An informatics approach to distinguish RNA modifications in nanopore direct RNA sequencing
An informatics approach to distinguish RNA modifications in nanopore direct RNA sequencing
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纳米孔直接 RNA 测序中区分 RNA 修饰的信息学方法
DOI：
10.1016/j.ygeno.2022.110372
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发表时间：
2022
期刊：
影响因子：
4.4
通讯作者：
Pandian Ganesh N.
中科院分区：
文献类型：
--
作者：
Ramasamy Soundhar;Mishra Shubham;Sharma Surbhi;Parimalam Sangamithirai Subramanian;Vaijayanthi Thangavel;Fujita Yoto;Kovi Basavaraj;Sugiyama Hiroshi;Pandian Ganesh N.
RNA的修饰可以影响其结构、功能和稳定性，在基因表达和调控中发挥重要作用。检测RNA修饰的方法依赖于低通量的生物物理技术，如色谱法或质谱法，或基于选择性反应性化学探针的高通量短读测序技术。最近的研究利用基于纳米孔的第四代测序方法，通过直接测序RNA的天然状态来检测修饰。然而，这些方法是基于修饰相关的错配错误，容易被snp混淆。此外，还需要生成匹配的敲除控制以供参考，这是很费力的。在这项工作中，我们引入了一种称为“IndoC”的内部比较策略，其中将潜在修饰位点的“痕迹”和“当前信号强度”等特征与样品中相同RNA分子上的相似序列上下文进行比较，从而减轻了对匹配敲除对照的需求。我们首先表明，在IVT模型中，“痕量”能够区分人工产生的snp和真正的假尿嘧啶（Ψ）修饰，两者都显示出高度相似的不匹配概况。然后，我们将IndoC应用于酵母和人类核糖体RNA上，以证明先前报道的Ψ位点与同一数据集中未修改的对应位点相比，其痕量和信号强度谱显示出显着变化。最后，我们用化学探针加合物（n -环己基- n ' -β-（4-甲基morpholinium）乙基碳二亚胺[CMC]）对含有Ψ完整的RNA进行了直接RNA测序，结果表明，CMC的反应性也以Ψ特定的方式诱导了痕量和信号强度分布的变化，使它们能够从显示snp样行为的高错配位点分离出来。
Modifications in RNA can influence their structure, function, and stability and play essential roles in gene expression and regulation. Methods to detect RNA modifications rely on biophysical techniques such as chromatography or mass spectrometry, which are low throughput, or on high throughput short-read sequencing techniques based on selectively reactive chemical probes. Recent studies have utilized nanopore-based fourth-generation sequencing methods to detect modifications by directly sequencing RNA in its native state. However, these approaches are based on modification-associated mismatch errors that are liable to be confounded by SNPs. Also, there is a need to generate matched knockout controls for reference, which is laborious. In this work, we introduce an internal comparison strategy termed “IndoC,” where features such as ‘trace’ and ‘current signal intensity’ of potentially modified sites are compared to similar sequence contexts on the same RNA molecule within the sample, alleviating the need for matched knockout controls. We first show that in an IVT model, ‘trace’ is able to distinguish between artificially generated SNPs and true pseudouridine (Ψ) modifications, both of which display highly similar mismatch profiles. We then apply IndoC on yeast and human ribosomal RNA to demonstrate that previously reported Ψ sites show marked changes in their trace and signal intensity profiles compared with their unmodified counterparts in the same dataset. Finally, we perform direct RNA sequencing of RNA containing Ψ intact with a chemical probe adduct (N-cyclohexyl-N′-β-(4-methylmorpholinium) ethylcarbodiimide [CMC]) and show that CMC reactivity also induces changes in trace and signal intensity distributions in a Ψ specific manner, allowing their separation from high mismatch sites that display SNP-like behavior.