Department of Computer Science, New Jersey Institute of Technology, Newark, NJ 07102 and Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
Bioinformatics. 2014 Aug 1;30(15):2162-70. doi: 10.1093/bioinformatics/btu189. Epub 2014 Apr 11.
Next-generation RNA sequencing offers an opportunity to investigate transcriptome in an unprecedented scale. Recent studies have revealed widespread alternative polyadenylation (polyA) in eukaryotes, leading to various mRNA isoforms differing in their 3' untranslated regions (3'UTR), through which, the stability, localization and translation of mRNA can be regulated. However, very few, if any, methods and tools are available for directly analyzing this special alternative RNA processing event. Conventional methods rely on annotation of polyA sites; yet, such knowledge remains incomplete, and identification of polyA sites is still challenging. The goal of this article is to develop methods for detecting 3'UTR switching without any prior knowledge of polyA annotations.
We propose a change-point model based on a likelihood ratio test for detecting 3'UTR switching. We develop a directional testing procedure for identifying dramatic shortening or lengthening events in 3'UTR, while controlling mixed directional false discovery rate at a nominal level. To our knowledge, this is the first approach to analyze 3'UTR switching directly without relying on any polyA annotations. Simulation studies and applications to two real datasets reveal that our proposed method is powerful, accurate and feasible for the analysis of next-generation RNA sequencing data.
The proposed method will fill a void among alternative RNA processing analysis tools for transcriptome studies. It can help to obtain additional insights from RNA sequencing data by understanding gene regulation mechanisms through the analysis of 3'UTR switching.
The software is implemented in Java and can be freely downloaded from http://utr.sourceforge.net/.
zhiwei@njit.edu or hongzhe@mail.med.upenn.edu
Supplementary data are available at Bioinformatics online.
新一代 RNA 测序为研究转录组提供了前所未有的机会。最近的研究表明,真核生物中广泛存在着可变多聚腺苷酸化(polyA),导致各种 mRNA 异构体在其 3'非翻译区(3'UTR)存在差异,通过这种方式,可以调节 mRNA 的稳定性、定位和翻译。然而,目前几乎没有直接分析这种特殊的可变 RNA 加工事件的方法和工具。传统的方法依赖于 polyA 位点的注释;然而,这种知识仍然不完整,而且 polyA 位点的识别仍然具有挑战性。本文的目的是开发无需任何 polyA 注释先验知识即可检测 3'UTR 切换的方法。
我们提出了一种基于似然比检验的变点模型,用于检测 3'UTR 切换。我们开发了一种有向测试程序,用于识别 3'UTR 中剧烈缩短或延长的事件,同时控制混合有向假发现率在名义水平上。据我们所知,这是第一种无需依赖任何 polyA 注释即可直接分析 3'UTR 切换的方法。模拟研究和对两个真实数据集的应用表明,我们提出的方法对于分析下一代 RNA 测序数据是强大、准确和可行的。
该方法将填补转录组研究中替代 RNA 处理分析工具的空白。通过分析 3'UTR 切换,了解基因调控机制,从而帮助从 RNA 测序数据中获得更多的见解。
该软件是用 Java 实现的,可以从 http://utr.sourceforge.net/ 免费下载。
zhiwei@njit.edu 或 hongzhe@mail.med.upenn.edu
补充数据可在 Bioinformatics 在线获取。