Primary sequence-assisted prediction of mA RNA methylation sites from Oxford nanopore direct RNA sequencing data.

Traditional epitranscriptome profiling approach relies on specific antibodies or chemical treatments to capture modified RNA molecules and then applies high throughput sequencing to identify their transcriptomic locations. However, due to the lack of suitable or high-quality antibodies, only a small proportion of the 170 documented RNA modifications were profiled with those approaches. Direct sequencing of native RNA molecules using Oxford Nanopore Technologies (ONT) enabled straight inspection of RNA modifications and offered a promising alternative solution. N6-methyladenosine (mA) is known to cause characteristic changes and increased base call errors of ONT signals compared with non-modified adenosines, based on which, the mA sites can be identified directly from ONT signals. Meanwhile, a number of studies have shown that it is possible to predict mA sites from RNA primary sequences. Using the mA sites revealed by Illumina technology as benchmark, we showed that, the accuracy of ONT-based mA site prediction can be further increased by integrating additional information from the primary sequences of RNA (AUROC of 0.918), compared with using ONT signals only (AUROC 0.878 using Base call error features, and 0.804 using Tombo features), providing a new perspective for more reliable mining of the relatively noisy ONT signals.