Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, 79110 Freiburg, Germany.
Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schaenzlestr. 18, 79104 Freiburg, Germany.
Gigascience. 2020 Nov 11;9(11). doi: 10.1093/gigascience/giaa108.
Post-transcriptional regulation via RNA-binding proteins plays a fundamental role in every organism, but the regulatory mechanisms lack important understanding. Nevertheless, they can be elucidated by cross-linking immunoprecipitation in combination with high-throughput sequencing (CLIP-Seq). CLIP-Seq answers questions about the functional role of an RNA-binding protein and its targets by determining binding sites on a nucleotide level and associated sequence and structural binding patterns. In recent years the amount of CLIP-Seq data skyrocketed, urging the need for an automatic data analysis that can deal with different experimental set-ups. However, noncanonical data, new protocols, and a huge variety of tools, especially for peak calling, made it difficult to define a standard.
CLIP-Explorer is a flexible and reproducible data analysis pipeline for iCLIP data that supports for the first time eCLIP, FLASH, and uvCLAP data. Individual steps like peak calling can be changed to adapt to different experimental settings. We validate CLIP-Explorer on eCLIP data, finding similar or nearly identical motifs for various proteins in comparison with other databases. In addition, we detect new sequence motifs for PTBP1 and U2AF2. Finally, we optimize the peak calling with 3 different peak callers on RBFOX2 data, discuss the difficulty of the peak-calling step, and give advice for different experimental set-ups.
CLIP-Explorer finally fills the demand for a flexible CLIP-Seq data analysis pipeline that is applicable to the up-to-date CLIP protocols. The article further shows the limitations of current peak-calling algorithms and the importance of a robust peak detection.
通过 RNA 结合蛋白的转录后调控在每个生物体中都起着至关重要的作用，但调控机制仍缺乏重要的认识。然而，通过交联免疫沉淀与高通量测序（CLIP-Seq）的结合，可以阐明这些机制。CLIP-Seq 通过在核苷酸水平上确定结合位点以及相关的序列和结构结合模式，回答关于 RNA 结合蛋白及其靶标的功能作用的问题。近年来，CLIP-Seq 数据呈爆炸式增长，迫切需要一种能够处理不同实验设置的自动数据分析方法。然而，非规范数据、新的协议以及大量的工具，特别是用于峰调用的工具，使得难以定义标准。
CLIP-Explorer 是一个灵活且可重复的 iCLIP 数据分析管道，首次支持 eCLIP、FLASH 和 uvCLAP 数据。可以更改单个步骤（如峰调用）以适应不同的实验设置。我们在 eCLIP 数据上验证了 CLIP-Explorer，与其他数据库相比，发现了各种蛋白质的相似或几乎相同的基序。此外，我们还检测到了 PTBP1 和 U2AF2 的新序列基序。最后，我们使用 3 种不同的峰调用器在 RBFOX2 数据上优化了峰调用，讨论了峰调用步骤的难度，并为不同的实验设置提供了建议。
CLIP-Explorer 最终满足了对灵活的 CLIP-Seq 数据分析管道的需求，该管道适用于最新的 CLIP 协议。该文章进一步展示了当前峰调用算法的局限性以及稳健的峰检测的重要性。
