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

Authors: Jin Wang; Bing Liang Alvin Chew; Yong Lai; Hongping Dong; Luang Xu; Seetharamsingh Balamkundu; Weiling Maggie Cai; +9 Authors

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

Abstract

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.

Countries
China (People's Republic of), China (People's Republic of), Singapore, United States, China (People's Republic of)
Keywords

RNA Caps, 570, Sequence Analysis, RNA, Mass Spectrometry-based Technique, 610, Saccharomyces cerevisiae, Dengue Virus, RNA Characterisation and Manipulation, Epigenesis, Genetic, Mice, Inbred C57BL, Mice, Methods Online, Animals, Humans, RNA, Viral, :Medicine [Science], Female, RNA Processing, Post-Transcriptional, Transcriptome, Cells, Cultured

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    179
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
179
Top 1%
Top 10%
Top 1%
Green
gold