Premium
AlkAniline‐Seq: Profiling of m 7 G and m 3 C RNA Modifications at Single Nucleotide Resolution
Author(s) -
Marchand Virginie,
Ayadi Lilia,
Ernst Felix G. M.,
Hertler Jasmin,
BourguigIgel Valérie,
Galvanin Adeline,
Kotter Annika,
Helm Mark,
Lafontaine Denis L. J.,
Motorin Yuri
Publication year - 2018
Publication title -
angewandte chemie
Language(s) - English
Resource type - Journals
eISSN - 1521-3757
pISSN - 0044-8249
DOI - 10.1002/ange.201810946
Subject(s) - rna , computational biology , ribozyme , adapter (computing) , nucleotide , deep sequencing , chemistry , biology , genetics , gene , microbiology and biotechnology , computer science , genome , operating system
RNA modifications play essential roles in gene expression regulation. Only seven out of >150 known RNA modifications are detectable transcriptome‐wide by deep sequencing. Here we describe a new principle of RNAseq library preparation, which relies on a chemistry based positive enrichment of reads in the resulting libraries, and therefore leads to unprecedented signal‐to‐noise ratios. The proposed approach eschews conventional RNA sequencing chemistry and rather exploits the generation of abasic sites and subsequent aniline cleavage. The newly generated 5′‐phosphates are used as unique entry for ligation of an adapter in library preparation. This positive selection, embodied in the AlkAniline‐Seq, enables a deep sequencing‐based technology for the simultaneous detection of 7‐methylguanosine (m 7 G) and 3‐methylcytidine (m 3 C) in RNA at single nucleotide resolution. As a proof‐of‐concept, we used AlkAniline‐Seq to comprehensively validate known m 7 G and m 3 C sites in bacterial, yeast, and human cytoplasmic and mitochondrial tRNAs and rRNAs, as well as for identifying previously unmapped positions.