选择性切割和聚腺苷酸化(APA),RNA处理事件,发生在超过70%的人类蛋白质编码基因中。APA产生具有不同3'末端的mRNA转录物。大多数APA发生在3个UTR内,包含可以影响mRNA稳定性的调控元件,翻译,和本地化。
APA可以使用许多已建立的计算工具进行分析,这些工具可以从标准,短读RNA-seq数据集。这里,我们对一些这样的工具进行了基准测试——TAPAS,卡塔尔,DaPars2,GETUTR,和APATRAP-对3'-Seq,一个专门的RNA-seq协议,在基因的3个末端富集读取,和Iso-Seq,太平洋生物科学(PacBio)单分子全长RNA-seq方法能够识别聚腺苷酸化位点并量化聚腺苷酸化位点的使用。我们证明了3'-Seq和Iso-Seq能够比采用短读RNA-seq作为输入的计算工具更可靠地识别和量化聚腺苷酸化位点的使用。然而,我们发现运行一个这样的工具,卡塔尔,通过一组源自少量3\'-Seq或Iso-Seq的聚腺苷酸化位点注释,可以可靠地量化不同条件下APA的变化,比如跨基因型,如成功定位替代聚腺苷酸化数量性状基因座(apaQTL)所证明的。
我们设想我们的分析将揭示采用更专业的测序方案研究APA的优势。例如3\'-Seq或Iso-Seq,以及用短读RNA-seq研究APA的局限性。我们提供了一个计算管道,以使用Iso-Seq数据作为输入来帮助识别聚腺苷酸化位点和定量聚腺苷酸化位点使用。
Alternative cleavage and polyadenylation (APA), an RNA processing event, occurs in over 70% of human protein-coding genes. APA results in mRNA transcripts with distinct 3\' ends. Most APA occurs within 3\' UTRs, which harbor regulatory elements that can impact mRNA stability, translation, and localization.
APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number of such tools-TAPAS, QAPA, DaPars2, GETUTR, and APATrap- against 3\'-Seq, a specialized RNA-seq protocol that enriches for reads at the 3\' ends of genes, and Iso-Seq, a Pacific Biosciences (PacBio) single-molecule full-length RNA-seq method in their ability to identify polyadenylation sites and quantify polyadenylation site usage. We demonstrate that 3\'-Seq and Iso-Seq are able to identify and quantify the usage of polyadenylation sites more reliably than computational tools that take short-read RNA-seq as input. However, we find that running one such tool, QAPA, with a set of polyadenylation site annotations derived from small quantities of 3\'-Seq or Iso-Seq can reliably quantify variation in APA across conditions, such asacross genotypes, as demonstrated by the successful mapping of alternative polyadenylation quantitative trait loci (apaQTL).
We envisage that our analyses will shed light on the advantages of studying APA with more specialized sequencing protocols, such as 3\'-Seq or Iso-Seq, and the limitations of studying APA with short-read RNA-seq. We provide a computational pipeline to aid in the identification of polyadenylation sites and quantification of polyadenylation site usages using Iso-Seq data as input.