Gillen Austin E, Goering Raeann, Taliaferro J Matthew
Division of Hematology, University of Colorado School of Medicine, Aurora, CO, United States.
Department of Biochemistry and Molecular Genetics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States; RNA Bioscience Initiative, University of Colorado Anschutz Medical Campus, Aurora, CO, United States.
Methods Enzymol. 2021;655:245-263. doi: 10.1016/bs.mie.2021.03.018. Epub 2021 Apr 23.
Alternative polyadenylation (APA) generates transcript isoforms that differ in their 3' UTR content and may therefore be subject to different regulatory fates. Although the existence of APA has been known for decades, quantification of APA isoforms from high-throughput RNA sequencing data has been difficult. To facilitate the study of APA in large datasets, we developed an APA quantification technique called LABRAT (Lightweight Alignment-Based Reckoning of Alternative Three-prime ends). LABRAT leverages modern transcriptome quantification approaches to determine the relative abundances of APA isoforms. In this manuscript we describe how LABRAT produces its calculations, provide a step-by-step protocol for its use, and demonstrate its ability to quantify APA in single-cell RNAseq data.
可变聚腺苷酸化（APA）产生的转录本异构体在其3'UTR含量上有所不同，因此可能受到不同的调控命运。尽管APA的存在已为人所知数十年，但从高通量RNA测序数据中对APA异构体进行定量一直很困难。为了便于在大型数据集中研究APA，我们开发了一种名为LABRAT（基于轻量级比对的可变3'末端计算）的APA定量技术。LABRAT利用现代转录组定量方法来确定APA异构体的相对丰度。在本手稿中，我们描述了LABRAT如何进行计算，提供了其使用的详细步骤方案，并展示了其在单细胞RNA测序数据中定量APA的能力。
