In recent years, nanopore direct RNA sequencing (DRS) became a valuable tool for studying the epitranscriptome, due to its ability to detect multiple modifications within the same full-length native RNA molecules. While RNA modifications can be identified in the form of systematic basecalling 'errors' in DRS datasets, N6-methyladenosine (m6A) modifications produce relatively low 'errors' compared to other RNA modifications, limiting the applicability of this approach to m6A sites that are modified at high stoichiometries. Here, we demonstrate that the use of alternative RNA basecalling models, trained with fully unmodified sequences, increases the 'error'signal of m6A, leading to enhanced detection and improved sensitivity even at low stoichiometries. Moreover, we find that high-accuracy alternative RNA basecalling models can show up to 97% median basecalling accuracy, outperforming currently available RNA basecalling models, which show 91% median basecalling accuracy. Notably, the use of high-accuracy basecalling models is accompanied by a significant increase in the number of mapped reads –especially in shorter RNA fractions– and increased basecalling error signatures at pseudouridine (Ψ) and N1-methylpseudouridine (m1Ψ) modified sites. Overall, our work demonstrates that alternative RNA basecalling models can be used to improve the detection of RNA modifications, read mappability, and basecalling accuracy in nanopore DRS datasets.

中文翻译：

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使用高精度纳米孔 RNA 碱基识别模型增强对 RNA 修饰和读取映射的检测


近年来，纳米孔直接 RNA 测序 (DRS) 成为研究表观转录组的重要工具，因为它能够检测同一全长天然 RNA 分子内的多种修饰。虽然 RNA 修饰可以在 DRS 数据集中以系统碱基识别“错误”的形式进行识别，但与其他 RNA 修饰相比，N6-甲基腺苷 (m6A) 修饰产生的“错误”相对较低，从而限制了该方法对修饰的 m6A 位点的适用性在高化学计量下。在这里，我们证明使用完全未修饰的序列训练的替代 RNA 碱基识别模型可以增加 m6A 的“错误”信号，从而增强检测并提高灵敏度，即使在低化学计量下也是如此。此外，我们发现高精度替代 RNA 碱基识别模型可以显示高达 97% 的中位碱基识别准确度，优于当前可用的 RNA 碱基识别模型，后者显示出 91% 的中位碱基识别准确度。值得注意的是，高精度碱基识别模型的使用伴随着映射读数数量的显着增加（尤其是在较短的 RNA 片段中）以及假尿苷 (Ψ) 和 N1-甲基假尿苷 (m1Ψ) 修饰位点的碱基识别错误特征的增加。总的来说，我们的工作表明，替代的 RNA 碱基识别模型可用于改善纳米孔 DRS 数据集中 RNA 修饰的检测、读取可映射性和碱基识别准确性。