从直接RNA测序数据中检测和量化5moURNA修饰
Jiayi Li1, Feiyang Sun2, Kunyang He1
1Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, 215123, China.
Current genomics
|August 1, 2024
概括
我们开发了NanoML-5moU,这是一个机器学习工具,用于检测治疗信使RNAs (mRNAs) 中的5-methoxyuridine (5moU) 修饰. 这种方法使用纳米孔直接RNA测序数据准确量化5moU,用于质量控制.
科学领域:
- 生物技术是生物技术.
- 生物信息学是一种生物信息学.
- 分子生物学分子生物学
背景情况:
- 治疗性信使RNAs (mRNAs) 越来越多地利用化学修饰,如5-甲基尤里丁 (5moU),以提高稳定性和有效性.
- 准确检测和量化5moU对于体外转录 (IVT) mRNA的质量控制至关重要.
- 现有的方法缺乏用于精确5moU检测的定量能力.
研究的目的:
- 介绍NanoML-5moU,一种用于读取级检测和量化5moU修改的新型机器学习框架.
- 为了利用牛津纳米孔直接RNA测序来分析IVT mRNA数据.
- 提供一个强大的工具,用于修改mRNAs的质量评估.
主要方法:
- 从5moU修饰和未修饰的控制IVTmRNA样本收集纳米孔直接RNA测序数据.
- 分析信号事件特征,包括当前强度和停留时间.
- 采用机器学习算法 (SVM,RF,XGBoost) 来识别5mer序列中的5moU.
主要成果:
- 使用信号事件属性,XGBoost算法实现了高性能 (AUROC高达0.9567),优于现有模型.
- 该框架在各种数据集中显示出强大的性能,验证了其一般适用性.
- 在读取级别上,NanoML-5moU准确地描述了5moU的修改.
结论:
- 纳米ML-5moU允许使用直接RNA测序精确量化IVTmRNA中的5moU修饰.
- 该框架作为一种有价值的工具,用于mRNA疗法开发的质量控制.
- 这种方法增强了化学修饰mRNAs的研究和应用.
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