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Simultaneous identification of m6A and m5C reveals coordinated RNA modification at single-molecule resolution [HeLa cells]

ABSTRACT: The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. However, the identification of multiple modification types in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual transcript molecules in a single condition as well as differential methylation between two conditions, using nanopore signals. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. Moreover, CHEUI’s unique capability to identify different modifications in the same signal data reveals a non-random co-occurrence of m6A and m5C in transcripts in human cell lines and during mouse embryonic brain development. CHEUI unlocks the capability of studying links between multiple RNA modifications and phenotypes, enabling the discovery of new epitranscriptome functions. Furthermore, CHEUI's training and testing protocols are adaptable to other modifications, making it a versatile RNA technology.

ORGANISM(S): Homo sapiens

PROVIDER: GSE211759 | GEO | 2022/10/31

REPOSITORIES: GEO

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Prediction of m6A and m5C at single-molecule resolution reveals a transcriptome-wide co-occurrence of RNA modifications

Project description:The expanding field of epitranscriptomics might rival the epigenome in the diversity of biological processes impacted. However, the identification of multiple modification types in individual RNA molecules remains challenging. We present CHEUI, a new method that detects N6-methyladenosine (m6A) and 5-methylcytidine (m5C) in individual transcript molecules in a single condition as well as differential methylation between two conditions, using nanopore signals. CHEUI processes observed and expected signals with convolutional neural networks to achieve high single-molecule accuracy and outperform other methods in detecting m6A and m5C sites and quantifying their stoichiometry. Moreover, CHEUI’s unique capability to identify different modifications in the same signal data reveals a non-random co-occurrence of m6A and m5C in transcripts in human cell lines and during mouse embryonic brain development. CHEUI unlocks the capability of studying links between multiple RNA modifications and phenotypes, enabling the discovery of new epitranscriptome functions. Furthermore, CHEUI's training and testing protocols are adaptable to other modifications, making it a versatile RNA technology.

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