m6Aboost

This package can help user to run the m6Aboost model on their own miCLIP2 data. The package includes functions to assign the read counts and get the features to run the m6Aboost model.

The cliProfiler package extension

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N6-methyladenosine (m6A) is the most abundant internal modification in mRNA. It impacts many different aspects of an mRNA’s life, e.g. nuclear export, translation, stability, etc.

m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation (miCLIP) and the improved miCLIP2 are m6A antibody-based methods that allow the transcriptome-wide mapping of m6A sites at a single-nucleotide resolution (Körtel et al. 2021)(Linder et al. 2015). In brief, UV crosslinking of the m6A antibody to the modified RNA leads to truncation of reverse transcription or C-to-T transitions in the case of readthrough. However, due to the limited specificity and high cross-reactivity of the m6A antibodies, the miCLIP data comprise a high background signal, which hampers the reliable identification of m6A sites from the data.

For accurately detecting m6A sites, we implemented an AdaBoost-based machine learning model (m6Aboost) for classifying the miCLIP2 peaks into m6A sites and background signals (Körtel et al. 2021). The model was trained on high-confidence m6A sites that were obtained by comparing wildtype and Mettl3 knockout mouse embryonic stem cells (mESC) lacking the major methyltransferase Mettl3. For classification, the m6Aboost model uses a series of features, including the experimental miCLIP2 signal (truncation events and C-to-T transitions) as well as the transcript region (5’UTR, CDS, 3’UTR) and the nucleotide sequence in a 21-nt window around the miCLIP2 peak.

The m6Aboost package is available at https://bioconductor.org and can be access with the following link: https://bioconductor.org/packages/release/bioc/html/m6Aboost.html.