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RNA BiologyMolecular BiologyPeer-reviewed journal article

Optimized chemical labeling method for isolation of 8-oxoG-modified RNA, ChLoRox-Seq, identifies mRNAs enriched in oxidation and transcriptome-wide distribution biases of oxidation events post environmental stress

Matthew R. BurroughsiD, Philip SweetiD, Lydia M. ContrerasiD

PDFDOIPreprint

Abstract

Bulk increases in nucleobase oxidation, most commonly manifesting as the guanine (G) nucleobase modification 8-oxo-7,8-dihydroguanine (8-oxoG), have been linked to several disease pathologies. Elucidating the effects of RNA oxidation on cellular homeostasis is limited by a lack of effective tools for detecting specific regions modified with 8-oxoG. Building on a previously published method for studying 8-oxoG in DNA, we developed ChLoRox-Seq, which works by covalently functionalizing 8-oxoG sites in RNA with biotin. Importantly, this method enables antibody-free enrichment of 8-oxoG-containing RNA fragments for Next Generation Sequencing-based detection of modified regions transcriptome-wide. We demonstrate the high specificity of ChLoRox-Seq for functionalizing 8-oxoG over unmodified nucleobases in RNA and benchmark this specificity to a commonly used antibody-based approach. Key advantages of ChLoRox-Seq include: (1) heightened resolution of RNA oxidation regions (e.g. exon-level) and (2) lower experimental costs. By applying ChLoRox-Seq to mRNA extracted from human lung epithelial cells (BEAS-2B) after exposure to environmentally relevant stress, we observe that 8-oxoG modifications tend to cluster in regions that are G-rich and within mRNA transcripts possessing longer 5 UTR and CDS regions. These findings provide new insight into the complex mechanisms that bias the accumulation of RNA oxidation across the transcriptome. Notably, our analysis suggests the possibility that most mRNA oxidation events are probabilistically driven and that mRNAs that possess more favorable intrinsic properties are prone to incur oxidation events at elevated rates. ChLoRox-Seq can be readily applied in future studies to identify regions of elevated RNA oxidation in any cellular model of interest.

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