Silberman Institute of Life Sciences, Hebrew University, Jerusalem, Israel.
Methods Mol Biol. 2021;2218:355-365. doi: 10.1007/978-1-0716-0970-5_28.
The stability of RNA transcripts is regulated by signals within their sequences, but the identity of those signals still remain elusive in many biological systems. Recently introduced massively parallel tools for the analysis of regulatory RNA sequences provide the ability to detect functional cis-regulatory sequences of post-transcriptional RNA regulation at a much larger scale and resolution than before. Their application formulates the underlying sequence-based rules and predicts the impact of genetic variations. Here, we describe the application of UTR-Seq, as a strategy to uncover cis-regulatory signals of RNA stability during early zebrafish embryogenesis. The method combines massively parallel reporter assays (MPRA) with computational regression models. It surveys the effect of tens of thousands of regulatory sequences on RNA stability and analyzes the results via regression models to identify sequence signals that impact RNA stability and to predict the in vivo effect of sequence variations.
RNA 转录本的稳定性受其序列中信号的调节，但在许多生物系统中，这些信号的身份仍然难以捉摸。最近引入的用于分析调控 RNA 序列的大规模平行工具，使我们能够以前所未有的更大规模和分辨率来检测转录后 RNA 调控的功能顺式调控序列。它们的应用形成了基于序列的基本规则，并预测了遗传变异的影响。在这里，我们描述了 UTR-Seq 的应用，这是一种在早期斑马鱼胚胎发生过程中揭示 RNA 稳定性的顺式调控信号的策略。该方法将大规模平行报告基因检测（MPRA）与计算回归模型相结合。它调查了数万个调控序列对 RNA 稳定性的影响，并通过回归模型分析结果，以识别影响 RNA 稳定性的序列信号，并预测序列变异的体内效应。
