-9

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, 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.

Highlights

The epitranscriptomics field has undergone an enormous expansion in the last few years; a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide
Indirect methods are required to identify RNA modifications transcriptome-wide, which has been mainly approached using two different strategies: (i) antibody immunoprecipitation, which recognizes the modified ribonucleotide[5,6,12,13,14]; and (ii) chemical-based detection, using chemical compounds that selectively react with the modified ribonucleotide of interest, followed by reversetranscription of the RNA fragment, which leads to accumulation of reads that have the same identical ends[8,9,15]
Here we find that base-calling “errors” can accurately identify N6-methyladenosine (m6A) RNA modifications in native RNA sequences, and propose a novel algorithm, EpiNano, which can be used to identify m6A RNA modifications from RNA reads with an overall accuracy of ~90%

Summary

Introduction

The epitranscriptomics field has undergone an enormous expansion in the last few years; a major limitation is the lack of generic methods to map RNA modifications transcriptome-wide. Indirect methods are required to identify RNA modifications transcriptome-wide, which has been mainly approached using two different strategies: (i) antibody immunoprecipitation, which recognizes the modified ribonucleotide[5,6,12,13,14]; and (ii) chemical-based detection, using chemical compounds that selectively react with the modified ribonucleotide of interest, followed by reversetranscription of the RNA fragment, which leads to accumulation of reads that have the same identical ends[8,9,15] These methods have provided highly valuable information, they are limited by the available repertoire of commercial antibodies and the lack of selective chemical reactivities towards a particular RNA modification[16], often lack single nucleotide resolution[5,6,7] or require complex protocols to achieve it[17], cannot provide quantitative estimates of the stoichiometry of the modification at a given site, and are often unable to identify the underlying RNA molecule that is modified. Current efforts have not yet yielded an efficient and accurate RNA modification detection algorithm, largely due to the challenges in the alignment and re-squiggling of RNA current intensities[22,23]

Methods

Results

Conclusion