Crosslinking or RNA immunoprecipitation followed by sequencing (CLIP-seq or RIP-seq) allows transcriptome-wide discovery of RNA regulatory sites. As CLIP-seq/RIP-seq reads are short, existing computational tools focus on uniquely mapped reads, while reads mapped to multiple loci are discarded. We present CLAM (CLIP-seq Analysis of Multi-mapped reads). CLAM uses an expectation–maximization algorithm to assign multi-mapped reads and calls peaks combining uniquely and multi-mapped reads. To demonstrate the utility of CLAM, we applied it to a wide range of public CLIP-seq/RIP-seq datasets involving numerous splicing factors, microRNAs and m⁶A RNA methylation. CLAM recovered a large number of novel RNA regulatory sites inaccessible by uniquely mapped reads. The functional significance of these sites was demonstrated by consensus motif patterns and association with alternative splicing (splicing factors), transcript abundance (AGO2) and mRNA half-life (m⁶A). CLAM provides a useful tool to discover novel protein–RNA interactions and RNA modification sites from CLIP-seq and RIP-seq data, and reveals the significant contribution of repetitive elements to the RNA regulatory landscape of the human transcriptome.

中文翻译：

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多重映射读物的CLIP-seq分析在人类转录组中发现了新的功能性RNA调控位点

交联或RNA免疫沉淀后再测序（CLIP-seq或RIP-seq）可以在转录组范围内发现RNA调控位点。由于CLIP-seq / RIP-seq读段很短，因此现有的计算工具专注于唯一映射的读段，而映射到多个基因座的读段将被丢弃。我们介绍了CLAM（多映射读取的CLIP-seq分析）。CLAM使用期望最大化算法来分配多个映射的读取，并调用结合了唯一映射和多个映射的读取的峰。为了证明CLAM的效用，我们将其应用于各种涉及大量剪接因子，microRNA和m ⁶的公共CLIP-seq / RIP-seq数据集RNA甲基化。CLAM回收了许多独特的映射读段无法访问的新型RNA调控位点。这些位点的功能意义已通过共有基序模式以及与其他剪接（剪接因子），转录本丰度（AGO2）和mRNA半衰期（m ⁶ A）的关联得到证明。CLAM提供了一个有用的工具，可以从CLIP-seq和RIP-seq数据中发现新颖的蛋白质-RNA相互作用和RNA修饰位点，并揭示了重复元件对人类转录组RNA调控格局的重大贡献。