Learning cis-regulatory principles of ADAR-based RNA editing from CRISPR-mediated mutagenesis

Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs. Despite a compelling need towards predictive understanding of natural and engineered editing events, how the RNA sequence and structure determine the editing efficiency and specificity (i.e., cis-regulation) is poorly understood. We apply a CRISPR/Cas9-mediated saturation mutagenesis approach to generate libraries of mutations near three natural editing substrates at their endogenous genomic loci. We use machine learning to integrate diverse RNA sequence and structure features to model editing levels measured by deep sequencing. We confirm known features and identify new features important for RNA editing. Training and testing XGBoost algorithm within the same substrate yield models that explain 68 to 86 percent of substrate-specific variation in editing levels. However, the models do not generalize across substrates, suggesting complex and context-dependent regulation patterns. Our integrative approach can be applied to larger scale experiments towards deciphering the RNA editing code. To study the effects of mutation on the RNA structure, we used chemical probing of in intro transcribed RNA to infer secondary structure of RNA libraries. Each RNA is barcoded with unique sequences. Libraries of RNA with designed mutations were made by in vitro transcribed using T7 RNA polymerase and DNA templates. RNA were purified by AMpure RNA beads before chemical treatmentment. RT-PCR reaction are followed to construct sequencing library to count chemically induced mutation rate (called reactivity) to infer the secodnary structure of RNA.

由ADAR酶催化的腺苷至肌苷（A-to-I）RNA编辑发生于双链RNA中。尽管学界迫切需要实现对天然与工程化编辑事件的预测性理解，但RNA序列与结构如何决定编辑效率与特异性（即顺式调控），目前仍未得到充分阐释。本研究采用CRISPR/Cas9介导的饱和诱变策略，在三个天然编辑底物的内源基因组位点附近构建突变文库。我们借助机器学习整合多样的RNA序列与结构特征，对深度测序测得的编辑水平进行建模。本研究验证了已知特征，并鉴定出对RNA编辑具有重要作用的全新特征。在同一底物内训练并测试XGBoost算法所得到的模型，可解释68%至86%的底物特异性编辑水平变异。但该模型无法跨底物泛化，这表明RNA编辑的调控模式具有复杂性与背景依赖性。本研究的整合策略可应用于更大规模的实验，以解析RNA编辑密码。

为研究突变对RNA结构的影响，我们采用体外转录RNA的化学探测法，以推断RNA文库的二级结构。每个RNA均带有独特序列的条形码标记。携带预设突变的RNA文库通过T7 RNA聚合酶与DNA模板进行体外转录制备。RNA在化学处理前通过AMpure RNA磁珠进行纯化。随后通过逆转录PCR（RT-PCR）构建测序文库，以计数化学诱导的突变率（即反应性），进而推断RNA的二级结构。