A reference-guided iterative approach to polish the nanopore sequencing basecalling for therapeutic RNA quality control

Nucleotide modifications deviate nanopore sequencing readouts, therefore generating artifacts during the basecalling of sequence backbones. Here, we present a reference-guided, iterative approach to polish modification-disturbed basecalling results. We show that such an approach is uniquely suitable for training biomolecule-specific high-accuracy basecallers, by improving the basecalling of both artificially-synthesized and real-world molecules. With demonstrated efficacy and reliability, we exploit the approach to precisely basecall therapeutic RNAs consisting of artificial or natural modifications. We first analyzed vaccine mRNAs, which are artificially modified to promote stability and reduce immunogenicity. Specifically, we quantified the sequence purity and integrity, the two most important quality metrics to be controlled during mRNA vaccine production. We also analyzed BioRNAs, which are human tRNA-based carriers for therapeutic RNA interference (RNAi) agents. Specifically, we examined modification hotspots, which are naturally incorporated in vivo during BioRNA production and essential for therapeutic efficacy. Our analysis expands the scope of therapeutic RNA quality control, from the conventional sequence-level to the current modification status-level.