PT  - JOURNAL ARTICLE
AU  - Jin Wang
AU  - Bing Liang Alvin Chew
AU  - Yong Lai
AU  - Hongping Dong
AU  - Luang Xu
AU  - Seetharamsingh Balamkundu
AU  - Weiling Maggie Cai
AU  - Liang Cui
AU  - Chuan Fa Liu
AU  - Xin-Yuan Fu
AU  - Zhenguo Lin
AU  - Pei-Yong Shi
AU  - Timothy K. Lu
AU  - Dahai Luo
AU  - Samie R. Jaffrey
AU  - Peter C. Dedon
TI  - Quantifying the RNA cap epitranscriptome reveals novel caps in cellular and viral RNA
AID  - 10.1101/683045
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 683045
4099  - http://biorxiv.org/content/early/2019/07/03/683045.short
4100  - http://biorxiv.org/content/early/2019/07/03/683045.full
AB  - 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 the cap epitranscriptome in any organism. 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, mice, and humans, we discovered four new cap structures in humans and mice (FAD, UDP-Glc, UDP-GlcNAc, and m7Gpppm6A), cell- and tissue-specific variations in cap methylation, and surprisingly high proportions of caps lacking 2’-O-methylation, such as m7Gpppm6A in mammals and m7GpppA in dengue virus, and we did not detect cap m1A/m1Am in humans. CapQuant accurately captured the preference for purine nucleotides at eukaryotic transcription start sites and the correlation between metabolite levels and metabolite caps. The mystery around cap m1A/m1Am analysis remains unresolved.