The covalent modification of RNA molecules is a pervasive feature of all classes of RNAs and has fundamental roles in the regulation of several cellular processes. Mapping the location of RNA modifications transcriptome-wide is key to unveiling their role and dynamic behaviour, but technical limitations have often hampered these efforts. Nanopore direct RNA sequencing is a third-generation sequencing technology that allows the sequencing of native RNA molecules, thus providing a direct way to detect modifications at single-molecule resolution. Despite recent advances, the analysis of nanopore sequencing data for RNA modification detection is still a complex task that presents many challenges. Many works have addressed this task using different approaches, resulting in a large number of tools with different features and performances. Here we review the diverse approaches proposed so far and outline the principles underlying currently available algorithms.

The direct RNA sequencing platform offered by Oxford Nanopore Technologies allows for direct measurement of RNA molecules without the need of conversion to complementary DNA, fragmentation or amplification. As such, it is virtually capable of detecting any given RNA modification present in the molecule that is being sequenced, as well as provide polyA tail length estimations at the level of individual RNA molecules. Although this technology has been publicly available since 2017, the complexity of the raw Nanopore data, together with the lack of systematic and reproducible pipelines, have greatly hindered the access of this technology to the general user. Here we address this problem by providing a fully benchmarked workflow for the analysis of direct RNA sequencing reads, termed MasterOfPores. The pipeline starts with a pre-processing module, which converts raw current intensities into multiple types of processed data including FASTQ and BAM, providing metrics of the quality of the run, quality-filtering, demultiplexing, base-calling and mapping. In a second step, the pipeline performs downstream analyses of the mapped reads, including prediction of RNA modifications and estimation of polyA tail lengths. Four direct RNA MinION sequencing runs can be fully processed and analyzed in 10 h on 100 CPUs. The pipeline can also be executed in GPU locally or in the cloud, decreasing the run time fourfold. The software is written using the NextFlow framework for parallelization and portability, and relies on Linux containers such as Docker and Singularity for achieving better reproducibility. The MasterOfPores workflow can be executed on any Unix-compatible OS on a computer, cluster or cloud without the need of installing any additional software or dependencies, and is freely available in Github (https://github.com/biocorecrg/master_of_pores). This workflow simplifies direct RNA sequencing data analyses, facilitating the study of the (epi)transcriptome at single molecule resolution.

RNA polyadenylation plays a central role in RNA maturation, fate, and stability. In response to developmental cues, polyA tail lengths can vary, affecting the translation efficiency and stability of mRNAs. Here we develop Nanopore 3′ end-capture sequencing (Nano3P-seq), a method that relies on nanopore cDNA sequencing to simultaneously quantify RNA abundance, tail composition, and tail length dynamics at per-read resolution. By employing a template-switching-based sequencing protocol, Nano3P-seq can sequence RNA molecule from its 3′ end, regardless of its polyadenylation status, without the need for PCR amplification or ligation of RNA adapters. We demonstrate that Nano3P-seq provides quantitative estimates of RNA abundance and tail lengths, and captures a wide diversity of RNA biotypes. We find that, in addition to mRNA and long non-coding RNA, polyA tails can be identified in 16S mitochondrial ribosomal RNA in both mouse and zebrafish models. Moreover, we show that mRNA tail lengths are dynamically regulated during vertebrate embryogenesis at an isoform-specific level, correlating with mRNA decay. Finally, we demonstrate the ability of Nano3P-seq in capturing non-A bases within polyA tails of various lengths, and reveal their distribution during vertebrate embryogenesis. Overall, Nano3P-seq is a simple and robust method for accurately estimating transcript levels, tail lengths, and tail composition heterogeneity in individual reads, with minimal library preparation biases, both in the coding and non-coding transcriptome.