NanOlympicsMod – benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing

N6-methyladenosine (m6A) is the most abundant internal eukaryotic mRNA modification, and is involved in the regulation of various biological processes. Direct Nanopore sequencing of native RNA (dRNA-seq) emerged as a leading approach for its identification. Several software were published for m6A detection and there is a strong need for independent studies benchmarking their performance on data from different species, and against various reference datasets. Moreover, a computational workflow is needed to streamline the execution of tools whose installation and execution remains complicated.

Researchers at the Fondazione Istituto Italiano di Tecnologia have developed NanOlympicsMod, a Nextflow pipeline exploiting containerized technology for comparing 14 tools for m6A detection on dRNA-seq data. NanOlympicsMod was tested on dRNA-seq data generated from in vitro (un)modified synthetic oligos. The m6A hits returned by each tool were compared to the m6A position known by design of the oligos. In addition, NanOlympicsMod was used on dRNA-seq datasets from wild-type and m6A-depleted yeast, mouse and human, and each tool’s hits were compared to reference m6A sets generated by leading orthogonal methods. The performance of the tools markedly differed across datasets, and methods adopting different approaches showed different preferences in terms of precision and recall. Changing the stringency cut-offs allowed for tuning the precision-recall trade-off towards user preferences. Finally, the researchers determined that precision and recall of tools are markedly influenced by sequencing depth, and that additional sequencing would likely reveal additional m6A sites. Thanks to the possibility of including novel tools, NanOlympicsMod will streamline the benchmarking of m6A detection tools on dRNA-seq data, improving future RNA modification characterization.

The NanOlympicsMod workflow and adopted datasets

The NanOlympicsMod workflow and adopted datasets. (A) Schema of NanOlympicsMod, including input data, pre-processing steps, tools execution, post-processing and comparative analyses. (B) Experimental design for the four different datasets analysed by NanOlympicsMod; the methods used to generate the reference set of m6A hits in yeast and mouse are illustrated.

(A) Schema of NanOlympicsMod, including input data, pre-processing steps, tools execution, post-processing and comparative analyses. (B) Experimental design for the four different datasets analysed by NanOlympicsMod; the methods used to generate the reference set of m6A hits in yeast and mouse are illustrated.

Availability – The source code for the NanOlympicsMod workflow, and for reproducing all the results included in this study, are available at the following GitHub repository: https://github.com/mfurla/NanOlympicsMod.

Maestri S, Furlan M, Mulroney L, Coscujuela Tarrero L, Ugolini C, Dalla Pozza F, Leonardi T, Birney E, Nicassio F, Pelizzola M. (2024) Benchmarking of computational methods for m6A profiling with Nanopore direct RNA sequencing. Brief Bioinform 25(2):bbae001. [article]

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