GSE174518
Nm-Mut-seq: The base-resolution quantitative method for mapping transcriptome-wide 2'-O-methylations
2'-O-methylation (Nm) is a prevalent post-transcriptional RNA modification present in many cellular RNAs and plays a critical role in modulating both the physical properties and regulation of eukaryotic RNAs. Studies of Nm modifications in RNA have long been hampered by a lack of effective mapping methods. Previously reported approaches can work well for detecting Nm modifications on abundant RNAs, but face challenges when applied to low-abundant RNAs, such as mRNA, lack stoichiometric information, and are challenged by issues of RNA sample degradation due to chemical treatment. Here, we present Nm-Mut-seq, a mutation signature-based Nm mapping method, which uses a custom reverse transcriptase (RT) that installs mutations at Am, Cm, and Gm-modified sites (Um is undetectable by this method). Our work provides a much-needed approach to detect Nm at base resolution in low abundant RNAs and to estimate the stoichiometry of each modified site transcriptome-wide. Overall design: [dataset1] 15 samples (Sample 1-15): Duplicates or Triplicates for "Input" and "Treated" samples in Nm-Mut-seq to detect Nm in total RNA and polyA+ RNA from wild-type HeLa and HepG2 cells. Note that RNA 3'-adaptor sequence is 5'rApp-NNNNN ATCACG AGATCGGAAGAGCACACGTCT-3SpC3; RNA 5'-adaptor sequence is 5'-GUUCAGAGUUCUACAGUCCGACGAUC NNNNN-3'. [datase2] 20 samples (Sample 16-35): Duplicates for "Input" and "Treated" samples in Nm-Mut-seq to depict Nm calibration curves for estimating Nm methylation fractions. [datase3] 18 samples (Sample 36-53): Triplicates for Nm-Mut-seq samples to reveal Nm methylation level change in total RNA and polyA+ RNA from siFBL or siFTSJ3 HepG2 cells versus siControl. Note that 5'rApp-NNNNN ATCACG AGATCGGAAGAGCACACGTCT-3SpC3 is for siFBL polyA+ RNA samples (Sample 48, 49, and 50); 5'rApp-NNNNN TTAGGC AGATCGGAAGAGCACACGTCT-3SpC3 is for all the rest samples in dataset3 (Sample 36-47, and Sample 51-53). RNA 5'-adaptor sequence is always 5'-GUUCAGAGUUCUACAGUCCGACGAUC NNNNN-3' for Sample 36-53.