PhOxi-seq detects enzyme-dependent m ² G in multiple RNA types

In recent years, RNA-modifying enzymes have gained significant attention due to their impact on critical RNA-based processes, and consequently human pathology. However, identifying sites of modifications throughout the transcriptome remains challenging largely due to the lack of accurate and sensitive detection technologies. Recently, we described PhOxi-seq as a method capable of confirming known sites of m ² G within abundant classes of RNA, namely purified rRNA and purified tRNA. Here, we further explore the selectivity of PhOxi-seq and describe an optimised PhOxi-seq workflow, coupled to a novel bioinformatic pipeline, that is capable of detecting enzyme-dependent m ² G sites throughout the transcriptome, including low abundant mRNAs. In this way, we generated the first database of high confidence sites of THUMPD3-dependent m ² G in multiple RNA classes within a human cancer cell line and further identify non-THUMPD3 controlled sites throughout the transcriptome.