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Quantitative profiling of native RNA modifications and their dynamics using nanopore sequencing (Total RNA Sequencing of Yeast)

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NIAID Data Ecosystem2026-03-12 收录
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https://www.ncbi.nlm.nih.gov/sra/ERP121128
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Here we systematically examined whether RNA modifications present in mRNAs and/or rRNAs can be identified using direct RNA sequencing, including N6-methyladenosine (m6A), N5-methylcytosine (m5C), N5-hydroxymethylcytosine (hm5C) and pseudouridine (?). Surprisingly, we find that both the choice of base-calling algorithm and mapper can drastically affect the accuracy of detection of RNA modifications. Once the optimal base-caller and mapper is employed, we find that all studied RNA modifications can be detected in the form of systematic base-calling 'errors', and that error 'signatures' depend on the identity of the underlying RNA modification. We then validate our approach in vivo, by showing that knockout of snoRNAs guiding pseudouridine modification depletes the base-calling error signals exclusively in known pseudouridine rRNA-modified positions. We then apply our approach to examine whether rRNAs from distinct polysomal gradients vary their rRNA modification profiles. Surprisingly, we find that only very minor differences can be identified between polysomal, monosomal and unassembled rRNA fractions.
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2021-06-16
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