The recent development and application of methods based on the general principle of “crosslinking and proximity ligation” (crosslink-ligation) are revolutionizing RNA structure studies in living cells. However, extracting structure information from such data presents unique challenges. Here we introduce a set of computational tools for the systematic analysis of data from a wide variety of cross-link-ligation methods, specifically focusing on read mapping, alignment classification and clustering. We design a new strategy to map short reads with irregular gaps at high sensitivity and specificity. Analysis of previously published data reveals distinct properties and bias caused by the crosslinking reactions. We perform rigorous and exhaustive classification of alignments and discover 8 types of arrangements that provide distinct information on RNA structures and interactions. To deconvolve the dense and inter-twined gapped alignments, we develop a network/graph-based tool CRSSANT (Crosslinked RNA Secondary Structure Analysis using Network Techniques), which enables clustering of gapped alignments and discovery of new alternative and dynamic conformations. We discover that multiple crosslinking and ligation events can occur on the same RNA, generating multi-segment alignments to report complex high level RNA structures and multi-RNA interactions. We find that alignments with overlapped segments are produced from potential homodimers and develop a new method for their de novo identification. Analysis of overlapping alignments revealed potential new homodimers in cellular noncoding RNAs and RNA virus genomes in the Picornaviridae family. Together, this suite of computational tools enables rapid and efficient analysis of RNA structure and interaction data in living cells.

中文翻译：

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RNA 交联连接数据的分类和聚类揭示了复杂的结构和同源二聚体

基于“交联和邻近连接”（crosslink-ligation）一般原理的方法的最新发展和应用正在彻底改变活细胞中的 RNA 结构研究。然而，从这些数据中提取结构信息提出了独特的挑战。在这里，我们介绍了一组用于系统分析来自各种交联连接方法的数据的计算工具，特别关注读取映射、对齐分类和聚类。我们设计了一种新策略，以高灵敏度和特异性映射具有不规则间隙的短读长。对先前公布的数据的分析揭示了由交联反应引起的不同性质和偏差。我们对比对进行严格而详尽的分类，并发现了 8 种类型的排列，它们提供了有关 RNA 结构和相互作用的不同信息。为了对密集和相互缠绕的间隙对齐进行解卷积，我们开发了一个基于网络/图的工具 CRSSANT（使用网络技术的交联 RNA 二级结构分析），它能够对间隙对齐进行聚类并发现新的替代和动态构象。我们发现多个交联和连接事件可以发生在同一个 RNA 上，产生多段比对以报告复杂的高级 RNA 结构和多 RNA 相互作用。我们发现与重叠片段的比对是由潜在的同源二聚体产生的，并开发了一种新的方法来进行从头识别。重叠比对分析揭示了小核糖核酸病毒科的细胞非编码 RNA 和 RNA 病毒基因组中潜在的新同源二聚体。总之，这套计算工具可以快速有效地分析活细胞中的 RNA 结构和相互作用数据。