Eukaryotic genes often generate a variety of RNA isoforms that can lead to functionally distinct protein variants. The synthesis and stability of RNA isoforms is poorly characterized because current methods to quantify RNA metabolism use short-read sequencing and cannot detect RNA isoforms. Here we present nanopore sequencing–based isoform dynamics (nano-ID), a method that detects newly synthesized RNA isoforms and monitors isoform metabolism. Nano-ID combines metabolic RNA labeling, long-read nanopore sequencing of native RNA molecules, and machine learning. Nano-ID derives RNA stability estimates and evaluates stability determining factors such as RNA sequence, poly(A)-tail length, secondary structure, translation efficiency, and RNA-binding proteins. Application of nano-ID to the heat shock response in human cells reveals that many RNA isoforms change their stability. Nano-ID also shows that the metabolism of individual RNA isoforms differs strongly from that estimated for the combined RNA signal at a specific gene locus. Nano-ID enables studies of RNA metabolism at the level of single RNA molecules and isoforms in different cell states and conditions.

中文翻译：

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通过纳米 ID 进行的天然分子测序揭示了 RNA 同种型的合成和稳定性。

真核基因通常会产生多种 RNA 异构体，这些异构体可以导致功能不同的蛋白质变体。RNA 异构体的合成和稳定性的特征很差，因为目前量化 RNA 代谢的方法使用短读长测序，无法检测 RNA 异构体。在这里，我们介绍了基于纳米孔测序的异构体动力学（nano-ID），这是一种检测新合成的 RNA 异构体并监测异构体代谢的方法。Nano-ID 结合了代谢 RNA 标记、天然 RNA 分子的长读长纳米孔测序和机器学习。Nano-ID 推导出 RNA 稳定性估计值并评估稳定性决定因素，例如 RNA 序列、poly(A) 尾长度、二级结构、翻译效率和 RNA 结合蛋白。将纳米 ID 应用于人体细胞的热休克反应表明许多 RNA 同种型改变了它们的稳定性。Nano-ID 还显示单个 RNA 同种型的代谢与特定基因位点的组合 RNA 信号估计的代谢有很大不同。Nano-ID 能够在不同细胞状态和条件下在单个 RNA 分子和同种型水平上研究 RNA 代谢。