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QsRNA测序:一种用于生成小RNA高通量测序文库的方案。

QsRNA-seq: A protocol for generating libraries for high-throughput sequencing of small RNAs.

作者信息

Fishman Alla, T Lamm Ayelet

机构信息

Faculty of Biology, Technion-Israel Institute of Technology, Technion City, Haifa 32000, Israel.

出版信息

Bio Protoc. 2019 Mar 5;9(5):e3179. doi: 10.21769/BioProtoc.3179.

Abstract

Small RNAs (sRNAs) are 20-30 nt long non-coding RNA molecules that regulate essentially all cellular processes. Besides being an intensively studied topic in academic research, sRNAs also hold a promise as clinical biomarkers. While the need for expressional profiling of sRNAs is growing, preparation of sRNA libraries for high-throughput sequencing (HTS) remains technically challenging, due to their small size. The common PAGE-based protocol is time-consuming and inefficient due to material loss, while gel-free protocols generate libraries of insufficient quality. To overcome these shortcomings, we modified the conditions of size-selection by Solid Phase Reversible Immobilization (SPRI) in a way that allows separation of nucleic acids shorter than 100 nt and differing in length by only 20 nt. Implementing the method for preparation of small RNA libraries for HTS resulted in QsRNA-seq, a gel-free, fast and easy-to-perform protocol, amenable to automation, generating very clean libraries that result in high-depth expression data. The protocol also utilizes Unique Molecular Identifiers (UMI) for reduction of library preparation biases and to quantify expression levels. QsRNA-seq provides an excellent solution to the growing needs for small RNA expression profiling for research clinical use.

摘要

小RNA(sRNA)是长度为20 - 30个核苷酸的非编码RNA分子,基本上调控着所有细胞过程。除了是学术研究中深入研究的课题外,sRNA作为临床生物标志物也具有前景。虽然对sRNA表达谱分析的需求不断增长,但由于其尺寸小,制备用于高通量测序(HTS)的sRNA文库在技术上仍然具有挑战性。基于聚丙烯酰胺凝胶电泳(PAGE)的常规方法由于材料损失而耗时且效率低下,而无凝胶方法产生的文库质量不足。为克服这些缺点,我们以允许分离短于100个核苷酸且长度仅相差20个核苷酸的核酸的方式,修改了固相可逆固定化(SPRI)的大小选择条件。实施用于HTS的小RNA文库制备方法产生了QsRNA-seq,这是一种无凝胶、快速且易于操作的方案,适合自动化,可生成非常纯净的文库,从而获得高深度表达数据。该方案还利用独特分子标识符(UMI)来减少文库制备偏差并量化表达水平。QsRNA-seq为研究临床应用中对小RNA表达谱分析不断增长的需求提供了出色的解决方案。

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