Busan Steven, Weeks Kevin M
Department of Chemistry, University of North Carolina, Chapel Hill, North Carolina 27599, USA.
RNA. 2017 Jul;23(7):1012-1018. doi: 10.1261/rna.060194.116. Epub 2017 Apr 20.
Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis.
RNA结构与功能之间相互关系的分析日益成为基因组研究的重要组成部分。SHAPE-MaP策略能够对长达数千碱基的非编码RNA和mRNA进行精确的RNA结构探测和逼真的结构建模。现有的用于可视化RNA结构模型的工具并不适合对长的、结构异质的RNA进行高效分析。此外,结构模型通常需要结合其他实验数据和基因注释信息进行解读才更具优势,而目前针对此的工具很少。我们在广泛使用且得到良好支持的开源整合基因组浏览器(IGV)中开发了一个模块,该模块能够在线性基因组数据轨道的背景下,可视化SHAPE和其他化学探测数据,包括原始反应性、数据驱动的结构熵以及数据约束的碱基对二级结构模型。我们通过探索大型病毒RNA基因组的结构模型、比较细菌mRNA在细胞内的结构与其在无细胞和无蛋白质条件下的结构,以及比较使用SHAPE数据建模的非编码RNA结构与通过序列共变分析推断的碱基配对模型,来说明在IGV中可视化RNA结构的实用性。