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使用 DEWSeq 提高 eCLIP 数据中 RNA 结合蛋白结合位点的发现。

Improved discovery of RNA-binding protein binding sites in eCLIP data using DEWSeq.

机构信息

European Molecular Biology Laboratory (EMBL), Meyerhofstraße 1, 69117 Heidelberg, Germany.

Department of Structural Biology and Center of Excellence for Data-Driven Discovery, St. Jude Children's Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA.

出版信息

Nucleic Acids Res. 2024 Jan 11;52(1):e1. doi: 10.1093/nar/gkad998.

Abstract

Enhanced crosslinking and immunoprecipitation (eCLIP) sequencing is a method for transcriptome-wide detection of binding sites of RNA-binding proteins (RBPs). However, identified crosslink sites can deviate from experimentally established functional elements of even well-studied RBPs. Current peak-calling strategies result in low replication and high false positive rates. Here, we present the R/Bioconductor package DEWSeq that makes use of replicate information and size-matched input controls. We benchmarked DEWSeq on 107 RBPs for which both eCLIP data and RNA sequence motifs are available and were able to more than double the number of motif-containing binding regions relative to standard eCLIP processing. The improvement not only relates to the number of binding sites (3.1-fold with known motifs for RBFOX2), but also their subcellular localization (1.9-fold of mitochondrial genes for FASTKD2) and structural targets (2.2-fold increase of stem-loop regions for SLBP. On several orthogonal CLIP-seq datasets, DEWSeq recovers a larger number of motif-containing binding sites (3.3-fold). DEWSeq is a well-documented R/Bioconductor package, scalable to adequate numbers of replicates, and tends to substantially increase the proportion and total number of RBP binding sites containing biologically relevant features.

摘要

增强交联和免疫沉淀(eCLIP)测序是一种用于检测 RNA 结合蛋白(RBPs)结合位点的全转录组方法。然而,即使是研究得很好的 RBP,鉴定出的交联位点也可能偏离实验确定的功能元件。当前的峰调用策略导致复制率低和假阳性率高。在这里,我们提出了 R / Bioconductor 包 DEWSeq,它利用了重复信息和大小匹配的输入对照。我们在 107 个具有 eCLIP 数据和 RNA 序列基序的 RBPs 上对 DEWSeq 进行了基准测试,与标准 eCLIP 处理相比,能够将包含基序的结合区域数量增加一倍以上。这种改进不仅与结合位点的数量(对于 RBFOX2,已知基序增加了 3.1 倍)有关,而且与它们的亚细胞定位(对于 FASTKD2,线粒体基因增加了 1.9 倍)和结构靶标(对于 SLBP,茎环区域增加了 2.2 倍)有关。在几个正交的 CLIP-seq 数据集上,DEWSeq 恢复了更多包含基序的结合位点(增加了 3.3 倍)。DEWSeq 是一个记录良好的 R / Bioconductor 包,可扩展到足够数量的重复,并且倾向于大大增加包含生物学相关特征的 RBP 结合位点的比例和总数。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d23e/10783507/df4a7843c078/gkad998figgra1.jpg

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