Quantifying the RNA cap epitranscriptome reveals novel caps in cellular and viral RNA

定量 RNA 帽表观转录组揭示细胞和病毒 RNA 中的新帽

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作者:Jin Wang, Bing Liang Alvin Chew, Yong Lai, Hongping Dong, Luang Xu, Seetharamsingh Balamkundu, Weiling Maggie Cai, Liang Cui, Chuan Fa Liu, Xin-Yuan Fu, Zhenguo Lin, Pei-Yong Shi, Timothy K Lu, Dahai Luo, Samie R Jaffrey, Peter C Dedon4

Abstract

Chemical modification of transcripts with 5' caps occurs in all organisms. Here, we report a systems-level mass spectrometry-based technique, CapQuant, for quantitative analysis of an organism's cap epitranscriptome. The method was piloted with 21 canonical caps-m7GpppN, m7GpppNm, GpppN, GpppNm, and m2,2,7GpppG-and 5 'metabolite' caps-NAD, FAD, UDP-Glc, UDP-GlcNAc, and dpCoA. Applying CapQuant to RNA from purified dengue virus, Escherichia coli, yeast, mouse tissues, and human cells, we discovered new cap structures in humans and mice (FAD, UDP-Glc, UDP-GlcNAc, and m7Gpppm6A), cell- and tissue-specific variations in cap methylation, and high proportions of caps lacking 2'-O-methylation (m7Gpppm6A in mammals, m7GpppA in dengue virus). While substantial Dimroth-induced loss of m1A and m1Am arose with specific RNA processing conditions, human lymphoblast cells showed no detectable m1A or m1Am in caps. CapQuant accurately captured the preference for purine nucleotides at eukaryotic transcription start sites and the correlation between metabolite levels and metabolite caps.

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